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ESP: PubMed Auto Bibliography 18 Sep 2026 at 01:46 Created:
Ecological Informatics
Wikipedia: Ecological Informatics Ecoinformatics, or ecological informatics, is the science of information (Informatics) in Ecology and Environmental science. It integrates environmental and information sciences to define entities and natural processes with language common to both humans and computers. However, this is a rapidly developing area in ecology and there are alternative perspectives on what constitutes ecoinformatics. A few definitions have been circulating, mostly centered on the creation of tools to access and analyze natural system data. However, the scope and aims of ecoinformatics are certainly broader than the development of metadata standards to be used in documenting datasets. Ecoinformatics aims to facilitate environmental research and management by developing ways to access, integrate databases of environmental information, and develop new algorithms enabling different environmental datasets to be combined to test ecological hypotheses. Ecoinformatics characterize the semantics of natural system knowledge. For this reason, much of today's ecoinformatics research relates to the branch of computer science known as Knowledge representation, and active ecoinformatics projects are developing links to activities such as the Semantic Web. Current initiatives to effectively manage, share, and reuse ecological data are indicative of the increasing importance of fields like Ecoinformatics to develop the foundations for effectively managing ecological information. Examples of these initiatives are National Science Foundation Datanet projects, DataONE and Data Conservancy.
Created with PubMed® Query: ( "ecology OR ecological" AND ("data management" OR informatics) NOT "assays for monitoring autophagy" ) NOT pmcbook NOT ispreviousversion
Citations The Papers (from PubMed®)
RevDate: 2026-09-17
CmpDate: 2026-09-17
Sex- and age-dependent physiological adaptation of captive père david's deer revealed by multi-omics analysis.
BMC genomics, 27(1):.
BACKGROUND: Understanding how age and sex influence molecular and physiological changes is essential for studying endangered species, particularly Père David's deer, which is extinct in the wild. In this study, multi-omics analyses were performed to investigate transcriptomic, metabolomic, and proteomic dynamics in male and female Père David's deer across different developmental stages under captive conditions.
RESULTS: The results revealed sex- and stage-specific molecular trajectories, with males showing enhanced ion metabolism during early life and females exhibiting increased lipid metabolism during the subadult stage. A substantial proportion of differentially abundant metabolites and differentially expressed proteins were associated with immune and inflammatory processes. Transcriptome-based age estimation indicated that individuals at the Fawn stage exhibited younger transcriptomic profiles, and enrichment analysis of highly weighted genes highlighted immune-related pathways. In addition, transcriptomic deconvolution analysis revealed coordinated alterations in innate and adaptive immune cell populations during development.
CONCLUSIONS: These findings provide a comprehensive multi-omics characterization of molecular and immune dynamics in captive Père David's deer and improve understanding of developmental and sex-associated biological variation in this endangered species.
Additional Links: PMID-42343219
PubMed:
Citation:
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@article {pmid42343219,
year = {2026},
author = {Yu, R and Zhang, S and Li, Y and Niu, G and Cheng, Z and Li, J and Bai, J and Zhang, S},
title = {Sex- and age-dependent physiological adaptation of captive père david's deer revealed by multi-omics analysis.},
journal = {BMC genomics},
volume = {27},
number = {1},
pages = {},
pmid = {42343219},
issn = {1471-2164},
support = {No.24CA003-2,No.25CD009//Financial Program of BJAST/ ; HNJG-20230079//Hunan Provincial Research Project on Teaching Reform in Colleges and Universities/ ; 2023JGSZ021//Hunan Provincial Research Project on Teaching Reform for Academic Degrees and Graduate Students/ ; },
mesh = {Animals ; *Deer/genetics/physiology/metabolism ; Female ; Multiomics ; Male ; *Adaptation, Physiological/genetics ; Transcriptome ; Proteomics ; Gene Expression Profiling ; Sex Factors ; Age Factors ; Metabolomics ; *Aging ; },
abstract = {BACKGROUND: Understanding how age and sex influence molecular and physiological changes is essential for studying endangered species, particularly Père David's deer, which is extinct in the wild. In this study, multi-omics analyses were performed to investigate transcriptomic, metabolomic, and proteomic dynamics in male and female Père David's deer across different developmental stages under captive conditions.
RESULTS: The results revealed sex- and stage-specific molecular trajectories, with males showing enhanced ion metabolism during early life and females exhibiting increased lipid metabolism during the subadult stage. A substantial proportion of differentially abundant metabolites and differentially expressed proteins were associated with immune and inflammatory processes. Transcriptome-based age estimation indicated that individuals at the Fawn stage exhibited younger transcriptomic profiles, and enrichment analysis of highly weighted genes highlighted immune-related pathways. In addition, transcriptomic deconvolution analysis revealed coordinated alterations in innate and adaptive immune cell populations during development.
CONCLUSIONS: These findings provide a comprehensive multi-omics characterization of molecular and immune dynamics in captive Père David's deer and improve understanding of developmental and sex-associated biological variation in this endangered species.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Animals
*Deer/genetics/physiology/metabolism
Female
Multiomics
Male
*Adaptation, Physiological/genetics
Transcriptome
Proteomics
Gene Expression Profiling
Sex Factors
Age Factors
Metabolomics
*Aging
RevDate: 2026-09-17
CmpDate: 2026-09-17
Leveraging perturbations to infer the population dynamics of human rhinovirus and interaction of influenza A virus.
PLoS computational biology, 22(9):e1014784.
Many respiratory pathogens co-circulate within human populations. Yet, how pathogen community structure shapes the dynamics of infectious diseases remains poorly understood. At the population level, investigating polymicrobial dynamics, with potential underlying competitive or cooperative interactions, is challenging, because of confounding factors such as differing seasonality. This is particularly true for endemic pathogens which typically exhibit stable periodic dynamics. Their disruption due to the implementation of non-pharmaceutical interventions during the COVID-19 pandemic thus represents a unique large-scale natural experiment that can be leveraged to provide valuable insights into the complex interplay between respiratory pathogens. Here, we focus on the population dynamics of human rhinovirus (common cold) and on the potential viral interference of influenza A virus (flu A), which is hypothesized to account for their asynchronous circulation. Using a Bayesian framework, we first show based on simulations that exogenous perturbations can be a powerful tool to disentangle the contribution of pathogen interaction from other epidemiological factors. We then apply our framework to surveillance time series from the US and Canada spanning the COVID-19 pandemic. We estimate key parameters of rhinovirus but find no conclusive support for an influence of influenza A virus at the population level.
Additional Links: PMID-42726893
PubMed:
Citation:
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@article {pmid42726893,
year = {2026},
author = {Benhamou, W and Howerton, E and Park, SW and Viboud, C and Metcalf, CJE and Grenfell, BT},
title = {Leveraging perturbations to infer the population dynamics of human rhinovirus and interaction of influenza A virus.},
journal = {PLoS computational biology},
volume = {22},
number = {9},
pages = {e1014784},
pmid = {42726893},
issn = {1553-7358},
mesh = {Humans ; *Rhinovirus/physiology/pathogenicity ; *Influenza A virus/physiology/pathogenicity ; *Influenza, Human/epidemiology/virology ; Bayes Theorem ; Population Dynamics ; SARS-CoV-2 ; COVID-19/epidemiology/virology ; Pandemics ; Common Cold/epidemiology/virology ; Canada/epidemiology ; Computational Biology ; Picornaviridae Infections/epidemiology/virology ; United States/epidemiology ; Models, Biological ; Computer Simulation ; },
abstract = {Many respiratory pathogens co-circulate within human populations. Yet, how pathogen community structure shapes the dynamics of infectious diseases remains poorly understood. At the population level, investigating polymicrobial dynamics, with potential underlying competitive or cooperative interactions, is challenging, because of confounding factors such as differing seasonality. This is particularly true for endemic pathogens which typically exhibit stable periodic dynamics. Their disruption due to the implementation of non-pharmaceutical interventions during the COVID-19 pandemic thus represents a unique large-scale natural experiment that can be leveraged to provide valuable insights into the complex interplay between respiratory pathogens. Here, we focus on the population dynamics of human rhinovirus (common cold) and on the potential viral interference of influenza A virus (flu A), which is hypothesized to account for their asynchronous circulation. Using a Bayesian framework, we first show based on simulations that exogenous perturbations can be a powerful tool to disentangle the contribution of pathogen interaction from other epidemiological factors. We then apply our framework to surveillance time series from the US and Canada spanning the COVID-19 pandemic. We estimate key parameters of rhinovirus but find no conclusive support for an influence of influenza A virus at the population level.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Humans
*Rhinovirus/physiology/pathogenicity
*Influenza A virus/physiology/pathogenicity
*Influenza, Human/epidemiology/virology
Bayes Theorem
Population Dynamics
SARS-CoV-2
COVID-19/epidemiology/virology
Pandemics
Common Cold/epidemiology/virology
Canada/epidemiology
Computational Biology
Picornaviridae Infections/epidemiology/virology
United States/epidemiology
Models, Biological
Computer Simulation
RevDate: 2026-09-16
CmpDate: 2026-09-16
From Mood Episodes to Digital Signatures: Passive and Active Phenotyping of Bipolar Disorder Over Time.
The International journal of social psychiatry, 72(6):1463-1474.
BACKGROUND: Digital phenotyping has emerged as a promising approach to capture real-time behavioral and physiological data in individuals with bipolar disorder (BD). By integrating passive and active data streams, this approach may enable the identification of dynamic patterns associated with mood instability. However, the conceptual integration of these data into clinically meaningful digital signatures remains insufficiently defined and lacks standardized operational frameworks.
METHODS: This narrative review synthesizes current evidence on digital phenotyping in BD and proposes a conceptual framework integrating passive sensing (e.g. smartphones, wearables, mobility and communication data, physiological signals) and active assessments (e.g. ecological momentary assessment, self-reported mood, cognitive tasks). The framework outlines how multimodal digital biomarkers can be analyzed using computational approaches, including machine learning and longitudinal modeling, to derive individualized digital signatures.
RESULTS: The proposed framework describes how continuous behavioral and physiological data can be transformed into multimodal digital biomarkers reflecting sleep-wake rhythms, motor activity, mobility patterns, social interaction dynamics, and autonomic physiology. Through multimodal data integration and personalized baselines, computational models can identify temporal deviations associated with mood changes. These individualized digital signatures capture the dynamic processes underlying mood regulation and may provide early warning signals of relapse, as well as markers of treatment response.
CONCLUSIONS: Digital signatures derived from integrated digital phenotyping data represent a promising step toward precision psychiatry in BD. However, this concept remains an emerging framework requiring further empirical validation and methodological standardization. This approach highlights the potential for early detection of mood instability, prediction of mood episodes, and personalized clinical decision-making. Future research should focus on validation in longitudinal clinical cohorts, standardization of methodologies, and ethical considerations related to data privacy and implementation.
Additional Links: PMID-42095358
Publisher:
PubMed:
Citation:
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@article {pmid42095358,
year = {2026},
author = {Torales, J and O'Higgins, M and Barrios, I and Ventriglio, A and Castaldelli-Maia, JM and Smith, A and Liebrenz, M},
title = {From Mood Episodes to Digital Signatures: Passive and Active Phenotyping of Bipolar Disorder Over Time.},
journal = {The International journal of social psychiatry},
volume = {72},
number = {6},
pages = {1463-1474},
doi = {10.1177/00207640261449667},
pmid = {42095358},
issn = {1741-2854},
mesh = {Humans ; *Bipolar Disorder/diagnosis/physiopathology/psychology ; Digital Health ; Phenotype ; Machine Learning ; *Affect ; Biomarkers ; Ecological Momentary Assessment ; Smartphone ; },
abstract = {BACKGROUND: Digital phenotyping has emerged as a promising approach to capture real-time behavioral and physiological data in individuals with bipolar disorder (BD). By integrating passive and active data streams, this approach may enable the identification of dynamic patterns associated with mood instability. However, the conceptual integration of these data into clinically meaningful digital signatures remains insufficiently defined and lacks standardized operational frameworks.
METHODS: This narrative review synthesizes current evidence on digital phenotyping in BD and proposes a conceptual framework integrating passive sensing (e.g. smartphones, wearables, mobility and communication data, physiological signals) and active assessments (e.g. ecological momentary assessment, self-reported mood, cognitive tasks). The framework outlines how multimodal digital biomarkers can be analyzed using computational approaches, including machine learning and longitudinal modeling, to derive individualized digital signatures.
RESULTS: The proposed framework describes how continuous behavioral and physiological data can be transformed into multimodal digital biomarkers reflecting sleep-wake rhythms, motor activity, mobility patterns, social interaction dynamics, and autonomic physiology. Through multimodal data integration and personalized baselines, computational models can identify temporal deviations associated with mood changes. These individualized digital signatures capture the dynamic processes underlying mood regulation and may provide early warning signals of relapse, as well as markers of treatment response.
CONCLUSIONS: Digital signatures derived from integrated digital phenotyping data represent a promising step toward precision psychiatry in BD. However, this concept remains an emerging framework requiring further empirical validation and methodological standardization. This approach highlights the potential for early detection of mood instability, prediction of mood episodes, and personalized clinical decision-making. Future research should focus on validation in longitudinal clinical cohorts, standardization of methodologies, and ethical considerations related to data privacy and implementation.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Humans
*Bipolar Disorder/diagnosis/physiopathology/psychology
Digital Health
Phenotype
Machine Learning
*Affect
Biomarkers
Ecological Momentary Assessment
Smartphone
RevDate: 2026-09-16
CmpDate: 2026-09-16
Human Lingual Biofilm Signatures in Gastrointestinal Disease: A Scoping Review.
International dental journal, 76(5):109762.
INTRODUCTION AND AIMS: The tongue dorsum represents a structurally complex oral biofilm niche that has traditionally been regarded as indicative of systemic health. Recent advances in oral microbiome research and multi-omics technologies facilitate the systematic evaluation of the association between tongue coating biofilm signals and gastrointestinal disease states. However, it remains unclear whether these tongue-derived signals indicate systemic gastrointestinal pathology or merely reflect localised oral ecological disturbances. This review synthesises current evidence on tongue-derived microbial and multi-omics signatures across inflammatory, precancerous, and malignant gastrointestinal conditions, and evaluates their ecological, biological, and clinical significance.
METHODS: A scoping review was conducted in accordance with PRISMA-ScR guidelines. Five electronic databases were searched (2010-2025) for human studies analysing tongue-coating samples using microbiome or multi-omics approaches.
RESULTS: A total of twenty-five cross-sectional studies involving more than 4500 participants, primarily from East Asian populations, were included. Three recurrent patterns were identified: (1) stage-associated microbial restructuring, which involved mild non-specific alterations in inflammatory states, structured dysbiosis in precancerous conditions, and more consistent ecological configurations in malignancy; (2) convergence of functional multi-omics signals on lipid metabolism pathways across independent cohorts; and (3) significant modification of microbial and functional profiles by tongue coating phenotype, including colour, thickness and classification system.
CONCLUSIONS: Tongue-derived microbial and multi-omics signatures demonstrate reproducible cross-sectional associations with gastrointestinal diseases, exhibiting functional convergence across multiple omics layers. However, the reliance on cross-sectional study designs, absence of external validation and insufficient adjustment for confounding variables currently limit their clinical application as diagnostic biomarkers.
CLINICAL RELEVANCE: Tongue examination is clinically useful for assessing oral biofilm burden, mucosal pathology and oral hygiene in dental practice. It should not be used to diagnose gastrointestinal disease until validated by longitudinal, confounder-controlled studies.
Additional Links: PMID-42520457
PubMed:
Citation:
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@article {pmid42520457,
year = {2026},
author = {Fakhruddin, KS and Shahwan, M and Kamal, A and Elmobarik, O and Chaiboonyarak, T and Nugraha, AP and Jung, HS and Samaranayake, L and Porntaveetus, T},
title = {Human Lingual Biofilm Signatures in Gastrointestinal Disease: A Scoping Review.},
journal = {International dental journal},
volume = {76},
number = {5},
pages = {109762},
pmid = {42520457},
issn = {1875-595X},
mesh = {Humans ; *Biofilms ; *Tongue/microbiology ; *Gastrointestinal Diseases/microbiology ; *Microbiota ; Multiomics ; },
abstract = {INTRODUCTION AND AIMS: The tongue dorsum represents a structurally complex oral biofilm niche that has traditionally been regarded as indicative of systemic health. Recent advances in oral microbiome research and multi-omics technologies facilitate the systematic evaluation of the association between tongue coating biofilm signals and gastrointestinal disease states. However, it remains unclear whether these tongue-derived signals indicate systemic gastrointestinal pathology or merely reflect localised oral ecological disturbances. This review synthesises current evidence on tongue-derived microbial and multi-omics signatures across inflammatory, precancerous, and malignant gastrointestinal conditions, and evaluates their ecological, biological, and clinical significance.
METHODS: A scoping review was conducted in accordance with PRISMA-ScR guidelines. Five electronic databases were searched (2010-2025) for human studies analysing tongue-coating samples using microbiome or multi-omics approaches.
RESULTS: A total of twenty-five cross-sectional studies involving more than 4500 participants, primarily from East Asian populations, were included. Three recurrent patterns were identified: (1) stage-associated microbial restructuring, which involved mild non-specific alterations in inflammatory states, structured dysbiosis in precancerous conditions, and more consistent ecological configurations in malignancy; (2) convergence of functional multi-omics signals on lipid metabolism pathways across independent cohorts; and (3) significant modification of microbial and functional profiles by tongue coating phenotype, including colour, thickness and classification system.
CONCLUSIONS: Tongue-derived microbial and multi-omics signatures demonstrate reproducible cross-sectional associations with gastrointestinal diseases, exhibiting functional convergence across multiple omics layers. However, the reliance on cross-sectional study designs, absence of external validation and insufficient adjustment for confounding variables currently limit their clinical application as diagnostic biomarkers.
CLINICAL RELEVANCE: Tongue examination is clinically useful for assessing oral biofilm burden, mucosal pathology and oral hygiene in dental practice. It should not be used to diagnose gastrointestinal disease until validated by longitudinal, confounder-controlled studies.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Humans
*Biofilms
*Tongue/microbiology
*Gastrointestinal Diseases/microbiology
*Microbiota
Multiomics
RevDate: 2026-09-15
CmpDate: 2026-09-15
Comparison of Cadmium Efflux in Wheat (Triticum aestivum) Cultivars with Contrasting Cadmium Accumulation.
Bulletin of environmental contamination and toxicology, 117(3):.
Cadmium (Cd) is a highly toxic heavy metal threatening human health. Wheat readily translocates Cd to grains, posing food safety risks in contaminated soils. Screening low-Cd cultivars is therefore critical. In pot experiments with 53 wheat cultivars, Kaimai 21 (KM21) and Lunxuan 6 (LX6) showed the lowest and highest grain Cd, respectively. Under 5-10 µM Cd in hydroponics, KM21 harbored 30.1%-63.6% lower root Cd, 54.7%-69.1% lower shoot Cd, and exhibited superior root growth and Cd tolerance than LX6. Crucially, KM21 showed a 36.9% higher Cd efflux rate and a larger Cd efflux proportion than LX6 (44.3% vs. 15.5%). Real-time Cd[2+] flux measurements using Non-invasive Micro-test Technology (NMT) further confirmed higher Cd efflux capacity in KM21, which contributed to higher Cd tolerance and lower Cd accumulation. Overall, KM21 is a stably high-Cd efflux and low-Cd accumulation wheat cultivar suitable for safe production in Cd-contaminated soils.
Additional Links: PMID-42742737
PubMed:
Citation:
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@article {pmid42742737,
year = {2026},
author = {Chen, Y and Wang, G and Xie, W and Wang, R and Cao, Y and Zou, X and Yang, F and Zhu, Y and Huang, J},
title = {Comparison of Cadmium Efflux in Wheat (Triticum aestivum) Cultivars with Contrasting Cadmium Accumulation.},
journal = {Bulletin of environmental contamination and toxicology},
volume = {117},
number = {3},
pages = {},
pmid = {42742737},
issn = {1432-0800},
support = {2023YFC3804203//National Key Research and Development Program of China/ ; 2023B1212060016//Research Fund Program of Guangdong Provincial Key Laboratory of Environmental Pollution Control and Remediation Technology/ ; },
mesh = {*Cadmium/metabolism/analysis ; *Triticum/metabolism ; *Soil Pollutants/metabolism/analysis ; },
abstract = {Cadmium (Cd) is a highly toxic heavy metal threatening human health. Wheat readily translocates Cd to grains, posing food safety risks in contaminated soils. Screening low-Cd cultivars is therefore critical. In pot experiments with 53 wheat cultivars, Kaimai 21 (KM21) and Lunxuan 6 (LX6) showed the lowest and highest grain Cd, respectively. Under 5-10 µM Cd in hydroponics, KM21 harbored 30.1%-63.6% lower root Cd, 54.7%-69.1% lower shoot Cd, and exhibited superior root growth and Cd tolerance than LX6. Crucially, KM21 showed a 36.9% higher Cd efflux rate and a larger Cd efflux proportion than LX6 (44.3% vs. 15.5%). Real-time Cd[2+] flux measurements using Non-invasive Micro-test Technology (NMT) further confirmed higher Cd efflux capacity in KM21, which contributed to higher Cd tolerance and lower Cd accumulation. Overall, KM21 is a stably high-Cd efflux and low-Cd accumulation wheat cultivar suitable for safe production in Cd-contaminated soils.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Cadmium/metabolism/analysis
*Triticum/metabolism
*Soil Pollutants/metabolism/analysis
RevDate: 2026-09-15
Corrigendum to "Non-reciprocal coevolution in a fungus-gardening ant" [Mol. Phylogenet. Evol. 220 (2026) 108608].
Additional Links: PMID-42744671
Publisher:
PubMed:
Citation:
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@article {pmid42744671,
year = {2026},
author = {Beigel, K and Bringhurst, B and Greenwold, M and Kellner, K and Seal, JN},
title = {Corrigendum to "Non-reciprocal coevolution in a fungus-gardening ant" [Mol. Phylogenet. Evol. 220 (2026) 108608].},
journal = {Molecular phylogenetics and evolution},
volume = {},
number = {},
pages = {108736},
doi = {10.1016/j.ympev.2026.108736},
pmid = {42744671},
issn = {1095-9513},
}
RevDate: 2026-09-15
CmpDate: 2026-09-15
On the state of protein function prediction: a report on the fourth CAFA challenge.
bioRxiv : the preprint server for biology.
BACKGROUND: The Critical Assessment of Functional Annotation (CAFA) is a community effort held to understand the field of computational protein function prediction. Every three years, since 2010, the organizers initiate an experiment to collect function predictions on a large set of proteins and then evaluate the performance of predicting methods on a subset of proteins that have accumulated experimental annotations between the submission deadline and the evaluation time. CAFA provides an independent and rigorous assessment of the current state of the art, thus leveling the playing field, highlighting successes, revealing bottlenecks, and offering a forum for the exchange of ideas in protein science. Here, we report the results of the fourth CAFA experiment (CAFA4).
RESULTS: CAFA4 featured the participation of 148 methods from 70 research groups on a total of 46,205 unique proteins over a 5-year annotation accumulation phase, the longest in any CAFA. In a comparison across CAFA2-CAFA4 methods, the prediction of Gene Ontology (GO) terms has clearly improved across all three GO aspects and traditional evaluation settings. While not achieving the first rank, several CAFA2 and CAFA3 methods featured in the top ten methods in many evaluations, suggesting that earlier methods still hold relevance. The performance is weaker in the newly introduced "partial knowledge" evaluation category (proteins with experimental annotations before submission deadline that gained additional annotations in the same GO aspect during the annotation accumulation phase), highlighting the need for a new class of methods. The rankings of the methods were stable over the years in traditional evaluation settings, but less so in the new partial knowledge evaluation. Overall, the field continues to progress with some influx of new participants. Sustained efforts will be necessary to substantially advance it.
Additional Links: PMID-42146430
PubMed:
Citation:
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@article {pmid42146430,
year = {2026},
author = {Ramola, R and De Paolis Kaluza, MC and Piovesan, D and Peng, Y and Joshi, P and Mehdiabadi, M and Quaglia, F and Pancsa, R and Chemes, LB and Ahn, H and Altenhoff, AM and Asgari, E and Aspromonte, MC and Atalay, V and Babbi, G and Baldazzi, D and Barot, MM and Ben-Hur, A and Benso, A and Berenberg, D and Björne, J and Boecker, F and Boldi, P and Bonello, J and Bordin, N and Borole, P and Boroojeny, AE and Cao, R and Di Carlo, S and Casadio, R and Casiraghi, E and Chang, JM and Chen, C and Chen, TM and Cheng, J and Chiu, S and Dalkıran, A and Davidović, RS and Dessimoz, C and Diao, R and Djeddi, WE and Dogan, T and Flannery, ST and Fontana, P and Frasca, M and Freddolino, L and Gemović, B and Gillis, J and Ginter, F and Gligorijevic, V and Grossi, G and Heinzinger, M and Hippe, K and Hoehndorf, R and Holm, L and Hou, J and Hover, JR and Huang, YT and Ispano, E and Jabin, S and Jain, A and Jones, DT and Kaewphan, S and Kagaya, Y and Kanerva, J and Kihara, D and Kulmanov, M and Kumar, S and Kurgan, L and Lavezzo, E and Lees, J and Liao, WH and Lin, H and Linial, M and Littmann, M and Liu, L and Liu, T and Liu, YW and Makrodimitris, S and Manuto, L and Martelli, PL and Mchardy, AC and Merino, GA and Milone, DH and Mishra, S and Mofrad, MRK and Moi, D and Nakamura, T and Narsapuram, VK and Nugnes, MV and Obayashi, T and Ofer, D and Paccanaro, A and Perovic, VR and Petrini, A and Politano, G and Raimondi, D and Rappoport, N and Rehman, HU and Reijnders, MJMF and Reinders, MJT and Renfrew, PD and Rifaioglu, AS and Romero, AE and Saraswathi, A and Savojardo, C and Scholes, HM and Schoof, H and Shen, Y and Sillitoe, I and Stegmayer, G and Stern, A and Tiittanen, H and Toonsi, S and Toppo, S and Toronen, P and Torres, M and Trucco, G and Valentini, G and Veljkovic, N and Vesztrocy, AW and Vidulin, V and Villegas-Morcillo, A and Virtanen, A and Vranken, W and Vucetic, S and Wan, C and Wang, Z and Wass, MN and Waterhouse, RM and Ben Yahia, S and Yang, H and Yao, S and You, R and Yunes, J and Zhang, C and Zhang, Y and Zhao, C and Zhou, X and Zhu, YH and Zhu, S and Zhu, H and Özsari, G and Rost, B and Orengo, C and Robinson-Rechavi, M and Durand, D and Brenner, SE and Greene, CS and Mooney, SD and Tosatto, SCE and Friedberg, I and Radivojac, P},
title = {On the state of protein function prediction: a report on the fourth CAFA challenge.},
journal = {bioRxiv : the preprint server for biology},
volume = {},
number = {},
pages = {},
pmid = {42146430},
issn = {2692-8205},
abstract = {BACKGROUND: The Critical Assessment of Functional Annotation (CAFA) is a community effort held to understand the field of computational protein function prediction. Every three years, since 2010, the organizers initiate an experiment to collect function predictions on a large set of proteins and then evaluate the performance of predicting methods on a subset of proteins that have accumulated experimental annotations between the submission deadline and the evaluation time. CAFA provides an independent and rigorous assessment of the current state of the art, thus leveling the playing field, highlighting successes, revealing bottlenecks, and offering a forum for the exchange of ideas in protein science. Here, we report the results of the fourth CAFA experiment (CAFA4).
RESULTS: CAFA4 featured the participation of 148 methods from 70 research groups on a total of 46,205 unique proteins over a 5-year annotation accumulation phase, the longest in any CAFA. In a comparison across CAFA2-CAFA4 methods, the prediction of Gene Ontology (GO) terms has clearly improved across all three GO aspects and traditional evaluation settings. While not achieving the first rank, several CAFA2 and CAFA3 methods featured in the top ten methods in many evaluations, suggesting that earlier methods still hold relevance. The performance is weaker in the newly introduced "partial knowledge" evaluation category (proteins with experimental annotations before submission deadline that gained additional annotations in the same GO aspect during the annotation accumulation phase), highlighting the need for a new class of methods. The rankings of the methods were stable over the years in traditional evaluation settings, but less so in the new partial knowledge evaluation. Overall, the field continues to progress with some influx of new participants. Sustained efforts will be necessary to substantially advance it.},
}
RevDate: 2026-09-15
CmpDate: 2026-09-15
Balanced DNA interpolation improves learning of genetic distance-informed embeddings in plants.
PLoS computational biology, 22(9):e1014722.
In taxonomic research, traditional phylogenetic tree and structure analyses of genetic data are increasingly complemented by machine-learning-based identification and representation learning. Although the amount of DNA data needed to train state-of-the-art machine learning models often exceeds what can realistically be collected and sequenced in biological studies, the number of samples can be extended artificially through data augmentation. Genetic data augmentation usually refers to the introduction of random base variations, translocations, and reverse complementing. These augmentations do not take into account the inherent structures of populations and species, potentially blurring the lines between entities within genetic datasets. Here, we propose DNAInterpolator, an approach based on interpolation of DNA sequences within a given dataset that presents a neighbor-guided alternative to random mutations. We tested interpolation as an augmentation technique using four flowering plant datasets and an artificial neural network trained to predict genetic distances between paired samples. To address unequally distributed distances within our training datasets, we examined the effect of balancing the distance distribution by curating interpolated sequences. We found that balancing helps models capture genetic distances across the full distance range by strengthening performance in underrepresented regions of the distribution. Our new approach leverages the potential of taxonomic DNA datasets for modern machine learning applications.
Additional Links: PMID-42691111
PubMed:
Citation:
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@article {pmid42691111,
year = {2026},
author = {Kösters, LM and Karbstein, K and Hodač, L and Albreht, L and Sahuquillo Balbuena, E and Botello, D and Hardy, O and Odufuwa, P and Pardo Otero, E and Phang, A and Pimentel, M and Piñeiro, R and Smith, J and Wilkie, P and Mäder, P and Wäldchen, J},
title = {Balanced DNA interpolation improves learning of genetic distance-informed embeddings in plants.},
journal = {PLoS computational biology},
volume = {22},
number = {9},
pages = {e1014722},
pmid = {42691111},
issn = {1553-7358},
mesh = {Computational Biology/methods ; Machine Learning ; *DNA, Plant/genetics ; Phylogeny ; *Plants/genetics/classification ; Neural Networks, Computer ; *Sequence Analysis, DNA/methods ; Models, Genetic ; },
abstract = {In taxonomic research, traditional phylogenetic tree and structure analyses of genetic data are increasingly complemented by machine-learning-based identification and representation learning. Although the amount of DNA data needed to train state-of-the-art machine learning models often exceeds what can realistically be collected and sequenced in biological studies, the number of samples can be extended artificially through data augmentation. Genetic data augmentation usually refers to the introduction of random base variations, translocations, and reverse complementing. These augmentations do not take into account the inherent structures of populations and species, potentially blurring the lines between entities within genetic datasets. Here, we propose DNAInterpolator, an approach based on interpolation of DNA sequences within a given dataset that presents a neighbor-guided alternative to random mutations. We tested interpolation as an augmentation technique using four flowering plant datasets and an artificial neural network trained to predict genetic distances between paired samples. To address unequally distributed distances within our training datasets, we examined the effect of balancing the distance distribution by curating interpolated sequences. We found that balancing helps models capture genetic distances across the full distance range by strengthening performance in underrepresented regions of the distribution. Our new approach leverages the potential of taxonomic DNA datasets for modern machine learning applications.},
}
MeSH Terms:
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Computational Biology/methods
Machine Learning
*DNA, Plant/genetics
Phylogeny
*Plants/genetics/classification
Neural Networks, Computer
*Sequence Analysis, DNA/methods
Models, Genetic
RevDate: 2026-09-14
CmpDate: 2026-09-14
Integrated metagenomic and metabolomic analysis identifies severity-specific inflammatory and metabolic signatures in post-stroke depression.
Gut microbes, 18(1):2726620.
Post-stroke depression (PSD) is a common complication that significantly impacts patient prognosis. This study aimed to systematically characterize the associations among gut microbial ecology, metabolic profiles, and inflammatory responses across different severities of PSD. We conducted metagenomic sequencing, non-targeted metabolomics, and serum cytokine analysis (IL-1β, IL-6, IL-10, IL-18, TNF-α, IFN-γ, and CRP) in 91 patients with varying degrees of PSD and non-PSD controls. Bioinformatics analyzes were employed to construct multi-omics association networks and machine learning models. Results indicated that PSD patients exhibited significantly increased gut microbiota alpha-diversity, suggesting dysbiosis. Mild depression was characterized by compensatory neural signaling activation, whereas the moderate depression group exhibited abnormalities in tryptophan/indole metabolism, oxidative stress-related metabolic imbalances, and functional decompensation. Further analyzes suggested that Alistipes, Blautia_A, Evtepia gabavorous, and Lachnospira were associated with inflammatory features, GABA-related metabolic alterations, aromatic amino acid/indole metabolism, and lipid-amino acid metabolism, respectively. Under a more rigorous 10-fold cross-validation framework, the performance of different multi-omics combination models showed heterogeneity; however, some combinations still demonstrated superior discriminatory ability compared to single-omics approaches. This study provides multi-omics clues suggesting associations between different PSD severity levels and features such as increased Alistipes abundance, reduced antioxidant capacity, and altered tryptophan metabolism. It provides candidate biomarker combinations that may be useful for PSD stratification and suggests that the gut microbiome may represent a potential target for future PSD intervention. In summary, PSD may be associated with dynamic alterations along the "gut-brain-inflammation-metabolism" axis. These findings provide integrated evidence for microbial, metabolic, and inflammatory abnormalities across different PSD severity levels, but still require validation in larger samples, longitudinal cohorts, and mechanistic studies.
Additional Links: PMID-42734183
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Citation:
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@article {pmid42734183,
year = {2026},
author = {Chen, W and Pan, Y and Chen, M and Zhou, S and Liu, X and Sun, M and Yang, Z and Zhi, Y},
title = {Integrated metagenomic and metabolomic analysis identifies severity-specific inflammatory and metabolic signatures in post-stroke depression.},
journal = {Gut microbes},
volume = {18},
number = {1},
pages = {2726620},
pmid = {42734183},
issn = {1949-0984},
mesh = {Humans ; *Stroke/complications/metabolism ; Metabolomics ; Metagenomics ; *Depression/metabolism/etiology/microbiology ; Female ; Multiomics ; Male ; *Gastrointestinal Microbiome ; Inflammation/metabolism ; Middle Aged ; Aged ; Cytokines/blood ; Bacteria/classification/genetics/isolation & purification ; Dysbiosis/microbiology ; Biomarkers/blood ; },
abstract = {Post-stroke depression (PSD) is a common complication that significantly impacts patient prognosis. This study aimed to systematically characterize the associations among gut microbial ecology, metabolic profiles, and inflammatory responses across different severities of PSD. We conducted metagenomic sequencing, non-targeted metabolomics, and serum cytokine analysis (IL-1β, IL-6, IL-10, IL-18, TNF-α, IFN-γ, and CRP) in 91 patients with varying degrees of PSD and non-PSD controls. Bioinformatics analyzes were employed to construct multi-omics association networks and machine learning models. Results indicated that PSD patients exhibited significantly increased gut microbiota alpha-diversity, suggesting dysbiosis. Mild depression was characterized by compensatory neural signaling activation, whereas the moderate depression group exhibited abnormalities in tryptophan/indole metabolism, oxidative stress-related metabolic imbalances, and functional decompensation. Further analyzes suggested that Alistipes, Blautia_A, Evtepia gabavorous, and Lachnospira were associated with inflammatory features, GABA-related metabolic alterations, aromatic amino acid/indole metabolism, and lipid-amino acid metabolism, respectively. Under a more rigorous 10-fold cross-validation framework, the performance of different multi-omics combination models showed heterogeneity; however, some combinations still demonstrated superior discriminatory ability compared to single-omics approaches. This study provides multi-omics clues suggesting associations between different PSD severity levels and features such as increased Alistipes abundance, reduced antioxidant capacity, and altered tryptophan metabolism. It provides candidate biomarker combinations that may be useful for PSD stratification and suggests that the gut microbiome may represent a potential target for future PSD intervention. In summary, PSD may be associated with dynamic alterations along the "gut-brain-inflammation-metabolism" axis. These findings provide integrated evidence for microbial, metabolic, and inflammatory abnormalities across different PSD severity levels, but still require validation in larger samples, longitudinal cohorts, and mechanistic studies.},
}
MeSH Terms:
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Humans
*Stroke/complications/metabolism
Metabolomics
Metagenomics
*Depression/metabolism/etiology/microbiology
Female
Multiomics
Male
*Gastrointestinal Microbiome
Inflammation/metabolism
Middle Aged
Aged
Cytokines/blood
Bacteria/classification/genetics/isolation & purification
Dysbiosis/microbiology
Biomarkers/blood
RevDate: 2026-09-14
CmpDate: 2026-09-14
Integrative Transcriptomic Network Modeling Coupled with Patient-Derived Validation for Circulating lncRNA Biomarker Discovery in NAFLD: A Comprehensive Workflow.
Methods in molecular biology (Clifton, N.J.), 3074:481-527.
.: Nonalcoholic fatty liver disease (NAFLD) is a significant global health concern, impacting roughly 25% of people and leading to chronic liver conditions. It involves excess fat accumulation in the liver without significant alcohol intake and can develop into nonalcoholic steatohepatitis (NASH), fibrosis, or cirrhosis. While liver biopsy remains the gold standard for diagnosis, its invasive nature and associated risks restrict its routine use. Noninvasive biomarkers, such as serum ALT, AST, and various composite scores, are available; however, their clinical usefulness is often limited by variable sensitivity and specificity across different populations and disease stages. To overcome these limitations, this chapter offers a comprehensive, reproducible protocol for identifying and clinically validating circulating long noncoding RNA (lncRNA) biomarkers for NAFLD and NASH. The workflow integrates bioinformatic analysis of four Gene Expression Omnibus (GEO) transcriptomic datasets (two human and two murine cohorts) with network-based inference to construct a NAFLD-related lncRNA-miRNA-mRNA coregulatory network. This is followed by candidate prioritization based on cross-dataset evidence and a literature review. Candidate lncRNAs are then experimentally validated in patient-derived blood samples using quantitative PCR (qPCR), and their diagnostic performance is quantified using receiver operating characteristic (ROC) analysis, both as individual markers and multi-lncRNA panels. Circulating lncRNAs are detected in diverse biofluids, remain stable under standard preanalytical conditions, and are often tissue-specific. This integrated approach facilitates the development of more precise, scalable, and noninvasive biomarkers for NAFLD/NASH. The chapter further emphasizes essential translational steps, including preanalytical standardization, analytical validation, and validation in independent patient cohorts with relevant clinical endpoints.
Additional Links: PMID-42734769
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Citation:
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@article {pmid42734769,
year = {2027},
author = {Hussein, MA and Abdelnaser, A},
title = {Integrative Transcriptomic Network Modeling Coupled with Patient-Derived Validation for Circulating lncRNA Biomarker Discovery in NAFLD: A Comprehensive Workflow.},
journal = {Methods in molecular biology (Clifton, N.J.)},
volume = {3074},
number = {},
pages = {481-527},
pmid = {42734769},
issn = {1940-6029},
mesh = {*Non-alcoholic Fatty Liver Disease/genetics/blood/diagnosis ; Humans ; *RNA, Long Noncoding/genetics/blood ; Biomarkers/blood ; Animals ; *Gene Expression Profiling/methods ; Workflow ; Computational Biology/methods ; *Transcriptome ; *Gene Regulatory Networks ; Mice ; MicroRNAs/genetics ; },
abstract = {.: Nonalcoholic fatty liver disease (NAFLD) is a significant global health concern, impacting roughly 25% of people and leading to chronic liver conditions. It involves excess fat accumulation in the liver without significant alcohol intake and can develop into nonalcoholic steatohepatitis (NASH), fibrosis, or cirrhosis. While liver biopsy remains the gold standard for diagnosis, its invasive nature and associated risks restrict its routine use. Noninvasive biomarkers, such as serum ALT, AST, and various composite scores, are available; however, their clinical usefulness is often limited by variable sensitivity and specificity across different populations and disease stages. To overcome these limitations, this chapter offers a comprehensive, reproducible protocol for identifying and clinically validating circulating long noncoding RNA (lncRNA) biomarkers for NAFLD and NASH. The workflow integrates bioinformatic analysis of four Gene Expression Omnibus (GEO) transcriptomic datasets (two human and two murine cohorts) with network-based inference to construct a NAFLD-related lncRNA-miRNA-mRNA coregulatory network. This is followed by candidate prioritization based on cross-dataset evidence and a literature review. Candidate lncRNAs are then experimentally validated in patient-derived blood samples using quantitative PCR (qPCR), and their diagnostic performance is quantified using receiver operating characteristic (ROC) analysis, both as individual markers and multi-lncRNA panels. Circulating lncRNAs are detected in diverse biofluids, remain stable under standard preanalytical conditions, and are often tissue-specific. This integrated approach facilitates the development of more precise, scalable, and noninvasive biomarkers for NAFLD/NASH. The chapter further emphasizes essential translational steps, including preanalytical standardization, analytical validation, and validation in independent patient cohorts with relevant clinical endpoints.},
}
MeSH Terms:
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*Non-alcoholic Fatty Liver Disease/genetics/blood/diagnosis
Humans
*RNA, Long Noncoding/genetics/blood
Biomarkers/blood
Animals
*Gene Expression Profiling/methods
Workflow
Computational Biology/methods
*Transcriptome
*Gene Regulatory Networks
Mice
MicroRNAs/genetics
RevDate: 2026-09-14
CmpDate: 2026-09-14
[Analysis of the global disease burden of cervical cancer in women aged 65 years and older based on the global burden of disease database].
Zhonghua yu fang yi xue za zhi [Chinese journal of preventive medicine], 60(9):1436-1446.
Objective: Based on the Global Burden of Disease (GBD) database, this study analyzed the disease burden and attributable risk factors of cervical cancer among women aged 65 years and older globally from 1990 to 2021, and explored its association with the Socio-demographic Index (SDI) as well as age-specific distribution characteristics. Methods: This ecological study utilized the GBD database to extract data on the number of incident cases, age-standardized incidence rate (ASIR), number of deaths, age-standardized mortality rate (ASMR), disability-adjusted life years (DALY), age-standardized DALY rate (ASDR), and risk factor-attributable burden for cervical cancer in women aged ≥65 years from 1990 to 2021. The average annual percent change (AAPC) was calculated using Joinpoint regression analysis. Spearman rank correlation analysis was employed to assess the association between ASIR, ASDR, and SDI. Locally weighted regression (LOESS) was applied to fit smooth curves to illustrate expected trends across different SDI levels. Results: From 1990 to 2021, the ASIR of cervical cancer among older women decreased from 41.23/100 000 (95%UI: 37.71/100 000-44.45/100 000) to 32.43/100 000 (95%UI: 28.61/100 000-35.57/100 000) [AAPC:-0.8(95%CI:-0.9 to -0.6)]. The ASMR declined from 35.45/100 000 (95%UI: 32.24/100 000-38.54/100 000) to 25.20/100 000 (95%UI: 22.23/100 000-27.62/100 000) [AAPC:-1.1(95%CI:-1.2 to -1.0)]. The ASDR decreased from 658.01/100 000 (95%UI: 602.42/100 000-714.72/100 000) to 467.29/100 000 (95%UI: 416.92/100 000-510.34/100 000) [AAPC:-1.1(95%CI:-1.2 to -0.9)]. A negative correlation was observed between cervical cancer burden and SDI globally and across the 21 GBD regions (r=-0.881 4, P<0.001), with a greater burden in regions with lower SDI among the 204 countries and territories (r=-0.713 4, P<0.001). The number of incident cases, deaths, and DALYs in the 65-69 and 70-74 age groups accounted for 64.82%, 56.22%, and 68.96% of the total for women aged ≥65 years, respectively. The attributable risk burden from smoking [AAPC:-2.1(95%CI:-2.2 to -2.0)] and high-risk sexual behavior [AAPC:-1.1(95%CI:-1.2 to -0.9)] both decreased over time, this declining trend in attributable risk burden for smoking and high-risk sexual behavior was also observed with increasing age. Conclusions: Population aging has contributed to an increase in the absolute burden of cervical cancer among older women, with those aged 65-74 years identified as a key population requiring attention. Expanding the coverage and age range of screening programs is essential for further reducing the the burden of cervical cancer.
Additional Links: PMID-42736147
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@article {pmid42736147,
year = {2026},
author = {Yuan, XH and Chen, Y and Kuang, ZY and Fang, LY and Wang, Y and Xie, Y and Fang, YH and Wang, RX and Sui, BL and Zhang, Y},
title = {[Analysis of the global disease burden of cervical cancer in women aged 65 years and older based on the global burden of disease database].},
journal = {Zhonghua yu fang yi xue za zhi [Chinese journal of preventive medicine]},
volume = {60},
number = {9},
pages = {1436-1446},
doi = {10.3760/cma.j.cn112150-20260207-00118},
pmid = {42736147},
issn = {0253-9624},
support = {CI2023C025YL//Key Collaborative Research Projects of Scientific and Technological Innovation Project/ ; ZZ17-RKX-01//Fundamental Research Funds for the Central Public Welfare Research Institutes of the China Academy of Chinese Medical Sciences/ ; },
mesh = {Female ; Humans ; *Uterine Cervical Neoplasms/epidemiology ; *Global Burden of Disease ; Aged ; Risk Factors ; Databases, Factual ; Incidence ; },
abstract = {Objective: Based on the Global Burden of Disease (GBD) database, this study analyzed the disease burden and attributable risk factors of cervical cancer among women aged 65 years and older globally from 1990 to 2021, and explored its association with the Socio-demographic Index (SDI) as well as age-specific distribution characteristics. Methods: This ecological study utilized the GBD database to extract data on the number of incident cases, age-standardized incidence rate (ASIR), number of deaths, age-standardized mortality rate (ASMR), disability-adjusted life years (DALY), age-standardized DALY rate (ASDR), and risk factor-attributable burden for cervical cancer in women aged ≥65 years from 1990 to 2021. The average annual percent change (AAPC) was calculated using Joinpoint regression analysis. Spearman rank correlation analysis was employed to assess the association between ASIR, ASDR, and SDI. Locally weighted regression (LOESS) was applied to fit smooth curves to illustrate expected trends across different SDI levels. Results: From 1990 to 2021, the ASIR of cervical cancer among older women decreased from 41.23/100 000 (95%UI: 37.71/100 000-44.45/100 000) to 32.43/100 000 (95%UI: 28.61/100 000-35.57/100 000) [AAPC:-0.8(95%CI:-0.9 to -0.6)]. The ASMR declined from 35.45/100 000 (95%UI: 32.24/100 000-38.54/100 000) to 25.20/100 000 (95%UI: 22.23/100 000-27.62/100 000) [AAPC:-1.1(95%CI:-1.2 to -1.0)]. The ASDR decreased from 658.01/100 000 (95%UI: 602.42/100 000-714.72/100 000) to 467.29/100 000 (95%UI: 416.92/100 000-510.34/100 000) [AAPC:-1.1(95%CI:-1.2 to -0.9)]. A negative correlation was observed between cervical cancer burden and SDI globally and across the 21 GBD regions (r=-0.881 4, P<0.001), with a greater burden in regions with lower SDI among the 204 countries and territories (r=-0.713 4, P<0.001). The number of incident cases, deaths, and DALYs in the 65-69 and 70-74 age groups accounted for 64.82%, 56.22%, and 68.96% of the total for women aged ≥65 years, respectively. The attributable risk burden from smoking [AAPC:-2.1(95%CI:-2.2 to -2.0)] and high-risk sexual behavior [AAPC:-1.1(95%CI:-1.2 to -0.9)] both decreased over time, this declining trend in attributable risk burden for smoking and high-risk sexual behavior was also observed with increasing age. Conclusions: Population aging has contributed to an increase in the absolute burden of cervical cancer among older women, with those aged 65-74 years identified as a key population requiring attention. Expanding the coverage and age range of screening programs is essential for further reducing the the burden of cervical cancer.},
}
MeSH Terms:
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Female
Humans
*Uterine Cervical Neoplasms/epidemiology
*Global Burden of Disease
Aged
Risk Factors
Databases, Factual
Incidence
RevDate: 2026-09-15
CmpDate: 2026-09-15
Educating minds with generative AI.
Communications psychology, 4(1):.
Generative artificial intelligence (GenAI) is rapidly entering education, framed as a tool for efficiency and personalization. In this Perspective, we argue this obscures a deeper transformation. Schools are cognitive ecologies in which tools and social practices actively shape learning. GenAI restructures this ecology, redistributing epistemic labour, consolidating pedagogical functions, and reorganizing how knowledge is accessed, produced, and evaluated. Unlike most educational technologies, it is active, persistent, and generalist. We identify two enduring misalignments: a pedagogical gap between learning sciences and AI design, and a goal gap between measurable performance and developmental aims. Both gaps reflect logics already embedded within existing educational systems organized around efficiency, standardization, and control. GenAI does not introduce but risks entrenching and amplifying these gaps. Rather than accommodating GenAI through technical adjustments, we propose treating it as a diagnostic opportunity to redesign schooling for embodied, collaborative, and distinctly human forms of learning.
Additional Links: PMID-42736335
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@article {pmid42736335,
year = {2026},
author = {Di Paolo, LD and Clark, A and Wachter, T},
title = {Educating minds with generative AI.},
journal = {Communications psychology},
volume = {4},
number = {1},
pages = {},
pmid = {42736335},
issn = {2731-9121},
abstract = {Generative artificial intelligence (GenAI) is rapidly entering education, framed as a tool for efficiency and personalization. In this Perspective, we argue this obscures a deeper transformation. Schools are cognitive ecologies in which tools and social practices actively shape learning. GenAI restructures this ecology, redistributing epistemic labour, consolidating pedagogical functions, and reorganizing how knowledge is accessed, produced, and evaluated. Unlike most educational technologies, it is active, persistent, and generalist. We identify two enduring misalignments: a pedagogical gap between learning sciences and AI design, and a goal gap between measurable performance and developmental aims. Both gaps reflect logics already embedded within existing educational systems organized around efficiency, standardization, and control. GenAI does not introduce but risks entrenching and amplifying these gaps. Rather than accommodating GenAI through technical adjustments, we propose treating it as a diagnostic opportunity to redesign schooling for embodied, collaborative, and distinctly human forms of learning.},
}
RevDate: 2026-09-15
CmpDate: 2026-09-15
PhageScout: Protease Cleavage Site Prediction Using an Experimental Substrate Phage Display Motif-Based Approach.
International journal of molecular sciences, 27(17):.
Identification of protease cleavage sites is essential for understanding biological regulation and disease mechanisms, yet many predictive approaches rely on annotated substrates and curated databases, limiting performance for poorly characterized proteases. We present PhageScout, a framework for database-independent generation of protease-specific features to predict cleavage sites using de novo experimental substrate phage display screening. We screened a randomized 5-mer phage display library against two neutrophil serine proteases (cathepsin G, elastase). Cleaved peptides generated position weight matrices (PWMs) and peptide enrichment scores to evaluate cleavage-site likelihood across substrate sequences. Sequence-derived scores were integrated with structural features, including accessibility and flexibility, using XGBoost classification models. Performance was benchmarked against annotated cleavage sites from the MEROPS peptidase database as reference data. Phage-derived PWM scores alone captured protease preferences and discriminated cleavage sites from background sites. Without model fitting, PWM scores achieved an area under the curve (AUC) of 0.756 (95%CI: 0.714-0.797) (cathepsin G) and 0.787 (95%CI: 0.753-0.821) (elastase). Combining broad and specific phage-derived scores improved cathepsin G prediction (AUC = 0.783), whereas this improvement was not observed for elastase. Compared to only phage-derived features, XGBoost models integrating phage sequence and structural features provided modest gains for elastase (AUC = 0.775 to 0.806), with phage-derived features ranking among the strongest predictors, but not cathepsin G (AUC = 0.702 to 0.710). Our findings demonstrate that PhageScout can use experimentally derived cleavage signatures to generate protease-specific predictive features and prioritize protease cleavage sites, providing a framework that warrants further validation across diverse proteases and biological contexts.
Additional Links: PMID-42737495
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@article {pmid42737495,
year = {2026},
author = {Yu, E and Holding, ML and Huang, R and Chan, A and Teney, C and Kretz, CA},
title = {PhageScout: Protease Cleavage Site Prediction Using an Experimental Substrate Phage Display Motif-Based Approach.},
journal = {International journal of molecular sciences},
volume = {27},
number = {17},
pages = {},
pmid = {42737495},
issn = {1422-0067},
support = {/CAPMC/CIHR/Canada ; //Natural Sciences and Engineering Research Council of Canada/ ; /NH/NIH HHS/United States ; },
mesh = {Peptide Library ; Substrate Specificity ; *Cathepsin G/metabolism/chemistry ; Humans ; Proteolysis ; *Computational Biology/methods ; Amino Acid Sequence ; *Peptide Hydrolases/metabolism/chemistry ; },
abstract = {Identification of protease cleavage sites is essential for understanding biological regulation and disease mechanisms, yet many predictive approaches rely on annotated substrates and curated databases, limiting performance for poorly characterized proteases. We present PhageScout, a framework for database-independent generation of protease-specific features to predict cleavage sites using de novo experimental substrate phage display screening. We screened a randomized 5-mer phage display library against two neutrophil serine proteases (cathepsin G, elastase). Cleaved peptides generated position weight matrices (PWMs) and peptide enrichment scores to evaluate cleavage-site likelihood across substrate sequences. Sequence-derived scores were integrated with structural features, including accessibility and flexibility, using XGBoost classification models. Performance was benchmarked against annotated cleavage sites from the MEROPS peptidase database as reference data. Phage-derived PWM scores alone captured protease preferences and discriminated cleavage sites from background sites. Without model fitting, PWM scores achieved an area under the curve (AUC) of 0.756 (95%CI: 0.714-0.797) (cathepsin G) and 0.787 (95%CI: 0.753-0.821) (elastase). Combining broad and specific phage-derived scores improved cathepsin G prediction (AUC = 0.783), whereas this improvement was not observed for elastase. Compared to only phage-derived features, XGBoost models integrating phage sequence and structural features provided modest gains for elastase (AUC = 0.775 to 0.806), with phage-derived features ranking among the strongest predictors, but not cathepsin G (AUC = 0.702 to 0.710). Our findings demonstrate that PhageScout can use experimentally derived cleavage signatures to generate protease-specific predictive features and prioritize protease cleavage sites, providing a framework that warrants further validation across diverse proteases and biological contexts.},
}
MeSH Terms:
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hide MeSH Terms
Peptide Library
Substrate Specificity
*Cathepsin G/metabolism/chemistry
Humans
Proteolysis
*Computational Biology/methods
Amino Acid Sequence
*Peptide Hydrolases/metabolism/chemistry
RevDate: 2026-09-15
CmpDate: 2026-09-15
Species identification, discovery, and biomonitoring: Strategic priorities for DNA barcoding in Europe, set in a global context.
Bioscience, 76(9):776-786.
The International Barcode of Life (iBOL) initiative is building a globally accessible DNA-based system for species identification and discovery. This paper outlines the mission and strategic priorities for the iBOL community in Europe (iBOL Europe), set in a global context. The mission of iBOL Europe is to produce, curate, and provide access to a complete DNA barcode reference library of European eukaryotic biodiversity, catalyzing species discovery and enabling comprehensive, harmonized species identification and biomonitoring, and supporting the global iBOL program. Immediate objectives include completing reference libraries for priority taxa, democratizing access to sequencing technologies, and strengthening a distributed community of practice. Key actions identified span five thematic areas: community building, sample collection and taxonomic verification, sequencing infrastructure, data management, and mainstreaming DNA-based approaches to meet societal needs. The strategy emphasizes integration with European research infrastructures to ensure long-term sustainability and resilience for biodiversity genomics in Europe.
Additional Links: PMID-42741543
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@article {pmid42741543,
year = {2026},
author = {Hollingsworth, PM and Fantoni, K and Koureas, D and Arakelyan, M and Aravanopoulos, FA and Bacela-Spychalska, K and Ballesteros-Mejia, L and Beja, P and Bonchev, GN and Bou Dagher Kharrat, M and Bourlat, SJ and Chkhartishvili, T and Čiampor, F and Costa, FO and Csabai, Z and Dankova, G and Ekrem, T and Emerson, B and Ferreira, S and Gadawski, P and Gkagkavouzis, K and Hebert, PDN and Ichim, MC and Jelić, M and Kaitetzidou, E and Kalamujić Stroil, B and Kamenova, S and Keskin, E and Laini, A and Lawniczak, M and Madesis, P and Montagna, M and Mutanen, M and Peters, RS and Price, B and Rewicz, T and Rougerie, R and Rulik, B and Szucsich, N and Vos, R and Goodall-Copestake, WP and Triantafyllidis, A and Grabowski, M},
title = {Species identification, discovery, and biomonitoring: Strategic priorities for DNA barcoding in Europe, set in a global context.},
journal = {Bioscience},
volume = {76},
number = {9},
pages = {776-786},
pmid = {42741543},
issn = {0006-3568},
abstract = {The International Barcode of Life (iBOL) initiative is building a globally accessible DNA-based system for species identification and discovery. This paper outlines the mission and strategic priorities for the iBOL community in Europe (iBOL Europe), set in a global context. The mission of iBOL Europe is to produce, curate, and provide access to a complete DNA barcode reference library of European eukaryotic biodiversity, catalyzing species discovery and enabling comprehensive, harmonized species identification and biomonitoring, and supporting the global iBOL program. Immediate objectives include completing reference libraries for priority taxa, democratizing access to sequencing technologies, and strengthening a distributed community of practice. Key actions identified span five thematic areas: community building, sample collection and taxonomic verification, sequencing infrastructure, data management, and mainstreaming DNA-based approaches to meet societal needs. The strategy emphasizes integration with European research infrastructures to ensure long-term sustainability and resilience for biodiversity genomics in Europe.},
}
RevDate: 2026-09-15
CmpDate: 2026-09-15
An integrated culturomic and genomic database and analysis platform for methanogenic archaea.
Database : the journal of biological databases and curation, 2026:.
Methanogenic archaea research is challenged by limited strain resources, fragmented genomic data, inconsistent genome quality, substantial uncultured lineages, and difficulties in laboratory culturing, hindering advances in biogas production, climate mitigation, and microbial ecology. These archaea play crucial roles in global carbon cycling and anaerobic environments, yet scattered data and unculturable strains limit systematic studies and applications. To address this, we created MethArDB (Methanogenic Archaeal Genome Database), a specialized database for methanogenic archaea, compiling 3919 genomes, 87 host-associated plasmids, and 42 phages, with standardized quality classifications (complete, scaffold, draft), protein sequences, and metadata on geography, habitats, metabolism, and inheritable elements. Integrated MethArCT (Methanogenic Archaeal Culturomics Toolkit) employs a dual-threshold orthologous/paralogous protein analysis to evaluate metabolic pathway completeness, predicting cultivation parameters and suggesting candidate cultivation strategies, including potential medium formulations and conditions, to support strain isolation. Overall, MethArDB and MethArCT form an integrated platform combining genomics and culturomics to facilitate methanogenic archaea research. Database URL: http://methardb.cn.
Additional Links: PMID-42742455
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@article {pmid42742455,
year = {2026},
author = {Chen, J and Ren, S and Tong, Z and Guan, Z and Zhang, W and Ren, S and Ma, L and Kong, L and Chong, H and Wang, Z and Yong, X and Yan, S and Wang, Y and Zhou, J},
title = {An integrated culturomic and genomic database and analysis platform for methanogenic archaea.},
journal = {Database : the journal of biological databases and curation},
volume = {2026},
number = {},
pages = {},
doi = {10.1093/database/baag055},
pmid = {42742455},
issn = {1758-0463},
support = {U24A20543//National Natural Science Foundation of China/ ; 32371538//National Natural Science Foundation of China/ ; JASTIF, CX [23]1038//Jiangsu Agriculture Science and Technology Innovation/ ; XTSW4C01//Jiangsu Synergetic Innovation Center for Advanced Bio-Manufacture/ ; },
mesh = {*Genome, Archaeal/genetics ; *Databases, Genetic ; *Archaea/genetics/metabolism ; *Genomics/methods ; Biocuration ; *Methane/metabolism ; },
abstract = {Methanogenic archaea research is challenged by limited strain resources, fragmented genomic data, inconsistent genome quality, substantial uncultured lineages, and difficulties in laboratory culturing, hindering advances in biogas production, climate mitigation, and microbial ecology. These archaea play crucial roles in global carbon cycling and anaerobic environments, yet scattered data and unculturable strains limit systematic studies and applications. To address this, we created MethArDB (Methanogenic Archaeal Genome Database), a specialized database for methanogenic archaea, compiling 3919 genomes, 87 host-associated plasmids, and 42 phages, with standardized quality classifications (complete, scaffold, draft), protein sequences, and metadata on geography, habitats, metabolism, and inheritable elements. Integrated MethArCT (Methanogenic Archaeal Culturomics Toolkit) employs a dual-threshold orthologous/paralogous protein analysis to evaluate metabolic pathway completeness, predicting cultivation parameters and suggesting candidate cultivation strategies, including potential medium formulations and conditions, to support strain isolation. Overall, MethArDB and MethArCT form an integrated platform combining genomics and culturomics to facilitate methanogenic archaea research. Database URL: http://methardb.cn.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Genome, Archaeal/genetics
*Databases, Genetic
*Archaea/genetics/metabolism
*Genomics/methods
Biocuration
*Methane/metabolism
RevDate: 2026-09-14
CmpDate: 2026-09-14
T2T Genome Assembly and Multi-Omics Data Reveal Terrestrial Adaptation and Mucus Biosynthesis in Tropical Leatherleaf Slug (Laevicaulis alte).
Advanced science (Weinheim, Baden-Wurttemberg, Germany), 13(51):e76129.
Laevichaulis alte is a slug in the order Systellommatophora that evolved from aquatic ancestors and now faces strong challenges from desiccation, respiration on land, and novel pathogens. Its mucus is essential for water retention, locomotion, and defense. To link terrestrial adaptation with mucus biosynthesis, we generated a gap-free genome assembly of L. alte using PacBio HiFi reads, Oxford Nanopore ultra-long reads, and Hi-C data. The genome shows low heterozygosity and holocentromeric chromosomes. Functional metabolomics revealed marked metabolic shifts between L. alte and the closely related aquatic species Peronia verruculata. In L. alte, differential metabolites were enriched in lipid metabolism, immune regulation, and stress response pathways, consistent with life in a dry and microbe-rich terrestrial environment. Comparative genomics and transcriptomics identified candidate genes linked to mucus secretion and physiological adaptation, including VEGF, ASGR2, and COL6A6. Further analyses highlighted the vascular endothelial growth factor (VEGF) gene family as a key regulator connecting angiogenesis, tissue remodeling, and mucus production pathways in L. alte. Together, this gap-free genome and multi-omics dataset establish a molecular framework that links genomic innovation, mucus biology, and terrestrial adaptation in Systellommatophora, and they offer a basis for understanding ecological niche specialization in land molluscs.
Additional Links: PMID-42294640
PubMed:
Citation:
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@article {pmid42294640,
year = {2026},
author = {Wang, G and He, S and Wang, Z and Pang, A and Sun, X and Liu, R and Wang, F and Chen, S and Bian, Z and Wei, D and Wu, L and Zhao, S and Ji, Q and Sun, Y and Sun, N and Fujaya, Y and Tang, B and Tan, K and Zhang, D and Chen, L},
title = {T2T Genome Assembly and Multi-Omics Data Reveal Terrestrial Adaptation and Mucus Biosynthesis in Tropical Leatherleaf Slug (Laevicaulis alte).},
journal = {Advanced science (Weinheim, Baden-Wurttemberg, Germany)},
volume = {13},
number = {51},
pages = {e76129},
pmid = {42294640},
issn = {2198-3844},
support = {32070526//National Natural Science Foundation of China/ ; 32270487//National Natural Science Foundation of China/ ; BE2020673//Key Research and Development Programme of Jiangsu Province/ ; 24KJA240003//Major Project of Jiangsu Higher Education Institutions for Basic Science (Natural Science) Research/ ; },
mesh = {Animals ; *Mucus/metabolism ; *Adaptation, Physiological/genetics ; Multiomics ; *Gastropoda/genetics/metabolism/physiology ; *Genome/genetics ; Genomics/methods ; Transcriptome/genetics ; },
abstract = {Laevichaulis alte is a slug in the order Systellommatophora that evolved from aquatic ancestors and now faces strong challenges from desiccation, respiration on land, and novel pathogens. Its mucus is essential for water retention, locomotion, and defense. To link terrestrial adaptation with mucus biosynthesis, we generated a gap-free genome assembly of L. alte using PacBio HiFi reads, Oxford Nanopore ultra-long reads, and Hi-C data. The genome shows low heterozygosity and holocentromeric chromosomes. Functional metabolomics revealed marked metabolic shifts between L. alte and the closely related aquatic species Peronia verruculata. In L. alte, differential metabolites were enriched in lipid metabolism, immune regulation, and stress response pathways, consistent with life in a dry and microbe-rich terrestrial environment. Comparative genomics and transcriptomics identified candidate genes linked to mucus secretion and physiological adaptation, including VEGF, ASGR2, and COL6A6. Further analyses highlighted the vascular endothelial growth factor (VEGF) gene family as a key regulator connecting angiogenesis, tissue remodeling, and mucus production pathways in L. alte. Together, this gap-free genome and multi-omics dataset establish a molecular framework that links genomic innovation, mucus biology, and terrestrial adaptation in Systellommatophora, and they offer a basis for understanding ecological niche specialization in land molluscs.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Animals
*Mucus/metabolism
*Adaptation, Physiological/genetics
Multiomics
*Gastropoda/genetics/metabolism/physiology
*Genome/genetics
Genomics/methods
Transcriptome/genetics
RevDate: 2026-09-13
Association of Community Factors, Firearm Laws, and Pediatric Firearm Injuries.
Pediatrics pii:209444 [Epub ahead of print].
OBJECTIVE: To conduct a zip code-level analysis of community measures and firearm legislation associated with pediatric fatal and nonfatal firearm injuries, ordered by strength of association.
METHODS: This was an ecological study of 46 states and the District of Columbia from January 1, 2018 to December 31, 2022. We examined 29 zip code-level variables from the American Community Survey, Social Vulnerability Index, Child Opportunity Index, Giffords Scorecard on Gun Safety Legislation, and the Structural Racism Effect Index. The outcome was the annual incidence of fatal and nonfatal pediatric firearm injuries in each zip code, as included in the National Emergency Medical Services (EMS) Information System (NEMSIS, all 9-1-1 EMS responses) and the Gun Violence Archive (GVA, all police-reported and publicly reported firearm events). We used negative binomial regression and machine learning analysis to evaluate predictors.
RESULTS: There were 28 631 zip codes included in the analysis. The average annual incidence of pediatric firearm injuries ranged from 0 to 16 per zip code in NEMSIS, with 1288 (4.5%) zip codes having at least one firearm incident. In GVA, annual incidence ranged from 0 to 35 per zip code, with 1180 (4.1%) zip codes having firearm events. Predictors of firearm injuries included structural racism (in social cohesion, built environment, employment, housing, and criminal justice), urbanicity, household income, unemployment, educational opportunities, and gun laws for background checks and firearm access.
CONCLUSIONS: Modifiable community characteristics and certain firearm legislation are associated with pediatric firearm injuries, providing focus areas for community planning, public health, and policy changes to reduce firearm-related injuries and deaths.
Additional Links: PMID-42732887
Publisher:
PubMed:
Citation:
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@article {pmid42732887,
year = {2026},
author = {Diaz, XN and Lin, A and Babcock, S and Salvi, A and Malveau, S and Mann, NC and Goldstick, JE and Carter, PM and Cook, JNB and Song, X and Wei, R and Lundrigan, AM and Beckstead, R and Hagos, B and Newgard, CD},
title = {Association of Community Factors, Firearm Laws, and Pediatric Firearm Injuries.},
journal = {Pediatrics},
volume = {},
number = {},
pages = {},
doi = {10.1542/peds.2025-074149},
pmid = {42732887},
issn = {1098-4275},
abstract = {OBJECTIVE: To conduct a zip code-level analysis of community measures and firearm legislation associated with pediatric fatal and nonfatal firearm injuries, ordered by strength of association.
METHODS: This was an ecological study of 46 states and the District of Columbia from January 1, 2018 to December 31, 2022. We examined 29 zip code-level variables from the American Community Survey, Social Vulnerability Index, Child Opportunity Index, Giffords Scorecard on Gun Safety Legislation, and the Structural Racism Effect Index. The outcome was the annual incidence of fatal and nonfatal pediatric firearm injuries in each zip code, as included in the National Emergency Medical Services (EMS) Information System (NEMSIS, all 9-1-1 EMS responses) and the Gun Violence Archive (GVA, all police-reported and publicly reported firearm events). We used negative binomial regression and machine learning analysis to evaluate predictors.
RESULTS: There were 28 631 zip codes included in the analysis. The average annual incidence of pediatric firearm injuries ranged from 0 to 16 per zip code in NEMSIS, with 1288 (4.5%) zip codes having at least one firearm incident. In GVA, annual incidence ranged from 0 to 35 per zip code, with 1180 (4.1%) zip codes having firearm events. Predictors of firearm injuries included structural racism (in social cohesion, built environment, employment, housing, and criminal justice), urbanicity, household income, unemployment, educational opportunities, and gun laws for background checks and firearm access.
CONCLUSIONS: Modifiable community characteristics and certain firearm legislation are associated with pediatric firearm injuries, providing focus areas for community planning, public health, and policy changes to reduce firearm-related injuries and deaths.},
}
RevDate: 2026-09-13
CmpDate: 2026-09-13
Unraveling the coastal marine plastisphere archaeome.
Nature communications, 17(1):.
Plastic pollution has created an expanding anthropogenic microbial niche, the plastisphere, raising questions about microbial ecology and associated impacts. Archaea, the third domain of life with fundamental ecological and evolutionary significance, remain poorly understood in this habitat. Here, using paired plastic debris and bulk-water samples from coastal marine ecosystems, key archaeal habitats increasingly threatened by plastic pollution, we characterize the plastisphere archaeome through archaeal amplicon sequencing and metagenomics. We show that the archaeome is significantly reshaped in the plastisphere, exhibiting higher taxonomic diversity, greater community heterogeneity, and selective enrichment of Euryarchaeota and Crenarchaeota. Archaeal genes involved in methane, nitrogen, and sulfur cycling are enriched in the plastisphere. Taxonomic and functional divergence between the plastisphere and bulk water increases with anthropogenic chemical stress. These findings suggest that plastic pollution could alter marine archaeal diversity, biogeography, and biogeochemical potential, extending understanding of plastisphere impacts to the archaeal domain.
Additional Links: PMID-42733080
PubMed:
Citation:
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@article {pmid42733080,
year = {2026},
author = {Li, C and Wang, Y and Zhou, ASK and Pan, X and Zhu, Y and Zhang, X and Chen, T and Xiong, A and Ho, YW and Liu, J and Zhou, Z and Wang, J and Adyel, TM and Fang, JK and Bank, MS and Rillig, MC and Jin, LN},
title = {Unraveling the coastal marine plastisphere archaeome.},
journal = {Nature communications},
volume = {17},
number = {1},
pages = {},
pmid = {42733080},
issn = {2041-1723},
mesh = {*Archaea/genetics/classification ; *Seawater/microbiology ; Crenarchaeota/genetics/classification ; Phylogeny ; Euryarchaeota/genetics/classification ; Metagenomics ; Ecosystem ; Biodiversity ; Methane/metabolism ; },
abstract = {Plastic pollution has created an expanding anthropogenic microbial niche, the plastisphere, raising questions about microbial ecology and associated impacts. Archaea, the third domain of life with fundamental ecological and evolutionary significance, remain poorly understood in this habitat. Here, using paired plastic debris and bulk-water samples from coastal marine ecosystems, key archaeal habitats increasingly threatened by plastic pollution, we characterize the plastisphere archaeome through archaeal amplicon sequencing and metagenomics. We show that the archaeome is significantly reshaped in the plastisphere, exhibiting higher taxonomic diversity, greater community heterogeneity, and selective enrichment of Euryarchaeota and Crenarchaeota. Archaeal genes involved in methane, nitrogen, and sulfur cycling are enriched in the plastisphere. Taxonomic and functional divergence between the plastisphere and bulk water increases with anthropogenic chemical stress. These findings suggest that plastic pollution could alter marine archaeal diversity, biogeography, and biogeochemical potential, extending understanding of plastisphere impacts to the archaeal domain.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Archaea/genetics/classification
*Seawater/microbiology
Crenarchaeota/genetics/classification
Phylogeny
Euryarchaeota/genetics/classification
Metagenomics
Ecosystem
Biodiversity
Methane/metabolism
RevDate: 2026-09-14
CmpDate: 2026-09-14
Invasive Flora Repository: Traits, environmental tolerances, and invasion history of invasive plant species in the United States.
Ecology, 107(9):e70492.
Species traits may serve as proxies for ecological mechanisms that drive invasion success and, therefore, are a promising framework for investigating invasion processes and predicting future outcomes of species that have been recently introduced. However, although many efforts exist to document species traits of plants, a centralized database of invasive plant species in the United States is not currently available. We have compiled traits data for 1024 invasive plants in the United States across 28 species characteristics, including functional morphological, reproductive, and dispersal traits, as well as characteristics related to the invasion history of the species, such as origin and invasion pathways. We identified our list of invasive plant species from EDDMapS, a web-based national network that aggregates observation records and distribution data of invasive species and pests in the United States and Canada, and the U.S. Register of Introduced and Invasive Species (US-RIIS). Traits data were collected from various online factsheet databases, including the CABI Compendium: Invasive Species, the USDA Plants Database, the North Carolina State Extension Plant Toolbox, the UC-Berkeley Jepson Herbarium, the USFS-Fire Effects Information System, and University of Michigan's CLIMBERS. We aimed to create a comprehensive database on traits of invasive species that can be utilized by researchers and conservationists and serve as a reference for those involved in the monitoring and control of invasive species. These data are available for reuse under CC BY 4.0 (Attribution) licensing.
Additional Links: PMID-42734095
Publisher:
PubMed:
Citation:
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@article {pmid42734095,
year = {2026},
author = {Al-Shayeb, SMA and Aguilar, C and Yousefi, M and George, Z and Pfadenhauer, WG and Nunez-Mir, GC},
title = {Invasive Flora Repository: Traits, environmental tolerances, and invasion history of invasive plant species in the United States.},
journal = {Ecology},
volume = {107},
number = {9},
pages = {e70492},
doi = {10.1002/ecy.70492},
pmid = {42734095},
issn = {1939-9170},
support = {23-01443//Walder Foundation/ ; },
mesh = {*Introduced Species ; United States ; *Plants/classification ; Databases, Factual ; },
abstract = {Species traits may serve as proxies for ecological mechanisms that drive invasion success and, therefore, are a promising framework for investigating invasion processes and predicting future outcomes of species that have been recently introduced. However, although many efforts exist to document species traits of plants, a centralized database of invasive plant species in the United States is not currently available. We have compiled traits data for 1024 invasive plants in the United States across 28 species characteristics, including functional morphological, reproductive, and dispersal traits, as well as characteristics related to the invasion history of the species, such as origin and invasion pathways. We identified our list of invasive plant species from EDDMapS, a web-based national network that aggregates observation records and distribution data of invasive species and pests in the United States and Canada, and the U.S. Register of Introduced and Invasive Species (US-RIIS). Traits data were collected from various online factsheet databases, including the CABI Compendium: Invasive Species, the USDA Plants Database, the North Carolina State Extension Plant Toolbox, the UC-Berkeley Jepson Herbarium, the USFS-Fire Effects Information System, and University of Michigan's CLIMBERS. We aimed to create a comprehensive database on traits of invasive species that can be utilized by researchers and conservationists and serve as a reference for those involved in the monitoring and control of invasive species. These data are available for reuse under CC BY 4.0 (Attribution) licensing.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Introduced Species
United States
*Plants/classification
Databases, Factual
RevDate: 2026-09-13
CmpDate: 2026-09-13
Genomic surveillance of a deeply sampled local population reveals age-specific drivers of RSV transmission.
medRxiv : the preprint server for health sciences.
Respiratory syncytial virus (RSV) disproportionately causes severe infections among infants and older adults, yet the key age group responsible for viral spread to other age groups remains poorly defined. While current immunization approaches effectively reduce disease severity among the most vulnerable, identifying the core drivers of infection is essential to effectively disrupt population-level transmission. By generating 910 whole-genome viral sequences of RSV from all age groups (<1 to 65+ years) in Connecticut, we identified that children aged 12-35 months are the primary drivers of viral transmission to other age groups. This group significantly shapes the genetic diversity of circulating strains. Furthermore, we found that RSV is introduced into the community through frequent and independent entries from other US regions throughout the year, rather than through a single explosive seasonal introduction or long-term local persistence. Ultimately, our findings justify prevention strategies that expand beyond reducing disease burden to actively prioritizing the reduction of transmission and infection.
Additional Links: PMID-42238416
PubMed:
Citation:
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@article {pmid42238416,
year = {2026},
author = {Kwon, J and de Vries, EM and Lemey, P and Li, K and Breban, M and Laing, K and Ferguson, D and Schulz, W and Oliveira, CR and Bont, LJ and Pitzer, VE and Weinberger, DM and Grubaugh, ND and Hill, V and Redmond, S},
title = {Genomic surveillance of a deeply sampled local population reveals age-specific drivers of RSV transmission.},
journal = {medRxiv : the preprint server for health sciences},
volume = {},
number = {},
pages = {},
pmid = {42238416},
support = {R01 AI137093/AI/NIAID NIH HHS/United States ; R01 AI179874/AI/NIAID NIH HHS/United States ; },
abstract = {Respiratory syncytial virus (RSV) disproportionately causes severe infections among infants and older adults, yet the key age group responsible for viral spread to other age groups remains poorly defined. While current immunization approaches effectively reduce disease severity among the most vulnerable, identifying the core drivers of infection is essential to effectively disrupt population-level transmission. By generating 910 whole-genome viral sequences of RSV from all age groups (<1 to 65+ years) in Connecticut, we identified that children aged 12-35 months are the primary drivers of viral transmission to other age groups. This group significantly shapes the genetic diversity of circulating strains. Furthermore, we found that RSV is introduced into the community through frequent and independent entries from other US regions throughout the year, rather than through a single explosive seasonal introduction or long-term local persistence. Ultimately, our findings justify prevention strategies that expand beyond reducing disease burden to actively prioritizing the reduction of transmission and infection.},
}
RevDate: 2026-09-13
CmpDate: 2026-09-13
HPRC2: A human pangenome reference with near-complete coverage of common genetic variation.
bioRxiv : the preprint server for biology.
A pangenome reference overcomes the inherent limitation of any individual reference genome by integrating the variation present in a population. We present the Human Pangenome Reference Consortium's (HPRC) Release 2 (HPRC2), an openly available, second phase pangenome that is an approximately fivefold expansion in genome number over HPRC Release 1 (HPRC1) and measurable improvement in genome completeness, contiguity, and accuracy. Selecting samples with a principled algorithm prioritising common variant coverage, HPRC2 contributes 460 haplotypes that together capture over 99% of common variation observed in the All of Us Research Program v8 cohort. Combining high-coverage long and ultra-long reads with modern assemblers and polishers, we produce thousands of telomere-to-telomere (T2T) chromosomes, and relative to HPRC1 halve the number of structurally unreliable regions as well as individual base errors per haplotype. We complement the assemblies with whole genome multiple alignments and gene annotations, and derive formal pangenome coordinate systems for addressing off-reference variation, demonstrating that individual human genomes contain more than one hundred thousand variants not succinctly described with respect to existing reference genomes. We also present the first matched long-read backed pantranscriptome and panepigenome at this scale, provide continuous local-ancestry estimates spanning every genome, and outline a host of new tools and applications that leverage the pangenome resource for improved genomics analysis.
Additional Links: PMID-42539208
PubMed:
Citation:
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@article {pmid42539208,
year = {2026},
author = {Lucas, JK and Hebbar, P and Liao, WW and Macias-Velasco, JF and Novak, AM and Asri, M and Balacco, JR and Blair, AP and Bolognini, D and Ebler, J and Gardner, JMV and Geleta, M and Groza, C and Guarracino, A and Heringer, P and Hickey, G and Koren, S and Lu, S and Marin, MG and Markovic, C and Mastoras, M and Mayoud, C and McNulty, B and Menendez, JM and Minkina, A and Mohanty, SK and Monlong, J and Munson, KM and Oshima, KK and Porubsky, D and Ranallo-Benavidez, TR and Raveane, A and Seligmann, WE and Shemirani, R and Suzuki, Y and Tierney, JAS and Violich, I and Yoo, D and Zhuo, X and Albracht, D and Alexandrov, IA and Allen, J and Alsheikh-Ali, AA and Andrews, C and Antipov, D and Antonacci-Fulton, L and Arguello, A and Ayllon, M and Belter, EA and Bender, HD and Bonini, KE and Buonaiuto, S and Cao, S and Mc Cartney, AM and Chang, PC and Chang, X and Cheema, J and Ciofi, C and Clawson, H and Cody, S and Colonna, V and Conwell, HC and Diekhans, M and Diroma, MA and Dong, Z and Dubocanin, D and Eizenga, JM and Eskandar, P and Ferro, E and Ford, SM and Ford, WW and Frankish, A and Freeberg, MA and Fu, Q and Gao, S and Gao, Y and Garcia, GH and Garcia, OA and Garza, JE and Ghorbani, M and Graves-Lindsay, TA and Gu, B and Haggerty, L and Hansen, NF and Hao, Y and Hillaker, TL and Hossain, SN and Huang, N and Hunt, SE and Hunt, T and Jafarzadeh, N and Jain, N and Jehangir, M and Jiang, J and Kim, J and Koo, B and Kremitzki, M and Li, D and Li, R and Lin, J and Liu, T and Lorig-Roach, R and Loucks, H and Loveland, JE and Lu, J and Ma, W and Marsico, FL and Medico, JA and Mokrab, Y and Moosa, S and Moreno-Ochando, A and Morishita, S and Mudge, JM and Mwaniki, N and Nassir, N and Natali, C and Negi, S and Ni, L and Okamoto, F and Owa, C and Paez, S and Peano, C and Pickett, BD and Pignata, L and Prodanov, T and Radhakrishnan, A and Raney, BJ and Rechtsteiner, A and Ren, L and Ryabov, F and Sacco, S and Salehi, F and Sehgal, A and Shabani, M and Shahatit, S and Shivakumar, VS and Sinha, S and Smeds, L and Solar, SJ and Sollitto, M and Soranzo, N and Suner, MM and Söylev, A and Tomlinson, C and Tricomi, FF and Ungaro, MT and Varki, R and Walenz, BP and Wang, C and Wang, LE and Wenger, AM and Whelan, CV and Xin, Z and Xu, Z and Zhang, W and Zhou, Y and Zunino, G and Altemose, N and Barthel, FP and Boucher, C and Bourque, G and Carroll, A and Cechova, M and Chaisson, MJP and Cheng, H and Cook-Deegan, R and Doerr, D and Durbin, R and Fiston-Lavier, AS and Formenti, G and Fullerton, SM and Fulton, RS and Garg, S and Garrison, NA and Green, RE and Greider, CW and Gymrek, M and Haeussler, M and Hashmi, MA and Haussler, D and Ioannidis, AG and Langley, CH and Langmead, B and Lawson, HA and Logsdon, GA and Makova, KD and Martin, FJ and Mitchell, MW and Ossorio, PN and Pisanti, N and Prins, P and Rautiainen, M and Rhie, A and Schatz, MC and Scheinfeldt, LB and Shafin, K and Sirén, J and Stergachis, AB and Tayoun, AA and Uddin, M and Villani, F and Vollger, MR and Ye, K and Eichler, EE and Garrison, E and Hall, IM and Jarvis, ED and Kenny, EE and Li, H and LoTempio, J and Marschall, T and Miga, KH and Phillippy, AM and Wang, T and Paten, B},
title = {HPRC2: A human pangenome reference with near-complete coverage of common genetic variation.},
journal = {bioRxiv : the preprint server for biology},
volume = {},
number = {},
pages = {},
pmid = {42539208},
issn = {2692-8205},
abstract = {A pangenome reference overcomes the inherent limitation of any individual reference genome by integrating the variation present in a population. We present the Human Pangenome Reference Consortium's (HPRC) Release 2 (HPRC2), an openly available, second phase pangenome that is an approximately fivefold expansion in genome number over HPRC Release 1 (HPRC1) and measurable improvement in genome completeness, contiguity, and accuracy. Selecting samples with a principled algorithm prioritising common variant coverage, HPRC2 contributes 460 haplotypes that together capture over 99% of common variation observed in the All of Us Research Program v8 cohort. Combining high-coverage long and ultra-long reads with modern assemblers and polishers, we produce thousands of telomere-to-telomere (T2T) chromosomes, and relative to HPRC1 halve the number of structurally unreliable regions as well as individual base errors per haplotype. We complement the assemblies with whole genome multiple alignments and gene annotations, and derive formal pangenome coordinate systems for addressing off-reference variation, demonstrating that individual human genomes contain more than one hundred thousand variants not succinctly described with respect to existing reference genomes. We also present the first matched long-read backed pantranscriptome and panepigenome at this scale, provide continuous local-ancestry estimates spanning every genome, and outline a host of new tools and applications that leverage the pangenome resource for improved genomics analysis.},
}
RevDate: 2026-09-12
CmpDate: 2026-09-12
National trends in neonatal and under-five mortality in Saudi Arabia (2018-2023): a descriptive ecological analysis using WHO Global Health Observatory data.
Frontiers in public health, 14:1903279.
BACKGROUND: Neonatal mortality rate (NMR) and under-five mortality rate (U5MR) are core child-survival indicators and are influenced by, though not a direct measure of, the quality of maternal and newborn care. Saudi Arabia has achieved substantial reductions in both indicators over recent decades; however, year-to-year dynamics during the period of Vision 2030 health reforms remain incompletely described using standardized, internationally comparable data.
OBJECTIVE: To describe annual trends in NMR and U5MR in Saudi Arabia from 2018 to 2023 using WHO Global Health Observatory (WHO-GHO) national estimates, and to situate these descriptive trends within the broader regional and international literature on child mortality.
METHODS: A descriptive ecological analysis was conducted using all available national annual estimates (2018-2023; n = 6 per indicator) from WHO-GHO. Descriptive statistics and annual percentage change (APC) were calculated as the primary analytical approach. An unadjusted linear regression of rate on year is reported to characterize the direction and approximate magnitude of change over the period; because six annual observations provide very limited statistical power, regression p-values are reported for completeness only and are not used to support claims of trend presence or absence.
RESULTS: NMR declined from 3.6 to 3.0 per 1,000 live births between 2018 and 2023 (mean 3.27; range 3.0-3.6), a change concentrated mainly in 2020. U5MR fluctuated within a narrow band, falling from 6.1 in 2018 to 5.6 in 2021, rising to 6.4 in 2022, and partially returning to 6.2 in 2023 (mean 5.98; range 5.6-6.4). The unadjusted linear slopes were -0.12/year for NMR and +0.03/year for U5MR.
CONCLUSION: Between 2018 and 2023, Saudi Arabia's NMR and U5MR remained low and comparatively stable by international standards, with a gradual decline in NMR and a transient fluctuation in U5MR centered on 2022. These are descriptive, population-level patterns; the dataset does not include measures of healthcare quality, patient safety, or COVID-19 service disruption, and any interpretation connecting the observed trends to these factors should be regarded as a hypothesis for future research rather than a finding of this study. Future work linking subnational data, cause-specific mortality, and direct quality-of-care indicators to these trends is needed.
Additional Links: PMID-42729549
PubMed:
Citation:
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@article {pmid42729549,
year = {2026},
author = {Alanazi, EM and Alkhalid, Y and Alqheedan, A and Alzughaibi, S},
title = {National trends in neonatal and under-five mortality in Saudi Arabia (2018-2023): a descriptive ecological analysis using WHO Global Health Observatory data.},
journal = {Frontiers in public health},
volume = {14},
number = {},
pages = {1903279},
pmid = {42729549},
issn = {2296-2565},
mesh = {Saudi Arabia/epidemiology ; Humans ; *Infant Mortality/trends ; World Health Organization ; Infant, Newborn ; *Child Mortality/trends ; Infant ; Global Health ; },
abstract = {BACKGROUND: Neonatal mortality rate (NMR) and under-five mortality rate (U5MR) are core child-survival indicators and are influenced by, though not a direct measure of, the quality of maternal and newborn care. Saudi Arabia has achieved substantial reductions in both indicators over recent decades; however, year-to-year dynamics during the period of Vision 2030 health reforms remain incompletely described using standardized, internationally comparable data.
OBJECTIVE: To describe annual trends in NMR and U5MR in Saudi Arabia from 2018 to 2023 using WHO Global Health Observatory (WHO-GHO) national estimates, and to situate these descriptive trends within the broader regional and international literature on child mortality.
METHODS: A descriptive ecological analysis was conducted using all available national annual estimates (2018-2023; n = 6 per indicator) from WHO-GHO. Descriptive statistics and annual percentage change (APC) were calculated as the primary analytical approach. An unadjusted linear regression of rate on year is reported to characterize the direction and approximate magnitude of change over the period; because six annual observations provide very limited statistical power, regression p-values are reported for completeness only and are not used to support claims of trend presence or absence.
RESULTS: NMR declined from 3.6 to 3.0 per 1,000 live births between 2018 and 2023 (mean 3.27; range 3.0-3.6), a change concentrated mainly in 2020. U5MR fluctuated within a narrow band, falling from 6.1 in 2018 to 5.6 in 2021, rising to 6.4 in 2022, and partially returning to 6.2 in 2023 (mean 5.98; range 5.6-6.4). The unadjusted linear slopes were -0.12/year for NMR and +0.03/year for U5MR.
CONCLUSION: Between 2018 and 2023, Saudi Arabia's NMR and U5MR remained low and comparatively stable by international standards, with a gradual decline in NMR and a transient fluctuation in U5MR centered on 2022. These are descriptive, population-level patterns; the dataset does not include measures of healthcare quality, patient safety, or COVID-19 service disruption, and any interpretation connecting the observed trends to these factors should be regarded as a hypothesis for future research rather than a finding of this study. Future work linking subnational data, cause-specific mortality, and direct quality-of-care indicators to these trends is needed.},
}
MeSH Terms:
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Saudi Arabia/epidemiology
Humans
*Infant Mortality/trends
World Health Organization
Infant, Newborn
*Child Mortality/trends
Infant
Global Health
RevDate: 2026-09-13
CmpDate: 2026-09-13
The genome sequence of the Tufted Button, Acleris cristana (Denis & Schiffermüller, 1775).
Wellcome open research, 8:236.
We present a genome assembly from an individual female Acleris cristana (the Tufted Button; Arthropoda; Insecta; Lepidoptera; Tortricidae). The genome sequence is 562.6 megabases in span. Most of the assembly is scaffolded into 31 chromosomal pseudomolecules, including the W and Z sex chromosomes. The mitochondrial genome has also been assembled and is 16.1 kilobases in length. Gene annotation of this assembly on Ensembl identified 12,598 protein coding genes.
Additional Links: PMID-42732105
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@article {pmid42732105,
year = {2023},
author = {Boyes, D and Boyes, C and , and , and , and , and , and , },
title = {The genome sequence of the Tufted Button, Acleris cristana (Denis & Schiffermüller, 1775).},
journal = {Wellcome open research},
volume = {8},
number = {},
pages = {236},
doi = {10.12688/wellcomeopenres.19508.2},
pmid = {42732105},
issn = {2398-502X},
abstract = {We present a genome assembly from an individual female Acleris cristana (the Tufted Button; Arthropoda; Insecta; Lepidoptera; Tortricidae). The genome sequence is 562.6 megabases in span. Most of the assembly is scaffolded into 31 chromosomal pseudomolecules, including the W and Z sex chromosomes. The mitochondrial genome has also been assembled and is 16.1 kilobases in length. Gene annotation of this assembly on Ensembl identified 12,598 protein coding genes.},
}
RevDate: 2026-09-13
CmpDate: 2026-09-13
The genome sequence of the 16-spot Ladybird, Tytthaspis sedecimpunctata (Linnaeus, 1758) (Coleoptera: Coccinellidae).
Wellcome open research, 11:402.
We present a genome assembly from an individual male Tytthaspis sedecimpunctata (16-spot Ladybird; Arthropoda; Insecta; Coleoptera; Coccinellidae). The genome sequence has a total length of 355.68 megabases. Most of the assembly (88.7%) is scaffolded into 10 chromosomal pseudomolecules, including the X sex chromosome. The mitochondrial genome has also been assembled, with a length of 18.38 kilobases. This assembly was generated as part of the Darwin Tree of Life project, which produces genomes for eukaryotic species found in Britain and Ireland.
Additional Links: PMID-42732112
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@article {pmid42732112,
year = {2026},
author = {Crowley, LM and Sivell, O and Mitchell, R and Sivell, D and Roy, HE and Brown, PMJ and , and , and , and , and , and , and , and , },
title = {The genome sequence of the 16-spot Ladybird, Tytthaspis sedecimpunctata (Linnaeus, 1758) (Coleoptera: Coccinellidae).},
journal = {Wellcome open research},
volume = {11},
number = {},
pages = {402},
pmid = {42732112},
issn = {2398-502X},
abstract = {We present a genome assembly from an individual male Tytthaspis sedecimpunctata (16-spot Ladybird; Arthropoda; Insecta; Coleoptera; Coccinellidae). The genome sequence has a total length of 355.68 megabases. Most of the assembly (88.7%) is scaffolded into 10 chromosomal pseudomolecules, including the X sex chromosome. The mitochondrial genome has also been assembled, with a length of 18.38 kilobases. This assembly was generated as part of the Darwin Tree of Life project, which produces genomes for eukaryotic species found in Britain and Ireland.},
}
RevDate: 2026-09-13
CmpDate: 2026-09-13
Daily Language as an Objective Indicator of Depressive Affective States: A Two-Week Ecological Momentary Assessment Study in Emotional Labor Workers.
Psychiatry investigation, 23(9):1096-1106.
OBJECTIVE: Workers performing emotional labor are at increased risk for depression, yet conventional self-report assessments often lack objectivity and temporal sensitivity. This study aimed to examine whether longitudinal analysis of daily natural language collected through ecological momentary assessment (EMA) can serve as an indicator of depressive affective states and to compare its temporal sensitivity with traditional self-report measures.
METHODS: A total of 400 call center employees completed three voice-recorded free-text entries per day for two weeks using an EMA application. Transcriptions were analyzed using a lexicon-based sentiment approach (Linguistic Inquiry and Word Count [LIWC]) and three large language models (LLMs; GPT-4o-mini, Qwen, and Mistral) under zero-shot prompting. Depressive symptoms were assessed using the Patient Health Questionnaire-9, and neuroticism was measured using both self-reported questionnaires and language-inferred scores.
RESULTS: LLM-derived sentiment scores significantly differentiated groups across levels of depressive symptom burden and consistently outperformed LIWC. Longitudinal analyses demonstrated clear group-level separation, particularly in morning entries, whereas self-reported mood ratings failed to distinguish groups and showed lower adherence over the two-week period. Language-inferred neuroticism exhibited stronger associations with depressive symptoms than self-reported neuroticism. A cumulative model based on morning sentiment scores showed progressively improved discrimination over time, reaching its highest performance on Day 10 (area under the curve=0.75).
CONCLUSION: Daily natural language captures meaningful longitudinal affective dynamics associated with depressive symptoms and may complement conventional self-report assessments as a low-burden and scalable indicator of depressive affective states in real-world occupational settings.
Additional Links: PMID-42732773
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@article {pmid42732773,
year = {2026},
author = {Kim, HH and Kim, SJ and Kim, DK and Jeon, EK and Choi, Y and Kim, JM and Kim, SW and Lee, S and Jhon, M and Kim, JW},
title = {Daily Language as an Objective Indicator of Depressive Affective States: A Two-Week Ecological Momentary Assessment Study in Emotional Labor Workers.},
journal = {Psychiatry investigation},
volume = {23},
number = {9},
pages = {1096-1106},
doi = {10.30773/pi.2026.0035},
pmid = {42732773},
issn = {1738-3684},
support = {HCRI25031//Chonnam National University Hwasun Hospital Institute for Biomedical Science/ ; RS-2024-00459226//National Research Foundation of Korea/ ; //Ministry of Science and ICT/ ; },
abstract = {OBJECTIVE: Workers performing emotional labor are at increased risk for depression, yet conventional self-report assessments often lack objectivity and temporal sensitivity. This study aimed to examine whether longitudinal analysis of daily natural language collected through ecological momentary assessment (EMA) can serve as an indicator of depressive affective states and to compare its temporal sensitivity with traditional self-report measures.
METHODS: A total of 400 call center employees completed three voice-recorded free-text entries per day for two weeks using an EMA application. Transcriptions were analyzed using a lexicon-based sentiment approach (Linguistic Inquiry and Word Count [LIWC]) and three large language models (LLMs; GPT-4o-mini, Qwen, and Mistral) under zero-shot prompting. Depressive symptoms were assessed using the Patient Health Questionnaire-9, and neuroticism was measured using both self-reported questionnaires and language-inferred scores.
RESULTS: LLM-derived sentiment scores significantly differentiated groups across levels of depressive symptom burden and consistently outperformed LIWC. Longitudinal analyses demonstrated clear group-level separation, particularly in morning entries, whereas self-reported mood ratings failed to distinguish groups and showed lower adherence over the two-week period. Language-inferred neuroticism exhibited stronger associations with depressive symptoms than self-reported neuroticism. A cumulative model based on morning sentiment scores showed progressively improved discrimination over time, reaching its highest performance on Day 10 (area under the curve=0.75).
CONCLUSION: Daily natural language captures meaningful longitudinal affective dynamics associated with depressive symptoms and may complement conventional self-report assessments as a low-burden and scalable indicator of depressive affective states in real-world occupational settings.},
}
RevDate: 2026-09-11
CmpDate: 2026-09-11
GenBank mining reveals novel insights into Rhizobium phylogeny: Identical 16S rRNA sequences are mainly uncoupled from species designation, host plant, and geographic origin: How this search suggested the definition of a direct 'microbial h-index'.
PloS one, 21(9):e0357973 pii:PONE-D-26-01783.
16S rDNA is the historical gold standard for bacterial identification, particularly in metabarcoding approaches reliant on sequence similarity thresholds. We analyzed 6,660 Rhizobium 16S rRNA gene sequences from GenBank to examine the relationship between sequence identity and three metadata: species name, host plant, and geographic origin. Using an iterative BLAST-based pipeline, we detected 116,069 pairwise matches and assessed concordance among sequences (average length 1,328 bp) sharing 100% identity. For those in which the organism name, host plant and country of isolation were present in the record, surprisingly, 66.59% of identical sequence pairs showed full discordance across all three metadata, while only 1.40% shared the same name, host, and country. The most widespread sequence, detected 371 times, was associated with over 56 different host plants across 25 countries and bore multiple species name designations. These results highlight a striking mismatch between the 16S barcode and the taxonomic, ecological, and phenotypic variability it is assumed to reflect, likely arising from the slow evolution of rRNA genes contrasted with the mobility of ecologically relevant genes via horizontal transfer on plasmids, transposons, and phages. Our findings further challenge the limitations of relying on 16S rRNA alone for fine-scale taxonomic and metadata-based inference in capturing the true functional and ecological diversity of bacteria, endorsing the critical importance of polyphasic taxonomic approaches that integrate genomic, phenotypic, and ecological data. An interesting byproduct of the analysis was to realize the possibility of treating these data as if they were 'citations.' The more one finds the same query sequence, the more that sequence can be considered biologically 'cited', i.e., re-proposed elsewhere in the world. Thus, one can also analyze the h-index of such a ranking. In our Rhizobium dataset, we calculated an h-index = 201, meaning the sequence ranked 201st had 202 identical homologues in GenBank. Although the research effort on given species is directly connected with it, this number provides a quantitative indicator of a taxon's sequence recurrence and distribution within public databases, independent of nomenclatural inconsistencies, offering a novel framework for assessing bacterial representation across global datasets.
Additional Links: PMID-42726808
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@article {pmid42726808,
year = {2026},
author = {Muresu, R and Rodriguez, M and Squartini, A},
title = {GenBank mining reveals novel insights into Rhizobium phylogeny: Identical 16S rRNA sequences are mainly uncoupled from species designation, host plant, and geographic origin: How this search suggested the definition of a direct 'microbial h-index'.},
journal = {PloS one},
volume = {21},
number = {9},
pages = {e0357973},
doi = {10.1371/journal.pone.0357973},
pmid = {42726808},
issn = {1932-6203},
mesh = {*RNA, Ribosomal, 16S/genetics ; *Rhizobium/genetics/classification ; *Phylogeny ; *Plants/microbiology ; *Databases, Nucleic Acid ; DNA Barcoding, Taxonomic ; },
abstract = {16S rDNA is the historical gold standard for bacterial identification, particularly in metabarcoding approaches reliant on sequence similarity thresholds. We analyzed 6,660 Rhizobium 16S rRNA gene sequences from GenBank to examine the relationship between sequence identity and three metadata: species name, host plant, and geographic origin. Using an iterative BLAST-based pipeline, we detected 116,069 pairwise matches and assessed concordance among sequences (average length 1,328 bp) sharing 100% identity. For those in which the organism name, host plant and country of isolation were present in the record, surprisingly, 66.59% of identical sequence pairs showed full discordance across all three metadata, while only 1.40% shared the same name, host, and country. The most widespread sequence, detected 371 times, was associated with over 56 different host plants across 25 countries and bore multiple species name designations. These results highlight a striking mismatch between the 16S barcode and the taxonomic, ecological, and phenotypic variability it is assumed to reflect, likely arising from the slow evolution of rRNA genes contrasted with the mobility of ecologically relevant genes via horizontal transfer on plasmids, transposons, and phages. Our findings further challenge the limitations of relying on 16S rRNA alone for fine-scale taxonomic and metadata-based inference in capturing the true functional and ecological diversity of bacteria, endorsing the critical importance of polyphasic taxonomic approaches that integrate genomic, phenotypic, and ecological data. An interesting byproduct of the analysis was to realize the possibility of treating these data as if they were 'citations.' The more one finds the same query sequence, the more that sequence can be considered biologically 'cited', i.e., re-proposed elsewhere in the world. Thus, one can also analyze the h-index of such a ranking. In our Rhizobium dataset, we calculated an h-index = 201, meaning the sequence ranked 201st had 202 identical homologues in GenBank. Although the research effort on given species is directly connected with it, this number provides a quantitative indicator of a taxon's sequence recurrence and distribution within public databases, independent of nomenclatural inconsistencies, offering a novel framework for assessing bacterial representation across global datasets.},
}
MeSH Terms:
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*RNA, Ribosomal, 16S/genetics
*Rhizobium/genetics/classification
*Phylogeny
*Plants/microbiology
*Databases, Nucleic Acid
DNA Barcoding, Taxonomic
RevDate: 2026-09-12
CmpDate: 2026-09-12
The effect of wind speed in increasing COVID-19 cases in Jakarta: a spatial-temporal analysis from March to September 2020.
F1000Research, 12:145.
BACKGROUND: The SARS-CoV-2 virus that causes COVID-19 is described as a highly contagious virus, and wind speed is suspected to be one of the climate elements that play a role in its spread, among others. This study aims to determine the relationship between wind speed and the increase in COVID-19 cases, as well as its potential spread, based on regional characteristics.
METHODS: The design of this study was an ecological study based on time and place to integrate geographic information systems and tested using statistical techniques. The data used were wind speed and weekly COVID-19 cases from March to September 2020. These records were obtained from the special coronavirus website of Jakarta Provincial Health Office and the Indonesian Meteorology, Climatology and Geophysics Agency. The data were analyzed by correlation, graphic/time trend, and spatial analysis.
RESULTS: The wind speed (maximum and mean) from March to September 2020 tended to fluctuate between 1.43 and 6.07 m/s. The correlation test results between the average wind speed and COVID-19 cases in Jakarta showed a strong positive correlation (r = 0.542; p value = 0.002).
CONCLUSIONS: Areas with high wind speeds tended to show an increase in the number of COVID-19 cases, especially in the coastal areas of Jakarta. Wind speed plays a role in increasing the spread of SARS-CoV-2, in people who did not implement health protocols properly. This mechanism can be worsened with support of environmental factors such as air pollution.
Additional Links: PMID-42728906
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@article {pmid42728906,
year = {2023},
author = {Susanna, D and Saputra, YA and Poddar, S},
title = {The effect of wind speed in increasing COVID-19 cases in Jakarta: a spatial-temporal analysis from March to September 2020.},
journal = {F1000Research},
volume = {12},
number = {},
pages = {145},
doi = {10.12688/f1000research.128908.3},
pmid = {42728906},
issn = {2046-1402},
mesh = {*Wind ; *COVID-19/epidemiology/transmission ; Humans ; Indonesia/epidemiology ; Spatio-Temporal Analysis ; SARS-CoV-2 ; Pandemics ; Geographic Information Systems ; },
abstract = {BACKGROUND: The SARS-CoV-2 virus that causes COVID-19 is described as a highly contagious virus, and wind speed is suspected to be one of the climate elements that play a role in its spread, among others. This study aims to determine the relationship between wind speed and the increase in COVID-19 cases, as well as its potential spread, based on regional characteristics.
METHODS: The design of this study was an ecological study based on time and place to integrate geographic information systems and tested using statistical techniques. The data used were wind speed and weekly COVID-19 cases from March to September 2020. These records were obtained from the special coronavirus website of Jakarta Provincial Health Office and the Indonesian Meteorology, Climatology and Geophysics Agency. The data were analyzed by correlation, graphic/time trend, and spatial analysis.
RESULTS: The wind speed (maximum and mean) from March to September 2020 tended to fluctuate between 1.43 and 6.07 m/s. The correlation test results between the average wind speed and COVID-19 cases in Jakarta showed a strong positive correlation (r = 0.542; p value = 0.002).
CONCLUSIONS: Areas with high wind speeds tended to show an increase in the number of COVID-19 cases, especially in the coastal areas of Jakarta. Wind speed plays a role in increasing the spread of SARS-CoV-2, in people who did not implement health protocols properly. This mechanism can be worsened with support of environmental factors such as air pollution.},
}
MeSH Terms:
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*Wind
*COVID-19/epidemiology/transmission
Humans
Indonesia/epidemiology
Spatio-Temporal Analysis
SARS-CoV-2
Pandemics
Geographic Information Systems
RevDate: 2026-09-12
CmpDate: 2026-09-12
The genome sequence of the muscid fly, Hydrotaea similis Meade, 1887 (Diptera: Muscidae).
Wellcome open research, 11:399.
We present a genome assembly from an individual female Hydrotaea similis (muscid fly; Arthropoda; Insecta; Diptera; Muscidae). The assembly contains two haplotypes with total lengths of 884.66 megabases and 852.78 megabases. Most of haplotype 1 (90.83%) is scaffolded into 5 chromosomal pseudomolecules. Haplotype 2 was assembled to scaffold level. The mitochondrial genome has also been assembled, with a length of 20.27 kilobases. This assembly was generated as part of the Darwin Tree of Life project, which produces genomes for eukaryotic species found in Britain and Ireland.
Additional Links: PMID-42728944
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@article {pmid42728944,
year = {2026},
author = {Falk, S and Crowley, LM and Grzywacz, A and , and , and , and , and , and , and , },
title = {The genome sequence of the muscid fly, Hydrotaea similis Meade, 1887 (Diptera: Muscidae).},
journal = {Wellcome open research},
volume = {11},
number = {},
pages = {399},
doi = {10.12688/wellcomeopenres.26885.2},
pmid = {42728944},
issn = {2398-502X},
abstract = {We present a genome assembly from an individual female Hydrotaea similis (muscid fly; Arthropoda; Insecta; Diptera; Muscidae). The assembly contains two haplotypes with total lengths of 884.66 megabases and 852.78 megabases. Most of haplotype 1 (90.83%) is scaffolded into 5 chromosomal pseudomolecules. Haplotype 2 was assembled to scaffold level. The mitochondrial genome has also been assembled, with a length of 20.27 kilobases. This assembly was generated as part of the Darwin Tree of Life project, which produces genomes for eukaryotic species found in Britain and Ireland.},
}
RevDate: 2026-09-12
CmpDate: 2026-09-12
The genome sequence of the Holly Tortrix, Rhopobota naevana (Hubner, 1817) (Lepidoptera: Tortricidae).
Wellcome open research, 11:400.
We present a genome assembly from an individual male Rhopobota naevana (Holly Tortrix; Arthropoda; Insecta; Lepidoptera; Tortricidae). The genome sequence has a total length of 581.80 megabases. Most of the assembly (99.48%) is scaffolded into 28 chromosomal pseudomolecules, including the Z sex chromosome. The mitochondrial genome has also been assembled, with a length of 16.5 kilobases. This assembly was generated as part of the Darwin Tree of Life project, which produces genomes for eukaryotic species found in Britain and Ireland.
Additional Links: PMID-42728953
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@article {pmid42728953,
year = {2026},
author = {Boyes, D and Hutchinson, F and Crowley, LM and Williams, CD and Boyes, C and , and , and , and , and , and , and , },
title = {The genome sequence of the Holly Tortrix, Rhopobota naevana (Hubner, 1817) (Lepidoptera: Tortricidae).},
journal = {Wellcome open research},
volume = {11},
number = {},
pages = {400},
doi = {10.12688/wellcomeopenres.26882.1},
pmid = {42728953},
issn = {2398-502X},
abstract = {We present a genome assembly from an individual male Rhopobota naevana (Holly Tortrix; Arthropoda; Insecta; Lepidoptera; Tortricidae). The genome sequence has a total length of 581.80 megabases. Most of the assembly (99.48%) is scaffolded into 28 chromosomal pseudomolecules, including the Z sex chromosome. The mitochondrial genome has also been assembled, with a length of 16.5 kilobases. This assembly was generated as part of the Darwin Tree of Life project, which produces genomes for eukaryotic species found in Britain and Ireland.},
}
RevDate: 2026-09-12
CmpDate: 2026-09-12
The chromosomal genome sequence of the lesser starlet coral, Siderastrea radians (Pallas, 1766) (Scleractinia: Rhizangiidae) and its associated microbial metagenome sequences.
Wellcome open research, 11:493.
We present a genome assembly from a specimen of Siderastrea radians (lesser starlet coral; Cnidaria; Anthozoa; Scleractinia; Rhizangiidae). The genome sequence has a total length of 807.19 megabases. Most of the assembly (94.17%) is scaffolded into 14 chromosomal pseudomolecules. The mitochondrial genome has also been assembled, with a length of 19.38 kilobases. Gene annotation of this assembly by Ensembl identified 47 051 protein-coding genes. From the metagenome data, we recovered two binned metagenomes assigned to the bacterial phylum Bacteroidota and class Bacteroidia.
Additional Links: PMID-42729027
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@article {pmid42729027,
year = {2026},
author = {Avelino, C and Karp, R and Baker, A and Metz, S and Sweet, M and Oatley, G and Sinclair, E and Aunin, E and Gettle, N and Santos, C and Paulini, M and Niu, H and McKenna, V and O'Brien, R and , and , and , and , and , },
title = {The chromosomal genome sequence of the lesser starlet coral, Siderastrea radians (Pallas, 1766) (Scleractinia: Rhizangiidae) and its associated microbial metagenome sequences.},
journal = {Wellcome open research},
volume = {11},
number = {},
pages = {493},
doi = {10.12688/wellcomeopenres.27286.1},
pmid = {42729027},
issn = {2398-502X},
abstract = {We present a genome assembly from a specimen of Siderastrea radians (lesser starlet coral; Cnidaria; Anthozoa; Scleractinia; Rhizangiidae). The genome sequence has a total length of 807.19 megabases. Most of the assembly (94.17%) is scaffolded into 14 chromosomal pseudomolecules. The mitochondrial genome has also been assembled, with a length of 19.38 kilobases. Gene annotation of this assembly by Ensembl identified 47 051 protein-coding genes. From the metagenome data, we recovered two binned metagenomes assigned to the bacterial phylum Bacteroidota and class Bacteroidia.},
}
RevDate: 2026-09-12
CmpDate: 2026-09-12
The chromosomal genome sequence of the maze coral, Meandrina meandrites (Linnaeus, 1758) (Scleractinia: Meandrinidae) and its associated microbial metagenome sequences.
Wellcome open research, 11:469.
We present a genome assembly from a specimen of Meandrina meandrites (maze coral; Cnidaria; Anthozoa; Scleractinia; Meandrinidae). The genome sequence has a total length of 551.16 megabases. Most of the assembly (99.25%) is scaffolded into 14 chromosomal pseudomolecules. The mitochondrial genome has also been assembled, with a length of 17.2 kilobases. Gene annotation of this assembly by Ensembl identified 30 464 protein-coding genes. We recovered two bins from the metagenome data.
Additional Links: PMID-42729039
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@article {pmid42729039,
year = {2026},
author = {Stewart, JM and Medina, M and Bruckner, A and May, L and Moffitt, ZJ and Lopez, JV and Woodley, CM and Metz, S and Sweet, M and Pruzinsky, N and Oatley, G and Sinclair, E and Aunin, E and Gettle, N and Santos, C and Paulini, M and Niu, H and McKenna, V and O'Brien, R and , and , and , and , and , },
title = {The chromosomal genome sequence of the maze coral, Meandrina meandrites (Linnaeus, 1758) (Scleractinia: Meandrinidae) and its associated microbial metagenome sequences.},
journal = {Wellcome open research},
volume = {11},
number = {},
pages = {469},
doi = {10.12688/wellcomeopenres.27184.1},
pmid = {42729039},
issn = {2398-502X},
abstract = {We present a genome assembly from a specimen of Meandrina meandrites (maze coral; Cnidaria; Anthozoa; Scleractinia; Meandrinidae). The genome sequence has a total length of 551.16 megabases. Most of the assembly (99.25%) is scaffolded into 14 chromosomal pseudomolecules. The mitochondrial genome has also been assembled, with a length of 17.2 kilobases. Gene annotation of this assembly by Ensembl identified 30 464 protein-coding genes. We recovered two bins from the metagenome data.},
}
RevDate: 2026-09-10
CmpDate: 2026-09-10
The Cognitive Transaction: Toward a Human Factors Research Agenda for AI in Anesthesia and Perioperative Care.
JMIR human factors, 13:e102683 pii:v13i1e102683.
AI is now embedded in the infrastructure of perioperative care. Risk stratification algorithms, hemodynamic prediction tools, and clinical decision support systems are active in operating rooms at major health systems, and their adoption is accelerating. However, the field has studied model performance and organizational implementation while largely bypassing the moment between them: the real-time encounter in which an anesthesia provider must decide, under active case conditions, what to do with an AI-generated output. We term this the cognitive transaction and argue that it is the fundamental unit of perioperative AI implementation. The perioperative environment presents a specific constellation of conditions that existing human-AI interaction research was not designed to address. Continuous real-time decision demands, extreme time compression, high cognitive load, and consequences that unfold in seconds distinguish the operating room from the clinical contexts where most provider-AI interaction research has been conducted. What we know about AI adoption in radiology, oncology, or ambulatory care does not readily translate to this setting. The cognitive moment in anesthesia has its own structure, its own failure modes, and its own research requirements. This paper examines what those requirements are. We analyze how the operating room functions as a pre-existing human-machine cognitive system into which AI is now being inserted, and why the conditions of that system generate predictable vulnerabilities: miscalibrated trust, automation bias, and cognitive friction produced by interfaces optimized for technical accuracy rather than clinical usability. We argue that these failure modes are not incidental but structural and that they will persist regardless of model performance until the provider-AI interaction is itself treated as a research object. We identify 4 priority research domains. The first concerns the structure of provider-AI disagreement and the methods needed to distinguish automation bias from legitimate clinical insight. The second concerns the longitudinal dynamics of trust calibration across repeated clinical encounters rather than single-session experimental designs. The third concerns interface design for high-acuity workflows, specifically what constitutes a usable AI output for a provider managing a patient in real time. The fourth concerns the need for ecologically valid study designs capable of capturing provider reasoning under actual perioperative conditions rather than retrospective or survey-based proxies. The anesthesia and perioperative research community is positioned to lead this work. The clinical specificity, domain knowledge, and professional stake required to design meaningful studies are all present within the field. Evaluating the cognitive transaction under perioperative conditions, not the computational model in isolation, is both a methodological imperative and a patient safety priority.
Additional Links: PMID-42721478
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@article {pmid42721478,
year = {2026},
author = {Warner, S and Stucky, CH and Haegerich, T and Yauger, YJ},
title = {The Cognitive Transaction: Toward a Human Factors Research Agenda for AI in Anesthesia and Perioperative Care.},
journal = {JMIR human factors},
volume = {13},
number = {},
pages = {e102683},
doi = {10.2196/102683},
pmid = {42721478},
issn = {2292-9495},
mesh = {Humans ; *Artificial Intelligence ; *Perioperative Care/methods ; *Anesthesia/methods ; *Ergonomics ; },
abstract = {AI is now embedded in the infrastructure of perioperative care. Risk stratification algorithms, hemodynamic prediction tools, and clinical decision support systems are active in operating rooms at major health systems, and their adoption is accelerating. However, the field has studied model performance and organizational implementation while largely bypassing the moment between them: the real-time encounter in which an anesthesia provider must decide, under active case conditions, what to do with an AI-generated output. We term this the cognitive transaction and argue that it is the fundamental unit of perioperative AI implementation. The perioperative environment presents a specific constellation of conditions that existing human-AI interaction research was not designed to address. Continuous real-time decision demands, extreme time compression, high cognitive load, and consequences that unfold in seconds distinguish the operating room from the clinical contexts where most provider-AI interaction research has been conducted. What we know about AI adoption in radiology, oncology, or ambulatory care does not readily translate to this setting. The cognitive moment in anesthesia has its own structure, its own failure modes, and its own research requirements. This paper examines what those requirements are. We analyze how the operating room functions as a pre-existing human-machine cognitive system into which AI is now being inserted, and why the conditions of that system generate predictable vulnerabilities: miscalibrated trust, automation bias, and cognitive friction produced by interfaces optimized for technical accuracy rather than clinical usability. We argue that these failure modes are not incidental but structural and that they will persist regardless of model performance until the provider-AI interaction is itself treated as a research object. We identify 4 priority research domains. The first concerns the structure of provider-AI disagreement and the methods needed to distinguish automation bias from legitimate clinical insight. The second concerns the longitudinal dynamics of trust calibration across repeated clinical encounters rather than single-session experimental designs. The third concerns interface design for high-acuity workflows, specifically what constitutes a usable AI output for a provider managing a patient in real time. The fourth concerns the need for ecologically valid study designs capable of capturing provider reasoning under actual perioperative conditions rather than retrospective or survey-based proxies. The anesthesia and perioperative research community is positioned to lead this work. The clinical specificity, domain knowledge, and professional stake required to design meaningful studies are all present within the field. Evaluating the cognitive transaction under perioperative conditions, not the computational model in isolation, is both a methodological imperative and a patient safety priority.},
}
MeSH Terms:
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Humans
*Artificial Intelligence
*Perioperative Care/methods
*Anesthesia/methods
*Ergonomics
RevDate: 2026-09-11
CmpDate: 2026-09-11
The genome sequence of a muscid fly, Lispocephala verna (Fabricius, 1794) (Diptera: Muscidae).
Wellcome open research, 11:394.
We present a genome assembly from an individual female Lispocephala verna (muscid fly; Arthropoda; Insecta; Diptera; Muscidae). The assembly contains two haplotypes with total lengths of 987.71 megabases and 934.62 megabases. Most of haplotype 1 (95.8%) is scaffolded into 5 chromosomal pseudomolecules. Haplotype 2 was assembled to scaffold level. The mitochondrial genome has also been assembled, with a length of 16.34 kilobases. This assembly was generated as part of the Darwin Tree of Life project, which produces genomes for eukaryotic species found in Britain and Ireland.
Additional Links: PMID-42723656
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Citation:
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@article {pmid42723656,
year = {2026},
author = {Crowley, LM and Falk, S and Hutchinson, F and Grzywacz, A and , and , and , and , and , and , and , },
title = {The genome sequence of a muscid fly, Lispocephala verna (Fabricius, 1794) (Diptera: Muscidae).},
journal = {Wellcome open research},
volume = {11},
number = {},
pages = {394},
pmid = {42723656},
issn = {2398-502X},
abstract = {We present a genome assembly from an individual female Lispocephala verna (muscid fly; Arthropoda; Insecta; Diptera; Muscidae). The assembly contains two haplotypes with total lengths of 987.71 megabases and 934.62 megabases. Most of haplotype 1 (95.8%) is scaffolded into 5 chromosomal pseudomolecules. Haplotype 2 was assembled to scaffold level. The mitochondrial genome has also been assembled, with a length of 16.34 kilobases. This assembly was generated as part of the Darwin Tree of Life project, which produces genomes for eukaryotic species found in Britain and Ireland.},
}
RevDate: 2026-09-10
CmpDate: 2026-09-10
Integrated molecular, epidemiological, and bioinformatics perspectives on the Mpox virus: Implications for surveillance and Global Health preparedness.
Journal of microbiological methods, 249:107656.
Mpox has re-emerged as a significant global zoonotic threat, driven mainly by two large waves the 2022 worldwide Clade IIb outbreak and the 2024 Clade Ib epidemic in Central Africa. This review examines the challenges of interpreting this evolving virus from molecular, epidemiological, and bioinformatics perspectives, with a focus on global health workforce preparedness. Clade IIb largely moved through sexual transmission across countries, but Clade Ib has appeared in a wider population-women, children, and individuals infected through household spread without any sexual contact. Early case series suggest that Clade Ib may cause a more severe disease burden, but more research is needed to directly compare severity and fatality rates with Clade IIb due to the limited number of current studies. The review examines the virus's strategies for evading the host's immune defenses throughout its ∼197 kbp genome, including how it disrupts interferon signaling and creates decoy receptors. This review summarizes the clinical findings of PALM007 and STOMP, noting that neither trial achieved its main efficacy endpoint making routine tecovirimat use less compelling-while leaving open whether it helps particular high-risk groups. A further point is that immunity from the MVA-BN vaccine wanes with time, leading to the growing adoption of booster vaccinations. In conclusion, the review calls for a One Health approach pairing genomic tracking with ecological intelligence and including wastewater surveillance to fill existing gaps in knowledge and enhance the global handling of new orthopoxvirus threats.
Additional Links: PMID-42562267
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PubMed:
Citation:
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@article {pmid42562267,
year = {2026},
author = {Detroja, R and Chandra, M},
title = {Integrated molecular, epidemiological, and bioinformatics perspectives on the Mpox virus: Implications for surveillance and Global Health preparedness.},
journal = {Journal of microbiological methods},
volume = {249},
number = {},
pages = {107656},
doi = {10.1016/j.mimet.2026.107656},
pmid = {42562267},
issn = {1872-8359},
mesh = {Humans ; Global Health ; Animals ; *Computational Biology/methods ; *Orthopoxvirus/genetics/immunology/classification ; Molecular Epidemiology ; Genome, Viral ; Disease Outbreaks ; Zoonoses/virology/epidemiology ; },
abstract = {Mpox has re-emerged as a significant global zoonotic threat, driven mainly by two large waves the 2022 worldwide Clade IIb outbreak and the 2024 Clade Ib epidemic in Central Africa. This review examines the challenges of interpreting this evolving virus from molecular, epidemiological, and bioinformatics perspectives, with a focus on global health workforce preparedness. Clade IIb largely moved through sexual transmission across countries, but Clade Ib has appeared in a wider population-women, children, and individuals infected through household spread without any sexual contact. Early case series suggest that Clade Ib may cause a more severe disease burden, but more research is needed to directly compare severity and fatality rates with Clade IIb due to the limited number of current studies. The review examines the virus's strategies for evading the host's immune defenses throughout its ∼197 kbp genome, including how it disrupts interferon signaling and creates decoy receptors. This review summarizes the clinical findings of PALM007 and STOMP, noting that neither trial achieved its main efficacy endpoint making routine tecovirimat use less compelling-while leaving open whether it helps particular high-risk groups. A further point is that immunity from the MVA-BN vaccine wanes with time, leading to the growing adoption of booster vaccinations. In conclusion, the review calls for a One Health approach pairing genomic tracking with ecological intelligence and including wastewater surveillance to fill existing gaps in knowledge and enhance the global handling of new orthopoxvirus threats.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Humans
Global Health
Animals
*Computational Biology/methods
*Orthopoxvirus/genetics/immunology/classification
Molecular Epidemiology
Genome, Viral
Disease Outbreaks
Zoonoses/virology/epidemiology
RevDate: 2026-09-10
CmpDate: 2026-09-10
Speeding up taxonomy in the digital age: A deep learning approach for identifying cryptic freshwater snails.
PLoS computational biology, 22(9):e1014733.
Cryptic species complexes pose fundamental challenges to biologists, as species exhibit minimal morphological differences that require integrating morphology, genetics, and biogeography for identification. Here, we present a deep learning approach to support species identification in the freshwater snail genus Radomaniola (Hydrobiidae), a morphologically cryptic group from the Balkans. Our approach mirrors the integrative workflow of expert taxonomists by combining shell images, morphometric measurements, and collection‑site metadata, with optional phylogenetic information. Despite being trained on fewer than 700 specimens across 20 visually similar species with strongly imbalanced class sizes, the system achieved high identification performance. Careful control of spurious correlations, such as those arising from site‑specific imaging conditions or overly precise geographic metadata, was essential to ensure that the network learned biologically meaningful features. Across all experiments, integrating multiple data types and jointly optimizing meaningful embeddings and classification consistently improved performance over image‑only and classification‑only baselines. On specimens from collection sites seen during training we achieved a macro-averaged F1 score of 0.93. Even though this dropped as low as 0.14 when evaluating on specimens from previously unsampled localities, it could be rapidly recovered by retraining with 2-3 newly labeled specimens. Additionally, model top-3 accuracy stayed consistently above 80% in all settings. These results show that relatively lightweight deep learning models can provide practical decision support in real taxonomic workflows.
Additional Links: PMID-42685092
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Citation:
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@article {pmid42685092,
year = {2026},
author = {Vetter, D and Ahsan, M and Delicado, D and Neubauer, TA and Wilke, T and Roig, G},
title = {Speeding up taxonomy in the digital age: A deep learning approach for identifying cryptic freshwater snails.},
journal = {PLoS computational biology},
volume = {22},
number = {9},
pages = {e1014733},
pmid = {42685092},
issn = {1553-7358},
mesh = {Animals ; *Deep Learning ; *Snails/classification/anatomy & histology ; Phylogeny ; Fresh Water ; Computational Biology/methods ; Classification Algorithms ; Image Processing, Computer-Assisted/methods ; Species Specificity ; },
abstract = {Cryptic species complexes pose fundamental challenges to biologists, as species exhibit minimal morphological differences that require integrating morphology, genetics, and biogeography for identification. Here, we present a deep learning approach to support species identification in the freshwater snail genus Radomaniola (Hydrobiidae), a morphologically cryptic group from the Balkans. Our approach mirrors the integrative workflow of expert taxonomists by combining shell images, morphometric measurements, and collection‑site metadata, with optional phylogenetic information. Despite being trained on fewer than 700 specimens across 20 visually similar species with strongly imbalanced class sizes, the system achieved high identification performance. Careful control of spurious correlations, such as those arising from site‑specific imaging conditions or overly precise geographic metadata, was essential to ensure that the network learned biologically meaningful features. Across all experiments, integrating multiple data types and jointly optimizing meaningful embeddings and classification consistently improved performance over image‑only and classification‑only baselines. On specimens from collection sites seen during training we achieved a macro-averaged F1 score of 0.93. Even though this dropped as low as 0.14 when evaluating on specimens from previously unsampled localities, it could be rapidly recovered by retraining with 2-3 newly labeled specimens. Additionally, model top-3 accuracy stayed consistently above 80% in all settings. These results show that relatively lightweight deep learning models can provide practical decision support in real taxonomic workflows.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Animals
*Deep Learning
*Snails/classification/anatomy & histology
Phylogeny
Fresh Water
Computational Biology/methods
Classification Algorithms
Image Processing, Computer-Assisted/methods
Species Specificity
RevDate: 2026-09-08
CmpDate: 2026-09-08
A One Health approach to Antimicrobial Resistance: Concepts, challenges, and advances in omics.
Advances in applied microbiology, 134:1-101.
Antimicrobial resistance (AMR) is a global threat driven by the interplay between microbial evolution and human activity. Antimicrobial use in human and veterinary medicine, as well as in agriculture, accelerates the selection and dissemination of resistant bacteria and genes across interconnected human, animal, and environmental reservoirs. These dynamic exchanges render single-sector interventions ineffective. A One Health approach integrating human, animal, and environmental health is therefore essential to understand and mitigate the emergence and spread of AMR. This chapter focuses on bacterial antimicrobial resistance, addressing key concepts, major challenges, and emerging technologies within a One Health framework. Advances in next-generation sequencing and omics technologies have transformed our capacity to resolve AMR at unprecedented scale and resolution. These tools enable the tracking of resistance genes and high-risk clones across ecosystems, uncover transmission pathways, and identify key drivers of dissemination. Such insights support real-time epidemiological surveillance, outbreak detection, and targeted interventions. However, translating these advances into routine practice remains a major challenge, requiring harmonized methodologies, data integration, and cross-sector coordination. Addressing AMR demands sustained collaboration across disciplines and stakeholders, including clinicians, veterinarians, farmers, researchers, policymakers, industry, and the public. And framing AMR as a shared ecological and societal responsibility underscores the urgency of coordinated global action. We call for the urgent integration of One Health principles into surveillance, policy, and innovation to preserve antimicrobial effectiveness and safeguard future health.
Additional Links: PMID-42711003
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PubMed:
Citation:
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@article {pmid42711003,
year = {2026},
author = {Ribeiro, IM and Almeida-Santos, AC and Peixe, L and Novais, C and Freitas, AR},
title = {A One Health approach to Antimicrobial Resistance: Concepts, challenges, and advances in omics.},
journal = {Advances in applied microbiology},
volume = {134},
number = {},
pages = {1-101},
doi = {10.1016/bs.aambs.2026.07.001},
pmid = {42711003},
issn = {0065-2164},
mesh = {Humans ; *One Health ; Animals ; *Drug Resistance, Bacterial ; *Anti-Bacterial Agents/pharmacology ; *Bacteria/drug effects/genetics ; *Bacterial Infections/microbiology/drug therapy ; Multiomics ; Genomics ; },
abstract = {Antimicrobial resistance (AMR) is a global threat driven by the interplay between microbial evolution and human activity. Antimicrobial use in human and veterinary medicine, as well as in agriculture, accelerates the selection and dissemination of resistant bacteria and genes across interconnected human, animal, and environmental reservoirs. These dynamic exchanges render single-sector interventions ineffective. A One Health approach integrating human, animal, and environmental health is therefore essential to understand and mitigate the emergence and spread of AMR. This chapter focuses on bacterial antimicrobial resistance, addressing key concepts, major challenges, and emerging technologies within a One Health framework. Advances in next-generation sequencing and omics technologies have transformed our capacity to resolve AMR at unprecedented scale and resolution. These tools enable the tracking of resistance genes and high-risk clones across ecosystems, uncover transmission pathways, and identify key drivers of dissemination. Such insights support real-time epidemiological surveillance, outbreak detection, and targeted interventions. However, translating these advances into routine practice remains a major challenge, requiring harmonized methodologies, data integration, and cross-sector coordination. Addressing AMR demands sustained collaboration across disciplines and stakeholders, including clinicians, veterinarians, farmers, researchers, policymakers, industry, and the public. And framing AMR as a shared ecological and societal responsibility underscores the urgency of coordinated global action. We call for the urgent integration of One Health principles into surveillance, policy, and innovation to preserve antimicrobial effectiveness and safeguard future health.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Humans
*One Health
Animals
*Drug Resistance, Bacterial
*Anti-Bacterial Agents/pharmacology
*Bacteria/drug effects/genetics
*Bacterial Infections/microbiology/drug therapy
Multiomics
Genomics
RevDate: 2026-09-10
A guide to understanding tumour evolution through the lens of population genetics.
Nature reviews. Cancer [Epub ahead of print].
Every cancer carries the history of its own evolution, hidden in its genome. Modern DNA sequencing can catalogue millions of mutations and profile tumours across space and time, but sequencing alone struggles to answer the questions that matter most: when did key adaptations emerge, how strongly were they selected, why do some tumours relapse whereas others do not, and how will the cancer evolve next? The reason is fundamental: sequencing is a snapshot, whereas evolution is a dynamic process. Bridging this gap requires moving beyond descriptive cancer genomics towards quantitative evolutionary inference. In this Review, we argue that population genetics provides the mathematical framework needed to extract evolutionary dynamics from cancer genomes. We show how models of mutation, selection and drift transform allele frequencies from descriptive measurements into quantitative estimates of clonal fitness and evolutionary timings. We discuss how these principles extend to epigenetic inheritance, plasticity and ecological interactions within the tumour ecosystem, and examine the assumptions and limitations for their application to modern sequencing data. By reframing cancer genomes as quantitative records of evolutionary processes rather than catalogues of mutations, researchers have used population genetics to provide a foundation for understanding - and ultimately predicting - the trajectories of cancer evolution.
Additional Links: PMID-42717056
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@article {pmid42717056,
year = {2026},
author = {Caravagna, G and Graham, TA and Sottoriva, A},
title = {A guide to understanding tumour evolution through the lens of population genetics.},
journal = {Nature reviews. Cancer},
volume = {},
number = {},
pages = {},
pmid = {42717056},
issn = {1474-1768},
abstract = {Every cancer carries the history of its own evolution, hidden in its genome. Modern DNA sequencing can catalogue millions of mutations and profile tumours across space and time, but sequencing alone struggles to answer the questions that matter most: when did key adaptations emerge, how strongly were they selected, why do some tumours relapse whereas others do not, and how will the cancer evolve next? The reason is fundamental: sequencing is a snapshot, whereas evolution is a dynamic process. Bridging this gap requires moving beyond descriptive cancer genomics towards quantitative evolutionary inference. In this Review, we argue that population genetics provides the mathematical framework needed to extract evolutionary dynamics from cancer genomes. We show how models of mutation, selection and drift transform allele frequencies from descriptive measurements into quantitative estimates of clonal fitness and evolutionary timings. We discuss how these principles extend to epigenetic inheritance, plasticity and ecological interactions within the tumour ecosystem, and examine the assumptions and limitations for their application to modern sequencing data. By reframing cancer genomes as quantitative records of evolutionary processes rather than catalogues of mutations, researchers have used population genetics to provide a foundation for understanding - and ultimately predicting - the trajectories of cancer evolution.},
}
RevDate: 2026-09-10
CmpDate: 2026-09-10
Conserved storage-carbohydrate metabolic modules are rewired during germination of Trichoderma asperelloides and other Sordariomycetes.
Frontiers in fungal biology, 7:1930613.
Conidial germination requires rapid mobilization and reorganization of storage carbohydrates, yet the network architecture underlying this process remains poorly defined in filamentous fungi. Using quantitative GC-MS/MS profiling, we provide the first quantitative identification of major soluble sugar species across four germination stages of Trichoderma asperelloides T203 and compared them with four representative models in the Sordariomycetes (Metarhizium anisopliae, Cordyceps militaris, Fusarium graminearum, and Neurospora crassa). In T. asperelloides, mannitol was the most prevalent measured sugar in dormant conidia, declined sharply at polarity establishment, and partially recovered at later stages, while trehalose displayed a reciprocal increase and other sugars remained comparatively stable. Comparative analyses revealed distinct species-specific carbon storage strategies: Dormant conidia of T. asperelloides, M. anisopliae, and C. militaris were mannitol-enriched, whereas in N. crassa and F. graminearum glucose was the most abundant; after germination onset, most species shifted toward glucose accumulation, but T. asperelloides uniquely transitioned from mannitol to trehalose dominance before partial re-accumulation of mannitol. Integration of sugar profiles with time-resolved RNA-seq and Bayesian network inference revealed conserved core interactions but also lineage-specific divergences in mannitol/trehalose-associated central-carbon modules that correspond to distinct nutrient and lifestyle strategies during early colonization. A focused analysis in T. asperelloides uncovered extensive stage-dependent transcriptional remodeling of metabolic-process genes and a mannitol-centered module involving mpd1 and mtd1 (encoding mannitol-1-phosphate 5-dehydrogenase and mannitol dehydrogenase, respectively). Antisense-based knockdown of mpd1 strongly reduced its transcript levels and led to stage-dependent upregulation of mtd1. However, these changes left mannitol content, soluble-sugar profiles, germination dynamics, and growth on mannitol essentially unchanged. Together, our comparative metabolic-network analysis shows that conidial mannitol and trehalose metabolism in T. asperelloides is embedded in a flexible, partially redundant central-carbon framework, and establishes this species as a tractable model for systems-level dissection of sugar metabolic regulation during early fungal development and colonization.
Additional Links: PMID-42718801
PubMed:
Citation:
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@article {pmid42718801,
year = {2026},
author = {Tenennbaum, B and Yakubovich, E and Wang, YW and Meng, G and Moonjely, S and Trail, F and Ben Ari, J and Wang, Z and Dong, C and Townsend, JP and Yarden, O},
title = {Conserved storage-carbohydrate metabolic modules are rewired during germination of Trichoderma asperelloides and other Sordariomycetes.},
journal = {Frontiers in fungal biology},
volume = {7},
number = {},
pages = {1930613},
pmid = {42718801},
issn = {2673-6128},
abstract = {Conidial germination requires rapid mobilization and reorganization of storage carbohydrates, yet the network architecture underlying this process remains poorly defined in filamentous fungi. Using quantitative GC-MS/MS profiling, we provide the first quantitative identification of major soluble sugar species across four germination stages of Trichoderma asperelloides T203 and compared them with four representative models in the Sordariomycetes (Metarhizium anisopliae, Cordyceps militaris, Fusarium graminearum, and Neurospora crassa). In T. asperelloides, mannitol was the most prevalent measured sugar in dormant conidia, declined sharply at polarity establishment, and partially recovered at later stages, while trehalose displayed a reciprocal increase and other sugars remained comparatively stable. Comparative analyses revealed distinct species-specific carbon storage strategies: Dormant conidia of T. asperelloides, M. anisopliae, and C. militaris were mannitol-enriched, whereas in N. crassa and F. graminearum glucose was the most abundant; after germination onset, most species shifted toward glucose accumulation, but T. asperelloides uniquely transitioned from mannitol to trehalose dominance before partial re-accumulation of mannitol. Integration of sugar profiles with time-resolved RNA-seq and Bayesian network inference revealed conserved core interactions but also lineage-specific divergences in mannitol/trehalose-associated central-carbon modules that correspond to distinct nutrient and lifestyle strategies during early colonization. A focused analysis in T. asperelloides uncovered extensive stage-dependent transcriptional remodeling of metabolic-process genes and a mannitol-centered module involving mpd1 and mtd1 (encoding mannitol-1-phosphate 5-dehydrogenase and mannitol dehydrogenase, respectively). Antisense-based knockdown of mpd1 strongly reduced its transcript levels and led to stage-dependent upregulation of mtd1. However, these changes left mannitol content, soluble-sugar profiles, germination dynamics, and growth on mannitol essentially unchanged. Together, our comparative metabolic-network analysis shows that conidial mannitol and trehalose metabolism in T. asperelloides is embedded in a flexible, partially redundant central-carbon framework, and establishes this species as a tractable model for systems-level dissection of sugar metabolic regulation during early fungal development and colonization.},
}
RevDate: 2026-09-10
Multi-mode design for studying cyber aggression in texts, Facebook and Twitter messages among middle school youth.
American journal of epidemiology pii:8789971 [Epub ahead of print].
With the explosion of the internet, cyber aggression has become one of the fastest growing forms of interpersonal violence. Methods used to understand aggressive communications content have been limited primarily to surveys. Here, we present multiple methods - panel surveys, electronic capture of social media, and Ecological Momentary Assessments - to characterize both behavioral and perceptual components of cyber aggression in a study of youth from two Iowa middle schools during the 2014-2015 school year. Youth completed a survey, and a sub-sample of smartphone owners installed an electronic application that collected over 150,000 text messages, Twitter posts, and Facebook posts. The sub-sample also participated in ecological momentary assessments to collect self-reported experiences of cyber aggression. To code for aggressive content in this large sample of messages, a case-control sampling strategy was used to identify a series of "case" messages from youth who reported aggression and "control" messages from youth who reported no aggression. We further present recruitment protocols, data management and qualitative coding methods as well as descriptive characteristics of the student cohort and nested sample of messages. These methods have potential use in future studies of "big data" captured from social media.
Additional Links: PMID-42720568
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PubMed:
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@article {pmid42720568,
year = {2026},
author = {Ramirez, MR and Gomez, NJS and Ryan, A and Chipara, O and Heimer, K and Peek-Asa, C and Campo, S and Snirivasan, P and Xiong, BN and Trotter, AG and Paik, A},
title = {Multi-mode design for studying cyber aggression in texts, Facebook and Twitter messages among middle school youth.},
journal = {American journal of epidemiology},
volume = {},
number = {},
pages = {},
doi = {10.1093/aje/kwag222},
pmid = {42720568},
issn = {1476-6256},
abstract = {With the explosion of the internet, cyber aggression has become one of the fastest growing forms of interpersonal violence. Methods used to understand aggressive communications content have been limited primarily to surveys. Here, we present multiple methods - panel surveys, electronic capture of social media, and Ecological Momentary Assessments - to characterize both behavioral and perceptual components of cyber aggression in a study of youth from two Iowa middle schools during the 2014-2015 school year. Youth completed a survey, and a sub-sample of smartphone owners installed an electronic application that collected over 150,000 text messages, Twitter posts, and Facebook posts. The sub-sample also participated in ecological momentary assessments to collect self-reported experiences of cyber aggression. To code for aggressive content in this large sample of messages, a case-control sampling strategy was used to identify a series of "case" messages from youth who reported aggression and "control" messages from youth who reported no aggression. We further present recruitment protocols, data management and qualitative coding methods as well as descriptive characteristics of the student cohort and nested sample of messages. These methods have potential use in future studies of "big data" captured from social media.},
}
RevDate: 2026-09-09
CmpDate: 2026-09-09
A synthetic microbiome drives a multi-omics response to remediate 1,4-dithiane-contaminated soil and simultaneously suppresses antibiotic resistance genes.
Journal of hazardous materials, 516:143337.
1,4-Dithiane, a degradation product of abandoned Japanese chemical weapons, is a persistent organic pollutant with ecological risks. A synthetic microbiome (SM) was constructed through pollution stress screening and ratio optimization, consisting of Shinella sp., Alcaligenes faecalis, Sphingomonas sp., and Stenotrophomonas sp. at an optimal ratio of 1: 1: 2: 2. The SM achieved a 1,4-dithiane degradation rate of 95.2% and reduced intermediate accumulation. Soil remediation experiments showed complete pollutant removal within 60 days, along with improved soil health: reduced bioavailability of heavy metals (Cu, Zn, Cd), increased pH (6.47-6.95), elevated organic matter and enzyme activities, and decreased salinity and redox potential. Integration of ionomics, 16S sequencing, metagenomics, metabolomics, and HT-qPCR revealed that SM colonization reshaped microbial community structure, suppressed ARG-harboring bacteria (e.g., Pseudomonas), and activated core pathways (oxidative phosphorylation and glutathione metabolism), enhancing metabolic activity and oxidative stress tolerance. Consequently, the diversity, abundance, and diffusion potential of soil ARGs and mobile genetic elements were significantly reduced. These findings provide microbial solutions and a theoretical basis for concurrent organic pollution control and soil ecological risk management.
Additional Links: PMID-42623872
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PubMed:
Citation:
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@article {pmid42623872,
year = {2026},
author = {Yang, X and Ji, XH and Li, C and Zhang, SR and Lai, JL and Luo, XG},
title = {A synthetic microbiome drives a multi-omics response to remediate 1,4-dithiane-contaminated soil and simultaneously suppresses antibiotic resistance genes.},
journal = {Journal of hazardous materials},
volume = {516},
number = {},
pages = {143337},
doi = {10.1016/j.jhazmat.2026.143337},
pmid = {42623872},
issn = {1873-3336},
mesh = {*Soil Pollutants/metabolism ; *Microbiota ; *Soil Microbiology ; *Drug Resistance, Microbial/genetics ; Biodegradation, Environmental ; Multiomics ; Genes, Bacterial ; },
abstract = {1,4-Dithiane, a degradation product of abandoned Japanese chemical weapons, is a persistent organic pollutant with ecological risks. A synthetic microbiome (SM) was constructed through pollution stress screening and ratio optimization, consisting of Shinella sp., Alcaligenes faecalis, Sphingomonas sp., and Stenotrophomonas sp. at an optimal ratio of 1: 1: 2: 2. The SM achieved a 1,4-dithiane degradation rate of 95.2% and reduced intermediate accumulation. Soil remediation experiments showed complete pollutant removal within 60 days, along with improved soil health: reduced bioavailability of heavy metals (Cu, Zn, Cd), increased pH (6.47-6.95), elevated organic matter and enzyme activities, and decreased salinity and redox potential. Integration of ionomics, 16S sequencing, metagenomics, metabolomics, and HT-qPCR revealed that SM colonization reshaped microbial community structure, suppressed ARG-harboring bacteria (e.g., Pseudomonas), and activated core pathways (oxidative phosphorylation and glutathione metabolism), enhancing metabolic activity and oxidative stress tolerance. Consequently, the diversity, abundance, and diffusion potential of soil ARGs and mobile genetic elements were significantly reduced. These findings provide microbial solutions and a theoretical basis for concurrent organic pollution control and soil ecological risk management.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Soil Pollutants/metabolism
*Microbiota
*Soil Microbiology
*Drug Resistance, Microbial/genetics
Biodegradation, Environmental
Multiomics
Genes, Bacterial
RevDate: 2026-09-08
CmpDate: 2026-09-08
Up-to-date, and taxonomy-curated mcrA reference databases for methanogen community profiling.
Systematic and applied microbiology, 49(5):126752.
The methyl-coenzyme M reductase subunit alpha gene (mcrA) is an important phylogenetic marker for high throughput ecological profiling of methanogenic archaea, central to industrial biological methane production and greenhouse gas emissions. Yet, dedicated reference databases predate current relevant NCBI sequence accumulation and archaeal taxonomic revision. We present three updated mcrA reference databases: (i) one derived from NCBI-catalogued methanogen genomes (1572 sequences); (ii) a database built by expansion of a previously published reference dataset, leveraging the NCBI nucleotide collection (27,942 sequences); (iii) a curated-taxonomy version of the latter. The updated amplicon databases provide a ∼ 3.5-fold sequence richness expansion, extend genus-level richness from 31 to 83 taxa, more than 4-fold species-level richness, and incorporate novel lineages compared with the previous reference dataset (e.g. Thermoplasmatota-encompassed). All databases were formatted to support analysis with relevant contemporary software pipelines and packages. Overall, the generated databases facilitate a highly improved characterization of methanogen diversity and ecology.
Additional Links: PMID-42468162
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PubMed:
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@article {pmid42468162,
year = {2026},
author = {Vasileiadis, S and Valmas, MI and Pitsikoglou, DS and Rodosthenous, J and Omirou, M and Kotsopoulos, TA and Yan, Y and Fu, D and Fotidis, IA},
title = {Up-to-date, and taxonomy-curated mcrA reference databases for methanogen community profiling.},
journal = {Systematic and applied microbiology},
volume = {49},
number = {5},
pages = {126752},
doi = {10.1016/j.syapm.2026.126752},
pmid = {42468162},
issn = {1618-0984},
mesh = {*Archaea/classification/genetics/enzymology ; *Methane/metabolism ; *Oxidoreductases/genetics ; Phylogeny ; *Databases, Genetic ; Biocuration ; },
abstract = {The methyl-coenzyme M reductase subunit alpha gene (mcrA) is an important phylogenetic marker for high throughput ecological profiling of methanogenic archaea, central to industrial biological methane production and greenhouse gas emissions. Yet, dedicated reference databases predate current relevant NCBI sequence accumulation and archaeal taxonomic revision. We present three updated mcrA reference databases: (i) one derived from NCBI-catalogued methanogen genomes (1572 sequences); (ii) a database built by expansion of a previously published reference dataset, leveraging the NCBI nucleotide collection (27,942 sequences); (iii) a curated-taxonomy version of the latter. The updated amplicon databases provide a ∼ 3.5-fold sequence richness expansion, extend genus-level richness from 31 to 83 taxa, more than 4-fold species-level richness, and incorporate novel lineages compared with the previous reference dataset (e.g. Thermoplasmatota-encompassed). All databases were formatted to support analysis with relevant contemporary software pipelines and packages. Overall, the generated databases facilitate a highly improved characterization of methanogen diversity and ecology.},
}
MeSH Terms:
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*Archaea/classification/genetics/enzymology
*Methane/metabolism
*Oxidoreductases/genetics
Phylogeny
*Databases, Genetic
Biocuration
RevDate: 2026-09-08
CmpDate: 2026-09-08
Simple birth-death-mutation models predict some-but not all-aspects of the experimental evolution of antibiotic resistance.
PLoS computational biology, 22(8):e1014666 pii:PCOMPBIOL-D-25-02099.
Mathematical modelling of antibiotic resistance plays an important role in understanding the mechanisms of resistance emergence and spreading, testing the feasibility of new treatment protocols, and antimicrobial stewardship. However, many assumptions underlying some of the most commonly used mathematical models have not been rigorously tested experimentally. We verify whether one of these models - a birth-death-mutation process - is able to quantitatively predict the outcome of laboratory experiments. We grow bacteria in a bioreactor in conditions that closely resemble the assumptions of the model, and compare the model predictions with experimental observables such as the probability and time to resistance evolution, mutant number distribution, and the genetic composition of the evolved populations. We show that the model fails to reproduce some aspects of the experiments (failing differently for different antibiotics) but that simple modifications of the model significantly improve its predictive power. These modifications give insight into the population dynamics of resistant mutants for each antibiotic tested, and highlight the importance of quantitative modelling for accurate prediction of antibiotic resistance evolution.
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@article {pmid42664271,
year = {2026},
author = {Lilja, E and Allen, RJ and Waclaw, B},
title = {Simple birth-death-mutation models predict some-but not all-aspects of the experimental evolution of antibiotic resistance.},
journal = {PLoS computational biology},
volume = {22},
number = {8},
pages = {e1014666},
doi = {10.1371/journal.pcbi.1014666},
pmid = {42664271},
issn = {1553-7358},
mesh = {*Mutation/genetics ; Anti-Bacterial Agents/pharmacology ; *Drug Resistance, Bacterial/genetics ; *Models, Genetic ; Evolution, Molecular ; *Drug Resistance, Microbial/genetics ; Escherichia coli/genetics/drug effects ; Bioreactors/microbiology ; Computational Biology ; },
abstract = {Mathematical modelling of antibiotic resistance plays an important role in understanding the mechanisms of resistance emergence and spreading, testing the feasibility of new treatment protocols, and antimicrobial stewardship. However, many assumptions underlying some of the most commonly used mathematical models have not been rigorously tested experimentally. We verify whether one of these models - a birth-death-mutation process - is able to quantitatively predict the outcome of laboratory experiments. We grow bacteria in a bioreactor in conditions that closely resemble the assumptions of the model, and compare the model predictions with experimental observables such as the probability and time to resistance evolution, mutant number distribution, and the genetic composition of the evolved populations. We show that the model fails to reproduce some aspects of the experiments (failing differently for different antibiotics) but that simple modifications of the model significantly improve its predictive power. These modifications give insight into the population dynamics of resistant mutants for each antibiotic tested, and highlight the importance of quantitative modelling for accurate prediction of antibiotic resistance evolution.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Mutation/genetics
Anti-Bacterial Agents/pharmacology
*Drug Resistance, Bacterial/genetics
*Models, Genetic
Evolution, Molecular
*Drug Resistance, Microbial/genetics
Escherichia coli/genetics/drug effects
Bioreactors/microbiology
Computational Biology
RevDate: 2026-09-07
CmpDate: 2026-09-07
Spatially resolved multi-omics analysis of indigenous Bacillus-fortified high-temperature Daqu.
Food research international (Ottawa, Ont.), 243(Pt 2):120404.
Layer-dependent patterns associated with indigenous Bacillus fortification on high-temperature Daqu remain unclear. Here, six indigenous functional Bacillus strains were combined to fortify Daqu at three inoculation levels (QH4, QH5, QH6), with non-fortified as the control (CK). Upper, middle, and lower shelf-layer samples were profiled by physicochemical measurements, volatilomics, organic acid analysis, untargeted metabolomics, 16S/ITS amplicon sequencing, and metagenomics. PERMANOVA showed significant effects of treatment, spatial layer, and their interaction on physicochemical, volatile, bacterial, and fungal profiles (P = 0.001). Among the three inoculation levels, QH5 showed the most balanced performance: QH5_M exhibited the highest observed mean peak temperature (63.3 °C; +4.5 °C relative to CK_M), and its group-mean temperature remained ≥ 60 °C for seven consecutive days. Multi-omics analyses indicated coordinated, non-linear, and layer-dependent differences associated with indigenous Bacillus fortification, with QH5_M showing the most pronounced combined thermal, pyrazine, substrate, microbial, and predicted functional profile. These findings indicate that moderate indigenous Bacillus fortification was associated with distinct layer-dependent thermal and flavor profiles and coordinated microbial, metabolic, and predicted functional differences.
Additional Links: PMID-42705761
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PubMed:
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@article {pmid42705761,
year = {2026},
author = {Shi, H and Shen, Y and Ye, Q and Yu, H and Tian, M and Wang, H and Wei, Y and Yan, S and Chen, Y and Zhang, J and Li, S and Yang, Y and Zhao, J},
title = {Spatially resolved multi-omics analysis of indigenous Bacillus-fortified high-temperature Daqu.},
journal = {Food research international (Ottawa, Ont.)},
volume = {243},
number = {Pt 2},
pages = {120404},
doi = {10.1016/j.foodres.2026.120404},
pmid = {42705761},
issn = {1873-7145},
mesh = {*Bacillus/metabolism/genetics ; Multiomics ; *Hot Temperature ; *Food, Fortified/microbiology ; Metabolomics ; Metagenomics ; *Food Microbiology ; },
abstract = {Layer-dependent patterns associated with indigenous Bacillus fortification on high-temperature Daqu remain unclear. Here, six indigenous functional Bacillus strains were combined to fortify Daqu at three inoculation levels (QH4, QH5, QH6), with non-fortified as the control (CK). Upper, middle, and lower shelf-layer samples were profiled by physicochemical measurements, volatilomics, organic acid analysis, untargeted metabolomics, 16S/ITS amplicon sequencing, and metagenomics. PERMANOVA showed significant effects of treatment, spatial layer, and their interaction on physicochemical, volatile, bacterial, and fungal profiles (P = 0.001). Among the three inoculation levels, QH5 showed the most balanced performance: QH5_M exhibited the highest observed mean peak temperature (63.3 °C; +4.5 °C relative to CK_M), and its group-mean temperature remained ≥ 60 °C for seven consecutive days. Multi-omics analyses indicated coordinated, non-linear, and layer-dependent differences associated with indigenous Bacillus fortification, with QH5_M showing the most pronounced combined thermal, pyrazine, substrate, microbial, and predicted functional profile. These findings indicate that moderate indigenous Bacillus fortification was associated with distinct layer-dependent thermal and flavor profiles and coordinated microbial, metabolic, and predicted functional differences.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Bacillus/metabolism/genetics
Multiomics
*Hot Temperature
*Food, Fortified/microbiology
Metabolomics
Metagenomics
*Food Microbiology
RevDate: 2026-09-08
CmpDate: 2026-09-08
From the margins to the core: village and community scientists should increasingly shape the future of ethnobiology and ethnoecology.
Journal of ethnobiology and ethnomedicine, 22(1):.
Ethnobiology was not only created as a field to understand the relationship between humans and their environments; it emerged from direct engagement with rural and Indigenous communities. Yet the great paradox is that, despite its field-based origins, the discipline continues to be reproduced within urban academic spaces that often exclude those who are assumed to be at the very heart of knowledge production. In this editorial, we do not simply propose the "inclusion" of rural or Indigenous communities. Instead, we call for a radical repositioning of the knowledge itself: Who can be considered a "scientist"? And who holds the authority to define scientific knowledge? We reject the assumption that urban academic affiliation or formal credentials are the sole basis for scientific credibility, and instead propose a different standard: knowledge should be assessed by its depth, explanatory power, and integrity when co-produced in genuine partnership with living communities. Drawing on our own experiences as researchers raised in rural villages, peripheral regions, and migrant/refugees' communities, we argue that local and Indigenous ecological knowledge is not a "raw material" for scientific research, but a form of scientific thinking in its own right with its own logic, observations, and rigour, and its own way of assessing, adapting and enacting this knowledge. We therefore call for a further step ahead in the classical structure of ethnobiology: not merely the inclusion of communities in research stages, but the recognition of some of their scholars as the core producers of scientific knowledge, from the formulation of research questions to the interpretation, dissemination and enactment of results. This transformation of the locus aims not only to improve ethnobiology as a field but also to redefine it. Without this redefinition, science will remain detached from the realities it claims to understand. With it, ethnobiology can become a more honest, more courageous discipline, better equipped to confront biodiversity loss, climate change, and the reconfiguration of more-than-human-nature relationships.
Additional Links: PMID-42706571
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@article {pmid42706571,
year = {2026},
author = {Pieroni, A and Hazarika, A and Alrhmoun, M and Yebouk, C and Dina, E and Manduzai, AK and Gillani, SW and Rexhepi, B and Ullah, I and Ali, S and Khadka, D and Khan, SM and Abbasi, AM and Suriano, E and Mendoza, JN and Soukand, R and Kalle, R},
title = {From the margins to the core: village and community scientists should increasingly shape the future of ethnobiology and ethnoecology.},
journal = {Journal of ethnobiology and ethnomedicine},
volume = {22},
number = {1},
pages = {},
pmid = {42706571},
issn = {1746-4269},
mesh = {Humans ; *Ecology/trends ; *Ethnology/trends ; Rural Population ; Knowledge ; },
abstract = {Ethnobiology was not only created as a field to understand the relationship between humans and their environments; it emerged from direct engagement with rural and Indigenous communities. Yet the great paradox is that, despite its field-based origins, the discipline continues to be reproduced within urban academic spaces that often exclude those who are assumed to be at the very heart of knowledge production. In this editorial, we do not simply propose the "inclusion" of rural or Indigenous communities. Instead, we call for a radical repositioning of the knowledge itself: Who can be considered a "scientist"? And who holds the authority to define scientific knowledge? We reject the assumption that urban academic affiliation or formal credentials are the sole basis for scientific credibility, and instead propose a different standard: knowledge should be assessed by its depth, explanatory power, and integrity when co-produced in genuine partnership with living communities. Drawing on our own experiences as researchers raised in rural villages, peripheral regions, and migrant/refugees' communities, we argue that local and Indigenous ecological knowledge is not a "raw material" for scientific research, but a form of scientific thinking in its own right with its own logic, observations, and rigour, and its own way of assessing, adapting and enacting this knowledge. We therefore call for a further step ahead in the classical structure of ethnobiology: not merely the inclusion of communities in research stages, but the recognition of some of their scholars as the core producers of scientific knowledge, from the formulation of research questions to the interpretation, dissemination and enactment of results. This transformation of the locus aims not only to improve ethnobiology as a field but also to redefine it. Without this redefinition, science will remain detached from the realities it claims to understand. With it, ethnobiology can become a more honest, more courageous discipline, better equipped to confront biodiversity loss, climate change, and the reconfiguration of more-than-human-nature relationships.},
}
MeSH Terms:
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Humans
*Ecology/trends
*Ethnology/trends
Rural Population
Knowledge
RevDate: 2026-09-08
CmpDate: 2026-09-08
Individual year-round movement patterns of the GPS-tracked Grey Herons (Ardea cinerea) in Central Europe: a multi-year case study.
PeerJ, 14:e21659.
BACKGROUND: The year-round migratory behaviour of Grey Herons (Ardea cinerea) breeding in Central Europe is recognized; however, individual consistency in their movement patterns remains poorly known. In this study, we present movements of three adult Grey Herons breeding in Northern Poland and Eastern German global positioning system (GPS)-tracked between 2012 and 2020.
METHODS: We analyzed annual movement trajectories, focusing on migration distances, fidelity to breeding and wintering grounds, and the use of stop-over sites. We performed an Analysis of Variance from Summary Data (ANOVA) on summary data to compare migratory parameters across different Eurasian populations and age groups.
RESULTS: We identified four main phases in the annual cycle of all studied individuals: breeding, wintering, spring and autumn migration. Our data reveal high inter-individual variation in migratory strategies. Although two individuals changed their wintering sites from year to year, all studied ones exhibited strict fidelity to the same breeding grounds across consecutive seasons. Migration distances ranged from 175 to 1,758 km; notably, the individual breeding in Eastern Germany covered the shortest distance (mean ± SD: 221 ± 51.8 km). We observed substantial inter-individual variation in winter site fidelity, migration distances, and stop-over numbers within this Central European Grey Heron population. The herons selected the shortest migration paths during spring, but not during autumn. While the broad migratory characteristics-specifically the number of stop-overs (3.0 ± 2.8), migration distance (1,220 ± 580.4 km), and migration duration (9 ± 9 days)-closely match findings from other populations, the tracked herons in our study made fewer stop-overs during autumn migration compared to the values reported in the literature.
CONCLUSIONS: We observed inter-individual variations in the annual movement patterns of the Grey Heron, encompassing the timing of the four annual cycle phases, the range of distances covered annually and the birds' fidelity to areas used as breeding or wintering grounds. Our report provides the first long-term, high-resolution insights into the year-round movements of GPS-tracked Grey Herons from Central Europe, emphasizing that specific individuals employ diverse and flexible migratory strategies, even within the same breeding region.
Additional Links: PMID-42708036
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Citation:
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@article {pmid42708036,
year = {2026},
author = {Manikowska-Ślepowrońska, B and Cieślińska, K and Ślepowroński, K and Poślińska, E and Siekiera, J and Goc, M and Iliszko, LM and Jakubas, D},
title = {Individual year-round movement patterns of the GPS-tracked Grey Herons (Ardea cinerea) in Central Europe: a multi-year case study.},
journal = {PeerJ},
volume = {14},
number = {},
pages = {e21659},
pmid = {42708036},
issn = {2167-8359},
mesh = {*Animal Migration/physiology ; Animals ; *Geographic Information Systems ; Seasons ; *Birds/physiology ; Germany ; Poland ; Europe ; },
abstract = {BACKGROUND: The year-round migratory behaviour of Grey Herons (Ardea cinerea) breeding in Central Europe is recognized; however, individual consistency in their movement patterns remains poorly known. In this study, we present movements of three adult Grey Herons breeding in Northern Poland and Eastern German global positioning system (GPS)-tracked between 2012 and 2020.
METHODS: We analyzed annual movement trajectories, focusing on migration distances, fidelity to breeding and wintering grounds, and the use of stop-over sites. We performed an Analysis of Variance from Summary Data (ANOVA) on summary data to compare migratory parameters across different Eurasian populations and age groups.
RESULTS: We identified four main phases in the annual cycle of all studied individuals: breeding, wintering, spring and autumn migration. Our data reveal high inter-individual variation in migratory strategies. Although two individuals changed their wintering sites from year to year, all studied ones exhibited strict fidelity to the same breeding grounds across consecutive seasons. Migration distances ranged from 175 to 1,758 km; notably, the individual breeding in Eastern Germany covered the shortest distance (mean ± SD: 221 ± 51.8 km). We observed substantial inter-individual variation in winter site fidelity, migration distances, and stop-over numbers within this Central European Grey Heron population. The herons selected the shortest migration paths during spring, but not during autumn. While the broad migratory characteristics-specifically the number of stop-overs (3.0 ± 2.8), migration distance (1,220 ± 580.4 km), and migration duration (9 ± 9 days)-closely match findings from other populations, the tracked herons in our study made fewer stop-overs during autumn migration compared to the values reported in the literature.
CONCLUSIONS: We observed inter-individual variations in the annual movement patterns of the Grey Heron, encompassing the timing of the four annual cycle phases, the range of distances covered annually and the birds' fidelity to areas used as breeding or wintering grounds. Our report provides the first long-term, high-resolution insights into the year-round movements of GPS-tracked Grey Herons from Central Europe, emphasizing that specific individuals employ diverse and flexible migratory strategies, even within the same breeding region.},
}
MeSH Terms:
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*Animal Migration/physiology
Animals
*Geographic Information Systems
Seasons
*Birds/physiology
Germany
Poland
Europe
RevDate: 2026-09-08
CmpDate: 2026-09-08
Decoding next-generation heavy metal bioremediation via species-specific Earthworm and its gut microbiome interactions: insights from molecular responses, multi-omics, synthetic biology, and artificial intelligence.
Biodegradation, 37(5):.
Heavy metal (HM) contamination represents a persistent global threat, demanding bioremediation strategies that are both mechanistically robust and ecologically sustainable. This review provides a next-generation perspective on vermiremediation by integrating species-level physiology, gut microbiome functionality, molecular detoxification pathways, synthetic biology innovations, multi-omics insights, and artificial intelligence (AI)-driven modeling into a unified framework. A central novelty of this work lies in the detailed elucidation of earthworm-microbe consortia and their synergistic contributions to metal sequestration, transformation, and detoxification-moving beyond traditional organism-centric views toward eco-engineered host-symbiont systems. We synthesize species-specific bioaccumulation patterns, toxicological responses, and detoxification mechanisms, supported by enrichment kinetic models. At the molecular scale, we highlight antioxidant defense pathways involving catalase, glutathione-S-transferase, and superoxide dismutase, alongside oxidative stress signaling, macromolecular damage, and thresholds that differentiate adaptive resilience from system failure. Advancements in synthetic biology includes gene editing, pathway reconstruction, and designer symbiotic microbes which are examined as emerging tools to enhance gut microbial functionality and engineer targeted metal-binding pathways. Multi-omics approaches provide a systems-level view of detoxification networks, revealing previously uncharacterized genes, enzymes, and metabolic signatures associated with HM tolerance and early biomarkers of sub-lethal stress. The incorporation of AI-based models introduces a data-driven dimension, enabling accurate prediction of remediation outcomes and optimization of vermiremediation strategies. Overall, this review advances vermiremediation from an empirical practice to a programmable, systems-biotechnology platform for sustainable HM bioremediation.
Additional Links: PMID-42709282
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@article {pmid42709282,
year = {2026},
author = {Kharmawphlang, IM and Gómez-Brandón, M and Hussain, N},
title = {Decoding next-generation heavy metal bioremediation via species-specific Earthworm and its gut microbiome interactions: insights from molecular responses, multi-omics, synthetic biology, and artificial intelligence.},
journal = {Biodegradation},
volume = {37},
number = {5},
pages = {},
pmid = {42709282},
issn = {1572-9729},
mesh = {Animals ; *Oligochaeta/metabolism/microbiology ; Biodegradation, Environmental ; Multiomics ; *Metals, Heavy/metabolism ; *Gastrointestinal Microbiome ; Synthetic Biology ; Artificial Intelligence ; *Soil Pollutants/metabolism ; },
abstract = {Heavy metal (HM) contamination represents a persistent global threat, demanding bioremediation strategies that are both mechanistically robust and ecologically sustainable. This review provides a next-generation perspective on vermiremediation by integrating species-level physiology, gut microbiome functionality, molecular detoxification pathways, synthetic biology innovations, multi-omics insights, and artificial intelligence (AI)-driven modeling into a unified framework. A central novelty of this work lies in the detailed elucidation of earthworm-microbe consortia and their synergistic contributions to metal sequestration, transformation, and detoxification-moving beyond traditional organism-centric views toward eco-engineered host-symbiont systems. We synthesize species-specific bioaccumulation patterns, toxicological responses, and detoxification mechanisms, supported by enrichment kinetic models. At the molecular scale, we highlight antioxidant defense pathways involving catalase, glutathione-S-transferase, and superoxide dismutase, alongside oxidative stress signaling, macromolecular damage, and thresholds that differentiate adaptive resilience from system failure. Advancements in synthetic biology includes gene editing, pathway reconstruction, and designer symbiotic microbes which are examined as emerging tools to enhance gut microbial functionality and engineer targeted metal-binding pathways. Multi-omics approaches provide a systems-level view of detoxification networks, revealing previously uncharacterized genes, enzymes, and metabolic signatures associated with HM tolerance and early biomarkers of sub-lethal stress. The incorporation of AI-based models introduces a data-driven dimension, enabling accurate prediction of remediation outcomes and optimization of vermiremediation strategies. Overall, this review advances vermiremediation from an empirical practice to a programmable, systems-biotechnology platform for sustainable HM bioremediation.},
}
MeSH Terms:
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Animals
*Oligochaeta/metabolism/microbiology
Biodegradation, Environmental
Multiomics
*Metals, Heavy/metabolism
*Gastrointestinal Microbiome
Synthetic Biology
Artificial Intelligence
*Soil Pollutants/metabolism
RevDate: 2026-09-08
CmpDate: 2026-09-08
Ecological sensitivity and sustainable spatial planning in a highly urbanized plain: An AHP-GIS and geodetector approach in the Yangtze River Delta Plain.
PloS one, 21(9):e0357598 pii:PONE-D-26-10647.
Rapid urbanization in plains exacerbates ecological pressures, while most ecological sensitivity (ES) research focuses on mountains, offering limited guidance for highly urbanized plains. This study assesses ES in the Yangtze River Delta Ecological Green Integrated Development Demonstration Zone (YRD EGI-DDZ) and its planning implications. Ten indicators, covering four criteria, geography, hydrology, natural resource, and human interference were integrated using Analytic Hierarchy Process (AHP) with Geographic Information System (GIS). Geodetector quantified drivers of ES spatial variation, and 2018-2020 land use data revealed recent development and fragmentation. Results show over 70% of the area under medium to extremely highly sensitivity, with high or extreme high zones clustered along Dianshan Lake, Yuandang, East Taihu, and contiguous ecological land. Low sensitivity mainly corresponds to urban land. Key drivers include land use, nighttime lights, population density, and water proximity, while elevation and slope contribute marginally. New construction land expands mainly along urban fringes and transport corridors, inserting low sensitivity strips into medium sensitivity belts and fragmenting high sensitivity cores. These findings inform a sensitivity-based zoning and corridor control framework, refining existing plans and supporting sustainable spatial development in similar plains.
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@article {pmid42709709,
year = {2026},
author = {Yao, T and Liu, Q and Zeng, H and Tang, J},
title = {Ecological sensitivity and sustainable spatial planning in a highly urbanized plain: An AHP-GIS and geodetector approach in the Yangtze River Delta Plain.},
journal = {PloS one},
volume = {21},
number = {9},
pages = {e0357598},
doi = {10.1371/journal.pone.0357598},
pmid = {42709709},
issn = {1932-6203},
mesh = {*Rivers ; *Urbanization ; *Geographic Information Systems ; China ; *Conservation of Natural Resources/methods ; *Ecosystem ; Humans ; Environmental Monitoring/methods ; },
abstract = {Rapid urbanization in plains exacerbates ecological pressures, while most ecological sensitivity (ES) research focuses on mountains, offering limited guidance for highly urbanized plains. This study assesses ES in the Yangtze River Delta Ecological Green Integrated Development Demonstration Zone (YRD EGI-DDZ) and its planning implications. Ten indicators, covering four criteria, geography, hydrology, natural resource, and human interference were integrated using Analytic Hierarchy Process (AHP) with Geographic Information System (GIS). Geodetector quantified drivers of ES spatial variation, and 2018-2020 land use data revealed recent development and fragmentation. Results show over 70% of the area under medium to extremely highly sensitivity, with high or extreme high zones clustered along Dianshan Lake, Yuandang, East Taihu, and contiguous ecological land. Low sensitivity mainly corresponds to urban land. Key drivers include land use, nighttime lights, population density, and water proximity, while elevation and slope contribute marginally. New construction land expands mainly along urban fringes and transport corridors, inserting low sensitivity strips into medium sensitivity belts and fragmenting high sensitivity cores. These findings inform a sensitivity-based zoning and corridor control framework, refining existing plans and supporting sustainable spatial development in similar plains.},
}
MeSH Terms:
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*Rivers
*Urbanization
*Geographic Information Systems
China
*Conservation of Natural Resources/methods
*Ecosystem
Humans
Environmental Monitoring/methods
RevDate: 2026-09-08
CmpDate: 2026-09-08
Mobile-First Web Access and Captioned Video in Francophone Cardiology Education: Multicountry Ecological Learning Analytics Study.
JMIR mHealth and uHealth, 14:e90345 pii:v14i1e90345.
BACKGROUND: Mobile health (mHealth) and online video are increasingly central to cardiology education and point-of-care decision support. However, little is known about how simple design choices, such as mobile-first web layouts and captioned videos, translate into real-world practice across countries with different income levels.
OBJECTIVE: This exploratory ecological study used routinely collected, cross-platform learning analytics from a francophone cardiology mHealth initiative to (1) describe how mobile web access and caption-enabled YouTube viewing varied across World Bank income groups and (2) examine whether greater reliance on mobile access was associated with poorer engagement on the website or on YouTube.
METHODS: We analyzed country-level analytics from the École Numérique de Cardiologie (ENC; Saint-Denis) mobile-optimized website and its companion YouTube channel (YouTube, LLC [Google LLC]) over a two-year window (September 2023 to September 2025). Countries were grouped as high-, middle-, or low-income (World Bank, three-level classification). Country-level metrics included mobile device session share; website bounce rate; time on page; and YouTube average view duration, audience retention, and intentional views. Caption-related and demographic YouTube metrics were available only as income-group aggregates and were therefore reported descriptively as between-group contrasts; country-level inferential analyses were restricted to country-level variables. Reporting followed the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) checklist.
RESULTS: Thirty-four countries contributed data: 13/34 (38%) high-income, 14/34 (41%) middle-income, and 7/34 (21%) low-income. Caption-enabled watch time was 18.8% in high-income countries (HICs), compared with 38.7% in middle-income countries (MICs) and 60.9% in low-income countries (LICs), representing a caption equity gap (CEG) of 42.1% between low- and high-income settings. Median website mobile share rose with decreasing income (36.5%, 63.3%, and 81.4%, respectively; Jonckheere-Terpstra P=.01). Across income groups, higher caption-enabled watch time coincided with a higher share of intentional views. At the country level, greater reliance on mobile access was not associated with higher bounce rate or shorter time on page, and Spearman correlations between mobile share and YouTube engagement metrics were small and nonsignificant (all |ρ|≤0.28; all P≥.18).
CONCLUSIONS: In this multicountry, francophone, mHealth learning analytics case study, mobile web access and captioned video were used most intensively in lower-income settings, and greater reliance on mobile access was not associated with measurable penalties in basic engagement metrics. These findings support treating mobile-optimized design and systematic captioning as core, low-cost, access-supporting features for equitable digital cardiology education. They also suggest that routinely collected platform indicators can serve as practical equity-monitoring signals for global mHealth initiatives, while underscoring that engagement metrics are not direct measures of learning or behavior change.
Additional Links: PMID-42710055
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PubMed:
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@article {pmid42710055,
year = {2026},
author = {Roussel, T and Benhaim, E and Perrard, L and Merat, B and Vally, S and Girerd, R and Deharo, P and Desroche, LM and , },
title = {Mobile-First Web Access and Captioned Video in Francophone Cardiology Education: Multicountry Ecological Learning Analytics Study.},
journal = {JMIR mHealth and uHealth},
volume = {14},
number = {},
pages = {e90345},
doi = {10.2196/90345},
pmid = {42710055},
issn = {2291-5222},
mesh = {*Cardiology/education ; Humans ; Digital Health ; Digital Media ; Telemedicine ; Internet ; },
abstract = {BACKGROUND: Mobile health (mHealth) and online video are increasingly central to cardiology education and point-of-care decision support. However, little is known about how simple design choices, such as mobile-first web layouts and captioned videos, translate into real-world practice across countries with different income levels.
OBJECTIVE: This exploratory ecological study used routinely collected, cross-platform learning analytics from a francophone cardiology mHealth initiative to (1) describe how mobile web access and caption-enabled YouTube viewing varied across World Bank income groups and (2) examine whether greater reliance on mobile access was associated with poorer engagement on the website or on YouTube.
METHODS: We analyzed country-level analytics from the École Numérique de Cardiologie (ENC; Saint-Denis) mobile-optimized website and its companion YouTube channel (YouTube, LLC [Google LLC]) over a two-year window (September 2023 to September 2025). Countries were grouped as high-, middle-, or low-income (World Bank, three-level classification). Country-level metrics included mobile device session share; website bounce rate; time on page; and YouTube average view duration, audience retention, and intentional views. Caption-related and demographic YouTube metrics were available only as income-group aggregates and were therefore reported descriptively as between-group contrasts; country-level inferential analyses were restricted to country-level variables. Reporting followed the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) checklist.
RESULTS: Thirty-four countries contributed data: 13/34 (38%) high-income, 14/34 (41%) middle-income, and 7/34 (21%) low-income. Caption-enabled watch time was 18.8% in high-income countries (HICs), compared with 38.7% in middle-income countries (MICs) and 60.9% in low-income countries (LICs), representing a caption equity gap (CEG) of 42.1% between low- and high-income settings. Median website mobile share rose with decreasing income (36.5%, 63.3%, and 81.4%, respectively; Jonckheere-Terpstra P=.01). Across income groups, higher caption-enabled watch time coincided with a higher share of intentional views. At the country level, greater reliance on mobile access was not associated with higher bounce rate or shorter time on page, and Spearman correlations between mobile share and YouTube engagement metrics were small and nonsignificant (all |ρ|≤0.28; all P≥.18).
CONCLUSIONS: In this multicountry, francophone, mHealth learning analytics case study, mobile web access and captioned video were used most intensively in lower-income settings, and greater reliance on mobile access was not associated with measurable penalties in basic engagement metrics. These findings support treating mobile-optimized design and systematic captioning as core, low-cost, access-supporting features for equitable digital cardiology education. They also suggest that routinely collected platform indicators can serve as practical equity-monitoring signals for global mHealth initiatives, while underscoring that engagement metrics are not direct measures of learning or behavior change.},
}
MeSH Terms:
show MeSH Terms
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*Cardiology/education
Humans
Digital Health
Digital Media
Telemedicine
Internet
RevDate: 2026-09-07
CmpDate: 2026-09-07
Towards an artificial intelligence clinical decision-support system based on immersive virtual reality for neurocognitive assessment.
Ergonomics, 69(10):1999-2016.
Recent cost reductions and technological advances have enabled the use of Immersive Virtual Reality (IVR) to assess performance tasks in high-fidelity 3D environments. This review outlines the current state of its application in neurocognitive assessment and examines the integration of Artificial Intelligence algorithms and biomedical sensors to standardise laboratory testing. An AI-driven clinical decision-support system (aiCDSS-IVR) is introduced as a modular framework in which immersive virtual reality, artificial intelligence, and biometric sensors are integrated to construct a digital twin that combines behavioural and physiological data for clinical decision support. This technological ecosystem could facilitate a more personalised approach to the assessment and rehabilitation of brain injuries.
Additional Links: PMID-40965469
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@article {pmid40965469,
year = {2026},
author = {León-Domínguez, U},
title = {Towards an artificial intelligence clinical decision-support system based on immersive virtual reality for neurocognitive assessment.},
journal = {Ergonomics},
volume = {69},
number = {10},
pages = {1999-2016},
doi = {10.1080/00140139.2025.2560581},
pmid = {40965469},
issn = {1366-5847},
mesh = {Humans ; *Artificial Intelligence ; *Virtual Reality ; *Decision Support Systems, Clinical ; Algorithms ; Brain Injuries/rehabilitation ; Neuropsychological Tests ; },
abstract = {Recent cost reductions and technological advances have enabled the use of Immersive Virtual Reality (IVR) to assess performance tasks in high-fidelity 3D environments. This review outlines the current state of its application in neurocognitive assessment and examines the integration of Artificial Intelligence algorithms and biomedical sensors to standardise laboratory testing. An AI-driven clinical decision-support system (aiCDSS-IVR) is introduced as a modular framework in which immersive virtual reality, artificial intelligence, and biometric sensors are integrated to construct a digital twin that combines behavioural and physiological data for clinical decision support. This technological ecosystem could facilitate a more personalised approach to the assessment and rehabilitation of brain injuries.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Humans
*Artificial Intelligence
*Virtual Reality
*Decision Support Systems, Clinical
Algorithms
Brain Injuries/rehabilitation
Neuropsychological Tests
RevDate: 2026-09-07
CmpDate: 2026-09-07
Supporting exploration and sustainable utilization of the medicinal plant Uncaria rhynchophylla in Kyushu, Japan through potential distribution modeling using MaxEnt and GIS.
Journal of natural medicines, 80(5):1417-1432.
Sustainable utilization of wild medicinal plant resources requires reproducible approaches for locating and managing natural populations. In Japan, exploration and resource planning for wild medicinal plants rely heavily on expert knowledge, and reproducible approaches remain scarce. We developed a species distribution model (SDM) for Uncaria rhynchophylla (Rubiaceae), a botanical source of the crude drug Uncaria Hook used in Kampo medicine, to estimate its potential distribution and identify major environmental correlates in the Kyushu region, southern Japan. Using 122 occurrence records collected from 2021 to 2023 and nine environmental predictors, MaxEnt models were trained with background points and bootstrap replicates. Because mean minimum winter temperature in January and mean maximum summer temperature in August were highly correlated, three candidate models were compared using the small-sample corrected Akaike information criterion (AICc), test omission rates, and test area under the receiver operating characteristic curve (AUC). The model including winter minimum temperature was best supported (test AUC = 0.82; test omission rate = 24%), whereas adding summer maximum temperature provided limited improvement (ΔAICc = + 75.75). Variable importance and jackknife tests ranked winter minimum temperature as the most influential predictor, followed by slope angle and distance to the nearest rivers. The suitable area, defined using the maximum training sensitivity plus specificity (MTSS) threshold, covered 10,595 km[2] (25.9% of the terrestrial area) and formed continuous zones across hilly and low-montane regions. Targeted surveys in high-suitability areas confirmed three additional sites in the Kirishima Mountains. Overall, integrating SDM and geographic information systems provides a reproducible, data-driven, decision-support framework for the exploration, planning of sustainable harvesting, and resource management of wild medicinal plants.
Additional Links: PMID-42380415
PubMed:
Citation:
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@article {pmid42380415,
year = {2026},
author = {Atsumi, T and Hokazono, S and Kikuchi, K and Fujii, T and Takejima, K and Wada, M and Miyake, K and Yahagi, T and Nakamura, K and Takano, A and Minami, M},
title = {Supporting exploration and sustainable utilization of the medicinal plant Uncaria rhynchophylla in Kyushu, Japan through potential distribution modeling using MaxEnt and GIS.},
journal = {Journal of natural medicines},
volume = {80},
number = {5},
pages = {1417-1432},
pmid = {42380415},
issn = {1861-0293},
support = {JP24ak0101159//Japan Agency for Medical Research and Development/ ; IDEAS202541//Collaboration Research Program of IDEAS, Chubu University/ ; },
mesh = {*Uncaria ; Japan ; *Plants, Medicinal ; Geographic Information Systems ; Seasons ; Temperature ; Conservation of Natural Resources ; Medicine, Kampo ; },
abstract = {Sustainable utilization of wild medicinal plant resources requires reproducible approaches for locating and managing natural populations. In Japan, exploration and resource planning for wild medicinal plants rely heavily on expert knowledge, and reproducible approaches remain scarce. We developed a species distribution model (SDM) for Uncaria rhynchophylla (Rubiaceae), a botanical source of the crude drug Uncaria Hook used in Kampo medicine, to estimate its potential distribution and identify major environmental correlates in the Kyushu region, southern Japan. Using 122 occurrence records collected from 2021 to 2023 and nine environmental predictors, MaxEnt models were trained with background points and bootstrap replicates. Because mean minimum winter temperature in January and mean maximum summer temperature in August were highly correlated, three candidate models were compared using the small-sample corrected Akaike information criterion (AICc), test omission rates, and test area under the receiver operating characteristic curve (AUC). The model including winter minimum temperature was best supported (test AUC = 0.82; test omission rate = 24%), whereas adding summer maximum temperature provided limited improvement (ΔAICc = + 75.75). Variable importance and jackknife tests ranked winter minimum temperature as the most influential predictor, followed by slope angle and distance to the nearest rivers. The suitable area, defined using the maximum training sensitivity plus specificity (MTSS) threshold, covered 10,595 km[2] (25.9% of the terrestrial area) and formed continuous zones across hilly and low-montane regions. Targeted surveys in high-suitability areas confirmed three additional sites in the Kirishima Mountains. Overall, integrating SDM and geographic information systems provides a reproducible, data-driven, decision-support framework for the exploration, planning of sustainable harvesting, and resource management of wild medicinal plants.},
}
MeSH Terms:
show MeSH Terms
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*Uncaria
Japan
*Plants, Medicinal
Geographic Information Systems
Seasons
Temperature
Conservation of Natural Resources
Medicine, Kampo
RevDate: 2026-09-06
Long-short-term decoupled residual learning for high-resolution spatio-temporal air quality inference.
Neural networks : the official journal of the International Neural Network Society, 205(Pt C):109575 pii:S0893-6080(26)01032-4 [Epub ahead of print].
Accurate high-resolution spatio-temporal air quality inference based on sparse monitoring stations is essential for environmental governance and public health. However, prevailing deep learning approaches often treat inference as direct regression on observed air quality concentrations, neglecting the distinct effects of a long-term static baseline and short-term dynamic perturbations on the inference. This limits the model's generalization ability and may cause spatial bias in the inference. In this paper, we propose a novel Spatio-Temporal Air Quality Inference Network (SAQIN) model, which provides an explicit decomposition of the static and dynamic effects in the inference. The static branch integrates high-resolution semantic segmentation, global context from remote sensing, population density, and elevation to construct a high-fidelity environmental prior. The dynamic branch employs multi-head self-attention mechanism to jointly encode geographic relationships and inter-pollutant chemical coupling effects. We further develop a residual learning module to model the inference process as a residual correction anchored to multiple reference stations and aggregates predictions through stepwise multi-station fusion with distance-weighted averaging, which successfully eliminates the Voronoi-partition-induced discontinuities and yielding a globally smooth physically plausible air quality inference field. SAQIN has been shown to demonstrate superior accuracy and strong zero-shot cross-domain generalisation when evaluated on large-scale real-world datasets, thus outperforming state-of-the-art methods across a range of criteria pollutants.
Additional Links: PMID-42702138
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PubMed:
Citation:
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@article {pmid42702138,
year = {2026},
author = {Zheng, H and Huang, J and Chen, H and Xiao, Z and Chen, N and Ding, X},
title = {Long-short-term decoupled residual learning for high-resolution spatio-temporal air quality inference.},
journal = {Neural networks : the official journal of the International Neural Network Society},
volume = {205},
number = {Pt C},
pages = {109575},
doi = {10.1016/j.neunet.2026.109575},
pmid = {42702138},
issn = {1879-2782},
abstract = {Accurate high-resolution spatio-temporal air quality inference based on sparse monitoring stations is essential for environmental governance and public health. However, prevailing deep learning approaches often treat inference as direct regression on observed air quality concentrations, neglecting the distinct effects of a long-term static baseline and short-term dynamic perturbations on the inference. This limits the model's generalization ability and may cause spatial bias in the inference. In this paper, we propose a novel Spatio-Temporal Air Quality Inference Network (SAQIN) model, which provides an explicit decomposition of the static and dynamic effects in the inference. The static branch integrates high-resolution semantic segmentation, global context from remote sensing, population density, and elevation to construct a high-fidelity environmental prior. The dynamic branch employs multi-head self-attention mechanism to jointly encode geographic relationships and inter-pollutant chemical coupling effects. We further develop a residual learning module to model the inference process as a residual correction anchored to multiple reference stations and aggregates predictions through stepwise multi-station fusion with distance-weighted averaging, which successfully eliminates the Voronoi-partition-induced discontinuities and yielding a globally smooth physically plausible air quality inference field. SAQIN has been shown to demonstrate superior accuracy and strong zero-shot cross-domain generalisation when evaluated on large-scale real-world datasets, thus outperforming state-of-the-art methods across a range of criteria pollutants.},
}
RevDate: 2026-09-07
CmpDate: 2026-09-07
Do Multi-Omics Approaches Improve the Diagnosis of Microbial Overgrowth Syndromes?.
Current gastroenterology reports, 28(1):.
PURPOSE OF REVIEW: This review investigates how advances in breath testing (BT), small bowel (SB) culture, metagenomics, metatranscriptomics, transcriptomics and proteomics are reshaping the definition and diagnosis of small intestinal bacterial overgrowth (SIBO). It also discusses whether SIBO should be redefined as part of a larger group of microbial overgrowth syndromes.
RECENT FINDINGS: Recent studies identify distinct hydrogen-, methane-, and hydrogen sulfide-associated overgrowth phenotypes, termed SIBO, intestinal methanogen overgrowth (IMO), and intestinal sulfide overproduction (ISO). SB sampling shows that these conditions involve different microbial patterns and functional activity, symptoms, and host responses. Quantitative shotgun metagenomics provides greater taxonomic and functional resolution than culture, while metatranscriptomics reveals active microbial pathways. On top of that, host transcriptomics and proteomics contribute to the better understanding of the predominant microbial effects in host cellular mechanisms in each of the distinct small bowel overgrowth types. SIBO has been increasingly identified as a disorder of microbial ecology and function rather than bacterial quantity alone. Integrating BT with SB sampling and multi-omics approaches may improve classification, clarify symptom mechanisms, and support a more individualized treatment, although standardized methods and further clinical validation remain necessary.
Additional Links: PMID-42704537
PubMed:
Citation:
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@article {pmid42704537,
year = {2026},
author = {de Freitas Germano, J and Leite, G and Pimentel, M},
title = {Do Multi-Omics Approaches Improve the Diagnosis of Microbial Overgrowth Syndromes?.},
journal = {Current gastroenterology reports},
volume = {28},
number = {1},
pages = {},
pmid = {42704537},
issn = {1534-312X},
mesh = {Humans ; Multiomics ; *Intestine, Small/microbiology ; Proteomics/methods ; *Blind Loop Syndrome/diagnosis/microbiology ; Breath Tests/methods ; Gastrointestinal Microbiome ; Metagenomics/methods ; Syndrome ; },
abstract = {PURPOSE OF REVIEW: This review investigates how advances in breath testing (BT), small bowel (SB) culture, metagenomics, metatranscriptomics, transcriptomics and proteomics are reshaping the definition and diagnosis of small intestinal bacterial overgrowth (SIBO). It also discusses whether SIBO should be redefined as part of a larger group of microbial overgrowth syndromes.
RECENT FINDINGS: Recent studies identify distinct hydrogen-, methane-, and hydrogen sulfide-associated overgrowth phenotypes, termed SIBO, intestinal methanogen overgrowth (IMO), and intestinal sulfide overproduction (ISO). SB sampling shows that these conditions involve different microbial patterns and functional activity, symptoms, and host responses. Quantitative shotgun metagenomics provides greater taxonomic and functional resolution than culture, while metatranscriptomics reveals active microbial pathways. On top of that, host transcriptomics and proteomics contribute to the better understanding of the predominant microbial effects in host cellular mechanisms in each of the distinct small bowel overgrowth types. SIBO has been increasingly identified as a disorder of microbial ecology and function rather than bacterial quantity alone. Integrating BT with SB sampling and multi-omics approaches may improve classification, clarify symptom mechanisms, and support a more individualized treatment, although standardized methods and further clinical validation remain necessary.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Humans
Multiomics
*Intestine, Small/microbiology
Proteomics/methods
*Blind Loop Syndrome/diagnosis/microbiology
Breath Tests/methods
Gastrointestinal Microbiome
Metagenomics/methods
Syndrome
RevDate: 2026-09-07
Global, regional, and national prevalence of second-hand smoke and attributable disease burden in 204 countries and territories, 1990-2023: a systematic analysis for the Global Burden of Disease Study 2023.
The Lancet. Public health pii:S2468-2667(26)00168-4 [Epub ahead of print].
BACKGROUND: Second-hand smoke (SHS) exposure remains a major source of morbidity and mortality among non-smokers. This study presents the first dedicated Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) publication to systematically quantify SHS prevalence and evaluate its effect as a global risk factor across a broader range of outcomes.
METHODS: Using the GBD 2023 comparative risk assessment framework, we estimated SHS exposure prevalence and attributable disease burden across 204 countries and territories from 1990 to 2023, stratified by age and sex. Exposure estimates were derived by synthesising population-based surveys and household composition data through spatiotemporal Gaussian process regression. Relative risks for nine health outcomes, now including asthma, were estimated using the Burden of Proof methodology, and applied to calculate attributable deaths and disability-adjusted life-years (DALYs).
FINDINGS: In 2023, an estimated 2·71 billion (95% UI 2·44-3·02) people worldwide were exposed to SHS, including 767 million (687-858) children aged 0-14 years. Age-standardised prevalence was highest in southeast Asia, east Asia, and Oceania (48·4% [44·0-53·4]), with female individuals in some countries experiencing nearly 1·8 times the exposure prevalence of male individuals. Despite a 22·2% (10·6-32·4) decline in global age-standardised prevalence since 1990, this progress has not been sufficient to reduce the absolute number of exposed individuals, which has remained stable globally and has risen sharply in sub-Saharan Africa (98·5% [62·0-144·4] increase) and North Africa and the Middle East (72·1% [47·8-101·8] increase). In 2023, SHS exposure accounted for 1·66 million (1·33-2·07) deaths and 44·8 million (35·8-54·3) DALYs globally. Ischaemic heart disease was the leading contributor to SHS-attributable DALYs (12·0 million [9·31-15·2]) overall, while lower respiratory infections predominated among children (5·16 million [3·48-7·12]).
INTERPRETATION: We estimated that SHS remains a substantial driver of global health loss, particularly through cardiovascular and paediatric respiratory diseases. Persistent geographical disparities and growing absolute numbers of exposed individuals in several regions underscore the urgent need for accelerated implementation and enforcement of comprehensive tobacco control measures, particularly to protect women and children in both public and domestic environments.
FUNDING: Bloomberg Philanthropies and the Gates Foundation.
Additional Links: PMID-42705247
Publisher:
PubMed:
Citation:
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@article {pmid42705247,
year = {2026},
author = {, },
title = {Global, regional, and national prevalence of second-hand smoke and attributable disease burden in 204 countries and territories, 1990-2023: a systematic analysis for the Global Burden of Disease Study 2023.},
journal = {The Lancet. Public health},
volume = {},
number = {},
pages = {},
doi = {10.1016/S2468-2667(26)00168-4},
pmid = {42705247},
issn = {2468-2667},
abstract = {BACKGROUND: Second-hand smoke (SHS) exposure remains a major source of morbidity and mortality among non-smokers. This study presents the first dedicated Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) publication to systematically quantify SHS prevalence and evaluate its effect as a global risk factor across a broader range of outcomes.
METHODS: Using the GBD 2023 comparative risk assessment framework, we estimated SHS exposure prevalence and attributable disease burden across 204 countries and territories from 1990 to 2023, stratified by age and sex. Exposure estimates were derived by synthesising population-based surveys and household composition data through spatiotemporal Gaussian process regression. Relative risks for nine health outcomes, now including asthma, were estimated using the Burden of Proof methodology, and applied to calculate attributable deaths and disability-adjusted life-years (DALYs).
FINDINGS: In 2023, an estimated 2·71 billion (95% UI 2·44-3·02) people worldwide were exposed to SHS, including 767 million (687-858) children aged 0-14 years. Age-standardised prevalence was highest in southeast Asia, east Asia, and Oceania (48·4% [44·0-53·4]), with female individuals in some countries experiencing nearly 1·8 times the exposure prevalence of male individuals. Despite a 22·2% (10·6-32·4) decline in global age-standardised prevalence since 1990, this progress has not been sufficient to reduce the absolute number of exposed individuals, which has remained stable globally and has risen sharply in sub-Saharan Africa (98·5% [62·0-144·4] increase) and North Africa and the Middle East (72·1% [47·8-101·8] increase). In 2023, SHS exposure accounted for 1·66 million (1·33-2·07) deaths and 44·8 million (35·8-54·3) DALYs globally. Ischaemic heart disease was the leading contributor to SHS-attributable DALYs (12·0 million [9·31-15·2]) overall, while lower respiratory infections predominated among children (5·16 million [3·48-7·12]).
INTERPRETATION: We estimated that SHS remains a substantial driver of global health loss, particularly through cardiovascular and paediatric respiratory diseases. Persistent geographical disparities and growing absolute numbers of exposed individuals in several regions underscore the urgent need for accelerated implementation and enforcement of comprehensive tobacco control measures, particularly to protect women and children in both public and domestic environments.
FUNDING: Bloomberg Philanthropies and the Gates Foundation.},
}
RevDate: 2026-09-06
CmpDate: 2026-09-06
Multi-omics reveal microbial functional traits and antifungal metabolites associated with lower Pseudogymnoascus destructans loads in bat cave soils.
Microbiological research, 313:128696.
White-nose syndrome, caused by Pseudogymnoascus destructans (Pd), is a major fungal disease threatening hibernating bats. Cave soils can serve as environmental reservoirs for Pd, yet the microbial and biochemical mechanisms underlying naturally low Pd burdens in some cave environments remain poorly understood. Here, we integrated soil microbiome profiling, metagenomics, metabolomics, multi-omics network analysis, and in vitro validation to investigate the ecological and functional basis of differential Pd loads in hibernating bat caves in Northeast China. The three caves shared cold, humid, and weakly acidic microenvironments, but differed significantly in electrical conductivity, soil water content, nutrient availability, and extracellular enzyme activities. Soil microbial communities showed significant inter-cave variation in composition, diversity, and niche breadth, with stochastic processes contributing substantially to community assembly. Environmental variables, particularly pH and Pd load, were important predictors of microbial community structure. Functional analyses revealed that the low-Pd Gezi Cave was enriched in genes associated with organic carbon degradation, nitrogen input and retention, and secondary metabolism. Metabolomic profiling further identified cave-specific metabolite signatures, among which Biochanin A, 4-Hydroxybenzaldehyde, Vanillin, and Arachidonic acid were negatively correlated with Pd loads. Integrated pathway and network analyses showed that differential genes and metabolites jointly mapped to secondary metabolite biosynthesis, aminobenzoate degradation, and flavonoid degradation pathways, forming a microbe-metabolite-functional gene coupling network involving key taxa such as Rhodococcus, Pseudorhodoplanes, and Rhodoplanes. In vitro assays confirmed that 4-Hydroxybenzaldehyde, Coumarin, and Vanillin inhibited Pd growth. Structural equation modelling further indicated that environmental heterogeneity was associated with variation in Pd loads through microbial functional attributes and metabolite profiles. These findings suggest that naturally low-Pd cave soils are associated with coordinated environmental filtering, microbial functional specialization, and antifungal metabolite production, providing mechanistic insight into microbial and biochemical constraints on Pd persistence in cave reservoirs.
Additional Links: PMID-42636663
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PubMed:
Citation:
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@article {pmid42636663,
year = {2026},
author = {Wang, D and Huang, Z and Sun, S and Song, W and Li, Y and Sun, K and Li, Z and Feng, J},
title = {Multi-omics reveal microbial functional traits and antifungal metabolites associated with lower Pseudogymnoascus destructans loads in bat cave soils.},
journal = {Microbiological research},
volume = {313},
number = {},
pages = {128696},
doi = {10.1016/j.micres.2026.128696},
pmid = {42636663},
issn = {1618-0623},
mesh = {Animals ; Multiomics ; *Soil Microbiology ; *Ascomycota/drug effects/isolation & purification ; *Caves/microbiology ; *Chiroptera/microbiology ; Metabolomics ; *Antifungal Agents/pharmacology/metabolism ; China ; Microbiota/genetics ; Metagenomics ; Soil/chemistry ; },
abstract = {White-nose syndrome, caused by Pseudogymnoascus destructans (Pd), is a major fungal disease threatening hibernating bats. Cave soils can serve as environmental reservoirs for Pd, yet the microbial and biochemical mechanisms underlying naturally low Pd burdens in some cave environments remain poorly understood. Here, we integrated soil microbiome profiling, metagenomics, metabolomics, multi-omics network analysis, and in vitro validation to investigate the ecological and functional basis of differential Pd loads in hibernating bat caves in Northeast China. The three caves shared cold, humid, and weakly acidic microenvironments, but differed significantly in electrical conductivity, soil water content, nutrient availability, and extracellular enzyme activities. Soil microbial communities showed significant inter-cave variation in composition, diversity, and niche breadth, with stochastic processes contributing substantially to community assembly. Environmental variables, particularly pH and Pd load, were important predictors of microbial community structure. Functional analyses revealed that the low-Pd Gezi Cave was enriched in genes associated with organic carbon degradation, nitrogen input and retention, and secondary metabolism. Metabolomic profiling further identified cave-specific metabolite signatures, among which Biochanin A, 4-Hydroxybenzaldehyde, Vanillin, and Arachidonic acid were negatively correlated with Pd loads. Integrated pathway and network analyses showed that differential genes and metabolites jointly mapped to secondary metabolite biosynthesis, aminobenzoate degradation, and flavonoid degradation pathways, forming a microbe-metabolite-functional gene coupling network involving key taxa such as Rhodococcus, Pseudorhodoplanes, and Rhodoplanes. In vitro assays confirmed that 4-Hydroxybenzaldehyde, Coumarin, and Vanillin inhibited Pd growth. Structural equation modelling further indicated that environmental heterogeneity was associated with variation in Pd loads through microbial functional attributes and metabolite profiles. These findings suggest that naturally low-Pd cave soils are associated with coordinated environmental filtering, microbial functional specialization, and antifungal metabolite production, providing mechanistic insight into microbial and biochemical constraints on Pd persistence in cave reservoirs.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Animals
Multiomics
*Soil Microbiology
*Ascomycota/drug effects/isolation & purification
*Caves/microbiology
*Chiroptera/microbiology
Metabolomics
*Antifungal Agents/pharmacology/metabolism
China
Microbiota/genetics
Metagenomics
Soil/chemistry
RevDate: 2026-09-05
CmpDate: 2026-09-05
Exposure-aware multi-omics and artificial intelligence for biomarker discovery and precision prevention in diffuse glioma.
Frontiers in immunology, 17:1874861.
Diffuse gliomas are now diagnosed and studied through integrated molecular classification, radiomics, single-cell biology, spatial profiling, proteogenomics, metabolomics, and artificial intelligence. Yet many precision-medicine models still begin at diagnosis and emphasize tumor-intrinsic molecular features, leaving environmental, occupational, lifestyle, microbiome, metabolic, immune, and treatment-related exposures at the margins. This review develops an exposome-informed view of diffuse glioma biomarker discovery. Biomarker discovery is separated from clinical prevention: current evidence does not justify population-level glioma screening based on environmental exposures, but it does support systematic integration of external exposures and internal exposure-related molecular states with tumor and host biology. The synthesis focuses on five linked dimensions: the limits of current artificial intelligence and multi-omics models when exposure biology is excluded; glioma-relevant exposure domains stratified by evidence strength and measurability; genotoxic, epigenetic, vascular, neuroimmune, and immunometabolic conduits through which exposures may shape tumor ecology; computational strategies for temporally anchored integration of geospatial, occupational, clinical, liquid-biopsy, imaging, tumor-omic, single-cell, spatial, microbiome, and metabolomic data; and clinically realistic applications in high-risk surveillance, recurrence-aware monitoring, treatment-toxicity reduction, and biomarker-guided trial stratification. By aligning exposome science with systems neuro-oncology, the review outlines a translational agenda for exposure-aware glioma biomarkers while maintaining a conservative boundary between established evidence, mechanistic hypotheses, and future clinical implementation.
Additional Links: PMID-42699236
PubMed:
Citation:
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@article {pmid42699236,
year = {2026},
author = {Zhang, S and Si, Z and Yang, N and Chen, X},
title = {Exposure-aware multi-omics and artificial intelligence for biomarker discovery and precision prevention in diffuse glioma.},
journal = {Frontiers in immunology},
volume = {17},
number = {},
pages = {1874861},
pmid = {42699236},
issn = {1664-3224},
mesh = {Humans ; *Glioma/etiology/prevention & control/diagnosis/genetics/metabolism ; Multiomics ; *Biomarkers, Tumor ; *Brain Neoplasms/prevention & control/etiology/diagnosis/genetics ; *Artificial Intelligence ; Precision Medicine/methods ; *Environmental Exposure/adverse effects ; Animals ; Metabolomics ; },
abstract = {Diffuse gliomas are now diagnosed and studied through integrated molecular classification, radiomics, single-cell biology, spatial profiling, proteogenomics, metabolomics, and artificial intelligence. Yet many precision-medicine models still begin at diagnosis and emphasize tumor-intrinsic molecular features, leaving environmental, occupational, lifestyle, microbiome, metabolic, immune, and treatment-related exposures at the margins. This review develops an exposome-informed view of diffuse glioma biomarker discovery. Biomarker discovery is separated from clinical prevention: current evidence does not justify population-level glioma screening based on environmental exposures, but it does support systematic integration of external exposures and internal exposure-related molecular states with tumor and host biology. The synthesis focuses on five linked dimensions: the limits of current artificial intelligence and multi-omics models when exposure biology is excluded; glioma-relevant exposure domains stratified by evidence strength and measurability; genotoxic, epigenetic, vascular, neuroimmune, and immunometabolic conduits through which exposures may shape tumor ecology; computational strategies for temporally anchored integration of geospatial, occupational, clinical, liquid-biopsy, imaging, tumor-omic, single-cell, spatial, microbiome, and metabolomic data; and clinically realistic applications in high-risk surveillance, recurrence-aware monitoring, treatment-toxicity reduction, and biomarker-guided trial stratification. By aligning exposome science with systems neuro-oncology, the review outlines a translational agenda for exposure-aware glioma biomarkers while maintaining a conservative boundary between established evidence, mechanistic hypotheses, and future clinical implementation.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Humans
*Glioma/etiology/prevention & control/diagnosis/genetics/metabolism
Multiomics
*Biomarkers, Tumor
*Brain Neoplasms/prevention & control/etiology/diagnosis/genetics
*Artificial Intelligence
Precision Medicine/methods
*Environmental Exposure/adverse effects
Animals
Metabolomics
RevDate: 2026-09-04
CmpDate: 2026-09-04
Spatiotemporal dynamics and ecological determinants of cutaneous Leishmaniasis in Errachidia Province, southeastern Morocco: A 16-year municipality-level analysis with SARIMA forecasting.
Parasitology international, 116:103363.
Leishmaniasis is a vector-borne parasitic disease transmitted by female sandflies of the genus Phlebotomus and affects approximately 1.2 million people annually in more than 90 countries worldwide. Morocco remains one of the most affected countries in North Africa, where the disease continues to represent a major public health concern. This study aimed to analyze the spatial and temporal trends of leishmaniasis incidence across all municipalities of Errachidia Province between 2010 and 2025 and to assess the influence of ecological, demographic, and socio-economic factors on its distribution. Also, the study aimed to predict the monthly CL cases using the Seasonal Autoregressive Integrated Moving Average (SARIMA) model. Epidemiological data on parasitologically confirmed cases obtained from the Errachidia Provincial Health Delegation were processed using geographic information system (GIS) tools and statistical methods to explore spatial patterns and correlations with environmental and socio-demographic variables. The models are trained and evaluated using monthly CL cases collected from 2010 to 2025, with the optimal model selected based on Akaike Information Criterion (AIC). During 16-years study period, 7034 cases were recorded in Errachidia Province, with the highest incidence reported in 2010 (860 cases per 100,000 inhabitants). Overall, the incidence showed marked temporal fluctuations but demonstrated a general decreasing trend over the study period. A pronounced spatial heterogeneity was observed between rural municipalities (Sid Ali, Melaab, and Ferkla) and urban municipalities (Errachidia, Arfoud, and Goulmima) (p < 0.01). The disease was slightly more frequent in females (54.41%) than in males (45.59%), and a significant difference was observed among age groups (p = 0.019), with the 0-9 and 10-19-year groups being the most affected. Seasonal analysis revealed a peak incidence during winter. In addition, higher incidence was associated with low- to medium-altitude municipalities, while no significant association was observed with poverty or vulnerability indices. The SARIMA (0,0,1)12 model demonstrated the best predictive performance. These findings highlight the heterogeneity and ecological determinants of leishmaniasis in southeastern Morocco and may support targeted surveillance and control strategies in high-risk areas.
Additional Links: PMID-42575387
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@article {pmid42575387,
year = {2027},
author = {El Alaoui, O and El Khiat, A and Hakem, A and Ouzyou, B and El Omari, H and Mohammed, B and Radi, FZ and Rhazi, O and En-Niari, I and Mahfoud, S and Taam, A and Talbi, FZ},
title = {Spatiotemporal dynamics and ecological determinants of cutaneous Leishmaniasis in Errachidia Province, southeastern Morocco: A 16-year municipality-level analysis with SARIMA forecasting.},
journal = {Parasitology international},
volume = {116},
number = {},
pages = {103363},
doi = {10.1016/j.parint.2026.103363},
pmid = {42575387},
issn = {1873-0329},
mesh = {Morocco/epidemiology ; *Leishmaniasis, Cutaneous/epidemiology ; Incidence ; Animals ; Humans ; Spatio-Temporal Analysis ; Geographic Information Systems ; Female ; Seasons ; Socioeconomic Factors ; *Phlebotomus/parasitology ; Male ; Insect Vectors/parasitology ; Forecasting ; Cities/epidemiology ; },
abstract = {Leishmaniasis is a vector-borne parasitic disease transmitted by female sandflies of the genus Phlebotomus and affects approximately 1.2 million people annually in more than 90 countries worldwide. Morocco remains one of the most affected countries in North Africa, where the disease continues to represent a major public health concern. This study aimed to analyze the spatial and temporal trends of leishmaniasis incidence across all municipalities of Errachidia Province between 2010 and 2025 and to assess the influence of ecological, demographic, and socio-economic factors on its distribution. Also, the study aimed to predict the monthly CL cases using the Seasonal Autoregressive Integrated Moving Average (SARIMA) model. Epidemiological data on parasitologically confirmed cases obtained from the Errachidia Provincial Health Delegation were processed using geographic information system (GIS) tools and statistical methods to explore spatial patterns and correlations with environmental and socio-demographic variables. The models are trained and evaluated using monthly CL cases collected from 2010 to 2025, with the optimal model selected based on Akaike Information Criterion (AIC). During 16-years study period, 7034 cases were recorded in Errachidia Province, with the highest incidence reported in 2010 (860 cases per 100,000 inhabitants). Overall, the incidence showed marked temporal fluctuations but demonstrated a general decreasing trend over the study period. A pronounced spatial heterogeneity was observed between rural municipalities (Sid Ali, Melaab, and Ferkla) and urban municipalities (Errachidia, Arfoud, and Goulmima) (p < 0.01). The disease was slightly more frequent in females (54.41%) than in males (45.59%), and a significant difference was observed among age groups (p = 0.019), with the 0-9 and 10-19-year groups being the most affected. Seasonal analysis revealed a peak incidence during winter. In addition, higher incidence was associated with low- to medium-altitude municipalities, while no significant association was observed with poverty or vulnerability indices. The SARIMA (0,0,1)12 model demonstrated the best predictive performance. These findings highlight the heterogeneity and ecological determinants of leishmaniasis in southeastern Morocco and may support targeted surveillance and control strategies in high-risk areas.},
}
MeSH Terms:
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Morocco/epidemiology
*Leishmaniasis, Cutaneous/epidemiology
Incidence
Animals
Humans
Spatio-Temporal Analysis
Geographic Information Systems
Female
Seasons
Socioeconomic Factors
*Phlebotomus/parasitology
Male
Insect Vectors/parasitology
Forecasting
Cities/epidemiology
RevDate: 2026-09-03
CmpDate: 2026-09-03
Multi-omics analysis reveals the mechanisms of biochar-mediated cadmium transport in Salix: insights into rhizosphere phosphorus-iron coupling and transporter expression.
Tree physiology, 46(9):.
Biochar addition promotes cadmium (Cd) phytoremediation of woody plants, especially phosphorus (P)-modified biochar. However, the underlying mechanism of the uptake and transport of Cd transport mediated by biochar remains unclear. Here, we integrated physiological, metagenomics, transcriptomics and in situ laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) imaging analysis to investigate how bamboo biochar (BBC) and phytic acid-modified biochar (PABC) impact Cd accumulation and transport in Salix J1010 through root-soil interface. Our results showed that PABC significantly increased Cd translocation from roots to aboveground by 77.9% and total Cd accumulation in plants by 203%, respectively. Iron plaque emerged as a key factor, with PABC-mediated inhibition of iron plaque (-44.6%) accelerating Cd uptake. This iron plaque decrease is closely accompanied by the decreased soil redox potential (Eh), enriched resin-P and inorganic P fractions, and potential coupling of P mineralization and Fe(III)-reducing processes in the rhizosphere soil. Transcriptomics analysis further revealed that PABC influenced root metal transporters expression, downregulating vacuolar sequestration-related ABC, CAX, metal tolerance protein gene families, while upregulating most ZIP, HMA and YSL genes families involved in xylem loading. LA-ICP-MS imaging corroborated the enhanced Cd transport in xylem tissue. PABC enhanced leaf cell-wall Cd binding and antioxidant defenses, thereby promoting Cd detoxification and accumulation. Collectively, the enhanced phytoremediation capacity of willow was driven by coordinating trade-offs across multiple levels, including the rhizosphere, subcellular scales and whole plant. These results provide a mechanistic basis for biochar-assisted phytoremediation strategies in Cd-contaminated soils.
Additional Links: PMID-42518220
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PubMed:
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@article {pmid42518220,
year = {2026},
author = {Di, D and Wang, S and Qiu, W and Gai, X and Xiao, J and Wang, S and Zhuo, R and Chen, G},
title = {Multi-omics analysis reveals the mechanisms of biochar-mediated cadmium transport in Salix: insights into rhizosphere phosphorus-iron coupling and transporter expression.},
journal = {Tree physiology},
volume = {46},
number = {9},
pages = {},
doi = {10.1093/treephys/tpag104},
pmid = {42518220},
issn = {1758-4469},
mesh = {*Cadmium/metabolism ; *Salix/metabolism/genetics ; Rhizosphere ; *Iron/metabolism ; *Phosphorus/metabolism ; *Charcoal ; Biological Transport ; Multiomics ; Biodegradation, Environmental ; Plant Roots/metabolism ; },
abstract = {Biochar addition promotes cadmium (Cd) phytoremediation of woody plants, especially phosphorus (P)-modified biochar. However, the underlying mechanism of the uptake and transport of Cd transport mediated by biochar remains unclear. Here, we integrated physiological, metagenomics, transcriptomics and in situ laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) imaging analysis to investigate how bamboo biochar (BBC) and phytic acid-modified biochar (PABC) impact Cd accumulation and transport in Salix J1010 through root-soil interface. Our results showed that PABC significantly increased Cd translocation from roots to aboveground by 77.9% and total Cd accumulation in plants by 203%, respectively. Iron plaque emerged as a key factor, with PABC-mediated inhibition of iron plaque (-44.6%) accelerating Cd uptake. This iron plaque decrease is closely accompanied by the decreased soil redox potential (Eh), enriched resin-P and inorganic P fractions, and potential coupling of P mineralization and Fe(III)-reducing processes in the rhizosphere soil. Transcriptomics analysis further revealed that PABC influenced root metal transporters expression, downregulating vacuolar sequestration-related ABC, CAX, metal tolerance protein gene families, while upregulating most ZIP, HMA and YSL genes families involved in xylem loading. LA-ICP-MS imaging corroborated the enhanced Cd transport in xylem tissue. PABC enhanced leaf cell-wall Cd binding and antioxidant defenses, thereby promoting Cd detoxification and accumulation. Collectively, the enhanced phytoremediation capacity of willow was driven by coordinating trade-offs across multiple levels, including the rhizosphere, subcellular scales and whole plant. These results provide a mechanistic basis for biochar-assisted phytoremediation strategies in Cd-contaminated soils.},
}
MeSH Terms:
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*Cadmium/metabolism
*Salix/metabolism/genetics
Rhizosphere
*Iron/metabolism
*Phosphorus/metabolism
*Charcoal
Biological Transport
Multiomics
Biodegradation, Environmental
Plant Roots/metabolism
RevDate: 2026-09-03
CmpDate: 2026-09-03
Exploiting Omic Data to Advance Predictive Ecotoxicology.
Environmental science & technology, 60(34):23642-23660.
Predicting species-specific chemical sensitivity using in silico approaches has the potential to transform environmental risk assessment, conservation, and biomonitoring, while reducing, and ultimately replacing, animal testing. Genomic and transcriptomic data capture extensive sensitivity-relevant variation, including differences in molecular targets, xenobiotic metabolism, and damage mitigation pathways. Large-scale sequencing initiatives therefore offer an unprecedented opportunity to address ecotoxicology's "too many species" problem. Although existing omic-based predictive tools provide proof of concept, they have so far been applied to a narrow set of relatively straightforward prediction scenarios. To achieve broader applicability, current and future tools must be firmly grounded in the diverse molecular mechanisms underlying differential chemical responses. Here, we critically evaluate the emerging field of predicting species sensitivity using molecular variation inferred from omic data. We analyze the strengths and limitations of current omic-based approaches and identify major sequence and ecotoxicological data gaps, as well as critical bioinformatic challenges. We then review the current knowledge of how molecular biology underlies differential chemical sensitivity, outlining research paths to allow the next generation of sensitivity prediction tools to exploit ever expanding omic data.
Additional Links: PMID-42689779
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@article {pmid42689779,
year = {2026},
author = {Short, S and Green Etxabe, A and Swart, E and Rivetti, C and Campos, B and Krishnan, R and Kille, P and Spurgeon, DJ},
title = {Exploiting Omic Data to Advance Predictive Ecotoxicology.},
journal = {Environmental science & technology},
volume = {60},
number = {34},
pages = {23642-23660},
doi = {10.1021/acs.est.6c01198},
pmid = {42689779},
issn = {1520-5851},
support = {101057014//European Partnership for the Assessment of Risks from Chemicals (PARC) under the EU Horizon Europe Research and Innovation Programme/ ; BB/X511468/1//Biotechnology and Biological Sciences Research Council (BBSRC), part of UK Research and Innovation (UKRI)/ ; NE/S00224/2//Natural Environment Research Council (NERC)/ ; },
mesh = {*Ecotoxicology ; Genomics ; Animals ; Risk Assessment ; Computational Biology ; },
abstract = {Predicting species-specific chemical sensitivity using in silico approaches has the potential to transform environmental risk assessment, conservation, and biomonitoring, while reducing, and ultimately replacing, animal testing. Genomic and transcriptomic data capture extensive sensitivity-relevant variation, including differences in molecular targets, xenobiotic metabolism, and damage mitigation pathways. Large-scale sequencing initiatives therefore offer an unprecedented opportunity to address ecotoxicology's "too many species" problem. Although existing omic-based predictive tools provide proof of concept, they have so far been applied to a narrow set of relatively straightforward prediction scenarios. To achieve broader applicability, current and future tools must be firmly grounded in the diverse molecular mechanisms underlying differential chemical responses. Here, we critically evaluate the emerging field of predicting species sensitivity using molecular variation inferred from omic data. We analyze the strengths and limitations of current omic-based approaches and identify major sequence and ecotoxicological data gaps, as well as critical bioinformatic challenges. We then review the current knowledge of how molecular biology underlies differential chemical sensitivity, outlining research paths to allow the next generation of sensitivity prediction tools to exploit ever expanding omic data.},
}
MeSH Terms:
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*Ecotoxicology
Genomics
Animals
Risk Assessment
Computational Biology
RevDate: 2026-09-03
CmpDate: 2026-09-03
Integrating genomics, multi-omics, CRISPR and speed breeding for stress-resilient vegetable legume improvement.
Functional & integrative genomics, 26(1):.
Vegetable legumes are nutritionally and ecologically important crops. However, their genetic improvement has not kept pace with the increasing challenges posed by climate change due to the polygenic nature of stress tolerance, narrow genetic diversity, and the persistent gap between molecular discoveries and field-level cultivar development. Although recent reviews have examined individual genomic tools or specific stress responses, a comprehensive synthesis integrating genomics-assisted breeding, multi-omics technologies, genome editing, and speed breeding within a unified crop improvement framework has been lacking. This review addresses that gap by critically evaluating how these complementary approaches can accelerate the development of stress-resilient vegetable legumes, including pea, common bean, cowpea, faba bean, cluster bean, yard-long bean, and hyacinth bean. This review synthesizes advances in QTL mapping, genome-wide association studies, transcriptomics, metabolomics, and CRISPR-based functional genomics that have identified key regulators and pathways underlying resistance to major biotic and abiotic stresses. Rather than considering these technologies independently, the review emphasizes their convergence into a systems-level breeding framework integrating genomic discovery, functional validation, predictive breeding, and accelerated generation advancement to improve breeding efficiency. Speed breeding, enabling up to seven to eight generations annually under optimized controlled-environment experimental conditions in cowpea, is discussed as a complementary strategy with genomic selection and genome editing. The review further identifies major translational bottlenecks, including transformation recalcitrance, limited genomic resources for underutilized vegetable legumes, inadequate multi-environment validation, and fragmented omics integration, and presents an integrated systems-breeding framework to bridge the gap between gene discovery and cultivar development.
Additional Links: PMID-42690503
PubMed:
Citation:
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@article {pmid42690503,
year = {2026},
author = {Indurthi, S and Kaur, G and Dutta, R and Madhu, S and Chodasani, B and Yadav, A and Singh, M and Meena, TK and Singh, G},
title = {Integrating genomics, multi-omics, CRISPR and speed breeding for stress-resilient vegetable legume improvement.},
journal = {Functional & integrative genomics},
volume = {26},
number = {1},
pages = {},
pmid = {42690503},
issn = {1438-7948},
mesh = {*Fabaceae/genetics/metabolism ; *Plant Breeding ; Multiomics ; *Stress, Physiological/genetics ; Genomics ; Quantitative Trait Loci ; Genome, Plant ; CRISPR-Cas Systems ; Gene Editing ; },
abstract = {Vegetable legumes are nutritionally and ecologically important crops. However, their genetic improvement has not kept pace with the increasing challenges posed by climate change due to the polygenic nature of stress tolerance, narrow genetic diversity, and the persistent gap between molecular discoveries and field-level cultivar development. Although recent reviews have examined individual genomic tools or specific stress responses, a comprehensive synthesis integrating genomics-assisted breeding, multi-omics technologies, genome editing, and speed breeding within a unified crop improvement framework has been lacking. This review addresses that gap by critically evaluating how these complementary approaches can accelerate the development of stress-resilient vegetable legumes, including pea, common bean, cowpea, faba bean, cluster bean, yard-long bean, and hyacinth bean. This review synthesizes advances in QTL mapping, genome-wide association studies, transcriptomics, metabolomics, and CRISPR-based functional genomics that have identified key regulators and pathways underlying resistance to major biotic and abiotic stresses. Rather than considering these technologies independently, the review emphasizes their convergence into a systems-level breeding framework integrating genomic discovery, functional validation, predictive breeding, and accelerated generation advancement to improve breeding efficiency. Speed breeding, enabling up to seven to eight generations annually under optimized controlled-environment experimental conditions in cowpea, is discussed as a complementary strategy with genomic selection and genome editing. The review further identifies major translational bottlenecks, including transformation recalcitrance, limited genomic resources for underutilized vegetable legumes, inadequate multi-environment validation, and fragmented omics integration, and presents an integrated systems-breeding framework to bridge the gap between gene discovery and cultivar development.},
}
MeSH Terms:
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hide MeSH Terms
*Fabaceae/genetics/metabolism
*Plant Breeding
Multiomics
*Stress, Physiological/genetics
Genomics
Quantitative Trait Loci
Genome, Plant
CRISPR-Cas Systems
Gene Editing
RevDate: 2026-09-02
CmpDate: 2026-09-02
Proteomics in environmental pollution research: Advances, challenges, and future directions.
Journal of proteomics, 331:105693.
Environmental proteomics has emerged as a powerful approach for elucidating the molecular mechanisms underlying pollutant-induced biological effects. Although this field has developed rapidly, the systematic review of recent proteomics applications in environmental pollution research remains limited. This review explored the emerging roles of toxicoproteomics in biomarker discovery and mechanistic elucidation, as well as ecotoxicoproteomics in ecological risk assessment and bioremediation strategies. Here, we review the field, highlighting recent trends such as the integration of proteomics with genomics, transcriptomics, and metabolomics to provide a comprehensive view of biological responses to environmental stressors. We further discuss the growing application of artificial intelligence in improving proteomics data interpretation and accelerating biomarker discovery. In addition, recent technological advances in environmental proteomics are highlighted, including next-generation tissue microarray proteomics, nanoscale proteomics, single-cell proteomics, and spatial proteomics. Despite its potential, proteomics faces challenges, such as high operational costs, computational complexity in analysis, and technical limitations in low-abundance protein detection. We propose that the convergence of proteomics with artificial intelligence and multi-omics approaches offers promising solutions to these challenges, enhancing the practical application of proteomics in environmental monitoring and risk assessment.
Additional Links: PMID-42276166
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PubMed:
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@article {pmid42276166,
year = {2026},
author = {Wei, C and Zeng, B and Zhou, X and Qing, B and Deng, L and Wu, Y and Huang, W and Zhang, Z and Jin, Y and Peng, S and Zhang, C and Qiu, S},
title = {Proteomics in environmental pollution research: Advances, challenges, and future directions.},
journal = {Journal of proteomics},
volume = {331},
number = {},
pages = {105693},
doi = {10.1016/j.jprot.2026.105693},
pmid = {42276166},
issn = {1876-7737},
mesh = {*Proteomics/methods/trends ; *Environmental Pollution/analysis/adverse effects ; *Environmental Monitoring/methods ; Humans ; Multiomics ; Artificial Intelligence ; Animals ; },
abstract = {Environmental proteomics has emerged as a powerful approach for elucidating the molecular mechanisms underlying pollutant-induced biological effects. Although this field has developed rapidly, the systematic review of recent proteomics applications in environmental pollution research remains limited. This review explored the emerging roles of toxicoproteomics in biomarker discovery and mechanistic elucidation, as well as ecotoxicoproteomics in ecological risk assessment and bioremediation strategies. Here, we review the field, highlighting recent trends such as the integration of proteomics with genomics, transcriptomics, and metabolomics to provide a comprehensive view of biological responses to environmental stressors. We further discuss the growing application of artificial intelligence in improving proteomics data interpretation and accelerating biomarker discovery. In addition, recent technological advances in environmental proteomics are highlighted, including next-generation tissue microarray proteomics, nanoscale proteomics, single-cell proteomics, and spatial proteomics. Despite its potential, proteomics faces challenges, such as high operational costs, computational complexity in analysis, and technical limitations in low-abundance protein detection. We propose that the convergence of proteomics with artificial intelligence and multi-omics approaches offers promising solutions to these challenges, enhancing the practical application of proteomics in environmental monitoring and risk assessment.},
}
MeSH Terms:
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*Proteomics/methods/trends
*Environmental Pollution/analysis/adverse effects
*Environmental Monitoring/methods
Humans
Multiomics
Artificial Intelligence
Animals
RevDate: 2026-09-02
CmpDate: 2026-09-02
AGSI: Adaptive group-enhanced strategy for iterative integration of single-cell multi-omics.
Computer methods and programs in biomedicine, 286:109556.
BACKGROUND AND OBJECTIVE: Single-cell multi-omics data integration is critical for understanding cellular heterogeneity and disease mechanisms. However, current methods face two key limitations: (1) uniform evaluation of cross-modal correspondence across all genes, neglecting the modular organization of biological systems, and (2) static integration strategies that fail to accommodate varying degrees of cell-level heterogeneity. To address these challenges, this study proposes AGSI, an adaptive framework for robust multi-omics integration through co-regulated gene modules and iterative reliability assessment.
METHODS: AGSI employs Latent Dirichlet Allocation to identify co-regulated gene modules and evaluates cross-modal correspondence at the module level. AGSI combines Wasserstein-enhanced similarity metrics with dual reliability modeling to progressively identify and integrate cells with high cross-modal concordance. Adaptive thresholding dynamically adjusts selection criteria throughout the iterative refinement process.
RESULTS: Extensive experiments on multiple datasets including PBMC, SNARE-seq mouse brain, 10x mouse brain, and large-scale human myocardial infarction data demonstrate that AGSI significantly outperforms seven state-of-the-art methods. Notably, AGSI achieves up to 25.6% F1 improvement over its ablation baseline and 11.9% over the best competing method on complex neural datasets, and maintains over 85% accuracy even under 50% data dropout.
CONCLUSIONS: AGSI provides a robust and scalable solution for multi-omics integration that preserves biological interpretability while achieving superior technical performance. AGSI is well suited to biomedical analyses requiring accurate cell type identification. The implementation code is available at https://github.com/CDMBlab/AGSI.
Additional Links: PMID-42497665
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PubMed:
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@article {pmid42497665,
year = {2026},
author = {Zhang, F and Shang, J and Jiang, S and Zhang, X and Yan, S and Sun, Y and Liu, JX},
title = {AGSI: Adaptive group-enhanced strategy for iterative integration of single-cell multi-omics.},
journal = {Computer methods and programs in biomedicine},
volume = {286},
number = {},
pages = {109556},
doi = {10.1016/j.cmpb.2026.109556},
pmid = {42497665},
issn = {1872-7565},
mesh = {*Multiomics ; Animals ; Humans ; Mice ; Algorithms ; Reproducibility of Results ; *Single-Cell Analysis ; Computational Biology/methods ; Software ; Myocardial Infarction/genetics ; Leukocytes, Mononuclear/metabolism ; Brain ; },
abstract = {BACKGROUND AND OBJECTIVE: Single-cell multi-omics data integration is critical for understanding cellular heterogeneity and disease mechanisms. However, current methods face two key limitations: (1) uniform evaluation of cross-modal correspondence across all genes, neglecting the modular organization of biological systems, and (2) static integration strategies that fail to accommodate varying degrees of cell-level heterogeneity. To address these challenges, this study proposes AGSI, an adaptive framework for robust multi-omics integration through co-regulated gene modules and iterative reliability assessment.
METHODS: AGSI employs Latent Dirichlet Allocation to identify co-regulated gene modules and evaluates cross-modal correspondence at the module level. AGSI combines Wasserstein-enhanced similarity metrics with dual reliability modeling to progressively identify and integrate cells with high cross-modal concordance. Adaptive thresholding dynamically adjusts selection criteria throughout the iterative refinement process.
RESULTS: Extensive experiments on multiple datasets including PBMC, SNARE-seq mouse brain, 10x mouse brain, and large-scale human myocardial infarction data demonstrate that AGSI significantly outperforms seven state-of-the-art methods. Notably, AGSI achieves up to 25.6% F1 improvement over its ablation baseline and 11.9% over the best competing method on complex neural datasets, and maintains over 85% accuracy even under 50% data dropout.
CONCLUSIONS: AGSI provides a robust and scalable solution for multi-omics integration that preserves biological interpretability while achieving superior technical performance. AGSI is well suited to biomedical analyses requiring accurate cell type identification. The implementation code is available at https://github.com/CDMBlab/AGSI.},
}
MeSH Terms:
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hide MeSH Terms
*Multiomics
Animals
Humans
Mice
Algorithms
Reproducibility of Results
*Single-Cell Analysis
Computational Biology/methods
Software
Myocardial Infarction/genetics
Leukocytes, Mononuclear/metabolism
Brain
RevDate: 2026-09-02
CmpDate: 2026-09-02
Investigating RNA Viruses Infecting Arbuscular Mycorrhizal Fungi.
Methods in molecular biology (Clifton, N.J.), 3045:171-183.
Fungi are known to be frequently infected by mycoviruses, which could play an important yet underexplored role in the fungal holobiont. Mycoviruses can enhance fungal traits, such as salinity tolerance and resistance to fungicides, and may also benefit plant hosts in tripartite interactions. While research on arbuscular mycorrhizal fungi (AMF) has focused on their ecological and agricultural value, few studies have explored their virome, possibly due to the difficulty of culturing AMF in the lab. This study presents an updated bioinformatic approach for virome characterization, emphasizing RNA viral ORFans and providing protocols for high-quality RNA extraction from AMF.
Additional Links: PMID-42681281
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Citation:
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@article {pmid42681281,
year = {2026},
author = {Mussano, P and Crosino, A and Lanfranco, L and Turina, M and Forgia, M},
title = {Investigating RNA Viruses Infecting Arbuscular Mycorrhizal Fungi.},
journal = {Methods in molecular biology (Clifton, N.J.)},
volume = {3045},
number = {},
pages = {171-183},
pmid = {42681281},
issn = {1940-6029},
mesh = {*Mycorrhizae/virology ; *RNA Viruses/genetics/isolation & purification ; *Fungal Viruses/genetics ; RNA, Viral/genetics/isolation & purification ; Computational Biology/methods ; Genome, Viral ; Virome ; },
abstract = {Fungi are known to be frequently infected by mycoviruses, which could play an important yet underexplored role in the fungal holobiont. Mycoviruses can enhance fungal traits, such as salinity tolerance and resistance to fungicides, and may also benefit plant hosts in tripartite interactions. While research on arbuscular mycorrhizal fungi (AMF) has focused on their ecological and agricultural value, few studies have explored their virome, possibly due to the difficulty of culturing AMF in the lab. This study presents an updated bioinformatic approach for virome characterization, emphasizing RNA viral ORFans and providing protocols for high-quality RNA extraction from AMF.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Mycorrhizae/virology
*RNA Viruses/genetics/isolation & purification
*Fungal Viruses/genetics
RNA, Viral/genetics/isolation & purification
Computational Biology/methods
Genome, Viral
Virome
RevDate: 2026-09-02
CmpDate: 2026-09-02
From Sampling to Identification of Arbuscular Mycorrhizal Fungi Through Next Generation Sequencing.
Methods in molecular biology (Clifton, N.J.), 3045:185-208.
In recent years, DNA sequencing technologies have advanced considerably with the rise of Next-Generation Sequencing (NGS) platforms, which have transformed microbial ecology research. These approaches enable the characterization of entire communities by using DNA traces to identify organisms taxonomically from a single sample. Arbuscular mycorrhizal fungi (AMF) are no exception and represent one of the most extensively studied groups of soil fungi. This chapter presents protocols for high-throughput, sequence-based analysis of AMF communities, covering the complete workflow from DNA extraction in plant or soil samples to the bioinformatic processing of sequencing data. It particularly focuses on rRNA gene metabarcoding, the most common strategy to provide estimates of AMF diversity and community composition through the amplification of DNA with taxon-specific primers followed by sequencing of barcode regions. Alternative strategies are described to accommodate different research objectives, including the selection of molecular markers.
Additional Links: PMID-42681282
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@article {pmid42681282,
year = {2026},
author = {Berruto, F and Bortolot, M and Lumini, E and Bianciotto, V},
title = {From Sampling to Identification of Arbuscular Mycorrhizal Fungi Through Next Generation Sequencing.},
journal = {Methods in molecular biology (Clifton, N.J.)},
volume = {3045},
number = {},
pages = {185-208},
pmid = {42681282},
issn = {1940-6029},
mesh = {*Mycorrhizae/genetics/classification/isolation & purification ; *High-Throughput Nucleotide Sequencing/methods ; Soil Microbiology ; DNA Barcoding, Taxonomic/methods ; DNA, Fungal/genetics ; Computational Biology/methods ; Sequence Analysis, DNA/methods ; },
abstract = {In recent years, DNA sequencing technologies have advanced considerably with the rise of Next-Generation Sequencing (NGS) platforms, which have transformed microbial ecology research. These approaches enable the characterization of entire communities by using DNA traces to identify organisms taxonomically from a single sample. Arbuscular mycorrhizal fungi (AMF) are no exception and represent one of the most extensively studied groups of soil fungi. This chapter presents protocols for high-throughput, sequence-based analysis of AMF communities, covering the complete workflow from DNA extraction in plant or soil samples to the bioinformatic processing of sequencing data. It particularly focuses on rRNA gene metabarcoding, the most common strategy to provide estimates of AMF diversity and community composition through the amplification of DNA with taxon-specific primers followed by sequencing of barcode regions. Alternative strategies are described to accommodate different research objectives, including the selection of molecular markers.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Mycorrhizae/genetics/classification/isolation & purification
*High-Throughput Nucleotide Sequencing/methods
Soil Microbiology
DNA Barcoding, Taxonomic/methods
DNA, Fungal/genetics
Computational Biology/methods
Sequence Analysis, DNA/methods
RevDate: 2026-09-02
CmpDate: 2026-09-02
Absolutist word usage in spoken language as a marker of depression: an ecological momentary assessment study.
BMC psychiatry, 26(1):.
BACKGROUND: Cognitive distortions are central to the maintenance of depression, as they bias information processing and negatively impact adaptive emotion regulation. As one manifestation of cognitive distortions, usage of absolutist words (e.g., always, never, must, completely) in written texts has been found to be indicative of underlying depression. Since absolutist word usage may allow important insights into maladaptive thinking patterns, it could be a relevant target for both monitoring and treating depressive symptoms. Therefore, we tested the relationships between absolutist word usage in spoken language with depression diagnosis, depressive symptom severity and current depressed mood.
METHOD: We recruited 144 age- and gender-matched participants with clinical depression (n = 48), subclinical depression (n = 48), and no history of depression (n = 48). By conducting smartphone-based ecological momentary assessments (EMA) three times daily for two weeks, participants provided ratings of depressed mood and speech samples, which included mood descriptions and mood-regulating statements. The Hamilton Rating Scale for Depression (HRSD) was administered at the end of the 2-week period to assess depressive symptom severity retrospectively. Group differences were calculated with ANOVAs, associations between depressed mood and absolutist word usage were evaluated with multilevel models, and the relationship between depressive symptom severity and absolutist word usage was calculated with regression models.
RESULTS: Results showed more frequent absolutist word usage over the EMA phase in individuals with clinical depression compared to individuals with no history of depression. Furthermore, absolutist word usage was negatively associated with momentary depressed mood among individuals with elevated depressive symptoms. Additional analyses testing the temporal relationship showed that greater absolutist word usage was associated with higher levels of depressed mood after 12-24 h. Accordingly, absolutist word usage was positively associated with depressive symptom severity assessed after the 2-week period.
CONCLUSION: Our results have several implications: First, absolutist word usage in spoken language appears to be an indicator of depression, which may be relevant for the optimization of depression assessment and monitoring approaches. Second, the finding that absolutist word usage was associated with lower depressed mood in the short-term, but higher depressed mood in the long-term provides important insights into the mechanisms of depression, and may help identify relevant treatment targets for clinicians.
TRIAL REGISTRATION: German Clinical Trial Registration DRKS00023670 on 19/01/2021 (https://drks.de/search/en/trial/DRKS00023670).
Additional Links: PMID-42681626
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@article {pmid42681626,
year = {2026},
author = {Bauer, JF and Gerczuk, M and Schindler-Gmelch, L and Schuller, B and Berking, M},
title = {Absolutist word usage in spoken language as a marker of depression: an ecological momentary assessment study.},
journal = {BMC psychiatry},
volume = {26},
number = {1},
pages = {},
pmid = {42681626},
issn = {1471-244X},
mesh = {Humans ; Female ; Ecological Momentary Assessment ; Male ; *Depression/diagnosis/psychology ; Adult ; Middle Aged ; Severity of Illness Index ; *Language ; },
abstract = {BACKGROUND: Cognitive distortions are central to the maintenance of depression, as they bias information processing and negatively impact adaptive emotion regulation. As one manifestation of cognitive distortions, usage of absolutist words (e.g., always, never, must, completely) in written texts has been found to be indicative of underlying depression. Since absolutist word usage may allow important insights into maladaptive thinking patterns, it could be a relevant target for both monitoring and treating depressive symptoms. Therefore, we tested the relationships between absolutist word usage in spoken language with depression diagnosis, depressive symptom severity and current depressed mood.
METHOD: We recruited 144 age- and gender-matched participants with clinical depression (n = 48), subclinical depression (n = 48), and no history of depression (n = 48). By conducting smartphone-based ecological momentary assessments (EMA) three times daily for two weeks, participants provided ratings of depressed mood and speech samples, which included mood descriptions and mood-regulating statements. The Hamilton Rating Scale for Depression (HRSD) was administered at the end of the 2-week period to assess depressive symptom severity retrospectively. Group differences were calculated with ANOVAs, associations between depressed mood and absolutist word usage were evaluated with multilevel models, and the relationship between depressive symptom severity and absolutist word usage was calculated with regression models.
RESULTS: Results showed more frequent absolutist word usage over the EMA phase in individuals with clinical depression compared to individuals with no history of depression. Furthermore, absolutist word usage was negatively associated with momentary depressed mood among individuals with elevated depressive symptoms. Additional analyses testing the temporal relationship showed that greater absolutist word usage was associated with higher levels of depressed mood after 12-24 h. Accordingly, absolutist word usage was positively associated with depressive symptom severity assessed after the 2-week period.
CONCLUSION: Our results have several implications: First, absolutist word usage in spoken language appears to be an indicator of depression, which may be relevant for the optimization of depression assessment and monitoring approaches. Second, the finding that absolutist word usage was associated with lower depressed mood in the short-term, but higher depressed mood in the long-term provides important insights into the mechanisms of depression, and may help identify relevant treatment targets for clinicians.
TRIAL REGISTRATION: German Clinical Trial Registration DRKS00023670 on 19/01/2021 (https://drks.de/search/en/trial/DRKS00023670).},
}
MeSH Terms:
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Humans
Female
Ecological Momentary Assessment
Male
*Depression/diagnosis/psychology
Adult
Middle Aged
Severity of Illness Index
*Language
RevDate: 2026-09-02
CmpDate: 2026-09-02
Remote sensing for monitoring and managing Eichhornia crassipes: a review of methods, applications, and decision-support frameworks.
Environmental monitoring and assessment, 198(9):.
Eichhornia crassipes (water hyacinth) is among the world's most aggressive aquatic invasive plants, with severe ecological and socioeconomic impacts on freshwater ecosystems. Over the last two decades, remote sensing has emerged as a critical tool for monitoring its spread and supporting management decisions, offering scalable, repeatable, and increasingly precise assessments. This review synthesizes 56 studies published between 2004 and 2025, examining how different platforms (satellites, UAVs, airborne, proximal), sensor types (multispectral, hyperspectral, SAR), and analytical methods (index thresholding, object-based classification, machine learning, deep learning) have been applied to detect, classify, and quantify E. crassipes. We highlight the evolution from early single-platform approaches to recent multimodal frameworks that integrate optical, radar, and UAV data, enabling both large-scale surveillance and fine-resolution diagnostics. Evidence demonstrates that species-level discrimination, phenological tracking, and biomass estimation are now feasible, with promising developments in linking spectral responses to pollutants and stress indicators. Despite these advances, key challenges remain in harmonizing data across platforms, reducing misclassification in mixed vegetation assemblages, and translating remote sensing outputs into decision-relevant information for adaptive management. We propose a decision-support framework built on five strategic pillars: multi-scale sensor fusion, ecologically interpretable classification schemes, scalable analytical ladders, early-warning indicators, and feedback loops linking monitoring to management actions. Together, these directions show how remote sensing can move beyond detection toward more responsive and decision-oriented approaches that support the sustainable management of E. crassipes invasions across diverse aquatic environments.
Additional Links: PMID-42684487
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@article {pmid42684487,
year = {2026},
author = {Salim, DHC and Mello, CCS and Pereira, G and Maretto, RV and Amorim, CC},
title = {Remote sensing for monitoring and managing Eichhornia crassipes: a review of methods, applications, and decision-support frameworks.},
journal = {Environmental monitoring and assessment},
volume = {198},
number = {9},
pages = {},
pmid = {42684487},
issn = {1573-2959},
mesh = {*Eichhornia/growth & development ; *Environmental Monitoring/methods ; *Remote Sensing Technology ; Decision Support Techniques ; Ecosystem ; Conservation of Natural Resources ; Introduced Species ; },
abstract = {Eichhornia crassipes (water hyacinth) is among the world's most aggressive aquatic invasive plants, with severe ecological and socioeconomic impacts on freshwater ecosystems. Over the last two decades, remote sensing has emerged as a critical tool for monitoring its spread and supporting management decisions, offering scalable, repeatable, and increasingly precise assessments. This review synthesizes 56 studies published between 2004 and 2025, examining how different platforms (satellites, UAVs, airborne, proximal), sensor types (multispectral, hyperspectral, SAR), and analytical methods (index thresholding, object-based classification, machine learning, deep learning) have been applied to detect, classify, and quantify E. crassipes. We highlight the evolution from early single-platform approaches to recent multimodal frameworks that integrate optical, radar, and UAV data, enabling both large-scale surveillance and fine-resolution diagnostics. Evidence demonstrates that species-level discrimination, phenological tracking, and biomass estimation are now feasible, with promising developments in linking spectral responses to pollutants and stress indicators. Despite these advances, key challenges remain in harmonizing data across platforms, reducing misclassification in mixed vegetation assemblages, and translating remote sensing outputs into decision-relevant information for adaptive management. We propose a decision-support framework built on five strategic pillars: multi-scale sensor fusion, ecologically interpretable classification schemes, scalable analytical ladders, early-warning indicators, and feedback loops linking monitoring to management actions. Together, these directions show how remote sensing can move beyond detection toward more responsive and decision-oriented approaches that support the sustainable management of E. crassipes invasions across diverse aquatic environments.},
}
MeSH Terms:
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*Eichhornia/growth & development
*Environmental Monitoring/methods
*Remote Sensing Technology
Decision Support Techniques
Ecosystem
Conservation of Natural Resources
Introduced Species
RevDate: 2026-09-02
CmpDate: 2026-09-02
Host-initiated microbial association leads to stable ectosymbiosis in an ecological model.
PLoS computational biology, 22(9):e1014699 pii:PCOMPBIOL-D-25-01620.
Microbial symbiosis is widespread among metabolically coupled cells; it presumably gave rise to mitochondria. However, how such symbioses emerge, evolve, and stabilize are unknown, particularly in the prokaryotic domain where endosymbiosis is virtually nonexistent. Yet there is growing evidence suggesting that mitochondria originated from such a metabolically driven prokaryotic partnership rather than phagocytotic predation. While prokaryotes almost ubiquitously engage in metabolic syntrophy, it is unknown whether syntrophy alone can enable stable physical associations that could pave the road toward physical integration. Here, we tested the hypothesis that syntrophy can transition into stable ectosymbiosis, using an ecological mathematical model. Starting from an existing syntrophic partnership between free-living hosts and symbionts, we demonstrate that population-level obligate ectosymbiosis can emerge and stabilize, even in unilateral syntrophy where only the symbiont consumes a host-produced metabolite. A key assumption is that the hosts' by-product inhibits their growth when it accumulates. By consuming the toxic by-product, the symbiont locally reduces hosts' self-inhibition at the contact surface, manifesting as a private benefit providing selective advantage. Our results show that due to the direct and indirect benefits, the ectosymbiotic consortium is stable against free-living forms and the consortial cooperation is ecologically selected for. Furthermore, solid metabolic coupling promotes population-level obligacy, ultimately excluding free-living individuals under stricter conditions. Our results support the hypothesis that cooperative, syntrophic microbes (particularly prokaryotes) are capable of forming stable, physical, and species-specific ectosymbiosis through inhibition reduction, providing a plausible first step toward potential, gradual endosymbiotic integration. Our work bridges the gap between models of microbial cooperation between free-living species and models that assume already-concluded, fully integrated endosymbiosis under multilevel selection.
Additional Links: PMID-42685140
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@article {pmid42685140,
year = {2026},
author = {Krishnan, N and Zachar, I and Kun, Á and Gokhale, CS and Garay, J},
title = {Host-initiated microbial association leads to stable ectosymbiosis in an ecological model.},
journal = {PLoS computational biology},
volume = {22},
number = {9},
pages = {e1014699},
doi = {10.1371/journal.pcbi.1014699},
pmid = {42685140},
issn = {1553-7358},
mesh = {*Symbiosis/physiology ; *Models, Biological ; *Host Microbial Interactions/physiology ; Computational Biology ; Ecosystem ; },
abstract = {Microbial symbiosis is widespread among metabolically coupled cells; it presumably gave rise to mitochondria. However, how such symbioses emerge, evolve, and stabilize are unknown, particularly in the prokaryotic domain where endosymbiosis is virtually nonexistent. Yet there is growing evidence suggesting that mitochondria originated from such a metabolically driven prokaryotic partnership rather than phagocytotic predation. While prokaryotes almost ubiquitously engage in metabolic syntrophy, it is unknown whether syntrophy alone can enable stable physical associations that could pave the road toward physical integration. Here, we tested the hypothesis that syntrophy can transition into stable ectosymbiosis, using an ecological mathematical model. Starting from an existing syntrophic partnership between free-living hosts and symbionts, we demonstrate that population-level obligate ectosymbiosis can emerge and stabilize, even in unilateral syntrophy where only the symbiont consumes a host-produced metabolite. A key assumption is that the hosts' by-product inhibits their growth when it accumulates. By consuming the toxic by-product, the symbiont locally reduces hosts' self-inhibition at the contact surface, manifesting as a private benefit providing selective advantage. Our results show that due to the direct and indirect benefits, the ectosymbiotic consortium is stable against free-living forms and the consortial cooperation is ecologically selected for. Furthermore, solid metabolic coupling promotes population-level obligacy, ultimately excluding free-living individuals under stricter conditions. Our results support the hypothesis that cooperative, syntrophic microbes (particularly prokaryotes) are capable of forming stable, physical, and species-specific ectosymbiosis through inhibition reduction, providing a plausible first step toward potential, gradual endosymbiotic integration. Our work bridges the gap between models of microbial cooperation between free-living species and models that assume already-concluded, fully integrated endosymbiosis under multilevel selection.},
}
MeSH Terms:
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*Symbiosis/physiology
*Models, Biological
*Host Microbial Interactions/physiology
Computational Biology
Ecosystem
RevDate: 2026-09-02
CmpDate: 2026-09-02
Comparison of Perioperative Complications of Early-Stage Endometrial Cancer Between Laparotomy, Laparoscopic, and Robotic-assisted Surgery using DPC Data: A Retrospective Cohort Study in Japan.
Journal of UOEH, 48(3):151-160.
Early-stage endometrial cancer can be cured surgically using three techniques: laparotomy, laparoscopic surgery, and robotic-assisted surgery. In this retrospective study, we used 4 years of data from the Japanese Diagnosis Procedure Combination to analyze perioperative sequelae for each surgical procedure. Patients with early-stage endometrial cancer were classified into three groups: laparotomy, laparoscopic surgery, and robotic-assisted surgery. The number of robotic-assisted surgeries is increasing, but hospitals with low surgical volumes performed laparotomy at a rate of 57.6%, while hospitals with higher surgical volume tended to perform fewer laparotomies and more laparoscopic and robotic-assisted surgeries. Compared with the laparotomy group, the in-hospital risk ratios and 95% confidence intervals for postoperative sequelae were 0.28 (0.18-0.44) and 0.39 (0.23-0.69) in the laparoscopic and robotic-assisted surgery groups, respectively (P = 0.001 for all). Regarding blood transfusion treatment, the incidence rate ratios were lower for laparoscopic and robotic-assisted surgery than for laparotomy (P < 0.001 for all), even after multivariable analysis. In conclusion, in early-stage endometrial cancer, laparotomy had the highest incidence of perioperative sequelae compared to laparoscopic surgery and robotic-assisted surgery.
Additional Links: PMID-42686520
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PubMed:
Citation:
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@article {pmid42686520,
year = {2026},
author = {Aoyama, Y and Watanabe, F and Tokutsu, K and Kinjo, Y and Muramatsu, K and Okawara, M and Kurita, T and Yoshino, K and Fushimi, K and Matsuda, S},
title = {Comparison of Perioperative Complications of Early-Stage Endometrial Cancer Between Laparotomy, Laparoscopic, and Robotic-assisted Surgery using DPC Data: A Retrospective Cohort Study in Japan.},
journal = {Journal of UOEH},
volume = {48},
number = {3},
pages = {151-160},
doi = {10.7888/juoeh.48.151},
pmid = {42686520},
issn = {0387-821X},
mesh = {Humans ; Female ; *Endometrial Neoplasms/surgery/pathology ; Retrospective Studies ; *Laparoscopy/adverse effects ; *Laparotomy/adverse effects ; *Robotic Surgical Procedures/adverse effects ; Japan/epidemiology ; *Postoperative Complications/epidemiology ; Aged ; Middle Aged ; Neoplasm Staging ; },
abstract = {Early-stage endometrial cancer can be cured surgically using three techniques: laparotomy, laparoscopic surgery, and robotic-assisted surgery. In this retrospective study, we used 4 years of data from the Japanese Diagnosis Procedure Combination to analyze perioperative sequelae for each surgical procedure. Patients with early-stage endometrial cancer were classified into three groups: laparotomy, laparoscopic surgery, and robotic-assisted surgery. The number of robotic-assisted surgeries is increasing, but hospitals with low surgical volumes performed laparotomy at a rate of 57.6%, while hospitals with higher surgical volume tended to perform fewer laparotomies and more laparoscopic and robotic-assisted surgeries. Compared with the laparotomy group, the in-hospital risk ratios and 95% confidence intervals for postoperative sequelae were 0.28 (0.18-0.44) and 0.39 (0.23-0.69) in the laparoscopic and robotic-assisted surgery groups, respectively (P = 0.001 for all). Regarding blood transfusion treatment, the incidence rate ratios were lower for laparoscopic and robotic-assisted surgery than for laparotomy (P < 0.001 for all), even after multivariable analysis. In conclusion, in early-stage endometrial cancer, laparotomy had the highest incidence of perioperative sequelae compared to laparoscopic surgery and robotic-assisted surgery.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Humans
Female
*Endometrial Neoplasms/surgery/pathology
Retrospective Studies
*Laparoscopy/adverse effects
*Laparotomy/adverse effects
*Robotic Surgical Procedures/adverse effects
Japan/epidemiology
*Postoperative Complications/epidemiology
Aged
Middle Aged
Neoplasm Staging
RevDate: 2026-08-31
CmpDate: 2026-08-31
Timber harvesting intensity and use of decision-support tools among semi-professional private forest owners: a Norwegian case study.
Scientific reports, 16(1):.
Non-industrial private forest owners are known to have multiple ownership values and objectives. Their management decisions have multiple impacts on the supply of ecosystem services from forests. Forest management plans, a main decision-support tool for many forest owners, tend to be timber-oriented, potentially leading to more harvesting and more frequent use among production-oriented owners. We investigated factors explaining harvest intensity, measured as the ratio of property-level actual harvest volumes to predicted harvest volumes and the use of forest management plans among 119 semi-professional, non-industrial, private forest owners in Norway. Harvest intensity decreased with forest area and with biodiversity and nextgeneration's need as ownership objectives and increased with wood prices and owner engagement but was not impacted by short-term profit or use of forest management plans. Use of forest management plans increased with forest area, having received instructions, trust in the harvest predictions, and economic ownership objectives. By using property-level harvest prediction, we could compare harvest figures to the actual timber resource, formed by each property's forest biophysical attributes. This approach may be a valuable step in developing models that provide enhanced understanding of how forest owner behavior is shaped by preferences and objectives.
Additional Links: PMID-42297904
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@article {pmid42297904,
year = {2026},
author = {Sjølie, HK and Tange, AC},
title = {Timber harvesting intensity and use of decision-support tools among semi-professional private forest owners: a Norwegian case study.},
journal = {Scientific reports},
volume = {16},
number = {1},
pages = {},
pmid = {42297904},
issn = {2045-2322},
mesh = {Norway ; *Forests ; *Forestry/methods ; *Conservation of Natural Resources/methods ; *Ownership ; *Decision Support Techniques ; Wood ; Biodiversity ; Humans ; Trees ; },
abstract = {Non-industrial private forest owners are known to have multiple ownership values and objectives. Their management decisions have multiple impacts on the supply of ecosystem services from forests. Forest management plans, a main decision-support tool for many forest owners, tend to be timber-oriented, potentially leading to more harvesting and more frequent use among production-oriented owners. We investigated factors explaining harvest intensity, measured as the ratio of property-level actual harvest volumes to predicted harvest volumes and the use of forest management plans among 119 semi-professional, non-industrial, private forest owners in Norway. Harvest intensity decreased with forest area and with biodiversity and nextgeneration's need as ownership objectives and increased with wood prices and owner engagement but was not impacted by short-term profit or use of forest management plans. Use of forest management plans increased with forest area, having received instructions, trust in the harvest predictions, and economic ownership objectives. By using property-level harvest prediction, we could compare harvest figures to the actual timber resource, formed by each property's forest biophysical attributes. This approach may be a valuable step in developing models that provide enhanced understanding of how forest owner behavior is shaped by preferences and objectives.},
}
MeSH Terms:
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Norway
*Forests
*Forestry/methods
*Conservation of Natural Resources/methods
*Ownership
*Decision Support Techniques
Wood
Biodiversity
Humans
Trees
RevDate: 2026-08-31
Seasonal and Temperature-Related Variation in Subarachnoid Hemorrhage Hospital Admissions: A Nationwide Ecological Time-Series Analysis in Brazil, 2020-2024.
Neurocritical care [Epub ahead of print].
BACKGROUND: Subarachnoid hemorrhage (SAH) carries high mortality worldwide. Seasonal patterns have been documented in temperate regions, but evidence from tropical and subtropical populations remains limited. We investigated associations between meteorological variables and SAH hospital admissions across diverse climate zones in Brazil.
METHODS: We conducted an ecological time-series analysis linking nationwide SAH hospitalizations [International Classification of Diseases Version 10 (ICD-10; I60.0-I60.9)] from Brazil's Unified Health System with meteorological data from the National Institute of Meteorology (January 2020-November 2024). Quasi-Poisson generalized linear models were used to estimate relative risks (RR) per 1 °C decrease in mean minimum temperature, overall and stratified by season. Sensitivity analyses excluded the first coronavirus disease 2019 (COVID-19) pandemic year.
RESULTS: Among 9903 SAH hospital admissions over 59 months, seasonal variation was observed, with the highest proportion occurring in autumn (27.2%, n = 2697) and the lowest in spring (23.4%, n = 2316; Chi-squared p < 0.001). The mean summer-winter difference in minimum temperature was 3.6 °C. Overall, the temperature-SAH association did not reach statistical significance [RR per 1 °C decrease: 1.019; 95% confidence interval (CI): 0.994-1.045; p = 0.14]. In season-stratified analyses, winter was the only season demonstrating a significant inverse association (RR = 1.133; 95% CI 1.008-1.275; p = 0.037). This finding was robust to the exclusion of the pandemic year 2020 (RR = 1.140; 95% CI 1.013-1.282; p = 0.030). In-hospital case fatality did not differ significantly across seasons (range 5.2-5.7%; p = 0.38).
CONCLUSIONS: SAH hospital admissions in Brazil exhibit modest seasonal variation, with a significant association with temperature observed only during the winter months. These findings extend evidence on environmental determinants of SAH to a tropical and subtropical setting, though the small effect size and ecological design warrant cautious interpretation.
Additional Links: PMID-42675342
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Citation:
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@article {pmid42675342,
year = {2026},
author = {Rodrigues, DLG and de Andrade, JBC and Silva, GS},
title = {Seasonal and Temperature-Related Variation in Subarachnoid Hemorrhage Hospital Admissions: A Nationwide Ecological Time-Series Analysis in Brazil, 2020-2024.},
journal = {Neurocritical care},
volume = {},
number = {},
pages = {},
pmid = {42675342},
issn = {1556-0961},
abstract = {BACKGROUND: Subarachnoid hemorrhage (SAH) carries high mortality worldwide. Seasonal patterns have been documented in temperate regions, but evidence from tropical and subtropical populations remains limited. We investigated associations between meteorological variables and SAH hospital admissions across diverse climate zones in Brazil.
METHODS: We conducted an ecological time-series analysis linking nationwide SAH hospitalizations [International Classification of Diseases Version 10 (ICD-10; I60.0-I60.9)] from Brazil's Unified Health System with meteorological data from the National Institute of Meteorology (January 2020-November 2024). Quasi-Poisson generalized linear models were used to estimate relative risks (RR) per 1 °C decrease in mean minimum temperature, overall and stratified by season. Sensitivity analyses excluded the first coronavirus disease 2019 (COVID-19) pandemic year.
RESULTS: Among 9903 SAH hospital admissions over 59 months, seasonal variation was observed, with the highest proportion occurring in autumn (27.2%, n = 2697) and the lowest in spring (23.4%, n = 2316; Chi-squared p < 0.001). The mean summer-winter difference in minimum temperature was 3.6 °C. Overall, the temperature-SAH association did not reach statistical significance [RR per 1 °C decrease: 1.019; 95% confidence interval (CI): 0.994-1.045; p = 0.14]. In season-stratified analyses, winter was the only season demonstrating a significant inverse association (RR = 1.133; 95% CI 1.008-1.275; p = 0.037). This finding was robust to the exclusion of the pandemic year 2020 (RR = 1.140; 95% CI 1.013-1.282; p = 0.030). In-hospital case fatality did not differ significantly across seasons (range 5.2-5.7%; p = 0.38).
CONCLUSIONS: SAH hospital admissions in Brazil exhibit modest seasonal variation, with a significant association with temperature observed only during the winter months. These findings extend evidence on environmental determinants of SAH to a tropical and subtropical setting, though the small effect size and ecological design warrant cautious interpretation.},
}
RevDate: 2026-09-01
CmpDate: 2026-09-01
Salivary gland microbiome of Anopheles gambiae: a mini-review of acquisition, composition, and functional significance.
Frontiers in insect science, 6:1911294.
The salivary gland (SG) is the final barrier for Plasmodium transmission to humans but remains comparatively understudied relative to the midgut microbiome. This review synthesizes current knowledge on SG microbiome acquisition routes, composition, and functional significance. Acquisition may occur via larval filter feeding, vertical (egg smearing), transstadial, or horizontal transmission during blood feeding, though their relative contributions are unknown. Compositional studies show Gram-negative genera Serratia, Elizabethkingia, Acinetobacter, Pseudomonas, and Asaia predominate; Plasmodium infection correlates with increased Serratia and decreased Elizabethkingia abundance. While immune-related genes (e.g., cecropins, defensin, GNBP, SRPN6) expressed in the SG may be modulated by resident bacteria, direct evidence of their effect on sporozoite invasion remains lacking. Gram-negative bacteria trigger Toll, Imd, and JAK-STAT pathways, but emerging evidence suggests the SG may mount a distinct, locally independent immune response compared to the systemic pathway. Paratransgenesis using Asaia shows promise, yet SG-targeted effector delivery remains untested. Ecological pressures common in West Africa, including agricultural pesticides, insecticide resistance, and larval water contamination, may influence mosquito-associated bacteria, but no studies explicitly link these to the SG microbiome. Significant knowledge gaps persist, notably the absence of field studies in high-burden regions like Nigeria and the lack of experimental manipulation to establish causality. Addressing these priorities is critical to determine whether the SG microbiome can be exploited as a transmission-blocking target.
Additional Links: PMID-42676645
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@article {pmid42676645,
year = {2026},
author = {Olafusi, CO and Afolabi, IS and Ogunlana, OO},
title = {Salivary gland microbiome of Anopheles gambiae: a mini-review of acquisition, composition, and functional significance.},
journal = {Frontiers in insect science},
volume = {6},
number = {},
pages = {1911294},
pmid = {42676645},
issn = {2673-8600},
abstract = {The salivary gland (SG) is the final barrier for Plasmodium transmission to humans but remains comparatively understudied relative to the midgut microbiome. This review synthesizes current knowledge on SG microbiome acquisition routes, composition, and functional significance. Acquisition may occur via larval filter feeding, vertical (egg smearing), transstadial, or horizontal transmission during blood feeding, though their relative contributions are unknown. Compositional studies show Gram-negative genera Serratia, Elizabethkingia, Acinetobacter, Pseudomonas, and Asaia predominate; Plasmodium infection correlates with increased Serratia and decreased Elizabethkingia abundance. While immune-related genes (e.g., cecropins, defensin, GNBP, SRPN6) expressed in the SG may be modulated by resident bacteria, direct evidence of their effect on sporozoite invasion remains lacking. Gram-negative bacteria trigger Toll, Imd, and JAK-STAT pathways, but emerging evidence suggests the SG may mount a distinct, locally independent immune response compared to the systemic pathway. Paratransgenesis using Asaia shows promise, yet SG-targeted effector delivery remains untested. Ecological pressures common in West Africa, including agricultural pesticides, insecticide resistance, and larval water contamination, may influence mosquito-associated bacteria, but no studies explicitly link these to the SG microbiome. Significant knowledge gaps persist, notably the absence of field studies in high-burden regions like Nigeria and the lack of experimental manipulation to establish causality. Addressing these priorities is critical to determine whether the SG microbiome can be exploited as a transmission-blocking target.},
}
RevDate: 2026-09-01
Planetary Boundaries and Absolute Sustainability in Life Cycle Assessment - past, present, and future.
Integrated environmental assessment and management pii:8778569 [Epub ahead of print].
Efforts to steer the social metabolism (i.e., how human societies interact with nature) towards sustainability are pulling assessment practice in two directions: "relative" product-to-product comparisons and "absolute" product-to-limit benchmarking, where the limit works as benchmark for the assessment. Within approaches such as Safe and Sustainable by Design, inherently threshold-based "absolute" chemical Risk Assessment is coupled to Life Cycle Assessment, which has traditionally been used as a tool for comparing alternatives. This coupling is driving the development of methodologies for comparative assessment of (eco)toxicological impact potentials (e.g., chemical footprinting). In parallel, the emergence of the Planetary Boundaries framework has renewed the interest in shifting from comparative assessments towards absolute benchmarking against global environmental limits, leading to Absolute Environmental Sustainability Assessment. This paper reviews how environmental limits are incorporated into Life Cycle Assessment through early distance to target methods (such as Ecological Scarcity, Environmental Themes, Eco-Indicator 95) to support business-driven eco-efficiency decisions and how impacts were anchored in national or regional targets and critical loads. We then discuss how the Planetary Boundaries framework reorganizes limits around Earth-system processes and how Planetary Boundaries based Life Cycle Assessment translates global boundaries into Life Cycle Assessment indicators and Planetary Boundaries based "budgets" for products and sectors. Across these developments, we show that setting and allocating thresholds reflects conflicting notions of "weak" and "strong" sustainability and is unavoidably value-laden and argue that making this "valuesphere" explicit is crucial if Planetary Boundaries based Life Cycle Assessment is to inform credible, product-level Safe and Sustainable by Design decisions on absolute sustainability.
Additional Links: PMID-42678384
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@article {pmid42678384,
year = {2026},
author = {Devecchi, S and Reppas-Chrysovitsinos, E and Tromer Dragsdahl, ALS and Pizzol, L and Semenzin, E and Zabeo, A and Hristozov, D and Rydberg, T},
title = {Planetary Boundaries and Absolute Sustainability in Life Cycle Assessment - past, present, and future.},
journal = {Integrated environmental assessment and management},
volume = {},
number = {},
pages = {},
doi = {10.1093/inteam/vjag150},
pmid = {42678384},
issn = {1551-3793},
abstract = {Efforts to steer the social metabolism (i.e., how human societies interact with nature) towards sustainability are pulling assessment practice in two directions: "relative" product-to-product comparisons and "absolute" product-to-limit benchmarking, where the limit works as benchmark for the assessment. Within approaches such as Safe and Sustainable by Design, inherently threshold-based "absolute" chemical Risk Assessment is coupled to Life Cycle Assessment, which has traditionally been used as a tool for comparing alternatives. This coupling is driving the development of methodologies for comparative assessment of (eco)toxicological impact potentials (e.g., chemical footprinting). In parallel, the emergence of the Planetary Boundaries framework has renewed the interest in shifting from comparative assessments towards absolute benchmarking against global environmental limits, leading to Absolute Environmental Sustainability Assessment. This paper reviews how environmental limits are incorporated into Life Cycle Assessment through early distance to target methods (such as Ecological Scarcity, Environmental Themes, Eco-Indicator 95) to support business-driven eco-efficiency decisions and how impacts were anchored in national or regional targets and critical loads. We then discuss how the Planetary Boundaries framework reorganizes limits around Earth-system processes and how Planetary Boundaries based Life Cycle Assessment translates global boundaries into Life Cycle Assessment indicators and Planetary Boundaries based "budgets" for products and sectors. Across these developments, we show that setting and allocating thresholds reflects conflicting notions of "weak" and "strong" sustainability and is unavoidably value-laden and argue that making this "valuesphere" explicit is crucial if Planetary Boundaries based Life Cycle Assessment is to inform credible, product-level Safe and Sustainable by Design decisions on absolute sustainability.},
}
RevDate: 2026-09-01
CmpDate: 2026-09-01
The 100 Diatom Genomes Project.
PLoS biology, 24(9):e3003947 pii:PBIOLOGY-D-26-00628.
One hundred diatom species have been selected for genome and transcriptome sequencing. The 100 Diatom Genomes Project aims to provide a scalable framework for understanding diatom biodiversity, ecology and evolution, and for investigating their use in biotechnology.
Additional Links: PMID-42678936
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PubMed:
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@article {pmid42678936,
year = {2026},
author = {Mock, T and Bilcke, G and Flaum, E and Fu, S and Hoch, L and Moog, K and Rijsdijk, N and Ruck, EC and Bishop, IW and Duchene, C and Gilbertson, R and Hopes, A and Johns, C and Manfellotto, F and Roberts, WR and Belshaw, N and Chandola, U and Chaerle, P and Chepurnova, O and Deleu, D and D'hondt, S and Di Costanzo, F and Dudin, O and Flori, S and Gaikwad, T and Groisillier, A and Hall, A and Ji, P and Lavier-Aydat, LJ and Lewis, WH and Menicot, S and Pinseel, E and Pottier, E and Sarkozi, K and Smerilli, A and Strauss, J and Thierens, S and Toseland, A and Touhami, Y and Utting, R and Van Bel, M and van Oosterhout, C and Wu, Y and Yang, F and Allhusen, E and Bolton, JJ and Bowler, C and Brinkhoff, T and Poehlein, A and Brovarone, T and Chen, N and Clark, G and Clark, MD and Copetti, D and Cui, Z and Deng, B and Jian, J and John, U and Jungblut, AD and Kang, J and Kristoffersen, JB and Lee, J and Liu, S and Mann, DG and Medlin, L and Moulton, V and Radojicic, J and Sato, S and Trobajo, R and Wolf, K and Yamada, N and Ye, N and Zhang, L and Zhuang, Y and Dey, G and Di Dato, V and Helliwell, K and Jaubert, M and Kroth, PG and Montresor, M and Romano, G and Rynearson, TA and Talag, J and Valentin, KU and Vincent, F and Waller, RF and Wheeler, G and Alverson, AJ and Barry, K and Boston, L and Falciatore, A and Ferrante, MI and Guo, J and Grimwood, J and Hayes, R and Herdean, A and Jenkins, J and Kim, M and Kooistra, WH and Kuo, A and Lipzen, A and Poulsen, N and Schmutz, J and Tirichine, L and Vandepoele, K and Verret, F and Vyverman, W and Grigoriev, IV},
title = {The 100 Diatom Genomes Project.},
journal = {PLoS biology},
volume = {24},
number = {9},
pages = {e3003947},
doi = {10.1371/journal.pbio.3003947},
pmid = {42678936},
issn = {1545-7885},
mesh = {*Diatoms/genetics/classification ; *Genome ; Biodiversity ; Transcriptome ; Genomics ; Phylogeny ; },
abstract = {One hundred diatom species have been selected for genome and transcriptome sequencing. The 100 Diatom Genomes Project aims to provide a scalable framework for understanding diatom biodiversity, ecology and evolution, and for investigating their use in biotechnology.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Diatoms/genetics/classification
*Genome
Biodiversity
Transcriptome
Genomics
Phylogeny
RevDate: 2026-09-01
CmpDate: 2026-09-01
Using high frequency GPS data to assess wintering goose proximity to commercial poultry facilities on the Delmarva peninsula for avian influenza risk management and surveillance.
PloS one, 21(9):e0355415 pii:PONE-D-26-14656.
The ongoing global outbreak of Highly Pathogenic Avian Influenza Virus (HPAIv) Clade 2.3.4.4 H5N1 in poultry, which was first detected in the United States (USA) in February 2022, underscores the importance of improving food biosecurity and wild bird surveillance. The Delmarva Peninsula is vital to wintering waterfowl and to poultry production, thereby increasing the risk of HPAIv outbreaks. By using fine-scale GPS tracking of Greater Snow Geese (GSGO, N = 59) and Canada Geese (CANG, N = 9) over four winters (2019-2023), we 1) demonstrate a risk ranking system for poultry facilities based on exposure to wintering waterfowl, and 2) model this exposure in relation to temporal, geographic, and land cover factors. We showed that an ordinal-percentile ranking system, based on goose points per hour (gp/h) at poultry facilities, effectively predicted HPAIv H5N1 outbreak risks in the Delmarva Peninsula. Seven facilities with outbreaks were in the 78-99th risk percentile, including one ranked among the top 25 of 6,021 facilities. Such ranking criteria could be used to guide biosecurity efforts when response teams' resources are limited. Notably, one-third of Delmarva poultry facilities had GPS-marked waterfowl present during winters, indicating a significant presence despite our limited sample sizes. We analyzed the variability in goose exposure rates near poultry facilities over four winters. Time (week) during winter was the key predictor of exposure, with greater GSGO presence in mid-late winter (Dec 15 to Feb 28) and CANG exposure peaking in early winter (Nov 28 to Dec 11), then stabilizing until late winter (Feb to Mar 13), whereupon exposure increased again. Colder temperatures (below 0°C) significantly increased GSGO exposure as they sought waste grain for energy. Goose exposure for both species was high throughout the winter, necessitating 24-hour surveillance. Proximity to sewage treatment plants (≤2 km), National Wildlife Refuges (≤5 km), water bodies (≤5 km), and the coast (≤20 km) increased exposure levels. Additionally, inland areas with features such as reservoirs and lakes supported large numbers of geese near facilities.
Additional Links: PMID-42678946
Publisher:
PubMed:
Citation:
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@article {pmid42678946,
year = {2026},
author = {Hardy, MJ and Williams, CK and Ladman, BS and Pitesky, ME and Overton, CT and Casazza, ML and Matchett, EL and Prosser, DJ and Legagneux, P and Lefebvre, J and Buler, JJ},
title = {Using high frequency GPS data to assess wintering goose proximity to commercial poultry facilities on the Delmarva peninsula for avian influenza risk management and surveillance.},
journal = {PloS one},
volume = {21},
number = {9},
pages = {e0355415},
doi = {10.1371/journal.pone.0355415},
pmid = {42678946},
issn = {1932-6203},
mesh = {Animals ; *Influenza in Birds/epidemiology/prevention & control/virology ; *Geese/virology ; Seasons ; Influenza A Virus, H5N1 Subtype/isolation & purification ; Geographic Information Systems ; Disease Outbreaks/prevention & control ; Risk Management ; *Poultry/virology ; *Poultry Diseases/epidemiology/virology ; },
abstract = {The ongoing global outbreak of Highly Pathogenic Avian Influenza Virus (HPAIv) Clade 2.3.4.4 H5N1 in poultry, which was first detected in the United States (USA) in February 2022, underscores the importance of improving food biosecurity and wild bird surveillance. The Delmarva Peninsula is vital to wintering waterfowl and to poultry production, thereby increasing the risk of HPAIv outbreaks. By using fine-scale GPS tracking of Greater Snow Geese (GSGO, N = 59) and Canada Geese (CANG, N = 9) over four winters (2019-2023), we 1) demonstrate a risk ranking system for poultry facilities based on exposure to wintering waterfowl, and 2) model this exposure in relation to temporal, geographic, and land cover factors. We showed that an ordinal-percentile ranking system, based on goose points per hour (gp/h) at poultry facilities, effectively predicted HPAIv H5N1 outbreak risks in the Delmarva Peninsula. Seven facilities with outbreaks were in the 78-99th risk percentile, including one ranked among the top 25 of 6,021 facilities. Such ranking criteria could be used to guide biosecurity efforts when response teams' resources are limited. Notably, one-third of Delmarva poultry facilities had GPS-marked waterfowl present during winters, indicating a significant presence despite our limited sample sizes. We analyzed the variability in goose exposure rates near poultry facilities over four winters. Time (week) during winter was the key predictor of exposure, with greater GSGO presence in mid-late winter (Dec 15 to Feb 28) and CANG exposure peaking in early winter (Nov 28 to Dec 11), then stabilizing until late winter (Feb to Mar 13), whereupon exposure increased again. Colder temperatures (below 0°C) significantly increased GSGO exposure as they sought waste grain for energy. Goose exposure for both species was high throughout the winter, necessitating 24-hour surveillance. Proximity to sewage treatment plants (≤2 km), National Wildlife Refuges (≤5 km), water bodies (≤5 km), and the coast (≤20 km) increased exposure levels. Additionally, inland areas with features such as reservoirs and lakes supported large numbers of geese near facilities.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Animals
*Influenza in Birds/epidemiology/prevention & control/virology
*Geese/virology
Seasons
Influenza A Virus, H5N1 Subtype/isolation & purification
Geographic Information Systems
Disease Outbreaks/prevention & control
Risk Management
*Poultry/virology
*Poultry Diseases/epidemiology/virology
RevDate: 2026-09-01
CmpDate: 2026-09-01
From fascination to fear and disgust: cross-cultural assessment of emotional and aesthetic responses to snake imagery.
Proceedings. Biological sciences, 293(2078):.
The primate visual system is thought to have evolved under selective pressures favouring rapid detection of snakes, ancestral predators that shaped perceptual and attentional mechanisms. Yet, the transition from visual detection to subjective fear remains poorly understood and may depend on specific morphological cues. Here, we examined how snake morphology modulates human emotional and aesthetic responses across ecological and cultural contexts. A total of 377 participants from Portugal (low snake biodiversity) and Brazil (high snake biodiversity) rated images of 92 snake species on fear, disgust, beauty, valence, arousal and perceived size. Cluster analyses revealed three consistent emotional profiles across populations: a High-Fear cluster (mainly viperids, boids and mimics with threatening traits), a High-Valence cluster (mostly harmless colubrids and dipsadids), and a smaller High-Disgust cluster (fossorial or limbless reptiles). Cluster membership was unaffected by country, indicating cross-cultural consistency in emotional evaluations of snake morphology. Species in the High-Fear cluster exhibited higher edge density. By contrast, greater exposure to snakes, particularly in natural environments, was associated with lower Snake Fear Questionnaire scores. These results support the view that humans rely on evolutionarily conserved morphological heuristics (e.g. triangular heads, keeled scales and disruptive patterns) to assess potential threats, while individual predispositions and experience modulate response intensity.
Additional Links: PMID-42680193
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PubMed:
Citation:
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@article {pmid42680193,
year = {2026},
author = {Biondi, L and Silva, F and Gomes, N and Maior, RS and Silva, S and Soares, SC},
title = {From fascination to fear and disgust: cross-cultural assessment of emotional and aesthetic responses to snake imagery.},
journal = {Proceedings. Biological sciences},
volume = {293},
number = {2078},
pages = {},
doi = {10.1098/rspb.2026.1328},
pmid = {42680193},
issn = {1471-2954},
support = {UID/04810/2020//Fundação para a Ciência e a Tecnologia/ ; 2022.06494.CEECIND//Fundação para a Ciência e a Tecnologia/ ; 2021.05287.BD//Fundação para a Ciência e a Tecnologia/ ; 308291/2020-4//Conselho Nacional de Desenvolvimento Científico e Tecnológico/ ; },
mesh = {Animals ; *Fear ; *Snakes/anatomy & histology ; Humans ; Portugal ; Female ; Cross-Cultural Comparison ; Brazil ; *Disgust ; *Emotions ; Male ; Esthetics ; Adult ; },
abstract = {The primate visual system is thought to have evolved under selective pressures favouring rapid detection of snakes, ancestral predators that shaped perceptual and attentional mechanisms. Yet, the transition from visual detection to subjective fear remains poorly understood and may depend on specific morphological cues. Here, we examined how snake morphology modulates human emotional and aesthetic responses across ecological and cultural contexts. A total of 377 participants from Portugal (low snake biodiversity) and Brazil (high snake biodiversity) rated images of 92 snake species on fear, disgust, beauty, valence, arousal and perceived size. Cluster analyses revealed three consistent emotional profiles across populations: a High-Fear cluster (mainly viperids, boids and mimics with threatening traits), a High-Valence cluster (mostly harmless colubrids and dipsadids), and a smaller High-Disgust cluster (fossorial or limbless reptiles). Cluster membership was unaffected by country, indicating cross-cultural consistency in emotional evaluations of snake morphology. Species in the High-Fear cluster exhibited higher edge density. By contrast, greater exposure to snakes, particularly in natural environments, was associated with lower Snake Fear Questionnaire scores. These results support the view that humans rely on evolutionarily conserved morphological heuristics (e.g. triangular heads, keeled scales and disruptive patterns) to assess potential threats, while individual predispositions and experience modulate response intensity.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Animals
*Fear
*Snakes/anatomy & histology
Humans
Portugal
Female
Cross-Cultural Comparison
Brazil
*Disgust
*Emotions
Male
Esthetics
Adult
RevDate: 2026-08-30
CmpDate: 2026-08-30
Rumen-derived Pichia membranifaciens modulates the rumen microbiome and metabolome and mitigates methane emissions in dairy cows.
NPJ biofilms and microbiomes, 12(1):.
Methane emissions from ruminants represent a significant environmental challenge and dietary energy loss. While yeasts are potential rumen modulators, specific methane-mitigating species remain poorly characterized. Here, we screened 73 rumen-derived strains in vitro, identifying Pichia membranifaciens M12 as the most effective candidate, reducing methane output by 17.1%. Subsequently, a randomized block trial with 36 dairy cows compared a control group with P. membranifaciens M12 supplementation at 2.5 and 5 × 10[11] CFU/cow/day. Methane yield per unit of dry matter intake significantly decreased in the high-dose group (18.7%, P = 0.003), without compromising lactation performance and animal health. Multi-omics analyses revealed that M12 suppressed hydrogenotrophic methanogens (e.g., Methanobrevibacter) and hydrogen-producing bacteria (e.g., Ruminococcus and Fibrobacter), while enriching specific eukaryotic taxa like Orpinomyces and Entodinium. Metabolomic profiling indicated a significant dose-dependent accumulation of metabolites. Metagenomic function analysis demonstrated the decreased abundance of key methanogenesis genes (e.g., mcrABCDG) and increased abundance of hydrogenase (hyaABC), lactate-forming (ghrB), and propionate-forming (mcmA1 and lcdB), suggesting a redirection of reducing equivalents from methanogenesis toward propionate synthesis, alongside enhanced butyrate production. These findings demonstrate that P. membranifaciens M12 mitigates methane emissions via coordinated ecological and metabolic modulation, highlighting its potential as a sustainable strategy for low-carbon ruminant production.
Additional Links: PMID-42230654
PubMed:
Citation:
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@article {pmid42230654,
year = {2026},
author = {Li, J and Liang, X and Liu, P and Zhu, W and Jin, W and Mao, S and Xie, F},
title = {Rumen-derived Pichia membranifaciens modulates the rumen microbiome and metabolome and mitigates methane emissions in dairy cows.},
journal = {NPJ biofilms and microbiomes},
volume = {12},
number = {1},
pages = {},
pmid = {42230654},
issn = {2055-5008},
mesh = {Animals ; *Rumen/microbiology ; *Methane/metabolism ; Cattle ; *Metabolome ; *Pichia/physiology/metabolism ; Female ; *Microbiota ; Lactation ; Animal Feed/analysis ; Bacteria/classification/genetics/metabolism ; Multiomics ; },
abstract = {Methane emissions from ruminants represent a significant environmental challenge and dietary energy loss. While yeasts are potential rumen modulators, specific methane-mitigating species remain poorly characterized. Here, we screened 73 rumen-derived strains in vitro, identifying Pichia membranifaciens M12 as the most effective candidate, reducing methane output by 17.1%. Subsequently, a randomized block trial with 36 dairy cows compared a control group with P. membranifaciens M12 supplementation at 2.5 and 5 × 10[11] CFU/cow/day. Methane yield per unit of dry matter intake significantly decreased in the high-dose group (18.7%, P = 0.003), without compromising lactation performance and animal health. Multi-omics analyses revealed that M12 suppressed hydrogenotrophic methanogens (e.g., Methanobrevibacter) and hydrogen-producing bacteria (e.g., Ruminococcus and Fibrobacter), while enriching specific eukaryotic taxa like Orpinomyces and Entodinium. Metabolomic profiling indicated a significant dose-dependent accumulation of metabolites. Metagenomic function analysis demonstrated the decreased abundance of key methanogenesis genes (e.g., mcrABCDG) and increased abundance of hydrogenase (hyaABC), lactate-forming (ghrB), and propionate-forming (mcmA1 and lcdB), suggesting a redirection of reducing equivalents from methanogenesis toward propionate synthesis, alongside enhanced butyrate production. These findings demonstrate that P. membranifaciens M12 mitigates methane emissions via coordinated ecological and metabolic modulation, highlighting its potential as a sustainable strategy for low-carbon ruminant production.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Animals
*Rumen/microbiology
*Methane/metabolism
Cattle
*Metabolome
*Pichia/physiology/metabolism
Female
*Microbiota
Lactation
Animal Feed/analysis
Bacteria/classification/genetics/metabolism
Multiomics
RevDate: 2026-08-30
CmpDate: 2026-08-30
Longitudinal dynamics of the maternal gut virome associate with metabolic features of preterm birth.
Nature communications, 17(1):.
Preterm birth (PTB) remains a major pregnancy complication, yet the role of the maternal gut virome in its etiology is largely unknown. Here we show that the maternal gut virome undergoes ecological destabilization prior to PTB, coupled with distinct host metabolic remodeling. Nested within the Tongji-Huaxi-Shuangliu Birth Cohort, we integrate longitudinal gut virome and bacteriome profiles from 300 stool samples, alongside matched serum metabolomes and clinical profiles, from 100 pregnant women (50 with PTB and 50 with term birth) across early, middle, and late pregnancy. We reveal that although the maternal gut virome is highly personalized and longitudinally stable within individuals, PTB is characterized by reduced virome convergence and specific alterations in viral populations emerging during mid-to-late pregnancy. Host-phage analyses identify remodeling of Klebsiella- and Prevotella-associated viral communities linked to PTB risk. PTB-associated virome alterations are further associated with amino acid metabolic remodeling, particularly glutamate- and aspartate-related pathways, supported by reproducible virus-metabolite associations and enriched viral auxiliary metabolic genes. In addition, L-aspartate partly mediates associations between monocyte-related inflammatory indices and PTB. Multi-omics modeling demonstrates that virome-metabolome signatures achieve strong predictive performance for both PTB and imminent delivery, with viral features contributing substantially to prediction accuracy and retaining predictive value in external validation. Collectively, these findings highlight the maternal virome and its metabolic signatures as key determinants of PTB susceptibility.
Additional Links: PMID-42669713
PubMed:
Citation:
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@article {pmid42669713,
year = {2026},
author = {Jiao, X and Yang, Y and Li, F and Zheng, JS and Lai, Y and Li, B and Wang, T and Dong, Y and Wang, Y and Li, Y and Li, R and Wu, Z and Wu, G and Yuan, J and Zhang, S and Li, S and Liu, G and Shi, J and Xiong, F and Pan, A and Liang, G and Huang, Y and Pan, XF},
title = {Longitudinal dynamics of the maternal gut virome associate with metabolic features of preterm birth.},
journal = {Nature communications},
volume = {17},
number = {1},
pages = {},
pmid = {42669713},
issn = {2041-1723},
support = {82473646//National Natural Science Foundation of China (National Science Foundation of China)/ ; },
mesh = {Humans ; Female ; Pregnancy ; *Premature Birth/metabolism/virology ; *Virome/genetics ; *Gastrointestinal Microbiome ; Feces/virology/microbiology ; Adult ; Longitudinal Studies ; Metabolome ; Infant, Newborn ; Multiomics ; },
abstract = {Preterm birth (PTB) remains a major pregnancy complication, yet the role of the maternal gut virome in its etiology is largely unknown. Here we show that the maternal gut virome undergoes ecological destabilization prior to PTB, coupled with distinct host metabolic remodeling. Nested within the Tongji-Huaxi-Shuangliu Birth Cohort, we integrate longitudinal gut virome and bacteriome profiles from 300 stool samples, alongside matched serum metabolomes and clinical profiles, from 100 pregnant women (50 with PTB and 50 with term birth) across early, middle, and late pregnancy. We reveal that although the maternal gut virome is highly personalized and longitudinally stable within individuals, PTB is characterized by reduced virome convergence and specific alterations in viral populations emerging during mid-to-late pregnancy. Host-phage analyses identify remodeling of Klebsiella- and Prevotella-associated viral communities linked to PTB risk. PTB-associated virome alterations are further associated with amino acid metabolic remodeling, particularly glutamate- and aspartate-related pathways, supported by reproducible virus-metabolite associations and enriched viral auxiliary metabolic genes. In addition, L-aspartate partly mediates associations between monocyte-related inflammatory indices and PTB. Multi-omics modeling demonstrates that virome-metabolome signatures achieve strong predictive performance for both PTB and imminent delivery, with viral features contributing substantially to prediction accuracy and retaining predictive value in external validation. Collectively, these findings highlight the maternal virome and its metabolic signatures as key determinants of PTB susceptibility.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Humans
Female
Pregnancy
*Premature Birth/metabolism/virology
*Virome/genetics
*Gastrointestinal Microbiome
Feces/virology/microbiology
Adult
Longitudinal Studies
Metabolome
Infant, Newborn
Multiomics
RevDate: 2026-08-31
CmpDate: 2026-08-31
Integrated risk assessment of industrial wastewater in a Bangladeshi export processing zone.
Journal of water and health, 24(8):1187-1204.
Industrial wastewater from export processing zones may comply with regulatory standards while concealing ecological risks not captured by routine monitoring. This study aimed to (1) evaluate effluent quality and regulatory compliance in the Chattogram Export Processing Zone (CEPZ), Bangladesh; (2) develop an integrated risk assessment framework integrating the Effluent Quality Index (EQI), ecotoxicity, metal speciation, and geographic information system (GIS) analysis; and (3) identify high-risk discharge corridors. Treated effluents (n = 6) and drinking water were analyzed for physicochemical parameters, Pb and Cr, acute ecotoxicity using Daphnia magna (EC50), metal speciation (Visual MINTEQ), and spatial distribution against ECR 2023 and WHO guidelines. Although pH and metal concentrations complied with regulatory limits, 5-day biochemical oxygen demand (95-180 mg L[-1]) exceeded the ECR limit (30 mg L[-1]) by up to 600%, while chemical oxygen demand (240-326 mg L[-1]) exceeded the 200 mg L[-1] limit by 63%. The washing-finishing sector exhibited the highest pollution burden (EQI = 3.10) and toxicity (EC50 = 18.5%). Metal speciation showed that 45-88% of regulated heavy metals occurred as bioavailable organic complexes. EQI correlated with EC50 (R[2] = 0.84, p < 0.01); GIS identified a 2-km high-risk corridor, potentially exposing 50,000-75,000 residents.
Additional Links: PMID-42670999
PubMed:
Citation:
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@article {pmid42670999,
year = {2026},
author = {Rahman, MS and Jalil, A and Ahmed, S},
title = {Integrated risk assessment of industrial wastewater in a Bangladeshi export processing zone.},
journal = {Journal of water and health},
volume = {24},
number = {8},
pages = {1187-1204},
pmid = {42670999},
issn = {1477-8920},
mesh = {Bangladesh ; *Water Pollutants, Chemical/toxicity/analysis ; Risk Assessment ; *Wastewater/analysis/chemistry ; Animals ; *Environmental Monitoring ; *Industrial Waste/analysis ; Daphnia magna/drug effects ; Metals, Heavy/analysis ; Geographic Information Systems ; },
abstract = {Industrial wastewater from export processing zones may comply with regulatory standards while concealing ecological risks not captured by routine monitoring. This study aimed to (1) evaluate effluent quality and regulatory compliance in the Chattogram Export Processing Zone (CEPZ), Bangladesh; (2) develop an integrated risk assessment framework integrating the Effluent Quality Index (EQI), ecotoxicity, metal speciation, and geographic information system (GIS) analysis; and (3) identify high-risk discharge corridors. Treated effluents (n = 6) and drinking water were analyzed for physicochemical parameters, Pb and Cr, acute ecotoxicity using Daphnia magna (EC50), metal speciation (Visual MINTEQ), and spatial distribution against ECR 2023 and WHO guidelines. Although pH and metal concentrations complied with regulatory limits, 5-day biochemical oxygen demand (95-180 mg L[-1]) exceeded the ECR limit (30 mg L[-1]) by up to 600%, while chemical oxygen demand (240-326 mg L[-1]) exceeded the 200 mg L[-1] limit by 63%. The washing-finishing sector exhibited the highest pollution burden (EQI = 3.10) and toxicity (EC50 = 18.5%). Metal speciation showed that 45-88% of regulated heavy metals occurred as bioavailable organic complexes. EQI correlated with EC50 (R[2] = 0.84, p < 0.01); GIS identified a 2-km high-risk corridor, potentially exposing 50,000-75,000 residents.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Bangladesh
*Water Pollutants, Chemical/toxicity/analysis
Risk Assessment
*Wastewater/analysis/chemistry
Animals
*Environmental Monitoring
*Industrial Waste/analysis
Daphnia magna/drug effects
Metals, Heavy/analysis
Geographic Information Systems
RevDate: 2026-08-31
CmpDate: 2026-08-31
Nonuniform resizing of marine life under climate change.
Proceedings of the National Academy of Sciences of the United States of America, 123(36):e2606099123.
Global warming is often predicted to drive universal declines in animal body size, but empirical evidence remains equivocal. This is particularly true in marine systems, where body size distributions are influenced not only by temperature but also by oxygen and productivity, all of which are expected to be greatly altered in future oceans. Differences in regional climate trajectories and the physiology of marine taxa also suggest that body size responses will not be spatially or ecologically uniform. We address these complexities by projecting future changes in mean body size across species within ocean basins using a database of 23,329 marine mollusc species. We quantify how body size distributions change across energetic gradients and forecast assemblage level shifts of the five major classes of molluscs across all 10 oceanic basins. Under high greenhouse gas emission scenarios, we project a significant decline in body size in 68% of class-basin combinations (34 of 50), with some clades expected to shrink by ~16% in mean length by 2100. However, these responses are not universal but are governed by clade-level differences in dominant ecological and physiological strategies and the geography of climate change. Because biomass scales allometrically with length, these trends can correspond to substantial changes in the mass of the average species, from a 46% decline to a 15% increase depending on clade and region. Such widespread functional disruptions may threaten critical ecosystem services (carbon sequestration, nutrient cycling, and human food provisioning), with implications for global marine ecosystem functioning and services.
Additional Links: PMID-42673461
Publisher:
PubMed:
Citation:
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@article {pmid42673461,
year = {2026},
author = {Trindade-Santos, I and Webb, TJ and Heim, NA and Knope, ML and Monarrez, PM and Payne, JL and Finnegan, S and McClain, CR},
title = {Nonuniform resizing of marine life under climate change.},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {123},
number = {36},
pages = {e2606099123},
doi = {10.1073/pnas.2606099123},
pmid = {42673461},
issn = {1091-6490},
mesh = {Animals ; *Climate Change ; Oceans and Seas ; *Mollusca/physiology ; *Aquatic Organisms/physiology ; Body Size ; Ecosystem ; Global Warming ; Biomass ; },
abstract = {Global warming is often predicted to drive universal declines in animal body size, but empirical evidence remains equivocal. This is particularly true in marine systems, where body size distributions are influenced not only by temperature but also by oxygen and productivity, all of which are expected to be greatly altered in future oceans. Differences in regional climate trajectories and the physiology of marine taxa also suggest that body size responses will not be spatially or ecologically uniform. We address these complexities by projecting future changes in mean body size across species within ocean basins using a database of 23,329 marine mollusc species. We quantify how body size distributions change across energetic gradients and forecast assemblage level shifts of the five major classes of molluscs across all 10 oceanic basins. Under high greenhouse gas emission scenarios, we project a significant decline in body size in 68% of class-basin combinations (34 of 50), with some clades expected to shrink by ~16% in mean length by 2100. However, these responses are not universal but are governed by clade-level differences in dominant ecological and physiological strategies and the geography of climate change. Because biomass scales allometrically with length, these trends can correspond to substantial changes in the mass of the average species, from a 46% decline to a 15% increase depending on clade and region. Such widespread functional disruptions may threaten critical ecosystem services (carbon sequestration, nutrient cycling, and human food provisioning), with implications for global marine ecosystem functioning and services.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Animals
*Climate Change
Oceans and Seas
*Mollusca/physiology
*Aquatic Organisms/physiology
Body Size
Ecosystem
Global Warming
Biomass
RevDate: 2026-08-30
CmpDate: 2026-08-30
A Darwin Core dataset of scorpions (Arachnida, Scorpiones) from the Royal Belgian Institute of Natural Sciences (RBINS) Collections.
Biodiversity data journal, 14:e188187.
BACKGROUND: This data paper details the publication of a dataset derived from the scorpion (Order Scorpiones C.L. Koch, 1850) collections preserved at the Royal Belgian Institute of Natural Sciences (RBINS), Brussels. The dataset includes all 3,652 specimens mostly identified to genus or species level during a recent re-evaluation. To maximise accessibility and interoperability, the entire dataset was fully standardised using the Darwin Core (DwC) standard and published as open data. The published dataset comprises a significant collection of records, encompassing eleven families, 56 genera and 117 species of scorpions. Geographically, the specimens originate from a wide range of locations, in 59 countries. The records within this dataset span a substantial chronological period, with collection dates ranging from 1872 to 2023. Most of the specimens were collected during expeditions led by researchers of RBINS.
NEW INFORMATION: The mobilisation and standardisation of this rich historical collection provide a valuable resource for global biodiversity informatics, supporting crucial research in taxonomy, ecology and biogeography of the order Scorpiones.
Additional Links: PMID-42668906
PubMed:
Citation:
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@article {pmid42668906,
year = {2026},
author = {Durante, F and Prendini, L and Pizzolotto, R and Wérenne, G and Baert, L and Musschoot, T and Dekoninck, W},
title = {A Darwin Core dataset of scorpions (Arachnida, Scorpiones) from the Royal Belgian Institute of Natural Sciences (RBINS) Collections.},
journal = {Biodiversity data journal},
volume = {14},
number = {},
pages = {e188187},
pmid = {42668906},
issn = {1314-2828},
abstract = {BACKGROUND: This data paper details the publication of a dataset derived from the scorpion (Order Scorpiones C.L. Koch, 1850) collections preserved at the Royal Belgian Institute of Natural Sciences (RBINS), Brussels. The dataset includes all 3,652 specimens mostly identified to genus or species level during a recent re-evaluation. To maximise accessibility and interoperability, the entire dataset was fully standardised using the Darwin Core (DwC) standard and published as open data. The published dataset comprises a significant collection of records, encompassing eleven families, 56 genera and 117 species of scorpions. Geographically, the specimens originate from a wide range of locations, in 59 countries. The records within this dataset span a substantial chronological period, with collection dates ranging from 1872 to 2023. Most of the specimens were collected during expeditions led by researchers of RBINS.
NEW INFORMATION: The mobilisation and standardisation of this rich historical collection provide a valuable resource for global biodiversity informatics, supporting crucial research in taxonomy, ecology and biogeography of the order Scorpiones.},
}
RevDate: 2026-08-29
CmpDate: 2026-08-29
Elevated defeatist performance beliefs predict state increases in negative symptoms in daily life in clinical high-risk for psychosis youth: implications for mobile health treatments.
European archives of psychiatry and clinical neuroscience, 276(6):2811-2820.
BACKGROUND: Negative symptoms are a strong predictor of conversion to a formal psychotic disorder in youth at clinical high-risk for developing psychosis (CHR). Identification of temporally precise mechanisms underlying increases in negative symptoms could enhance early intervention and specifically support the utility of mobile health treatments. Guided by Cognitive Behavioral models of psychopathology, we examine whether a core type of biased thinking-defeatist performance beliefs (DPB)-is a real-world mechanism of negative symptoms as well as a secondary symptom that is common in CHR youth: depressed mood.
METHODS: CHR youth (n = 119) and healthy control (CN; 59) subjects completed ecological momentary assessment surveys assessing DPB, negative symptoms, and depressed mood for six days.
RESULTS: CHR youth reported elevated DPB in daily life compared to CN. Greater DPB were associated with greater concurrent negative symptoms and depressed mood in daily life. Time-lagged analyses demonstrated that increased DPB at time t led to elevations in negative symptoms and depressed mood at t + 1 above and beyond the effects of the respective symptom at time t; DPB also varied across time of day, study day, day of the week, activity context, and social partners.
CONCLUSIONS: DPB may be a promising shared mechanism contributing to negative symptoms and depressed mood in CHR youth in their daily life. Findings also provide proof-of-concept support for the utility of mobile health treatments targeting DPB by identifying key moments where DPB fluctuate in CHR youths' everyday environments.
Additional Links: PMID-41212304
PubMed:
Citation:
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@article {pmid41212304,
year = {2026},
author = {Luther, L and Raugh, IM and Webber, LBG and Grant, PM and Beck, AT and Mittal, VA and Walker, E and Strauss, GP},
title = {Elevated defeatist performance beliefs predict state increases in negative symptoms in daily life in clinical high-risk for psychosis youth: implications for mobile health treatments.},
journal = {European archives of psychiatry and clinical neuroscience},
volume = {276},
number = {6},
pages = {2811-2820},
pmid = {41212304},
issn = {1433-8491},
support = {R21-MH119438/MH/NIMH NIH HHS/United States ; R01-MH116039/MH/NIMH NIH HHS/United States ; R21-MH119438/MH/NIMH NIH HHS/United States ; },
mesh = {Humans ; *Psychotic Disorders/physiopathology/therapy/psychology ; Adolescent ; Female ; Male ; Ecological Momentary Assessment ; *Depression/physiopathology/etiology ; Risk ; Digital Health ; },
abstract = {BACKGROUND: Negative symptoms are a strong predictor of conversion to a formal psychotic disorder in youth at clinical high-risk for developing psychosis (CHR). Identification of temporally precise mechanisms underlying increases in negative symptoms could enhance early intervention and specifically support the utility of mobile health treatments. Guided by Cognitive Behavioral models of psychopathology, we examine whether a core type of biased thinking-defeatist performance beliefs (DPB)-is a real-world mechanism of negative symptoms as well as a secondary symptom that is common in CHR youth: depressed mood.
METHODS: CHR youth (n = 119) and healthy control (CN; 59) subjects completed ecological momentary assessment surveys assessing DPB, negative symptoms, and depressed mood for six days.
RESULTS: CHR youth reported elevated DPB in daily life compared to CN. Greater DPB were associated with greater concurrent negative symptoms and depressed mood in daily life. Time-lagged analyses demonstrated that increased DPB at time t led to elevations in negative symptoms and depressed mood at t + 1 above and beyond the effects of the respective symptom at time t; DPB also varied across time of day, study day, day of the week, activity context, and social partners.
CONCLUSIONS: DPB may be a promising shared mechanism contributing to negative symptoms and depressed mood in CHR youth in their daily life. Findings also provide proof-of-concept support for the utility of mobile health treatments targeting DPB by identifying key moments where DPB fluctuate in CHR youths' everyday environments.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Humans
*Psychotic Disorders/physiopathology/therapy/psychology
Adolescent
Female
Male
Ecological Momentary Assessment
*Depression/physiopathology/etiology
Risk
Digital Health
RevDate: 2026-08-29
CmpDate: 2026-08-29
Nucleic acid and multi-omics approaches for understanding plant-microbiome interactions in grassland ecosystems.
International journal of biological macromolecules, 375:153356.
Grasslands are among the largest terrestrial biomes and play essential roles in livestock production, carbon sequestration and global food security. The productivity and resilience of these ecosystems are driven by complex molecular interactions between plants and their associated microbiomes. Although recent advances in nucleic acid research and multi-omics approaches have provided new insights into these interactions, the molecular mechanisms underpinning plant-microbiome interactions in these ecosystems remain insufficiently explored. This review synthesizes the latest progress in nucleic-acid and multi-omics approaches to better understand plant-microbiome interactions. It integrates nucleic acid-based technologies with multi-omics frameworks to explain plant-microbiome interactions across molecular, ecological, and management scales. By linking microbial community structure, functional genes, gene expression, metabolite profiles, ecosystem multifunctionality and sustainable grassland management, this review provides a broader framework for translating molecular insights into practical strategies for grassland resilience, productivity, and food security. Advances in amplicon sequencing, shotgun and long-read metagenomics, environmental DNA (eDNA) monitoring, plant and microbiome genome-wide association studies (GWAS) and transcriptomics have provided valuable insights into plant-microbiome interaction. This review highlights how these techniques enable functional and mechanistic understanding by linking microbial diversity with gene expression, nutrient cycling and plant performance. Additionally, long-read sequencing technologies provide genome-resolved analysis, improving the detection of structural and epigenetic variations, which are essential for understanding these interactions. These approaches reveal the role of beneficial microbes in enhancing grassland fertility, ultimately improving grassland productivity. Integrating these findings with metabolomics and phenomics offers a novel approach for predictive modeling in sustainable grassland management. The review concludes by emphasizing the need for standardized protocols, longitudinal field studies and experimental validation through synthetic communities and genome editing to harness plant-microbiome interactions for enhanced productivity and food security.
Additional Links: PMID-42398615
Publisher:
PubMed:
Citation:
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@article {pmid42398615,
year = {2026},
author = {Majeed, A and Javaid, MH and Mahreen, N and Hussain, M and Kang, Y and Hussain, K and Su, J},
title = {Nucleic acid and multi-omics approaches for understanding plant-microbiome interactions in grassland ecosystems.},
journal = {International journal of biological macromolecules},
volume = {375},
number = {},
pages = {153356},
doi = {10.1016/j.ijbiomac.2026.153356},
pmid = {42398615},
issn = {1879-0003},
mesh = {Multiomics ; *Grassland ; *Plants/microbiology/genetics/metabolism ; *Microbiota/genetics ; Metagenomics/methods ; *Nucleic Acids/genetics ; Ecosystem ; },
abstract = {Grasslands are among the largest terrestrial biomes and play essential roles in livestock production, carbon sequestration and global food security. The productivity and resilience of these ecosystems are driven by complex molecular interactions between plants and their associated microbiomes. Although recent advances in nucleic acid research and multi-omics approaches have provided new insights into these interactions, the molecular mechanisms underpinning plant-microbiome interactions in these ecosystems remain insufficiently explored. This review synthesizes the latest progress in nucleic-acid and multi-omics approaches to better understand plant-microbiome interactions. It integrates nucleic acid-based technologies with multi-omics frameworks to explain plant-microbiome interactions across molecular, ecological, and management scales. By linking microbial community structure, functional genes, gene expression, metabolite profiles, ecosystem multifunctionality and sustainable grassland management, this review provides a broader framework for translating molecular insights into practical strategies for grassland resilience, productivity, and food security. Advances in amplicon sequencing, shotgun and long-read metagenomics, environmental DNA (eDNA) monitoring, plant and microbiome genome-wide association studies (GWAS) and transcriptomics have provided valuable insights into plant-microbiome interaction. This review highlights how these techniques enable functional and mechanistic understanding by linking microbial diversity with gene expression, nutrient cycling and plant performance. Additionally, long-read sequencing technologies provide genome-resolved analysis, improving the detection of structural and epigenetic variations, which are essential for understanding these interactions. These approaches reveal the role of beneficial microbes in enhancing grassland fertility, ultimately improving grassland productivity. Integrating these findings with metabolomics and phenomics offers a novel approach for predictive modeling in sustainable grassland management. The review concludes by emphasizing the need for standardized protocols, longitudinal field studies and experimental validation through synthetic communities and genome editing to harness plant-microbiome interactions for enhanced productivity and food security.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Multiomics
*Grassland
*Plants/microbiology/genetics/metabolism
*Microbiota/genetics
Metagenomics/methods
*Nucleic Acids/genetics
Ecosystem
RevDate: 2025-07-21
CmpDate: 2025-03-07
Southern Islands Vascular Flora (SIVFLORA) dataset: A global plant database from Southern Ocean islands.
Scientific data, 12(1):397.
The Southern Islands Vascular Flora (SIVFLORA) dataset is a globally significant, open-access resource that compiles essential biodiversity data on vascular plants from islands across the Southern Ocean. The SIVFLORA dataset was generated through five steps: study area delimitation, compiling the dataset, validating and harmonizing taxonomy, structuring dataset attributes, and establishing file format and open access. Covering major taxonomic divisions, SIVFLORA offers a comprehensive overview of plant occurrences, comprising 14,589 records representing 886 species, 95 families, and 42 orders. This dataset documents that 58.62% of the taxa are native, 9.61% are endemic, and 31.77% are alien species. The Falkland/Malvinas Archipelago, the most species-rich, contrast sharply with less diverse islands like the South Orkney Archipelago. SIVFLORA serves as a taxonomically harmonized, interoperable resource for investigating plant diversity patterns, ecosystem responses to climate change in extreme environments, island biogeography, endemism, and the effects of anthropogenic pressures on Southern Ocean flora.
Additional Links: PMID-40055331
PubMed:
Citation:
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@article {pmid40055331,
year = {2025},
author = {Guerrero, PC and Contador, T and Díaz, A and Escobar, C and Orlando, J and Marín, C and Medina, P},
title = {Southern Islands Vascular Flora (SIVFLORA) dataset: A global plant database from Southern Ocean islands.},
journal = {Scientific data},
volume = {12},
number = {1},
pages = {397},
pmid = {40055331},
issn = {2052-4463},
mesh = {Islands ; *Biodiversity ; *Plants/classification ; Climate Change ; Ecosystem ; Oceans and Seas ; Databases, Factual ; },
abstract = {The Southern Islands Vascular Flora (SIVFLORA) dataset is a globally significant, open-access resource that compiles essential biodiversity data on vascular plants from islands across the Southern Ocean. The SIVFLORA dataset was generated through five steps: study area delimitation, compiling the dataset, validating and harmonizing taxonomy, structuring dataset attributes, and establishing file format and open access. Covering major taxonomic divisions, SIVFLORA offers a comprehensive overview of plant occurrences, comprising 14,589 records representing 886 species, 95 families, and 42 orders. This dataset documents that 58.62% of the taxa are native, 9.61% are endemic, and 31.77% are alien species. The Falkland/Malvinas Archipelago, the most species-rich, contrast sharply with less diverse islands like the South Orkney Archipelago. SIVFLORA serves as a taxonomically harmonized, interoperable resource for investigating plant diversity patterns, ecosystem responses to climate change in extreme environments, island biogeography, endemism, and the effects of anthropogenic pressures on Southern Ocean flora.},
}
MeSH Terms:
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hide MeSH Terms
Islands
*Biodiversity
*Plants/classification
Climate Change
Ecosystem
Oceans and Seas
Databases, Factual
RevDate: 2025-05-12
CmpDate: 2025-05-12
Identifying leptospirosis hotspots in Selangor: uncovering climatic connections using remote sensing and developing a predictive model.
PeerJ, 13:e18851.
BACKGROUND: Leptospirosis is an endemic disease in countries with tropical climates such as South America, Southern Asia, and Southeast Asia. There has been an increase in leptospirosis incidence in Malaysia from 1.45 to 25.94 cases per 100,000 population between 2005 and 2014. With increasing incidence in Selangor, Malaysia, and frequent climate change dynamics, a study on the disease hotspot areas and their association with the hydroclimatic factors could enhance disease surveillance and public health interventions.
METHODS: This ecological cross-sectional study utilised a geographic information system (GIS) and remote sensing techniques to analyse the spatiotemporal distribution of leptospirosis in Selangor from 2011 to 2019. Laboratory-confirmed leptospirosis cases (n = 1,045) were obtained from the Selangor State Health Department. Using ArcGIS Pro, spatial autocorrelation analysis (Moran's I) and Getis-Ord Gi* (hotspot analysis) was conducted to identify hotspots based on the monthly aggregated cases for each subdistrict. Satellite-derived rainfall and land surface temperature (LST) data were acquired from NASA's Giovanni EarthData website and processed into monthly averages. These data were integrated into ArcGIS Pro as thematic layers. Machine learning algorithms, including support vector machine (SVM), Random Forest (RF), and light gradient boosting machine (LGBM) were employed to develop predictive models for leptospirosis hotspot areas. Model performance was then evaluated using cross-validation and metrics such as accuracy, precision, sensitivity, and F1-score.
RESULTS: Moran's I analysis revealed a primarily random distribution of cases across Selangor, with only 20 out of 103 observed having a clustered distribution. Meanwhile, hotspot areas were mainly scattered in subdistricts throughout Selangor with clustering in the central region. Machine learning analysis revealed that the LGBM algorithm had the best performance scores compared to having a cross-validation score of 0.61, a precision score of 0.16, and an F1-score of 0.23. The feature importance score indicated river water level and rainfall contributes most to the model.
CONCLUSIONS: This GIS-based study identified a primarily sporadic occurrence of leptospirosis in Selangor with minimal spatial clustering. The LGBM algorithm effectively predicted leptospirosis hotspots based on the analysed hydroclimatic factors. The integration of GIS and machine learning offers a promising framework for disease surveillance, facilitating targeted public health interventions in areas at high risk for leptospirosis.
Additional Links: PMID-40061226
PubMed:
Citation:
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@article {pmid40061226,
year = {2025},
author = {Ab Kadir, MA and Abdul Manaf, R and Mokhtar, SA and Ismail, LI},
title = {Identifying leptospirosis hotspots in Selangor: uncovering climatic connections using remote sensing and developing a predictive model.},
journal = {PeerJ},
volume = {13},
number = {},
pages = {e18851},
pmid = {40061226},
issn = {2167-8359},
mesh = {*Leptospirosis/epidemiology ; Humans ; Malaysia/epidemiology ; Cross-Sectional Studies ; Geographic Information Systems ; *Remote Sensing Technology ; Incidence ; Climate Change ; Climate ; },
abstract = {BACKGROUND: Leptospirosis is an endemic disease in countries with tropical climates such as South America, Southern Asia, and Southeast Asia. There has been an increase in leptospirosis incidence in Malaysia from 1.45 to 25.94 cases per 100,000 population between 2005 and 2014. With increasing incidence in Selangor, Malaysia, and frequent climate change dynamics, a study on the disease hotspot areas and their association with the hydroclimatic factors could enhance disease surveillance and public health interventions.
METHODS: This ecological cross-sectional study utilised a geographic information system (GIS) and remote sensing techniques to analyse the spatiotemporal distribution of leptospirosis in Selangor from 2011 to 2019. Laboratory-confirmed leptospirosis cases (n = 1,045) were obtained from the Selangor State Health Department. Using ArcGIS Pro, spatial autocorrelation analysis (Moran's I) and Getis-Ord Gi* (hotspot analysis) was conducted to identify hotspots based on the monthly aggregated cases for each subdistrict. Satellite-derived rainfall and land surface temperature (LST) data were acquired from NASA's Giovanni EarthData website and processed into monthly averages. These data were integrated into ArcGIS Pro as thematic layers. Machine learning algorithms, including support vector machine (SVM), Random Forest (RF), and light gradient boosting machine (LGBM) were employed to develop predictive models for leptospirosis hotspot areas. Model performance was then evaluated using cross-validation and metrics such as accuracy, precision, sensitivity, and F1-score.
RESULTS: Moran's I analysis revealed a primarily random distribution of cases across Selangor, with only 20 out of 103 observed having a clustered distribution. Meanwhile, hotspot areas were mainly scattered in subdistricts throughout Selangor with clustering in the central region. Machine learning analysis revealed that the LGBM algorithm had the best performance scores compared to having a cross-validation score of 0.61, a precision score of 0.16, and an F1-score of 0.23. The feature importance score indicated river water level and rainfall contributes most to the model.
CONCLUSIONS: This GIS-based study identified a primarily sporadic occurrence of leptospirosis in Selangor with minimal spatial clustering. The LGBM algorithm effectively predicted leptospirosis hotspots based on the analysed hydroclimatic factors. The integration of GIS and machine learning offers a promising framework for disease surveillance, facilitating targeted public health interventions in areas at high risk for leptospirosis.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Leptospirosis/epidemiology
Humans
Malaysia/epidemiology
Cross-Sectional Studies
Geographic Information Systems
*Remote Sensing Technology
Incidence
Climate Change
Climate
RevDate: 2025-05-12
CmpDate: 2025-05-12
Recombination Analysis of Geminiviruses Using Recombination Detection Program (RDP).
Methods in molecular biology (Clifton, N.J.), 2912:125-143.
Geminiviruses are recombination-prone, and characterizing this evolutionary process within their genomes is a frequent goal of researchers. RDP is a stand-alone Windows program combining many algorithms that detect and characterize recombination. It has been widely used by the geminivirus community (and beyond). Here we describe the use of RDP4 and RDP5 for analysis of geminiviral nucleotide sequences including: (i) obtaining a reasonable dataset for analysis, (ii) making a credible multiple sequence alignment and (iii) analyzing an alignment with RDP on that alignment. RDP to both characterize recombination events and to produce statistically recombination-free datasets for other molecular evolution analyses.
Additional Links: PMID-40064777
PubMed:
Citation:
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@article {pmid40064777,
year = {2025},
author = {Crespo-Bellido, A and Martin, DP and Duffy, S},
title = {Recombination Analysis of Geminiviruses Using Recombination Detection Program (RDP).},
journal = {Methods in molecular biology (Clifton, N.J.)},
volume = {2912},
number = {},
pages = {125-143},
pmid = {40064777},
issn = {1940-6029},
mesh = {*Geminiviridae/genetics ; *Recombination, Genetic ; *Software ; Genome, Viral ; Algorithms ; Sequence Alignment ; *Computational Biology/methods ; Evolution, Molecular ; },
abstract = {Geminiviruses are recombination-prone, and characterizing this evolutionary process within their genomes is a frequent goal of researchers. RDP is a stand-alone Windows program combining many algorithms that detect and characterize recombination. It has been widely used by the geminivirus community (and beyond). Here we describe the use of RDP4 and RDP5 for analysis of geminiviral nucleotide sequences including: (i) obtaining a reasonable dataset for analysis, (ii) making a credible multiple sequence alignment and (iii) analyzing an alignment with RDP on that alignment. RDP to both characterize recombination events and to produce statistically recombination-free datasets for other molecular evolution analyses.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Geminiviridae/genetics
*Recombination, Genetic
*Software
Genome, Viral
Algorithms
Sequence Alignment
*Computational Biology/methods
Evolution, Molecular
RevDate: 2025-05-12
CmpDate: 2025-05-12
BioArchLinux: community-driven fresh reproducible software repository for life sciences.
Bioinformatics (Oxford, England), 41(3):.
MOTIVATION: The BioArchLinux project was initiated to address challenges in bioinformatics software reproducibility and freshness. Relying on Arch Linux's user-driven ecosystem, we aim to create a comprehensive and continuously updated repository for life sciences research.
RESULTS: BioArchLinux provides a PKGBUILD-based system for seamless software packaging and maintenance, enabling users to access the latest bioinformatics tools across multiple programming languages. The repository includes Docker images, Windows Subsystem for Linux (WSL) support, and Junest for nonroot environments, enhancing accessibility across platforms. Although being developed and maintained by a small core team, BioArchLinux is a fast-growing bioinformatics repository that offers a participatory and community-driven environment.
The repository, documentation, and tools are freely available at https://bioarchlinux.org and https://github.com/BioArchLinux. Users and developers are encouraged to contribute and expand this open-source initiative.
Additional Links: PMID-40067093
PubMed:
Citation:
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@article {pmid40067093,
year = {2025},
author = {Zhang, G and Ristola, P and Su, H and Kumar, B and Zhang, B and Hu, Y and Elliot, MG and Drobot, V and Zhu, J and Staal, J and Larralde, M and Wang, S and Yi, Y and Yu, H},
title = {BioArchLinux: community-driven fresh reproducible software repository for life sciences.},
journal = {Bioinformatics (Oxford, England)},
volume = {41},
number = {3},
pages = {},
pmid = {40067093},
issn = {1367-4811},
mesh = {*Software ; *Computational Biology/methods ; *Biological Science Disciplines ; Programming Languages ; Reproducibility of Results ; },
abstract = {MOTIVATION: The BioArchLinux project was initiated to address challenges in bioinformatics software reproducibility and freshness. Relying on Arch Linux's user-driven ecosystem, we aim to create a comprehensive and continuously updated repository for life sciences research.
RESULTS: BioArchLinux provides a PKGBUILD-based system for seamless software packaging and maintenance, enabling users to access the latest bioinformatics tools across multiple programming languages. The repository includes Docker images, Windows Subsystem for Linux (WSL) support, and Junest for nonroot environments, enhancing accessibility across platforms. Although being developed and maintained by a small core team, BioArchLinux is a fast-growing bioinformatics repository that offers a participatory and community-driven environment.
The repository, documentation, and tools are freely available at https://bioarchlinux.org and https://github.com/BioArchLinux. Users and developers are encouraged to contribute and expand this open-source initiative.},
}
MeSH Terms:
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*Software
*Computational Biology/methods
*Biological Science Disciplines
Programming Languages
Reproducibility of Results
RevDate: 2025-05-12
CmpDate: 2025-05-12
UnifiedGreatMod: a new holistic modelling paradigm for studying biological systems on a complete and harmonious scale.
Bioinformatics (Oxford, England), 41(3):.
MOTIVATION: Computational models are crucial for addressing critical questions about systems evolution and deciphering system connections. The pivotal feature of making this concept recognizable from the biological and clinical community is the possibility of quickly inspecting the whole system, bearing in mind the different granularity levels of its components. This holistic view of system behaviour expands the evolution study by identifying the heterogeneous behaviours applicable, e.g. to the cancer evolution study.
RESULTS: To address this aspect, we propose a new modelling paradigm, UnifiedGreatMod, which allows modellers to integrate fine-grained and coarse-grained biological information into a unique model. It enables functional studies by combining the analysis of the system's multi-level stable states with its fluctuating conditions. This approach helps to investigate the functional relationships and dependencies among biological entities. This is achieved, thanks to the hybridization of two analysis approaches that capture a system's different granularity levels. The proposed paradigm was then implemented into the open-source, general modelling framework GreatMod, in which a graphical meta-formalism is exploited to simplify the model creation phase and R languages to define user-defined analysis workflows. The proposal's effectiveness was demonstrated by mechanistically simulating the metabolic output of Escherichia coli under environmental nutrient perturbations and integrating a gene expression dataset. Additionally, the UnifiedGreatMod was used to examine the responses of luminal epithelial cells to Clostridium difficile infection.
GreatMod https://qbioturin.github.io/epimod/, epimod_FBAfunctions https://github.com/qBioTurin/epimod_FBAfunctions, first case study E. coli https://github.com/qBioTurin/Ec_coli_modelling, second case study C. difficile https://github.com/qBioTurin/EpiCell_CDifficile.
Additional Links: PMID-40073274
PubMed:
Citation:
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@article {pmid40073274,
year = {2025},
author = {Aucello, R and Pernice, S and Tortarolo, D and Calogero, RA and Herrera-Rincon, C and Ronchi, G and Geuna, S and Cordero, F and Lió, P and Beccuti, M},
title = {UnifiedGreatMod: a new holistic modelling paradigm for studying biological systems on a complete and harmonious scale.},
journal = {Bioinformatics (Oxford, England)},
volume = {41},
number = {3},
pages = {},
pmid = {40073274},
issn = {1367-4811},
support = {//Ministero dell'Univerisita' e della Ricerca/ ; },
mesh = {*Models, Biological ; *Software ; *Systems Biology/methods ; Escherichia coli/metabolism/genetics ; Computer Simulation ; Clostridioides difficile ; *Computational Biology/methods ; },
abstract = {MOTIVATION: Computational models are crucial for addressing critical questions about systems evolution and deciphering system connections. The pivotal feature of making this concept recognizable from the biological and clinical community is the possibility of quickly inspecting the whole system, bearing in mind the different granularity levels of its components. This holistic view of system behaviour expands the evolution study by identifying the heterogeneous behaviours applicable, e.g. to the cancer evolution study.
RESULTS: To address this aspect, we propose a new modelling paradigm, UnifiedGreatMod, which allows modellers to integrate fine-grained and coarse-grained biological information into a unique model. It enables functional studies by combining the analysis of the system's multi-level stable states with its fluctuating conditions. This approach helps to investigate the functional relationships and dependencies among biological entities. This is achieved, thanks to the hybridization of two analysis approaches that capture a system's different granularity levels. The proposed paradigm was then implemented into the open-source, general modelling framework GreatMod, in which a graphical meta-formalism is exploited to simplify the model creation phase and R languages to define user-defined analysis workflows. The proposal's effectiveness was demonstrated by mechanistically simulating the metabolic output of Escherichia coli under environmental nutrient perturbations and integrating a gene expression dataset. Additionally, the UnifiedGreatMod was used to examine the responses of luminal epithelial cells to Clostridium difficile infection.
GreatMod https://qbioturin.github.io/epimod/, epimod_FBAfunctions https://github.com/qBioTurin/epimod_FBAfunctions, first case study E. coli https://github.com/qBioTurin/Ec_coli_modelling, second case study C. difficile https://github.com/qBioTurin/EpiCell_CDifficile.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Models, Biological
*Software
*Systems Biology/methods
Escherichia coli/metabolism/genetics
Computer Simulation
Clostridioides difficile
*Computational Biology/methods
RevDate: 2025-05-27
CmpDate: 2025-03-13
CaecilianTraits, an individual level trait database of Caecilians worldwide.
Scientific data, 12(1):428.
Functional traits differ among species, which determine the ecological niche a species occupies and its ability to adapt to environment. However, differences in traits also exist at intraspecific level. Such variations shape differences in individual survival capabilities. Investigating intraspecific differences of functional traits is important for ecology, evolutionary biology and biodiversity conservation. Individual trait-based approaches have been applied in plant ecology. But for animals, most databases only provide data at the species level. In this study, we presented a global database of morphological traits for caecilians (Amphibia, Gymnophiona) at both species and individual level. Caecilians are a unique group of amphibians characterized by their secretive habits, which have limited our understanding of this taxon. We compiled the most comprehensive database covering 218 out of 222 known species, with 215 of them have individual level data. This database will facilitate research in the ecology, evolutionary biology, conservation biology, and taxonomy of caecilians. Furthermore, this dataset can be utilized to test ecological and evolutionary hypotheses at the individual level.
Additional Links: PMID-40074756
PubMed:
Citation:
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@article {pmid40074756,
year = {2025},
author = {Wei, P and Song, Y and Tian, R and Wang, Y and Chen, J and Yuan, Z and Zhou, W},
title = {CaecilianTraits, an individual level trait database of Caecilians worldwide.},
journal = {Scientific data},
volume = {12},
number = {1},
pages = {428},
pmid = {40074756},
issn = {2052-4463},
support = {32170445//National Natural Science Foundation of China (National Science Foundation of China)/ ; },
mesh = {Animals ; *Amphibians/anatomy & histology/classification ; *Databases, Factual ; Biological Evolution ; Biodiversity ; },
abstract = {Functional traits differ among species, which determine the ecological niche a species occupies and its ability to adapt to environment. However, differences in traits also exist at intraspecific level. Such variations shape differences in individual survival capabilities. Investigating intraspecific differences of functional traits is important for ecology, evolutionary biology and biodiversity conservation. Individual trait-based approaches have been applied in plant ecology. But for animals, most databases only provide data at the species level. In this study, we presented a global database of morphological traits for caecilians (Amphibia, Gymnophiona) at both species and individual level. Caecilians are a unique group of amphibians characterized by their secretive habits, which have limited our understanding of this taxon. We compiled the most comprehensive database covering 218 out of 222 known species, with 215 of them have individual level data. This database will facilitate research in the ecology, evolutionary biology, conservation biology, and taxonomy of caecilians. Furthermore, this dataset can be utilized to test ecological and evolutionary hypotheses at the individual level.},
}
MeSH Terms:
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Animals
*Amphibians/anatomy & histology/classification
*Databases, Factual
Biological Evolution
Biodiversity
RevDate: 2025-05-12
CmpDate: 2025-05-12
Multi-omics analysis revealed the novel role of NQO1 in microenvironment, prognosis and immunotherapy of hepatocellular carcinoma.
Scientific reports, 15(1):8591.
NAD(P)H dehydrogenase quinone 1 (NQO1) is overexpressed in various cancers and is strongly associated with an immunosuppressive microenvironment and poor prognosis. In this study, we explored the role of NQO1 in the microenvironment, prognosis and immunotherapy of Hepatocellular carcinoma (HCC) using multi-omics analysis and machine learning. The results revealed that NQO1 was significantly overexpressed in HCC cells. NQO1[+]HCC cells were correlated with poor prognosis and facilitated tumor-associated macrophages (TAMs) polarization to M2 macrophages. We identified core NQO1-related genes (NRGs) and developed the NRGs-related risk-scores in hepatocellular carcinoma (NRSHC). The comprehensive nomogram integrating NRSHC, age, and pathological tumor-node-metastasis (pTNM) Stage achieved an area under the curve (AUC) above 0.7, demonstrating its accuracy in predicting survival outcomes and immunotherapy responses of HCC patients. High-risk patients exhibited worse prognoses but greater sensitivity to immunotherapy. Additionally, a web-based prediction tool was designed to enhance clinical utility. In conclusion, NQO1 may play a critical role in M2 polarization and accelerates HCC progression. The NRSHC model and accompanying tools offer valuable insights for personalized HCC treatment.
Additional Links: PMID-40074806
PubMed:
Citation:
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@article {pmid40074806,
year = {2025},
author = {Tang, Y and Hu, H and Chen, S and Hao, B and Xu, X and Zhu, H and Zhan, W and Zhang, T and Hu, H and Chen, G},
title = {Multi-omics analysis revealed the novel role of NQO1 in microenvironment, prognosis and immunotherapy of hepatocellular carcinoma.},
journal = {Scientific reports},
volume = {15},
number = {1},
pages = {8591},
pmid = {40074806},
issn = {2045-2322},
support = {24B0413//the Scientific Research Project of the Hunan Provincial Department of Education/ ; 2024JJ7455//Natural Science Foundation of Hunan Province/ ; 20224310NHYCG04//University of South China Clinical Research 4310 Program/ ; 20224310NHYCG01//University of South China Clinical Research 4310 Program/ ; 82473965//National Natural Science Foundation of China/ ; 2023JJ50156//the Natural Science Foundation of Hunan Province/ ; 202250045223//Science and technology innovation Program of Hengyang City/ ; ZYYD2024CG17//Central Government Guided Local Science and Technology Development Fund Project in Xinjiang Uygur Autonomous Region/ ; 2024WK4008//Hunan Province Innovation Ecological Construction Plan Science and Technology Assistance Project in Xinjiang Uygur Autonomous Region/ ; SYTG-Y202429//Health Technology Promotion Project in Xinjiang Uygur Autonomous Region/ ; },
mesh = {Humans ; *Carcinoma, Hepatocellular/therapy/genetics/pathology/mortality/immunology/metabolism ; *NAD(P)H Dehydrogenase (Quinone)/genetics/metabolism ; *Liver Neoplasms/therapy/genetics/pathology/mortality/immunology/metabolism ; *Tumor Microenvironment/genetics ; *Immunotherapy/methods ; Prognosis ; Male ; Gene Expression Regulation, Neoplastic ; Female ; Tumor-Associated Macrophages/immunology/metabolism ; Middle Aged ; Cell Line, Tumor ; Nomograms ; Multiomics ; },
abstract = {NAD(P)H dehydrogenase quinone 1 (NQO1) is overexpressed in various cancers and is strongly associated with an immunosuppressive microenvironment and poor prognosis. In this study, we explored the role of NQO1 in the microenvironment, prognosis and immunotherapy of Hepatocellular carcinoma (HCC) using multi-omics analysis and machine learning. The results revealed that NQO1 was significantly overexpressed in HCC cells. NQO1[+]HCC cells were correlated with poor prognosis and facilitated tumor-associated macrophages (TAMs) polarization to M2 macrophages. We identified core NQO1-related genes (NRGs) and developed the NRGs-related risk-scores in hepatocellular carcinoma (NRSHC). The comprehensive nomogram integrating NRSHC, age, and pathological tumor-node-metastasis (pTNM) Stage achieved an area under the curve (AUC) above 0.7, demonstrating its accuracy in predicting survival outcomes and immunotherapy responses of HCC patients. High-risk patients exhibited worse prognoses but greater sensitivity to immunotherapy. Additionally, a web-based prediction tool was designed to enhance clinical utility. In conclusion, NQO1 may play a critical role in M2 polarization and accelerates HCC progression. The NRSHC model and accompanying tools offer valuable insights for personalized HCC treatment.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Humans
*Carcinoma, Hepatocellular/therapy/genetics/pathology/mortality/immunology/metabolism
*NAD(P)H Dehydrogenase (Quinone)/genetics/metabolism
*Liver Neoplasms/therapy/genetics/pathology/mortality/immunology/metabolism
*Tumor Microenvironment/genetics
*Immunotherapy/methods
Prognosis
Male
Gene Expression Regulation, Neoplastic
Female
Tumor-Associated Macrophages/immunology/metabolism
Middle Aged
Cell Line, Tumor
Nomograms
Multiomics
RevDate: 2025-07-05
CmpDate: 2025-07-03
Short Read Lengths Recover Ecological Patterns in 16S rRNA Gene Amplicon Data.
Molecular ecology resources, 25(6):e14102.
16S rRNA gene metabarcoding, the study of amplicon sequences of the 16S rRNA gene from mixed environmental samples, is an increasingly popular and accessible method for assessing bacterial communities across a wide range of environments. As metabarcoding sequence data archives continue to grow, data reuse will likely become an important source of novel insights into the ecology of microbes. While recent work has demonstrated the benefits of longer read lengths for the study of microbial communities from 16S rRNA gene segments, no studies have explored the use of shorter (< 200 bp) read lengths in the context of data reuse. Nevertheless, this information is essential to improve the reuse and comparability of metabarcoding data across existing datasets. This study reanalyzed nine 16S rRNA datasets targeting aquatic, animal-associated and soil microbiomes, and evaluated how processing the sequence data across a range of read lengths affected the resulting taxonomic assignments, biodiversity metrics and differential (i.e., before-after treatment) analyses. Short read lengths successfully recovered ecological patterns and allowed for the use of more sequences. Limited increases in resolution were observed beyond 150 bp reads across environments. Furthermore, abundance-weighted diversity metrics (e.g., Inverse Simpson index, Morisita-Horn dissimilarities or weighted Unifrac distances) were more robust to variation in read lengths. Read lengths alone contributed to consistent increases in the total number of ASVs detected, highlighting the need to consider metabarcoding-derived diversity estimates within the context of the bioinformatics parameters selected. This study provides evidence-based guidelines for the processing of short reads.
Additional Links: PMID-40079420
PubMed:
Citation:
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@article {pmid40079420,
year = {2025},
author = {Jurburg, SD},
title = {Short Read Lengths Recover Ecological Patterns in 16S rRNA Gene Amplicon Data.},
journal = {Molecular ecology resources},
volume = {25},
number = {6},
pages = {e14102},
pmid = {40079420},
issn = {1755-0998},
mesh = {*RNA, Ribosomal, 16S/genetics ; *Bacteria/genetics/classification ; *Metagenomics/methods ; Microbiota ; Animals ; *DNA Barcoding, Taxonomic/methods ; Biodiversity ; Computational Biology/methods ; Sequence Analysis, DNA/methods ; },
abstract = {16S rRNA gene metabarcoding, the study of amplicon sequences of the 16S rRNA gene from mixed environmental samples, is an increasingly popular and accessible method for assessing bacterial communities across a wide range of environments. As metabarcoding sequence data archives continue to grow, data reuse will likely become an important source of novel insights into the ecology of microbes. While recent work has demonstrated the benefits of longer read lengths for the study of microbial communities from 16S rRNA gene segments, no studies have explored the use of shorter (< 200 bp) read lengths in the context of data reuse. Nevertheless, this information is essential to improve the reuse and comparability of metabarcoding data across existing datasets. This study reanalyzed nine 16S rRNA datasets targeting aquatic, animal-associated and soil microbiomes, and evaluated how processing the sequence data across a range of read lengths affected the resulting taxonomic assignments, biodiversity metrics and differential (i.e., before-after treatment) analyses. Short read lengths successfully recovered ecological patterns and allowed for the use of more sequences. Limited increases in resolution were observed beyond 150 bp reads across environments. Furthermore, abundance-weighted diversity metrics (e.g., Inverse Simpson index, Morisita-Horn dissimilarities or weighted Unifrac distances) were more robust to variation in read lengths. Read lengths alone contributed to consistent increases in the total number of ASVs detected, highlighting the need to consider metabarcoding-derived diversity estimates within the context of the bioinformatics parameters selected. This study provides evidence-based guidelines for the processing of short reads.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*RNA, Ribosomal, 16S/genetics
*Bacteria/genetics/classification
*Metagenomics/methods
Microbiota
Animals
*DNA Barcoding, Taxonomic/methods
Biodiversity
Computational Biology/methods
Sequence Analysis, DNA/methods
RevDate: 2025-05-13
CmpDate: 2025-05-13
Multiomics analysis revealed the effects of polystyrene nanoplastics at different environmentally relevant concentrations on intestinal homeostasis.
Environmental pollution (Barking, Essex : 1987), 372:126050.
Nanoplastics pollution is a global issue, with the digestive tract being one of the first affected organs, requiring further research on its impact on intestinal health. This study involved orally exposing mice to polystyrene nanoplastics (PS-NPs) at doses of 0.1, 0.5, or 2.5 mg/d for 42 days. The effects on intestinal health were thoroughly assessed via microbiomics, metabolomics, transcriptomics, and molecular biology. Our study demonstrated that the administration of all three doses of PS-NPs resulted in increased colonic permeability, heightened colonic and peripheral inflammation, reduced levels of antimicrobial peptides, and shortened colonic length. These effects may be attributed to a reduction in the abundance of probiotic bacteria, such as Clostridia_UCG-014, Roseburia, and Akkermansia, alongside an increase in the abundance of the pathogenic bacterium Desulfovibrionaceae induced by PS-NPs. Furthermore, we underscored the crucial role of histidine metabolism in PS-NPs-induced colonic injury, characterized by a significant reduction of L-histidine, which is closely related to microbial ecological dysregulation. Corresponding to microbiota deterioration and metabolic dysregulation, transcriptome analysis revealed that PS-NPs may disrupt colonic immune homeostasis by activating the TLR4/MyD88/NF-κB/NLRP3 signaling pathway. In conclusion, this study provided novel insights into the mechanisms by which PS-NPs disrupt intestinal homeostasis through integrated multiomics analysis, revealing critical molecular pathway and providing a scientific basis for future risk assessment of nanoplastics exposure.
Additional Links: PMID-40086783
Publisher:
PubMed:
Citation:
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@article {pmid40086783,
year = {2025},
author = {Yang, JZ and Li, JH and Liu, JL and Zhou, AD and Wang, H and Xie, XL and Zhang, KK and Wang, Q},
title = {Multiomics analysis revealed the effects of polystyrene nanoplastics at different environmentally relevant concentrations on intestinal homeostasis.},
journal = {Environmental pollution (Barking, Essex : 1987)},
volume = {372},
number = {},
pages = {126050},
doi = {10.1016/j.envpol.2025.126050},
pmid = {40086783},
issn = {1873-6424},
mesh = {Animals ; Mice ; *Polystyrenes/toxicity ; Homeostasis/drug effects ; *Microplastics/toxicity ; Gastrointestinal Microbiome/drug effects ; *Intestines/drug effects ; Male ; Metabolomics ; Multiomics ; },
abstract = {Nanoplastics pollution is a global issue, with the digestive tract being one of the first affected organs, requiring further research on its impact on intestinal health. This study involved orally exposing mice to polystyrene nanoplastics (PS-NPs) at doses of 0.1, 0.5, or 2.5 mg/d for 42 days. The effects on intestinal health were thoroughly assessed via microbiomics, metabolomics, transcriptomics, and molecular biology. Our study demonstrated that the administration of all three doses of PS-NPs resulted in increased colonic permeability, heightened colonic and peripheral inflammation, reduced levels of antimicrobial peptides, and shortened colonic length. These effects may be attributed to a reduction in the abundance of probiotic bacteria, such as Clostridia_UCG-014, Roseburia, and Akkermansia, alongside an increase in the abundance of the pathogenic bacterium Desulfovibrionaceae induced by PS-NPs. Furthermore, we underscored the crucial role of histidine metabolism in PS-NPs-induced colonic injury, characterized by a significant reduction of L-histidine, which is closely related to microbial ecological dysregulation. Corresponding to microbiota deterioration and metabolic dysregulation, transcriptome analysis revealed that PS-NPs may disrupt colonic immune homeostasis by activating the TLR4/MyD88/NF-κB/NLRP3 signaling pathway. In conclusion, this study provided novel insights into the mechanisms by which PS-NPs disrupt intestinal homeostasis through integrated multiomics analysis, revealing critical molecular pathway and providing a scientific basis for future risk assessment of nanoplastics exposure.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Animals
Mice
*Polystyrenes/toxicity
Homeostasis/drug effects
*Microplastics/toxicity
Gastrointestinal Microbiome/drug effects
*Intestines/drug effects
Male
Metabolomics
Multiomics
RevDate: 2026-07-28
CmpDate: 2025-07-03
ParAquaSeq, a Database of Ecologically Annotated rRNA Sequences Covering Zoosporic Parasites Infecting Aquatic Primary Producers in Natural and Industrial Systems.
Molecular ecology resources, 25(6):e14099.
Amplicon sequencing tools such as metabarcoding are commonly used for thorough characterisation of microbial diversity in natural samples. They mostly rely on the amplification of conserved universal markers, mainly ribosomal genes, allowing the taxonomic assignment of barcodes. However, linking taxonomic classification with functional traits is not straightforward and requires knowledge of each taxonomic group to confidently assign taxa to a given functional trait. Zoosporic parasites are highly diverse and yet understudied, with many undescribed species and host associations. However, they can have important impacts on host populations in natural ecosystems (e.g., controlling harmful algal blooms), as well as on industrial-scale algae production, e.g. aquaculture, causing their collapse or economic losses. Here, we present ParAquaSeq, a curated database of available molecular ribosomal sequences belonging to zoosporic parasites infecting aquatic vascular plants, macroalgae and photosynthetic microorganisms, i.e. microalgae and cyanobacteria. These sequences are aligned with ancillary data and other information currently available, including details on their hosts, occurrence, culture availability and associated bibliography. The database includes 1131 curated sequences from marine, freshwater and industrial or artificial environments, and belonging to 13 different taxonomic groups, including Chytridiomycota, Oomycota, Phytomyxea, and Syndiniophyceae. The curated database will allow a comprehensive analysis of zoosporic parasites in molecular datasets to answer questions related to their occurrence and distribution in natural communities. Especially through meta-analysis, the database serves as a valuable tool for developing effective mitigation and sustainable management strategies in the algae biomass industry, but it will also help to identify knowledge gaps for future research.
Additional Links: PMID-40087979
PubMed:
Citation:
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@article {pmid40087979,
year = {2025},
author = {Van den Wyngaert, S and Cerbin, S and Garzoli, L and Grossart, HP and Gsell, AS and Kraberg, A and Lepère, C and Neuhauser, S and Stupar, M and Tarallo, A and Cunliffe, M and Gachon, C and Gavrilović, A and Masigol, H and Rasconi, S and Selmeczy, GB and Schmeller, DS and Scholz, B and Timoneda, N and Trbojević, I and Wilk-Woźniak, E and Reñé, A},
title = {ParAquaSeq, a Database of Ecologically Annotated rRNA Sequences Covering Zoosporic Parasites Infecting Aquatic Primary Producers in Natural and Industrial Systems.},
journal = {Molecular ecology resources},
volume = {25},
number = {6},
pages = {e14099},
pmid = {40087979},
issn = {1755-0998},
support = {PID2020-112978GB-I00//Ministerio de Ciencia, Innovación y Universidades/ ; CA20125//European Cooperation in Science and Technology/ ; 451-03-66/2024-03/200178//Ministarstvo Prosvete, Nauke i Tehnološkog Razvoja/ ; 239548-051//RANNIS Icelandic Research Fund/ ; 340659/WT_/Wellcome Trust/United Kingdom ; 346387//Research Council of Finland/ ; 101086521//European Commission/ ; IR0000005//European Commission/ ; NKFIH KKP 144068//National Laboratory for Water Science and Water Security/ ; RRF-2.3.1-21-2022-00008//National Laboratory for Water Science and Water Security/ ; Y0801-B16//Austrian Science Fund/ ; //AXA Research Fund/ ; ANR-21-BIRE-0002-01//Agence Nationale de la Recherche/ ; 101052342//Biodiversa+/ ; CIR-01_00028//Italian Ministry of University and Research/ ; GR1540/33-1//Deutsche Forschungsgemeinschaft/ ; GR1540/47-1//Deutsche Forschungsgemeinschaft/ ; GR1540/48-1//Deutsche Forschungsgemeinschaft/ ; GR1540/51-1//Deutsche Forschungsgemeinschaft/ ; CEX2019-000928-S//AEI/ ; },
mesh = {*Aquatic Organisms/parasitology ; *RNA, Ribosomal/genetics ; Microalgae/parasitology ; *Parasites/genetics/classification ; *Databases, Genetic ; },
abstract = {Amplicon sequencing tools such as metabarcoding are commonly used for thorough characterisation of microbial diversity in natural samples. They mostly rely on the amplification of conserved universal markers, mainly ribosomal genes, allowing the taxonomic assignment of barcodes. However, linking taxonomic classification with functional traits is not straightforward and requires knowledge of each taxonomic group to confidently assign taxa to a given functional trait. Zoosporic parasites are highly diverse and yet understudied, with many undescribed species and host associations. However, they can have important impacts on host populations in natural ecosystems (e.g., controlling harmful algal blooms), as well as on industrial-scale algae production, e.g. aquaculture, causing their collapse or economic losses. Here, we present ParAquaSeq, a curated database of available molecular ribosomal sequences belonging to zoosporic parasites infecting aquatic vascular plants, macroalgae and photosynthetic microorganisms, i.e. microalgae and cyanobacteria. These sequences are aligned with ancillary data and other information currently available, including details on their hosts, occurrence, culture availability and associated bibliography. The database includes 1131 curated sequences from marine, freshwater and industrial or artificial environments, and belonging to 13 different taxonomic groups, including Chytridiomycota, Oomycota, Phytomyxea, and Syndiniophyceae. The curated database will allow a comprehensive analysis of zoosporic parasites in molecular datasets to answer questions related to their occurrence and distribution in natural communities. Especially through meta-analysis, the database serves as a valuable tool for developing effective mitigation and sustainable management strategies in the algae biomass industry, but it will also help to identify knowledge gaps for future research.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Aquatic Organisms/parasitology
*RNA, Ribosomal/genetics
Microalgae/parasitology
*Parasites/genetics/classification
*Databases, Genetic
RevDate: 2025-05-16
CmpDate: 2025-05-09
Trends in stroke mortality in Latin America and the Caribbean from 1997 to 2020 and predictions to 2035: An analysis of gender, and geographical disparities.
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association, 34(6):108286.
BACKGROUND: Stroke is a leading cause of death and disability globally, with significant public health implications. In Latin America, while mortality rates have declined, the number of stroke cases has increased due to prevalent risk factors like high blood pressure and obesity. Unlike Europe, recent trends in stroke mortality in this region remain underreported.
OBJECTIVE: This study evaluates stroke mortality rates in Latin America Latin American and Caribbean (LAC) countries from 1997 to 2020 and predictions to 2035.
METHODS: This ecological observational study utilized mortality data from the World Health Organization database. Trends were analyzed using Joinpoint regression to evaluate the annual percent change (APC) by sex and country. Predicted mortality rates through 2035 were calculated using the Nordpred package in R. Changes in stroke mortality were assessed by disentangling the effects of population growth, aging, and risk factor modifications, based on age-specific rates and projections. Results were presented as absolute case numbers and relative percentages.
RESULTS: From 1997 to 2020, twelve countries presented significant reductions in stroke mortality rates for men in LAC, the main ones being Chile (-4.2 %), El Salvador (-4.2 %), and Puerto Rico (-4.0 %). Thirteen countries reported a reduction in their mortality for women, mainly in Puerto Rico (-4.3 %), Chile (-3.7 %), Argentina, El Salvador, and Uruguay (-3.5 %). By 2035, an increase in deaths among men and women is expected, mainly due to the increase in population structure and size. However, a decrease in the mortality rate will be reported, mainly due to the reduction of risk factors.
CONCLUSION: Our final findings show a reduction in stroke mortality trends in LAC countries between 1997 and 2020, due to creating public awareness about vascular risk factors by authorities and the implementation of effective health policies. By 2035, an overall increase in mortality is expected, mainly due to population change in each country.
Additional Links: PMID-40089216
Publisher:
PubMed:
Citation:
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@article {pmid40089216,
year = {2025},
author = {Torres-Roman, JS and Quispe-Vicuña, C and Benavente-Casas, A and Julca-Marin, D and Rios-Garcia, W and Challapa-Mamani, MR and Rio-Muñiz, LD and Ybaseta-Medina, J},
title = {Trends in stroke mortality in Latin America and the Caribbean from 1997 to 2020 and predictions to 2035: An analysis of gender, and geographical disparities.},
journal = {Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association},
volume = {34},
number = {6},
pages = {108286},
doi = {10.1016/j.jstrokecerebrovasdis.2025.108286},
pmid = {40089216},
issn = {1532-8511},
mesh = {Humans ; Latin America/epidemiology ; Female ; Male ; *Stroke/mortality/diagnosis ; Caribbean Region/epidemiology ; Risk Factors ; Sex Factors ; Middle Aged ; Sex Distribution ; Time Factors ; Databases, Factual ; Aged ; Adult ; *Health Status Disparities ; Age Distribution ; Forecasting ; Risk Assessment ; Age Factors ; Young Adult ; Aged, 80 and over ; },
abstract = {BACKGROUND: Stroke is a leading cause of death and disability globally, with significant public health implications. In Latin America, while mortality rates have declined, the number of stroke cases has increased due to prevalent risk factors like high blood pressure and obesity. Unlike Europe, recent trends in stroke mortality in this region remain underreported.
OBJECTIVE: This study evaluates stroke mortality rates in Latin America Latin American and Caribbean (LAC) countries from 1997 to 2020 and predictions to 2035.
METHODS: This ecological observational study utilized mortality data from the World Health Organization database. Trends were analyzed using Joinpoint regression to evaluate the annual percent change (APC) by sex and country. Predicted mortality rates through 2035 were calculated using the Nordpred package in R. Changes in stroke mortality were assessed by disentangling the effects of population growth, aging, and risk factor modifications, based on age-specific rates and projections. Results were presented as absolute case numbers and relative percentages.
RESULTS: From 1997 to 2020, twelve countries presented significant reductions in stroke mortality rates for men in LAC, the main ones being Chile (-4.2 %), El Salvador (-4.2 %), and Puerto Rico (-4.0 %). Thirteen countries reported a reduction in their mortality for women, mainly in Puerto Rico (-4.3 %), Chile (-3.7 %), Argentina, El Salvador, and Uruguay (-3.5 %). By 2035, an increase in deaths among men and women is expected, mainly due to the increase in population structure and size. However, a decrease in the mortality rate will be reported, mainly due to the reduction of risk factors.
CONCLUSION: Our final findings show a reduction in stroke mortality trends in LAC countries between 1997 and 2020, due to creating public awareness about vascular risk factors by authorities and the implementation of effective health policies. By 2035, an overall increase in mortality is expected, mainly due to population change in each country.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Humans
Latin America/epidemiology
Female
Male
*Stroke/mortality/diagnosis
Caribbean Region/epidemiology
Risk Factors
Sex Factors
Middle Aged
Sex Distribution
Time Factors
Databases, Factual
Aged
Adult
*Health Status Disparities
Age Distribution
Forecasting
Risk Assessment
Age Factors
Young Adult
Aged, 80 and over
RevDate: 2025-06-04
CmpDate: 2025-05-29
Integrative omics reveals mechanisms of biosynthesis and regulation of floral scent in Cymbidium tracyanum.
Plant biotechnology journal, 23(6):2162-2181.
Flower scent is a crucial determiner in pollinator attraction and a significant horticultural trait in ornamental plants. Orchids, which have long been of interest in evolutionary biology and horticulture, exhibit remarkable diversity in floral scent type and intensity. However, the mechanisms underlying floral scent biosynthesis and regulation in orchids remain largely unexplored. In this study, we focus on floral scent in Cymbidium tracyanum, a wild species known for its strong floral fragrance and as a primary breeding parent of commercial Cymbidium hybrids. We present a chromosome-level genome assembly of C. tracyanum, totaling 3.79 Gb in size. Comparative genomic analyses reveal significant expansion of gene families associated with terpenoid biosynthesis and related metabolic pathways in C. tracyanum. Integrative analysis of genomic, volatolomic and transcriptomic data identified terpenoids as the predominant volatile components in the flowers of C. tracyanum. We characterized the spatiotemporal patterns of these volatiles and identified CtTPS genes responsible for volatile terpenoid biosynthesis, validating their catalytic functions in vitro. Dual-luciferase reporter assays, yeast one-hybrid assays and EMSA experiments confirmed that CtTPS2, CtTPS3, and CtTPS8 could be activated by various transcription factors (i.e., CtAP2/ERF1, CtbZIP1, CtMYB2, CtMYB3 and CtAP2/ERF4), thereby regulating the production of corresponding monoterpenes and sesquiterpenes. Our study elucidates the biosynthetic and regulatory mechanisms of floral scent in C. tracyanum, which is of great significance for the breeding of fragrant Cymbidium varieties and understanding the ecological adaptability of orchids. This study also highlights the importance of integrating multi-omics data in deciphering key horticultural traits in orchids.
Additional Links: PMID-40091604
PubMed:
Citation:
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@article {pmid40091604,
year = {2025},
author = {Tu, M and Liu, N and He, ZS and Dong, XM and Gao, TY and Zhu, A and Yang, JB and Zhang, SB},
title = {Integrative omics reveals mechanisms of biosynthesis and regulation of floral scent in Cymbidium tracyanum.},
journal = {Plant biotechnology journal},
volume = {23},
number = {6},
pages = {2162-2181},
pmid = {40091604},
issn = {1467-7652},
support = {202403AC100032//Key Research and Development Program of Yunnan Province/ ; YNWR-CYJS-2020-023//High-level Talent Support Plan of Yunnan Province/ ; XDB31000000//Strategic Priority Research Program of the Chinese Academy of Sciences/ ; 32170393//National Natural Science Foundation of China/ ; 2024YFF1306703//National Key Research and Development Program of China/ ; 202201AU070123//Yunnan Fundamental Research Project/ ; 202301AT070306//Yunnan Fundamental Research Project/ ; },
mesh = {*Flowers/metabolism/genetics ; *Orchidaceae/genetics/metabolism ; *Odorants/analysis ; Terpenes/metabolism ; Gene Expression Regulation, Plant ; Transcriptome ; Volatile Organic Compounds/metabolism ; Genomics ; Plant Proteins/metabolism/genetics ; Multiomics ; },
abstract = {Flower scent is a crucial determiner in pollinator attraction and a significant horticultural trait in ornamental plants. Orchids, which have long been of interest in evolutionary biology and horticulture, exhibit remarkable diversity in floral scent type and intensity. However, the mechanisms underlying floral scent biosynthesis and regulation in orchids remain largely unexplored. In this study, we focus on floral scent in Cymbidium tracyanum, a wild species known for its strong floral fragrance and as a primary breeding parent of commercial Cymbidium hybrids. We present a chromosome-level genome assembly of C. tracyanum, totaling 3.79 Gb in size. Comparative genomic analyses reveal significant expansion of gene families associated with terpenoid biosynthesis and related metabolic pathways in C. tracyanum. Integrative analysis of genomic, volatolomic and transcriptomic data identified terpenoids as the predominant volatile components in the flowers of C. tracyanum. We characterized the spatiotemporal patterns of these volatiles and identified CtTPS genes responsible for volatile terpenoid biosynthesis, validating their catalytic functions in vitro. Dual-luciferase reporter assays, yeast one-hybrid assays and EMSA experiments confirmed that CtTPS2, CtTPS3, and CtTPS8 could be activated by various transcription factors (i.e., CtAP2/ERF1, CtbZIP1, CtMYB2, CtMYB3 and CtAP2/ERF4), thereby regulating the production of corresponding monoterpenes and sesquiterpenes. Our study elucidates the biosynthetic and regulatory mechanisms of floral scent in C. tracyanum, which is of great significance for the breeding of fragrant Cymbidium varieties and understanding the ecological adaptability of orchids. This study also highlights the importance of integrating multi-omics data in deciphering key horticultural traits in orchids.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Flowers/metabolism/genetics
*Orchidaceae/genetics/metabolism
*Odorants/analysis
Terpenes/metabolism
Gene Expression Regulation, Plant
Transcriptome
Volatile Organic Compounds/metabolism
Genomics
Plant Proteins/metabolism/genetics
Multiomics
RevDate: 2025-07-25
CmpDate: 2025-07-25
Missing Data in Discrete Time State-Space Modeling of Ecological Momentary Assessment Data: A Monte-Carlo Study of Imputation Methods.
Multivariate behavioral research, 60(4):695-710.
When using ecological momentary assessment data (EMA), missing data is pervasive as participant attrition is a common issue. Thus, any EMA study must have a missing data plan. In this paper, we discuss missingness in time series analysis and the appropriate way to handle missing data when the data is modeled as an idiographic discrete time continuous measure state-space model. We found that Missing Completely at Random, Missing At Random, and Time-dependent Missing At Random data have less bias and variability than Autoregressive Time-dependent Missing At Random and Missing Not At Random. The Kalman filter excelled at handling missing data under most conditions. Contrary to the literature, we found that using a variety of methods, multiple imputations struggled to recover the parameters.
Additional Links: PMID-40091737
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PubMed:
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@article {pmid40091737,
year = {2025},
author = {Slipetz, LR and Falk, A and Henry, TR},
title = {Missing Data in Discrete Time State-Space Modeling of Ecological Momentary Assessment Data: A Monte-Carlo Study of Imputation Methods.},
journal = {Multivariate behavioral research},
volume = {60},
number = {4},
pages = {695-710},
doi = {10.1080/00273171.2025.2469055},
pmid = {40091737},
issn = {1532-7906},
mesh = {*Ecological Momentary Assessment ; Humans ; *Monte Carlo Method ; *Models, Statistical ; Data Interpretation, Statistical ; Bias ; Computer Simulation ; Time Factors ; },
abstract = {When using ecological momentary assessment data (EMA), missing data is pervasive as participant attrition is a common issue. Thus, any EMA study must have a missing data plan. In this paper, we discuss missingness in time series analysis and the appropriate way to handle missing data when the data is modeled as an idiographic discrete time continuous measure state-space model. We found that Missing Completely at Random, Missing At Random, and Time-dependent Missing At Random data have less bias and variability than Autoregressive Time-dependent Missing At Random and Missing Not At Random. The Kalman filter excelled at handling missing data under most conditions. Contrary to the literature, we found that using a variety of methods, multiple imputations struggled to recover the parameters.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Ecological Momentary Assessment
Humans
*Monte Carlo Method
*Models, Statistical
Data Interpretation, Statistical
Bias
Computer Simulation
Time Factors
RevDate: 2025-05-13
CmpDate: 2025-05-13
Generative AI extracts ecological meaning from the complex three dimensional shapes of bird bills.
PLoS computational biology, 21(3):e1012887.
Data on the three dimensional shape of organismal morphology is becoming increasingly available, and forms part of a new revolution in high-throughput phenomics that promises to help understand ecological and evolutionary processes that influence phenotypes at unprecedented scales. However, in order to meet the potential of this revolution we need new data analysis tools to deal with the complexity and heterogeneity of large-scale phenotypic data such as 3D shapes. In this study we explore the potential of generative Artificial Intelligence to help organize and extract meaning from complex 3D data. Specifically, we train a deep representational learning method known as DeepSDF on a dataset of 3D scans of the bills of 2,020 bird species. The model is designed to learn a continuous vector representation of 3D shapes, along with a 'decoder' function, that allows the transformation from this vector space to the original 3D morphological space. We find that approach successfully learns coherent representations: particular directions in latent space are associated with discernible morphological meaning (such as elongation, flattening, etc.). More importantly, learned latent vectors have ecological meaning as shown by their ability to predict the trophic niche of the bird each bill belongs to with a high degree of accuracy. Unlike existing 3D morphometric techniques, this method has very little requirements for human supervised tasks such as landmark placement, increasing it accessibility to labs with fewer labour resources. It has fewer strong assumptions than alternative dimension reduction techniques such as PCA. Once trained, 3D morphology predictions can be made from latent vectors very computationally cheaply. The trained model has been made publicly available and can be used by the community, including for finetuning on new data, representing an early step toward developing shared, reusable AI models for analyzing organismal morphology.
Additional Links: PMID-40096239
PubMed:
Citation:
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@article {pmid40096239,
year = {2025},
author = {Dinnage, R and Kleineberg, M},
title = {Generative AI extracts ecological meaning from the complex three dimensional shapes of bird bills.},
journal = {PLoS computational biology},
volume = {21},
number = {3},
pages = {e1012887},
pmid = {40096239},
issn = {1553-7358},
mesh = {Animals ; *Birds/anatomy & histology ; *Imaging, Three-Dimensional/methods ; Computational Biology ; *Beak/anatomy & histology ; *Artificial Intelligence ; Deep Learning ; },
abstract = {Data on the three dimensional shape of organismal morphology is becoming increasingly available, and forms part of a new revolution in high-throughput phenomics that promises to help understand ecological and evolutionary processes that influence phenotypes at unprecedented scales. However, in order to meet the potential of this revolution we need new data analysis tools to deal with the complexity and heterogeneity of large-scale phenotypic data such as 3D shapes. In this study we explore the potential of generative Artificial Intelligence to help organize and extract meaning from complex 3D data. Specifically, we train a deep representational learning method known as DeepSDF on a dataset of 3D scans of the bills of 2,020 bird species. The model is designed to learn a continuous vector representation of 3D shapes, along with a 'decoder' function, that allows the transformation from this vector space to the original 3D morphological space. We find that approach successfully learns coherent representations: particular directions in latent space are associated with discernible morphological meaning (such as elongation, flattening, etc.). More importantly, learned latent vectors have ecological meaning as shown by their ability to predict the trophic niche of the bird each bill belongs to with a high degree of accuracy. Unlike existing 3D morphometric techniques, this method has very little requirements for human supervised tasks such as landmark placement, increasing it accessibility to labs with fewer labour resources. It has fewer strong assumptions than alternative dimension reduction techniques such as PCA. Once trained, 3D morphology predictions can be made from latent vectors very computationally cheaply. The trained model has been made publicly available and can be used by the community, including for finetuning on new data, representing an early step toward developing shared, reusable AI models for analyzing organismal morphology.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Animals
*Birds/anatomy & histology
*Imaging, Three-Dimensional/methods
Computational Biology
*Beak/anatomy & histology
*Artificial Intelligence
Deep Learning
RevDate: 2026-02-17
CmpDate: 2026-02-17
Information storage across a microbial community using universal RNA barcoding.
Nature biotechnology, 44(2):269-276.
Gene transfer can be studied using genetically encoded reporters or metagenomic sequencing but these methods are limited by sensitivity when used to monitor the mobile DNA host range in microbial communities. To record information about gene transfer across a wastewater microbiome, a synthetic catalytic RNA was used to barcode a highly conserved segment of ribosomal RNA (rRNA). By writing information into rRNA using a ribozyme and reading out native and modified rRNA using amplicon sequencing, we find that microbial community members from 20 taxonomic orders participate in plasmid conjugation with an Escherichia coli donor strain and observe differences in 16S rRNA barcode signal across amplicon sequence variants. Multiplexed rRNA barcoding using plasmids with pBBR1 or ColE1 origins of replication reveals differences in host range. This autonomous RNA-addressable modification provides information about gene transfer without requiring translation and will enable microbiome engineering across diverse ecological settings and studies of environmental controls on gene transfer and cellular uptake of extracellular materials.
Additional Links: PMID-40102641
PubMed:
Citation:
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@article {pmid40102641,
year = {2026},
author = {Kalvapalle, PB and Staubus, A and Dysart, MJ and Gambill, L and Reyes Gamas, K and Lu, LC and Silberg, JJ and Stadler, LB and Chappell, J},
title = {Information storage across a microbial community using universal RNA barcoding.},
journal = {Nature biotechnology},
volume = {44},
number = {2},
pages = {269-276},
pmid = {40102641},
issn = {1546-1696},
support = {2021-33522-35356//United States Department of Agriculture | National Institute of Food and Agriculture (NIFA)/ ; W911NF-24-2-0073//United States Department of Defense | United States Army | U.S. Army Research, Development and Engineering Command | Army Research Office (ARO)/ ; 1805901//National Science Foundation (NSF)/ ; 1828869//National Science Foundation (NSF)/ ; 2227526//National Science Foundation (NSF)/ ; 2237052//National Science Foundation (NSF)/ ; 2237512//National Science Foundation (NSF)/ ; FWP 78814//U.S. Department of Energy (DOE)/ ; A23-0202-004//Robert J. Kleberg, Jr. and Helen C. Kleberg Foundation/ ; },
mesh = {*Microbiota/genetics ; *RNA, Ribosomal, 16S/genetics ; *DNA Barcoding, Taxonomic/methods ; Escherichia coli/genetics ; Plasmids/genetics ; *Information Storage and Retrieval/methods ; RNA, Bacterial/genetics ; RNA, Catalytic/genetics ; Wastewater/microbiology ; },
abstract = {Gene transfer can be studied using genetically encoded reporters or metagenomic sequencing but these methods are limited by sensitivity when used to monitor the mobile DNA host range in microbial communities. To record information about gene transfer across a wastewater microbiome, a synthetic catalytic RNA was used to barcode a highly conserved segment of ribosomal RNA (rRNA). By writing information into rRNA using a ribozyme and reading out native and modified rRNA using amplicon sequencing, we find that microbial community members from 20 taxonomic orders participate in plasmid conjugation with an Escherichia coli donor strain and observe differences in 16S rRNA barcode signal across amplicon sequence variants. Multiplexed rRNA barcoding using plasmids with pBBR1 or ColE1 origins of replication reveals differences in host range. This autonomous RNA-addressable modification provides information about gene transfer without requiring translation and will enable microbiome engineering across diverse ecological settings and studies of environmental controls on gene transfer and cellular uptake of extracellular materials.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Microbiota/genetics
*RNA, Ribosomal, 16S/genetics
*DNA Barcoding, Taxonomic/methods
Escherichia coli/genetics
Plasmids/genetics
*Information Storage and Retrieval/methods
RNA, Bacterial/genetics
RNA, Catalytic/genetics
Wastewater/microbiology
RevDate: 2026-04-28
CmpDate: 2025-05-08
The draft genome assembly of the cosmopolitan pelagic fish dolphinfish Coryphaena hippurus.
G3 (Bethesda, Md.), 15(5):.
For the first time, the complete genome assembly of the dolphinfish (Coryphaena hippurus), a tropical cosmopolitan species with commercial fishing importance was sequenced. Using a combination of Illumina and Nanopore sequencing technologies, a draft genome of 497.8 Mb was assembled into 6,044 contigs, with an N50 of 200.9 kb and a BUSCO genome completeness score of 89%. This high-quality genome assembly provides a valuable resource to study adaptive evolutionary processes and supports conservation and management strategies for this ecologically and economically significant species.
Additional Links: PMID-40102961
PubMed:
Citation:
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@article {pmid40102961,
year = {2025},
author = {Hinojosa-Alvarez, S and Mendoza-Portillo, V and Chavez-Santoscoy, RA and Hernández-Pérez, J and Felix-Ceniceros, A and Magallón-Gayón, E and Mar-Silva, AF and Ochoa-Zavala, M and Díaz-Jaimes, P},
title = {The draft genome assembly of the cosmopolitan pelagic fish dolphinfish Coryphaena hippurus.},
journal = {G3 (Bethesda, Md.)},
volume = {15},
number = {5},
pages = {},
pmid = {40102961},
issn = {2160-1836},
support = {CF-2023-G-493//Consejo Nacional de Humanidades, Ciencias y Tecnologías/ ; },
mesh = {Animals ; *Genome ; Molecular Sequence Annotation ; *Genomics/methods ; *Perciformes/genetics ; Sequence Analysis, DNA ; High-Throughput Nucleotide Sequencing ; *Fishes/genetics ; Whole Genome Sequencing ; Computational Biology/methods ; },
abstract = {For the first time, the complete genome assembly of the dolphinfish (Coryphaena hippurus), a tropical cosmopolitan species with commercial fishing importance was sequenced. Using a combination of Illumina and Nanopore sequencing technologies, a draft genome of 497.8 Mb was assembled into 6,044 contigs, with an N50 of 200.9 kb and a BUSCO genome completeness score of 89%. This high-quality genome assembly provides a valuable resource to study adaptive evolutionary processes and supports conservation and management strategies for this ecologically and economically significant species.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Animals
*Genome
Molecular Sequence Annotation
*Genomics/methods
*Perciformes/genetics
Sequence Analysis, DNA
High-Throughput Nucleotide Sequencing
*Fishes/genetics
Whole Genome Sequencing
Computational Biology/methods
RevDate: 2025-05-13
CmpDate: 2025-05-13
How immunity shapes the long-term dynamics of influenza H3N2.
PLoS computational biology, 21(3):e1012893.
Since its emergence in 1968, influenza A H3N2 has caused yearly epidemics in temperate regions. While infection confers immunity against antigenically similar strains, new antigenically distinct strains that evade existing immunity regularly emerge ('antigenic drift'). Immunity at the individual level is complex, depending on an individual's lifetime infection history. An individual's first infection with influenza typically elicits the greatest response with subsequent infections eliciting progressively reduced responses ('antigenic seniority'). The combined effect of individual-level immune responses and antigenic drift on the epidemiological dynamics of influenza are not well understood. Here we develop an integrated modelling framework of influenza transmission, immunity, and antigenic drift to show how individual-level exposure, and the build-up of population level immunity, shape the long-term epidemiological dynamics of H3N2. Including antigenic seniority in the model, we observe that following an initial decline after the pandemic year, the average annual attack rate increases over the next 80 years, before reaching an equilibrium, with greater increases in older age-groups. Our analyses suggest that the average attack rate of H3N2 is still in a growth phase. Further increases, particularly in the elderly, may be expected in coming decades, driving an increase in healthcare demand due to H3N2 infections.
Additional Links: PMID-40111995
PubMed:
Citation:
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@article {pmid40111995,
year = {2025},
author = {Eales, O and Shearer, FM and McCaw, JM},
title = {How immunity shapes the long-term dynamics of influenza H3N2.},
journal = {PLoS computational biology},
volume = {21},
number = {3},
pages = {e1012893},
pmid = {40111995},
issn = {1553-7358},
mesh = {Humans ; *Influenza, Human/immunology/epidemiology/transmission/virology ; *Influenza A Virus, H3N2 Subtype/immunology/genetics ; Computational Biology ; *Models, Immunological ; Adult ; Aged ; Middle Aged ; Adolescent ; },
abstract = {Since its emergence in 1968, influenza A H3N2 has caused yearly epidemics in temperate regions. While infection confers immunity against antigenically similar strains, new antigenically distinct strains that evade existing immunity regularly emerge ('antigenic drift'). Immunity at the individual level is complex, depending on an individual's lifetime infection history. An individual's first infection with influenza typically elicits the greatest response with subsequent infections eliciting progressively reduced responses ('antigenic seniority'). The combined effect of individual-level immune responses and antigenic drift on the epidemiological dynamics of influenza are not well understood. Here we develop an integrated modelling framework of influenza transmission, immunity, and antigenic drift to show how individual-level exposure, and the build-up of population level immunity, shape the long-term epidemiological dynamics of H3N2. Including antigenic seniority in the model, we observe that following an initial decline after the pandemic year, the average annual attack rate increases over the next 80 years, before reaching an equilibrium, with greater increases in older age-groups. Our analyses suggest that the average attack rate of H3N2 is still in a growth phase. Further increases, particularly in the elderly, may be expected in coming decades, driving an increase in healthcare demand due to H3N2 infections.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Humans
*Influenza, Human/immunology/epidemiology/transmission/virology
*Influenza A Virus, H3N2 Subtype/immunology/genetics
Computational Biology
*Models, Immunological
Adult
Aged
Middle Aged
Adolescent
RevDate: 2025-05-08
CmpDate: 2025-05-08
Multi-omics analysis provided insights into the fruit softening of postharvest okra under carboxymethyl chitosan treatment.
International journal of biological macromolecules, 307(Pt 3):142149.
To understand the potential regulatory mechanism of carboxymethyl chitosan (CMCS) treatment on postharvest softening of okra, a joint analysis of physiologic index, transcriptome and metabolome was used. The results showed that CMCS could delay the deterioration of the apparent quality of okra and reduce the degradation of chlorophyll. CMCS can reduce the accumulation of WSP and CSP and the decrease of NSP, and inhibit the enzyme activities of pectin degradation (PE, PG, PL). The results of metabolic pathways related to quality and texture showed that CMCS could increase the metabolic level of pentose phosphate pathway (PPP), inhibit the expression of membrane lipid degradation-related genes, and balance the expression of antioxidant-related genes. Ethylene and abscisic acid (ABA) are two important phytohormones. CMCS down-regulates the biosynthesis of ethylene and increases the expression of ABA. The combined analysis of transcriptome and metabolome showed that CMCS could significantly up-regulate flavonoid biosynthesis metabolites and transcriptional expression levels. Cellulose and pectin are important polymers to maintain the rigidity of okra cell wall. CMCS treatment can slow down the accumulation of cellulose by regulating the expression of DEGs related to cellulose synthesis (CesA) and degradation (EGase). CMCS slowed down the degradation of pectin by down-regulating the expression of pectin degradation-related genes. These results indicate that the quality of okra is deteriorated and the fruit is softened during cold storage. CMCS treatment can improve the nutritional quality of okra and slow down its texture decline. In this study, the regulatory effect of CMCS on softening and quality deterioration of okra during cold storage was discussed at the molecular level, which provided a reference for improving the quality of postharvest okra.
Additional Links: PMID-40112992
Publisher:
PubMed:
Citation:
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@article {pmid40112992,
year = {2025},
author = {Wei, L and Luo, Z and Wu, X and Liu, C and Shi, Y and Zhang, Q and Chen, M and Qin, W},
title = {Multi-omics analysis provided insights into the fruit softening of postharvest okra under carboxymethyl chitosan treatment.},
journal = {International journal of biological macromolecules},
volume = {307},
number = {Pt 3},
pages = {142149},
doi = {10.1016/j.ijbiomac.2025.142149},
pmid = {40112992},
issn = {1879-0003},
mesh = {*Chitosan/analogs & derivatives/pharmacology ; *Fruit/drug effects/metabolism/genetics ; *Abelmoschus/genetics/metabolism/drug effects ; Gene Expression Regulation, Plant/drug effects ; Transcriptome/drug effects ; *Metabolomics/methods ; Metabolome/drug effects ; Gene Expression Profiling ; Pectins/metabolism ; Multiomics ; },
abstract = {To understand the potential regulatory mechanism of carboxymethyl chitosan (CMCS) treatment on postharvest softening of okra, a joint analysis of physiologic index, transcriptome and metabolome was used. The results showed that CMCS could delay the deterioration of the apparent quality of okra and reduce the degradation of chlorophyll. CMCS can reduce the accumulation of WSP and CSP and the decrease of NSP, and inhibit the enzyme activities of pectin degradation (PE, PG, PL). The results of metabolic pathways related to quality and texture showed that CMCS could increase the metabolic level of pentose phosphate pathway (PPP), inhibit the expression of membrane lipid degradation-related genes, and balance the expression of antioxidant-related genes. Ethylene and abscisic acid (ABA) are two important phytohormones. CMCS down-regulates the biosynthesis of ethylene and increases the expression of ABA. The combined analysis of transcriptome and metabolome showed that CMCS could significantly up-regulate flavonoid biosynthesis metabolites and transcriptional expression levels. Cellulose and pectin are important polymers to maintain the rigidity of okra cell wall. CMCS treatment can slow down the accumulation of cellulose by regulating the expression of DEGs related to cellulose synthesis (CesA) and degradation (EGase). CMCS slowed down the degradation of pectin by down-regulating the expression of pectin degradation-related genes. These results indicate that the quality of okra is deteriorated and the fruit is softened during cold storage. CMCS treatment can improve the nutritional quality of okra and slow down its texture decline. In this study, the regulatory effect of CMCS on softening and quality deterioration of okra during cold storage was discussed at the molecular level, which provided a reference for improving the quality of postharvest okra.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Chitosan/analogs & derivatives/pharmacology
*Fruit/drug effects/metabolism/genetics
*Abelmoschus/genetics/metabolism/drug effects
Gene Expression Regulation, Plant/drug effects
Transcriptome/drug effects
*Metabolomics/methods
Metabolome/drug effects
Gene Expression Profiling
Pectins/metabolism
Multiomics
RevDate: 2026-05-12
CmpDate: 2025-05-14
Healthy microbiome-moving towards functional interpretation.
GigaScience, 14:.
BACKGROUND: Microbiome-based disease prediction has significant potential as an early, noninvasive marker of multiple health conditions linked to dysbiosis of the human gut microbiota, thanks in part to decreasing sequencing and analysis costs. Microbiome health indices and other computational tools currently proposed in the field often are based on a microbiome's species richness and are completely reliant on taxonomic classification. A resurgent interest in a metabolism-centric, ecological approach has led to an increased understanding of microbiome metabolic and phenotypic complexity, revealing substantial restrictions of taxonomy-reliant approaches.
FINDINGS: In this study, we introduce a new metagenomic health index developed as an answer to recent developments in microbiome definitions, in an effort to distinguish between healthy and unhealthy microbiomes, here in focus, inflammatory bowel disease (IBD). The novelty of our approach is a shift from a traditional Linnean phylogenetic classification toward a more holistic consideration of the metabolic functional potential underlining ecological interactions between species. Based on well-explored data cohorts, we compare our method and its performance with the most comprehensive indices to date, the taxonomy-based Gut Microbiome Health Index (GMHI), and the high-dimensional principal component analysis (hiPCA) methods, as well as to the standard taxon- and function-based Shannon entropy scoring. After demonstrating better performance on the initially targeted IBD cohorts, in comparison with other methods, we retrain our index on an additional 27 datasets obtained from different clinical conditions and validate our index's ability to distinguish between healthy and disease states using a variety of complementary benchmarking approaches. Finally, we demonstrate its superiority over the GMHI and the hiPCA on a longitudinal COVID-19 cohort and highlight the distinct robustness of our method to sequencing depth.
CONCLUSIONS: Overall, we emphasize the potential of this metagenomic approach and advocate a shift toward functional approaches to better understand and assess microbiome health as well as provide directions for future index enhancements. Our method, q2-predict-dysbiosis (Q2PD), is freely available (https://github.com/Kizielins/q2-predict-dysbiosis).
Additional Links: PMID-40117176
PubMed:
Citation:
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@article {pmid40117176,
year = {2025},
author = {Zielińska, K and Udekwu, KI and Rudnicki, W and Frolova, A and Łabaj, PP},
title = {Healthy microbiome-moving towards functional interpretation.},
journal = {GigaScience},
volume = {14},
number = {},
pages = {},
pmid = {40117176},
issn = {2047-217X},
support = {2020/38/E/NZ2/00598//NCN/ ; PLG/2023/016234//Jagiellonian University in Krakow/ ; },
mesh = {Humans ; *Gastrointestinal Microbiome/genetics ; *Inflammatory Bowel Diseases/microbiology ; *Metagenomics/methods ; Dysbiosis/microbiology ; Phylogeny ; *Microbiota ; Principal Component Analysis ; Computational Biology/methods ; },
abstract = {BACKGROUND: Microbiome-based disease prediction has significant potential as an early, noninvasive marker of multiple health conditions linked to dysbiosis of the human gut microbiota, thanks in part to decreasing sequencing and analysis costs. Microbiome health indices and other computational tools currently proposed in the field often are based on a microbiome's species richness and are completely reliant on taxonomic classification. A resurgent interest in a metabolism-centric, ecological approach has led to an increased understanding of microbiome metabolic and phenotypic complexity, revealing substantial restrictions of taxonomy-reliant approaches.
FINDINGS: In this study, we introduce a new metagenomic health index developed as an answer to recent developments in microbiome definitions, in an effort to distinguish between healthy and unhealthy microbiomes, here in focus, inflammatory bowel disease (IBD). The novelty of our approach is a shift from a traditional Linnean phylogenetic classification toward a more holistic consideration of the metabolic functional potential underlining ecological interactions between species. Based on well-explored data cohorts, we compare our method and its performance with the most comprehensive indices to date, the taxonomy-based Gut Microbiome Health Index (GMHI), and the high-dimensional principal component analysis (hiPCA) methods, as well as to the standard taxon- and function-based Shannon entropy scoring. After demonstrating better performance on the initially targeted IBD cohorts, in comparison with other methods, we retrain our index on an additional 27 datasets obtained from different clinical conditions and validate our index's ability to distinguish between healthy and disease states using a variety of complementary benchmarking approaches. Finally, we demonstrate its superiority over the GMHI and the hiPCA on a longitudinal COVID-19 cohort and highlight the distinct robustness of our method to sequencing depth.
CONCLUSIONS: Overall, we emphasize the potential of this metagenomic approach and advocate a shift toward functional approaches to better understand and assess microbiome health as well as provide directions for future index enhancements. Our method, q2-predict-dysbiosis (Q2PD), is freely available (https://github.com/Kizielins/q2-predict-dysbiosis).},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Humans
*Gastrointestinal Microbiome/genetics
*Inflammatory Bowel Diseases/microbiology
*Metagenomics/methods
Dysbiosis/microbiology
Phylogeny
*Microbiota
Principal Component Analysis
Computational Biology/methods
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ESP Quick Facts
ESP Origins
In the early 1990's, Robert Robbins was a faculty member at Johns Hopkins, where he directed the informatics core of GDB — the human gene-mapping database of the international human genome project. To share papers with colleagues around the world, he set up a small paper-sharing section on his personal web page. This small project evolved into The Electronic Scholarly Publishing Project.
ESP Support
In 1995, Robbins became the VP/IT of the Fred Hutchinson Cancer Research Center in Seattle, WA. Soon after arriving in Seattle, Robbins secured funding, through the ELSI component of the US Human Genome Project, to create the original ESP.ORG web site, with the formal goal of providing free, world-wide access to the literature of classical genetics.
ESP Rationale
Although the methods of molecular biology can seem almost magical to the uninitiated, the original techniques of classical genetics are readily appreciated by one and all: cross individuals that differ in some inherited trait, collect all of the progeny, score their attributes, and propose mechanisms to explain the patterns of inheritance observed.
ESP Goal
In reading the early works of classical genetics, one is drawn, almost inexorably, into ever more complex models, until molecular explanations begin to seem both necessary and natural. At that point, the tools for understanding genome research are at hand. Assisting readers reach this point was the original goal of The Electronic Scholarly Publishing Project.
ESP Usage
Usage of the site grew rapidly and has remained high. Faculty began to use the site for their assigned readings. Other on-line publishers, ranging from The New York Times to Nature referenced ESP materials in their own publications. Nobel laureates (e.g., Joshua Lederberg) regularly used the site and even wrote to suggest changes and improvements.
ESP Content
When the site began, no journals were making their early content available in digital format. As a result, ESP was obliged to digitize classic literature before it could be made available. For many important papers — such as Mendel's original paper or the first genetic map — ESP had to produce entirely new typeset versions of the works, if they were to be available in a high-quality format.
ESP Help
Early support from the DOE component of the Human Genome Project was critically important for getting the ESP project on a firm foundation. Since that funding ended (nearly 20 years ago), the project has been operated as a purely volunteer effort. Anyone wishing to assist in these efforts should send an email to Robbins.
ESP Plans
With the development of methods for adding typeset side notes to PDF files, the ESP project now plans to add annotated versions of some classical papers to its holdings. We also plan to add new reference and pedagogical material. We have already started providing regularly updated, comprehensive bibliographies to the ESP.ORG site.
ESP Picks from Around the Web (updated 28 JUL 2024 )
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Fossils of miniature humans (hobbits) discovered in Indonesia
Paleontology
Dinosaur tail, complete with feathers, found preserved in amber.
Astronomy
Mysterious fast radio burst (FRB) detected in the distant universe.
Big Data & Informatics
Big Data: Buzzword or Big Deal?
Hacking the genome: Identifying anonymized human subjects using publicly available data.