@article {pmid41348994,
year = {2026},
author = {Tomarovsky, AA and Khan, R and Dudchenko, O and Beklemisheva, VR and Perelman, PL and Totikov, AA and Serdyukova, NA and Bulyonkova, TM and Pobedintseva, M and Abramov, AV and Weisz, D and Yakupova, A and Zhuk, A and Graphodatsky, AS and Powell, R and Aiden, EL and Koepfli, KP and Kliver, S},
title = {Novel chromosome-length genome assemblies of three distinct subspecies of pine marten, sable, and yellow-throated marten (genus Martes, family Mustelidae).},
journal = {The Journal of heredity},
volume = {117},
number = {3},
pages = {583-591},
doi = {10.1093/jhered/esaf101},
pmid = {41348994},
issn = {1465-7333},
support = {CF22-0680//Carlsbergfondet Research Infrastructure/ ; },
mesh = {Animals ; *Mustelidae/genetics/classification ; *Genome ; Karyotype ; },
abstract = {The genus Martes consists of medium-sized carnivores within the family Mustelidae that are commonly known as martens, many of which exhibit extensive geographic variation and taxonomic uncertainty. Here, we report chromosome-length genome assemblies for three subspecies, each representing a different marten species: the Tobol sable (Martes zibellina zibellina), the Ural pine marten (Martes martes uralensis), and the Far East yellow-throated marten (Martes flavigula aterrima). Using linked-read sequencing and Hi-C scaffolding, we generated assemblies with total lengths of 2.39 to 2.45 Gbp, N50 values of 137 to 145 Mbp, and high BUSCO scores (93.6% to 96.4%). We identified 19 chromosomal scaffolds for sable and pine marten, and 20 for yellow-throated marten, which agrees with the known karyotypes of these species (2n = 38 and 2n = 40, respectively). Annotation predicted ~ 20,000 protein-coding genes per genome, of which > 90% were assigned functional names. Repeats encompass 36.9% to 40.4% of the assemblies, with a prevalence of LINEs and SINEs, and are conservative across the genus. Synteny analysis of our generated and available marten genome assemblies revealed assembly artifacts in previously published assemblies, which we confirmed through investigation of Hi-C contact maps. Among other rearrangements, we verify a sable-specific inversion on chromosome 11 using the published cytogenetic data. Our assemblies broaden the genomic resources available for Martes, extending coverage to geographically distant and taxonomically significant subspecies. Together, they provide a robust framework for assessing intraspecific genetic diversity, identifying signatures of hybridization, and refining the complex taxonomy of the genus. Beyond conservation and evolutionary applications, these references will facilitate comparative genomics across Mustelidae and other carnivorans.},
}

Animals
*Mustelidae/genetics/classification
*Genome
Karyotype

@article {pmid41844600,
year = {2026},
author = {Xie, H and Hu, J and Zhao, X and Chen, J and Yue, X and Zhou, C and Navarro-Muñoz, JC and Jiang, J and Tang, X and Zhao, F and Hatmaker, EA and Rokas, A and Barber, AE and Drott, MT and Keller, NP and Zhang, Q and van der Hooft, JJJ and Medema, MH and Li, P},
title = {Large-scale multi-omics profiling reveals environmental and evolutionary drivers of fungal phylogeographic and metabolic diversity.},
journal = {Nature communications},
volume = {17},
number = {1},
pages = {},
pmid = {41844600},
issn = {2041-1723},
mesh = {Phylogeography ; *Aspergillus flavus/genetics/metabolism/classification ; Phylogeny ; Metabolomics/methods ; Metabolome/genetics ; China ; Genome, Fungal ; Mycotoxins/metabolism/genetics/biosynthesis ; Evolution, Molecular ; Genome-Wide Association Study ; Multiomics ; },
abstract = {Chemical innovation is essential for fungi to adapt to ever-changing ecological environments. However, the environmental and evolutionary drivers of fungal metabolic differentiation remain ambiguous. Here, we show the phylogeographic diversity of 1052 Aspergillus flavus strains across four continents, as conducted through phylogenetic and biogeographical analysis, including 544 newly sequenced strains from China. These strains exhibit varying levels of population-specific mycotoxin production, as determined by population metabolomics analysis. We report a toxigenic subpopulation from China, identified through comparative population genomics analysis. Pan-metabolome analysis reveals strong phylogeographic metabolic patterns associated with specific ecological niches. Low-mycotoxin production clades harbor distinct uncharacterized biosynthetic gene clusters and produce different specialized metabolites instead. This discrepancy is only partially explained by variation in biosynthetic pathway genes, and changes in regulation and primary metabolism appear to mainly drive differentiation of specialized metabolite profiles across fungal populations, as indicated by pangenome profiling, metabolites-genome-wide association study, genotype-environment association study, pan-transcriptome analysis, and gene knockout experiments. Altogether, our results reveal how environmental shifts drive the fungal metabolic evolution, and provide insights for predicting the risk of harmful fungal outbreaks and for biogeographically-informed, precise control measures.},
}

Phylogeography
*Aspergillus flavus/genetics/metabolism/classification
Phylogeny
Metabolomics/methods
Metabolome/genetics
China
Genome, Fungal
Mycotoxins/metabolism/genetics/biosynthesis
Evolution, Molecular
Genome-Wide Association Study
Multiomics

@article {pmid42054418,
year = {2026},
author = {Arnold, CRK and Kong, AC and Winter, AK and Moss, WJ and Patenaude, BN and Ferrari, MJ},
title = {Individual and population level uncertainty interact to determine the performance of outbreak surveillance systems.},
journal = {PLoS computational biology},
volume = {22},
number = {4},
pages = {e1013309},
doi = {10.1371/journal.pcbi.1013309},
pmid = {42054418},
issn = {1553-7358},
mesh = {Humans ; *Disease Outbreaks/statistics & numerical data ; Measles/epidemiology/diagnosis ; Uncertainty ; Computer Simulation ; Computational Biology ; *Population Surveillance/methods ; Stochastic Processes ; Incidence ; },
abstract = {BACKGROUND: Outbreak detection frequently relies on imperfect individual-level case diagnosis. Both outbreaks and cases are discrete events that can be misclassified and uncertainty at the case level may impact the performance of outbreak alert and detection systems. Here, we describe how the performance of outbreak detection depends on individual-level diagnostic test characteristics and population-level epidemiology, and describe settings where imperfect individual-level tests can achieve consistent performance comparable to "perfect" diagnostic tests.

METHODOLOGY: We generated a stochastic SEIR model to simulate daily incidence of measles (i.e., true) and non-measles (i.e., noise) febrile rash illness. We modeled non-measles sources as either independent static (Poisson) noise, or dynamical noise consistent with an independent SEIR process (e.g., rubella). Defining outbreak alerts as the exceedance of a threshold by the 7-day rolling average of observed test positives, we optimized the threshold that maximized outbreak detection accuracy across sets of noise structures and magnitudes, diagnostic test accuracy (consistent with either a perfect test, or proposed rapid diagnostic tests), and testing rates.

CONCLUSIONS: The optimal threshold for each diagnostic test typically increased monotonically with testing rate. With static noise, outbreak detection with RDT-like and perfect tests achieved accuracies of 90%, with comparable delays to outbreak detection. With dynamical noise, the accuracy of perfect test scenarios was superior to those achieved with RDTs (≈ 90% vs. ≤ 80%). Outbreak detection accuracy declined as dynamical noise increased and leads to permanent alert status with RDT-like tests at very high noise. The performance of an outbreak detection system is highly sensitive to the structure and the magnitude of the background noise. Depending on the epidemiological context, outbreak detection using RDTs can perform as well as perfect tests.},
}

Humans
*Disease Outbreaks/statistics & numerical data
Measles/epidemiology/diagnosis
Uncertainty
Computer Simulation
Computational Biology
*Population Surveillance/methods
Stochastic Processes
Incidence

@article {pmid42083045,
year = {2026},
author = {Bertram, H and Jawad, M and Michanski, S and Tiemann, I and Schmitt, AO and Gültas, M},
title = {Whole-genome resequencing data of the Ixworth chicken breed.},
journal = {BMC research notes},
volume = {19},
number = {1},
pages = {},
pmid = {42083045},
issn = {1756-0500},
mesh = {Animals ; *Chickens/genetics ; *Breeding ; Male ; *Whole Genome Sequencing ; *Genome ; Polymorphism, Single Nucleotide ; Germany ; Genetic Variation ; },
abstract = {OBJECTIVES: The Ixworth chicken is a British dual-purpose breed and mostly maintained by small-scale farmers. Due to legislation regarding the ban on male chick culling in European countries, such as in Germany, renewed interest has arisen in rearing dual-purpose chickens that provide both meat and eggs from the same genetic line. This dataset was generated within the scope of projects aiming to evaluate the viability of dual-purpose breeds for sustainable and welfare-oriented poultry production. One of the objectives was to characterize the genetic potential of the Ixworth chicken as a model for breeding programs that combine conservation and practical use in ecological farming systems.

DATA DESCRIPTION: Liver samples from 49 male Ixworth chickens were collected after scheduled slaughter at the Campus Frankenforst of the Faculty of Agricultural, Nutritional and Engineering Sciences of the University of Bonn, Germany. Genomic DNA was extracted and subjected to whole-genome resequencing using the Illumina NovaSeq 6000 platform. The dataset provides high-resolution genomic information on a rare breed with a pure dual-purpose background. This resource represents the first public sequencing dataset of the Ixworth chicken and thus offers a valuable foundation for future studies on genetic diversity, conservation genomics, and breeding strategies for sustainable poultry production.},
}

Animals
*Chickens/genetics
*Breeding
Male
*Whole Genome Sequencing
*Genome
Polymorphism, Single Nucleotide
Germany
Genetic Variation

@article {pmid42083334,
year = {2026},
author = {Ye, JF and Zheng, S and Liu, PL},
title = {Multifunctional Online Medical Record Use and Patient Empowerment: Examining the Mediating Role of Patient-Centered Communication Across the Life Span in the Greater China Region.},
journal = {Health communication},
volume = {},
number = {},
pages = {1-13},
doi = {10.1080/10410236.2026.2668013},
pmid = {42083334},
issn = {1532-7027},
abstract = {The Greater China region represents the fastest-growing market for online medical records (OMR) implementation. However, the implications of these technologies for patient-centered care remain unclear. This study examined the relationships among different types of OMR usage (online patient-provider interactions, health information management, self-health management, and decision-making), patient-centered communication (PCC), and patient empowerment using a national sample (N = 6,271) of patients from Mainland China, Taiwan, Hong Kong, and Macao. Results revealed that OMR usage for online patient-provider interactions, self-health management, and decision-making was associated with patient empowerment among younger (18-34) and middle-aged (35-59) cohorts, with PCC mediating these relationships. eHealth literacy (eHL) moderated the relationship between self-health management and PCC in younger and middle-aged cohorts, while also moderating the association between decision-making and PCC across all age cohorts. Framed within the ecological model of health communication and life span perspectives, these findings suggest that future OMR studies would benefit from more nuanced and dialectical approaches. Practical implications are also discussed.},
}

@article {pmid42089043,
year = {2026},
author = {Johnston, JM and Perkins, E and Glynn, PD and von Stackelberg, K and Hope, BK and Harwell, MC},
title = {Interoperability to Improve Science-Based Decision Making: Adapting a Risk Analysis Framework to Improve Translational Environmental Health Science.},
journal = {Electronics},
volume = {15},
number = {3},
pages = {574},
pmid = {42089043},
issn = {2079-9292},
abstract = {The protection of human and ecological health has become more challenging because of the myriad of human and climate stressors, and the sustainability of our social, economic, and environmental systems would be enhanced by further defensible risk assessment. There are scientific, technological, and cultural challenges to interoperability, bridging the necessary disciplines and integrating data from the genome to globe. Interoperability makes possible the use and reuse of data and modeling approaches and is a contemporary and rapidly progressing area advancing toxicology and exposure science. We present a coherent vision of human and ecological risk assessment, including the types of information and modeling science to create knowledge and apply it for improved decision-making. We focus on science-based decision-making, emphasizing decisions where science is the primary or sole driver, as in human toxicology and ecological risk assessment. This contrasts with decision-making where science has a minor role, if at all, in weighing decision options. We also examine the barriers that exist in the creation and application of systems thinking. We identify: the (1) needs and challenges for the application of a systems approach to informing decisions; (2) case studies that illustrate informatics needs for 21st-century science-based decision-making; and (3) recommendations on how to progress towards a systems approach to informing decisions.},
}

@article {pmid42089848,
year = {2026},
author = {DiFiore, G and Martin, H and Mitchell, JA and Barnett, I and Wiebe, D and Basner, M and Fiks, AG and Glanz, K and Mayne, SL},
title = {Association of Stress and Neighborhood Social Context With Actigraphy-Measured and Self-Reported Adolescent Sleep Outcomes.},
journal = {The Journal of adolescent health : official publication of the Society for Adolescent Medicine},
volume = {},
number = {},
pages = {},
doi = {10.1016/j.jadohealth.2026.02.022},
pmid = {42089848},
issn = {1879-1972},
abstract = {PURPOSE: Chronic stress and unfavorable neighborhood environments may increase adolescents' risk for poor sleep. Few studies have examined whether neighborhood social environments moderate associations of adolescents' perceptions of stress with actigraphy-measured and self-reported sleep outcomes.

METHODS: In a cross-sectional study of adolescents aged 15-18 (n = 163) years, perceived stress (10-item Perceived Stress Scale) and perceived neighborhood collective efficacy and safety were assessed via survey. Over 14 days, actigraphy measured nightly sleep duration and timing, while ecological momentary assessment (EMA) measured daily stress, self-reported sleep problems, and sleep environment disruptions. Multivariable mixed effects regression estimated associations of stress and neighborhood social factors with nightly sleep patterns and self-reported sleep outcomes, while multivariable linear regression estimated associations with sleep variability (intraindividual standard deviation of each sleep measure).

RESULTS: Higher 10-item Perceived Stress Scale scores and daily EMA-reported stress were associated with more variable sleep duration, onset, and offset timing, and higher and more variable sleep problem scores. Daily EMA-reported stress was also associated with earlier sleep timing. Higher neighborhood collective efficacy was associated with less variable sleep duration and timing, and lower and less variable sleep problem scores. Neighborhood collective efficacy and safety moderated associations between stress and several sleep outcomes (e.g., stronger associations between stress and sleep variability were present among adolescents with low neighborhood safety or collective efficacy).

DISCUSSION: Lower perceived stress and higher neighborhood collective efficacy were associated with less variable sleep patterns and lower sleep problem scores. Results suggest positive neighborhood social environments may moderate the relationship of stress with adolescent sleep variability.},
}

@article {pmid42091644,
year = {2026},
author = {Iqbal, M and Yaro, D and Apeanti, WO and Akuamoah, SW and Aljohani, A and Gouadria, S and Ceesay, B},
title = {Optical soliton solutions of the nonlinear coupled Konno-Oono system by using the new analytical approach and modulation instability analysis.},
journal = {Scientific reports},
volume = {},
number = {},
pages = {},
doi = {10.1038/s41598-026-51821-3},
pmid = {42091644},
issn = {2045-2322},
abstract = {This study primarily aims to apply the Riccati equation rational expansion method (REREM) to the nonlinear coupled Konno-Oono system (NCKOS) in order to construct novel and flexible optical soliton solutions. In addition, the modulation instability of the NCKOS is examined. The NCKOS represents current-field strings that interact with an external magnetic field. By employing REREM, we obtain various new types of solutions, including hyperbolic, bright, dark, periodic, kink and anti-kink, peakon, bell-shaped, and many other solitary wave structures. Several physical illustrations of some of the derived solutions are provided to enhance clarity. The findings demonstrate that the proposed technique is more powerful, efficient, and effective for investigating the solutions of other complex nonlinear models. Furthermore, the newly obtained solutions have potential applications in hydrodynamics, solid-state physics, cosmology, ecology, and quantum electronics.},
}

@article {pmid42000490,
year = {2026},
author = {Kahraman, ÜO and Üçağaç, A and İnal, V and Mucahit Aydin, },
title = {Dynamic environmental management and liability attribution using an AlphaZero-Bayes framework: Intelligent decision support for multi-agent risk systems.},
journal = {Journal of environmental management},
volume = {405},
number = {},
pages = {129672},
doi = {10.1016/j.jenvman.2026.129672},
pmid = {42000490},
issn = {1095-8630},
mesh = {Bayes Theorem ; *Decision Support Techniques ; },
abstract = {Attributing liability in environmental systems involving multiple strategic actors poses significant challenges for policy-makers and regulators, particularly under conditions of uncertainty, feedback dynamics, and distributed responsibility. Traditional deterministic models of causation are often inadequate for such complex contexts. In this study, we propose a novel hybrid framework that integrates AlphaZero-based reinforcement learning with Bayesian probabilistic inference to construct an intelligent decision support system for multi-agent environmental liability attribution. Our primary motivation is to solve the very difficult legal causality puzzles in environmental fields by making a Gestalt leap, offering more legitimate, intelligent and consistent solutions than those currently found in the literature. While this work does not exhaust the full landscape of such puzzles, its principal contribution is to stimulate further inquiry and open new horizons for computational legal reasoning. The framework introduces a Dynamic Causation Index (DCI) that quantifies each agent's simulated contribution to ecological harm and updates their posterior responsibility using Bayesian inference. AlphaZero models the actors' long-term strategic behavior within environmental and regulatory environments, while the Bayesian layer incorporates historical priors and likelihoods derived from simulation outcomes. This enables both counterfactual analysis and probabilistic responsibility estimation, overcoming key limitations in current environmental decision-making practices. We apply this framework to a hypothetical river pollution case study involving three industrial facilities, demonstrating how the model supports transparent, proportionate, and adaptive allocation of liability. The results show that Factory B bears the highest causal share (55.1%), followed by Factory A (37.5%) and Factory C (7.4%), based on their strategic leverage and posterior responsibility estimates. The results illustrate how strategic leverage and probabilistic confidence can be combined to enhance environmental governance and intervention planning. The proposed methodology offers a scalable and explainable approach to regulatory design and system-level environmental accountability, with potential applications across sustainability science, environmental law, and intelligent governance.},
}

Bayes Theorem
*Decision Support Techniques

@article {pmid42077975,
year = {2026},
author = {Zhang, ZS and Ding, Y and Cao, KJ and Guo, ZZ and Zhou, SX and Lu, ZP and Dong, JL},
title = {Urban building carbon emissions based on BIM-LCA-GIS.},
journal = {Frontiers in public health},
volume = {14},
number = {},
pages = {1713246},
pmid = {42077975},
issn = {2296-2565},
mesh = {China ; Humans ; *Geographic Information Systems ; *Carbon/analysis ; *Construction Materials ; *Environmental Monitoring/methods ; Carbon Footprint/statistics & numerical data ; Cities ; Urbanization ; },
abstract = {With the continuous advancement of China's urbanization process and building technologies, traditional cast-in-situ construction methods have become increasingly incompatible with the concepts of green and healthy development due to significant energy consumption and carbon emissions generated throughout their entire lifecycle, including material production, construction processes, and related upstream and downstream industrial activities, while the advantages of the prefabricated building model have become increasingly prominent in this context; to address the need for in-depth carbon emission analysis of prefabricated buildings, this paper develops an integrated carbon emission analysis model integrating Building Information Modeling (BIM), Life Cycle Assessment (LCA), and Geographic Information Systems (GIS), applies this model to conduct in-depth analysis of carbon emissions at each stage of the prefabricated building's lifecycle to acquire accurate and specific carbon emission data, and adopts three analytical methods, input-output analysis, and ecological footprint analysis-to perform spatial analysis on the collected data, specifically combining BIM models with the LCA framework to quantify and assess the impacts of different building materials and structural components on energy efficiency and the surrounding environment and using the three computational methods for spatial carbon emission analysis; this integrated model effectively achieves accurate quantification and in-depth analysis of carbon emissions at each lifecycle stage of prefabricated buildings, obtaining specific and reliable carbon emission data and clarifying the spatial distribution characteristics and influencing factors of carbon emissions through spatial analysis; the research findings thus provide valuable insights and practical references for future initiatives to promote low carbon and energy efficient building practices and advance the development of low-carbon buildings, while the established integrated analysis model overcomes the limitations of single-method analysis and improves the accuracy and comprehensiveness of carbon emission analysis for prefabricated.},
}

China
Humans
*Geographic Information Systems
*Carbon/analysis
*Construction Materials
*Environmental Monitoring/methods
Carbon Footprint/statistics & numerical data
Cities
Urbanization

@article {pmid42081716,
year = {2026},
author = {Eliasson, ET and Sutori, S and Mura, F and Ortiz, V and Catrambone, V and Hadlaczky, G and Todorov, I and Alfeo, AL and Cardi, V and Cimino, MGCA and Mioni, G and Raya, MA and Valenza, G and Carli, V and Gentili, C},
title = {Curiosity in a Novel Virtual Reality Scenario and Its Association With Symptoms of Depression: Observational Pilot Investigation.},
journal = {JMIR formative research},
volume = {10},
number = {},
pages = {e80120},
doi = {10.2196/80120},
pmid = {42081716},
issn = {2561-326X},
mesh = {Humans ; *Virtual Reality ; Pilot Projects ; Female ; Male ; *Exploratory Behavior/physiology ; Adult ; *Depression/psychology ; Young Adult ; Self Report ; Middle Aged ; },
abstract = {BACKGROUND: Curiosity plays a fundamental role in human learning, development, and motivation, and emerging evidence suggests that reduced curiosity is linked to poorer mental health outcomes, including depressive symptoms (DS). However, to date, the majority of curiosity research relies on self-report assessments and thus risks biased reporting. Virtual reality (VR), a novel tool increasingly used within mental health research and treatment, might represent a potent tool for offering ecologically valid insights into curiosity-driven behaviors while circumventing issues related to self-report assessments, including demand characteristics and recall bias.

OBJECTIVE: The study aimed to enhance the assessment of curiosity by using a novel VR environment and to examine its relevance to DS. Specifically, we tested 2 hypotheses using a novel VR environment: first, that curiosity, as assessed through spontaneous exploratory interactions and behaviors in VR, positively correlates with self-reported curiosity, and second, that VR-based curiosity is inversely associated with DS.

METHODS: This exploratory study used an observational design that included 100 volunteers. All participants completed self-reported assessments of DS and curiosity before engaging in a novel VR scenario. Although progression in the virtual environment required solving cognitive tasks, these were embedded as structural elements rather than framed as the primary objective. Instead, participants' free explorations and interactions with objects formed the basis for the 4 curiosity metrics used in this study. After VR exposure, participants completed a questionnaire assessing cybersickness symptoms.

RESULTS: Hypothesis 1 was not supported, as only one curiosity metric, namely object interactions, was positively associated with one aspect of curiosity relating to motivation to seek new knowledge and experiences. Further, diminishing significance after correction for multiple testing warranted caution. Results relating to hypothesis 2 indicated partial support, in that object interaction was significantly associated with DS while controlling for age, sex, and cybersickness levels. Sensitivity analyses showed no associations between object interactions and self-reported anxiety and stress symptoms.

CONCLUSIONS: VR may be a potent tool for assessing exploratory behaviors in a controlled, yet ecologically valid, environment that avoids issues related to self-report. However, whether such motivations translate to established curiosity constructs warrants further research. This study also provided preliminary insights into how assessing exploratory interactions in VR may be a promising avenue that could enhance the understanding of the etiology and assessment of DS-particularly its early stages.},
}

Humans
*Virtual Reality
Pilot Projects
Female
Male
*Exploratory Behavior/physiology
Adult
*Depression/psychology
Young Adult
Self Report
Middle Aged

@article {pmid42070741,
year = {2026},
author = {Medernach, JP and Aleithe, P and Sanchez, X and Memmert, D and Henz, J},
title = {The Priming Effect and its Impact on Sport Performance and Difficulty Judgment: Evidence From Olympic Bouldering.},
journal = {Psychology of sport and exercise},
volume = {},
number = {},
pages = {103147},
doi = {10.1016/j.psychsport.2026.103147},
pmid = {42070741},
issn = {1878-5476},
abstract = {INTRODUCTION: Priming refers to the psychological phenomenon whereby a prior stimulus modulates cognitive processes and behavioural responses. To date, perceptual-cognitive mechanisms through which priming influences sporting performance remain underexplored. Olympic Bouldering provides a compelling and ecologically valid context for investigating psychological priming, as it involves perceptual-cognitive processes sensitive to priming while offering robust performance indicators and a controllable experimental environment. This study aimed to advance theoretical and empirical understanding of psychological priming by examining the impact of manipulated difficulty labels, assigned to boulders (short climbing routes) and serving as primes, on climbers' performance outcomes and their perceived difficulty judgments (targets).

METHODS: Twenty-eight female climbers previewed and attempted four boulders that were equivalent in movement demands and difficulty, but presented with manipulated difficulty labels: B1 (labelled easier than actual difficulty), B2 (true difficulty), B3 (labelled harder than actual difficulty), and B4 (no difficulty label). Measures included climbing performance and perceived boulder difficulty.

RESULTS: Among the boulders included in the priming manipulation (B1-B3), climbing performance (successful completion, number of attempts) was lowest in B3, labelled as most difficult (negative priming), and highest in B1, labelled as easiest (positive priming). Although all four boulders were of identical difficulty, participants perceived B3 as most difficult and B1 as easiest.

CONCLUSION: Findings indicate that priming through manipulated difficulty labels can influence athletes' climbing performance and perceived boulder difficulty. The study provides empirical evidence that exposure to prime stimuli can activate pre-existing internal representations, modulating both procedural and expectancy processes, and ultimately shaping sporting performance.},
}

@article {pmid42071145,
year = {2026},
author = {Pina-Martins, F and Poiares-Oliveira, G and Oliveira, J and Pesquita, C},
title = {FAIR Omics Data Management: Overview, Challenges, and Best Practices.},
journal = {Advances in experimental medicine and biology},
volume = {1504},
number = {},
pages = {187-204},
pmid = {42071145},
issn = {0065-2598},
mesh = {Humans ; *Data Management/standards/methods ; *Genomics/standards ; *Computational Biology/standards/methods ; Computer Security ; Metadata/standards ; },
abstract = {This chapter provides a comprehensive overview of FAIR principles applied to omics data management, addressing key challenges in handling large-scale, heterogeneous datasets while promoting reproducibility, collaboration, and open science practices. It covers essential strategies including Data Management Plans (DMPs), file organization, metadata standards, ontologies, repository selection, interoperability protocols, and security measures for privacy and ethics compliance. Best practices are outlined for achieving Findable, Accessible, Interoperable, and Reusable data, with recommendations for continuous improvement to support cross-omics integration and long-term data stewardship.},
}

Humans
*Data Management/standards/methods
*Genomics/standards
*Computational Biology/standards/methods
Computer Security
Metadata/standards

@article {pmid42074365,
year = {2026},
author = {Seixas, AA and Chung, DP},
title = {Reintegrating the Human in Health: A Triadic Blueprint for Whole-Person Care in the Age of AI.},
journal = {International journal of environmental research and public health},
volume = {23},
number = {4},
pages = {},
doi = {10.3390/ijerph23040426},
pmid = {42074365},
issn = {1660-4601},
mesh = {Humans ; *Artificial Intelligence ; *Precision Medicine ; *Delivery of Health Care ; },
abstract = {Modern healthcare remains structurally and conceptually fragmented, with profound clinical and policy implications. At its root lies an ontological fracture: the prevailing biomedical model reduces patients to discrete biological systems (organs, biomarkers, and symptoms) detached from the psychological, social, and ecological contexts in which health and illness are experienced. This is compounded by epistemological fragmentation, where medical knowledge is compartmentalized into increasingly narrow specialties, limiting holistic understanding. These philosophical divisions manifest in downstream operational, informational, financial, and policy dysfunctions duplicative testing, misaligned incentives, disconnected care pathways, and population health failures. To address these multilevel fractures, we propose a unified architecture grounded in three interlocking components. First, the Precision and Personalized Population Health (P3H) framework offers a principle-based realignment toward care that is integrated, personalized, proactive, and population wide. P3H addresses the conceptual shortcomings of fragmented care by focusing on the full human trajectory across time, systems, and determinants. Second, General Purpose Technologies including artificial intelligence, biosensors, mobile diagnostics, and multimodal data systems enable the operationalization of whole-person care at scale, especially in low-resource settings. Third, the AI-WHOLE policy framework (Alignment, Integration, Workflow, Holism, Outcomes, Learning, and Equity) provides governance principles to guide ethical, equitable, and context-specific implementation. We argue that this triadic blueprint is particularly critical for Global South nations, where the lack of legacy infrastructure offers an opportunity for leapfrogging toward integrated, intelligent systems of care. Early models illustrate how policy-aligned, technology-enabled care rooted in whole-person principles can yield improvements in continuity, cost-efficiency, and chronic disease outcomes. This manuscript offers a systems-level strategy to overcome fragmentation and reimagine healthcare delivery, not only by refining clinical tools, but by redefining what it means to care for the human being in full.},
}

Humans
*Artificial Intelligence
*Precision Medicine
*Delivery of Health Care

@article {pmid42074397,
year = {2026},
author = {Abasilim, OR and Nwosu, KOS and Akintimehin, OO and Ezeigwe, OJ and Dimgba, OO and Lama, M and Njoku, AH and Okoye, NC and Obekpa, EO},
title = {Food Insecurity and Adolescent Obesity in the United States: A Social Ecological Analysis of Multi-Level Risk Factors and Structural Inequities.},
journal = {International journal of environmental research and public health},
volume = {23},
number = {4},
pages = {},
doi = {10.3390/ijerph23040458},
pmid = {42074397},
issn = {1660-4601},
mesh = {Humans ; Adolescent ; *Food Insecurity ; United States/epidemiology ; Female ; Male ; *Pediatric Obesity/epidemiology/etiology ; Child ; Risk Factors ; Cross-Sectional Studies ; Poverty ; },
abstract = {While the association between food insecurity and adolescent obesity is well-established, the mechanisms through which these co-occurring public health crises are linked remain inadequately understood. Using the Social Ecological Model as a theoretical framework, this study examines how individual (physical activity), interpersonal (household food security), community (poverty level, residence), and societal (race/ethnicity) factors interact to influence adolescent weight outcomes. Cross-sectional data from 37,425 adolescents aged 12-17 years in the 2022-2023 National Survey of Children's Health using weighted multinomial logistic regression with interaction terms were used. Adolescents experiencing nutrition insecurity (adequate quantity but poor-quality food) had 41% higher odds of obesity (adjusted odds ratio (aOR) = 1.41; 95% CI: 1.20-1.65), while those with food insecurity (insufficient quantity) had 48% higher odds (aOR = 1.48; 95% CI: 1.08-2.02) compared to food-secure peers. Significant effect modification emerged across ecological levels: poverty below the 200% federal poverty level (FPL) significantly amplified the food insecurity-obesity relationship (interaction p < 0.001), Hispanic and Black adolescents demonstrated 49% and 78% higher obesity odds, respectively, independent of household food and nutrition security status, and physical activity showed protective effects that varied by food security context (interaction p = 0.003). These findings underscore the necessity of multi-level interventions addressing structural inequities alongside individual behaviors to combat adolescent obesity in food-insecure populations effectively.},
}

Humans
Adolescent
*Food Insecurity
United States/epidemiology
Female
Male
*Pediatric Obesity/epidemiology/etiology
Child
Risk Factors
Cross-Sectional Studies
Poverty

@article {pmid42075709,
year = {2026},
author = {Purgatová, S and Mangová, B and Selyemová, D and Krumpálová, Z and Chvostáč, M and Didyk, YM and Rajská, P and Kazimírová, M and Rusňáková Tarageľová, V},
title = {Sympatric Occurrence of Five Exophilic Tick Species in the Levice Region (Southwestern Slovakia) and Their Infection with Tick-Borne Pathogens.},
journal = {Pathogens (Basel, Switzerland)},
volume = {15},
number = {4},
pages = {},
doi = {10.3390/pathogens15040382},
pmid = {42075709},
issn = {2076-0817},
support = {APVV 22-0372//Slovak Research and Development Agency/ ; },
mesh = {Animals ; Slovakia/epidemiology ; *Tick-Borne Diseases/epidemiology/microbiology/parasitology/veterinary ; Sheep/parasitology ; Babesia/isolation & purification/genetics ; Sympatry ; Rickettsia/isolation & purification/genetics ; Theileria/isolation & purification/genetics ; *Ticks/microbiology/parasitology ; *Tick Infestations/veterinary/epidemiology/parasitology ; },
abstract = {Among the 24 tick species documented in Slovakia, Ixodes ricinus is the most widespread and abundant. In some sites, 2-5 epidemiologically important tick species co-occur. Such sites represent hotspots for studying the co-circulation of tick-borne pathogens. Sympatric occurrence of five exophilic species (I. ricinus, Dermacentor reticulatus, D. marginatus, Haemaphysalis concinna, and H. inermis) was confirmed in the environs of the Žemberovce village (Levice region, south-western Slovakia). Here, the seasonal activity and abundance of questing ticks and the tick infestation of game and sheep were investigated. Questing ticks, spleens of game, and ticks removed from game and sheep were examined for the presence of tick-borne pathogens (Babesia spp., Theileria spp., Anaplasma phagocytophilum, Rickettsia spp., Borrelia burgdorferi s.l., and Borrelia miyamotoi) by molecular methods. Among the questing ticks, I. ricinus prevailed. Presence of Babesia crassa, B. microti, Rickettsia helvetica, R. raoultii, A. phagocytophilum, Borrelia afzelii, B. garinii, B. valaisiana, B. burgdorferi sensu stricto and B. miyamotoi was detected. Dermacentor marginatus, I. ricinus and H. concinna were collected from sheep. They were infected with A. phagocytophilum, A. ovis, R. slovaca, and R. raoultii. Anaplasma phagocytophilum was detected in all examined red deer and roe deer and in 55.6% of wild boar. All cervids were positive for Theileria spp. Infestation of game with all five tick species, with a predominance of I. ricinus, was confirmed. In these ticks, A. phagocytophilum, R. helvetica, R. raoultii, Babesia sp. hc-hlj212, B. crassa, B. microti, Babesia spp. and B. miyamotoi were detected. This study confirmed the presence of B. crassa in Slovakia for the first time. The investigated area, with the co-occurrence of five exophilic tick species and a wide spectrum of tick-borne pathogens, represents an epidemiologically important hotspot with the risk of infections of humans and domestic animals.},
}

Animals
Slovakia/epidemiology
*Tick-Borne Diseases/epidemiology/microbiology/parasitology/veterinary
Sheep/parasitology
Babesia/isolation & purification/genetics
Sympatry
Rickettsia/isolation & purification/genetics
Theileria/isolation & purification/genetics
*Ticks/microbiology/parasitology
*Tick Infestations/veterinary/epidemiology/parasitology

@article {pmid42076550,
year = {2026},
author = {Khazaei, M and Raeisi, K and Fiedler, P and Croce, P and Zappasodi, F and Comani, S},
title = {Suppressing Non-Stationary Motion Artefacts in Mobile EEG Using Generalized Eigenvalue Decomposition.},
journal = {Sensors (Basel, Switzerland)},
volume = {26},
number = {8},
pages = {},
doi = {10.3390/s26082440},
pmid = {42076550},
issn = {1424-8220},
support = {101007521//European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant/ ; 01QE2316C, 13GW0721C//German Federal Ministry of Research, Technology and Space/ ; 57712119//German Academic Exchange Service/ ; },
mesh = {Humans ; *Electroencephalography/methods ; Artifacts ; Signal Processing, Computer-Assisted ; *Brain/physiology ; Motion ; Algorithms ; Movement/physiology ; Male ; },
abstract = {Mobile EEG enables investigating brain activity during real-world behaviour, but remains susceptible to motion artefacts, limiting signal interpretability and the use of advanced analytical techniques. Methods developed for removing motion-related artefacts induced by periodic activity like cycling, walking or juggling showed degraded performance with increasing movement variability and speed. To fill this gap, we developed a method based on generalized eigenvalue decomposition (GED) to identify and suppress highly variable, non-periodic-especially transient-artefacts due to very rapid, free full body movements of different types, as they occur during sports practice. By leveraging the contrast between covariance matrices of artefactual and resting-state EEG segments, this approach isolates motion-related components for removal during multichannel EEG signal reconstruction. The method was validated on two ecological datasets featuring stereotyped head and body movements and dynamic table tennis. Comparison with state-of-the-art technique showed superior performance of our method in terms of signal-to-error ratio (SER), artefact-to-residue ratio (ARR), brain spectral power preservation and computation time. Sensitivity analysis was applied to demonstrate the method's robustness to parameter changes. These findings highlight the potential of the proposed method as a robust, generalizable approach for motion artefact suppression in mobile EEG, particularly when applied in extreme recording conditions like during active sports activity.},
}

Humans
*Electroencephalography/methods
Artifacts
Signal Processing, Computer-Assisted
*Brain/physiology
Motion
Algorithms
Movement/physiology
Male

@article {pmid42059556,
year = {2026},
author = {Dunham, SJB and Willkeen, GA and Darby, B and Corley, JM and Hahn, A and Klapper, I and Bean, HD and Caverly, LJ and Thornton, CS and Martin, C and Quinn, RA and Widder, S and Bailey, BA and Wagner, BD and Garg, N and Planet, PJ and Hunter, RC and LiPuma, JJ and Rohwer, F and Whiteson, KL},
title = {The Guild Model of CF Airway Microbial Ecology.},
journal = {mBio},
volume = {},
number = {},
pages = {e0366825},
doi = {10.1128/mbio.03668-25},
pmid = {42059556},
issn = {2150-7511},
abstract = {Ecological guilds are groups of organisms that utilize the same class of resources and occupy similar niches, regardless of their taxonomic identities. Here we propose the Guild Model for Cystic Fibrosis Airway Microbial Ecology, which considers the ecological function and wider role of each microbe in the ecosystem. This model consists of four functional guilds: (i) "Brewers" metabolize host-derived substrates (e.g., mucins) and produce fermentation products; (ii) "Drunkards" exploit the metabolic niche built by Brewers, consuming fermentation products and secreting exopolysaccharides to build biofilms; (iii) "Putrifiers" produce toxic compounds causing inflammation and tissue necrosis; and (iv) "Nihilists" are specialist pathogens characterized by intracellular or lytic life cycles and cytotoxin production. By focusing on microbial function and the broader community context, this model offers a refined framework for interpreting cystic fibrosis airway ecology. Although developed for CF, the Guild Model is adaptable to other diseases influenced by microbial ecology.},
}

@article {pmid42061074,
year = {2026},
author = {Yang, C and Liu, F and Zhang, C and Dong, J},
title = {Dual-functional carboxymethyl-β-cyclodextrin for enhanced peroxydisulfate/Fe[2+] removal of tetrachloroethylene in simulated groundwater.},
journal = {Journal of environmental management},
volume = {406},
number = {},
pages = {129733},
doi = {10.1016/j.jenvman.2026.129733},
pmid = {42061074},
issn = {1095-8630},
abstract = {The removal of contaminants by peroxydisulfate (PDS)/Fe[2+] system is a promising groundwater decontamination technology, while the non-recyclability of Fe[2+] and the restricted mass transfer of contaminants in water limit the decontamination efficiency. Here, we developed carboxymethyl-β-cyclodextrin (CM-β-CD) to chelate Fe[2+] coupled with enhancing the solubization of contaminants in groundwater for efficient decontamination. Results showed that a 4.60-fold enhancement in the perchloroethylene (PCE) degradation rate following the addition of 1 g/L CM-β-CD to the PDS/Fe[2+] system. The ternary complex formed by CM-β-CD, Fe[2+] and PCE was confirmed via ultraviolet absorption spectra and nuclear magnetic resonance hydrogen spectrum. Electron paramagnetic resonance, complemented by chemical probe and radical quenching experiments, identified singlet oxygen ([1]O2), high-valent iron (Fe(IV)), and hydroxyl radicals ([•]OH) as the dominant reactive species in the PDS/Fe[2+]/CM-β-CD system, with relative contributions to PCE degradation quantified at 30.4%, 26.2%, and 18.1%, respectively. The presence of humic acid and common inorganic ions showed negligible effects on PCE degradation efficiency. The primary PCE degradation intermediate is dichloromethane, mediated by [1]O2, Fe(IV), and •OH, with mineralization occurring via dechlorination pathways. This study developed an environmentally sustainable remediation strategy utilizing CM-β-CD as a dual-functional agent for simultaneous Fe[2+] chelation and contaminant solubilization, enabling efficient groundwater decontamination.},
}

@article {pmid42056695,
year = {2026},
author = {Kim, KM and Hwang, K},
title = {Phylogenomic Tree Reconstruction from Bacterial Genomes.},
journal = {Methods in molecular biology (Clifton, N.J.)},
volume = {2981},
number = {},
pages = {221-233},
pmid = {42056695},
issn = {1940-6029},
mesh = {*Phylogeny ; *Genome, Bacterial ; *Genomics/methods ; *Bacteria/genetics/classification ; *Computational Biology/methods ; Software ; Databases, Genetic ; Gene Transfer, Horizontal ; },
abstract = {The recent, rapid expansion of available prokaryotic genomes has fueled significant advancements in phylogenomics within microbial ecology and evolution. However, comprehensive protocols for reconstructing phylogenomic trees from bacterial genomes remain scarce. To address this gap, we present a series of essential bioinformatics steps. This protocol begins with setting up a Docker environment to ensure consistent implementation across different operating systems. We demonstrate phylogenomic tree reconstruction using the Genome Taxonomy Database and its toolkits with five test genomes, which were retrieved from the NCBI database, quality-checked with CheckM, aligned using GTDB-Tk, and analyzed for tree reconstruction with RAxML. Genome-level phylogenetic analyses are often complicated by gene duplication, horizontal gene transfer, and computational demands that increase with the number of taxa. We discuss practical strategies for addressing these issues and highlight the value of orthologous gene concatenation in generating accurate phylogenomic trees.},
}

*Phylogeny
*Genome, Bacterial
*Genomics/methods
*Bacteria/genetics/classification
*Computational Biology/methods
Software
Databases, Genetic
Gene Transfer, Horizontal

@article {pmid42056701,
year = {2026},
author = {Hernández-Morales, R and Luna, CCG and Lazcano, A and Becerra, A},
title = {Protein Architecture Comparisons and the Reconstruction of the Last Universal Common Ancestor (LUCA).},
journal = {Methods in molecular biology (Clifton, N.J.)},
volume = {2981},
number = {},
pages = {309-322},
pmid = {42056701},
issn = {1940-6029},
mesh = {Phylogeny ; *Evolution, Molecular ; Archaea/genetics ; *Computational Biology/methods ; Bacteria/genetics ; *Proteins/chemistry/genetics ; },
abstract = {The Last Universal Common Ancestor (LUCA) represents an early stage of evolution that can be studied using phylogenetic and bioinformatic methods. Research efforts focus on reconstructing LUCA's genome, proteome, metabolism, habitat, ecological context, and timeline. A novel method developed by our group identifies structural homologs by comparing protein architectures, defined as the sequential arrangement of homologous domains within a protein. In our approach, proteins are considered homologous if they share identical domain types in the same N-to-C-terminal order. Homologous proteins with the same architecture found in the primary branches of both Bacteria and Archaea are potential candidates for those present in LUCA.},
}

Phylogeny
*Evolution, Molecular
Archaea/genetics
*Computational Biology/methods
Bacteria/genetics
*Proteins/chemistry/genetics

@article {pmid42057267,
year = {2026},
author = {Dolk, H and Damase-Michel, C and Morris, J and Neville, A and Garne, E and Jordan, S and Rissmann, A and Coi, A and Folan, D and Broekstra, D and Broughan, JM and Bruneau, L and Cavero-Carbonell, C and den Hond, E and Gatt, M and Gissler, M and Khoshnood, B and Bielenska, AL and Nordeng, H and Odak, L and O'Mahony, M and Perthus, I and Richardson, JL and Rouget, F and Sichitiu, J and Tucker, D and Zymak-Zakutnya, N and Loane, M},
title = {The EUROmediCAT Network and Databases: A Resource for Pharmacovigilance in Pregnancy.},
journal = {Pharmacoepidemiology and drug safety},
volume = {35},
number = {5},
pages = {e70360},
doi = {10.1002/pds.70360},
pmid = {42057267},
issn = {1099-1557},
support = {//Seventh Framework Programme/ ; //Innovative Medicines Initiative/ ; //Ulster University/ ; },
mesh = {*Pharmacovigilance ; Pregnancy ; Humans ; Female ; *Databases, Factual/statistics & numerical data ; *Abnormalities, Drug-Induced/epidemiology/etiology ; Europe/epidemiology ; Registries ; Adverse Drug Reaction Reporting Systems/statistics & numerical data ; Pregnancy Trimester, First ; *Drug-Related Side Effects and Adverse Reactions/epidemiology ; Pharmacoepidemiology/methods ; },
abstract = {BACKGROUND: The evidence gap relating to the risk of congenital anomalies (CA) associated with first trimester medication exposure in pregnancy is well recognized.

AIMS: We describe the EUROmediCAT network and databases, and the methodological approach to pregnancy pharmacovigilance.

MATERIAL AND METHODS: Multidisciplinary expertise includes CA diagnosis and epidemiology, pharmacoepidemiology, pharmacology and teratology. The EUROmediCAT central database comprises standardized data from 19 EUROCAT CA registries in 14 countries, including more than 40 000 CA cases 1995-2021 with first trimester medication exposure data recorded, and a population coverage of 14.6 million births, growing by more than 650 000 births per year. The distributed database enables federated data analysis across eight countries which can link data from CA registries to electronic healthcare data, with population coverage of up to 900 000 births per year for linkage to maternal prescriptions, of which 300 000 births per year for linkage also to data on all births.

RESULTS: The databases have enabled a variety of study designs: case-malformed control studies, cohort studies, disease cohort studies, signal detection studies, prevalence and ecological studies, and medication utilization studies.

DISCUSSION: A key strength is that studies of CA risk can address accurately the specificity of risk by type of CA.

CONCLUSION: EUROmediCAT presents a unique data and expert resource for tackling the enormous evidence gap regarding the safety of medication during pregnancy.},
}

*Pharmacovigilance
Pregnancy
Humans
Female
*Databases, Factual/statistics & numerical data
*Abnormalities, Drug-Induced/epidemiology/etiology
Europe/epidemiology
Registries
Adverse Drug Reaction Reporting Systems/statistics & numerical data
Pregnancy Trimester, First
*Drug-Related Side Effects and Adverse Reactions/epidemiology
Pharmacoepidemiology/methods

@article {pmid42057917,
year = {2026},
author = {Szentiványi, T and Bruszniczky, B and Biró, Z and Katona, K and Klein, Á and Bende, A and Bánáti, L and Vass, G and Lehotzky, P and Kovács, D and Földvári, G and Csivincsik, Á and Nagy, G and Nagy, RR and Miklós, M and Szabadi, KL and Szabó, ÉS and Garamszegi, LZ},
title = {Unwelcome guests: Nematodes of zoonotic and animal health importance in native and invasive carnivores of Hungary.},
journal = {Current research in parasitology & vector-borne diseases},
volume = {9},
number = {},
pages = {100380},
pmid = {42057917},
issn = {2667-114X},
abstract = {Wild carnivores are important reservoirs of parasitic nematodes, several of which have veterinary and zoonotic significance. In Europe, the role of invasive carnivores in parasite circulation remains poorly understood. Here, we screened 371 individuals of six wild carnivore species from Hungary (red foxes, badgers, golden jackals, raccoons, raccoon dogs, and beech martens), using molecular markers (cox1 and S12), and detected five nematode parasites: Dirofilaria immitis, Crenosoma vulpis, Angiostrongylus vasorum, Thelazia callipaeda, and Spirocerca lupi. The highest prevalence was observed in badgers (32.0%) and red foxes (15.7%), while invasive raccoons also showed a relatively high infection rate (13.2%). Dirofilaria immitis was one of the most common nematode species detected: it was found in four host species, including the first confirmed cases in Hungarian badgers and invasive raccoons, extending the known host range of this parasite in central Europe. Importantly, T. callipaeda was recorded in red foxes and an invasive raccoon dog, representing the first invasive host records of this zoonotic eyeworm in Hungary. Crenosoma vulpis was identified in raccoons, suggesting invasive species may act as incidental carriers of endemic parasites. Both C. vulpis and D. immitis showed low host specificity. These findings indicate that invasive carnivores, particularly raccoons, may harbour unexpectedly high prevalence and play a greater role in local parasite networks than previously assumed. Our results highlight the epidemiological significance of both native and invasive carnivores in sustaining nematodes of zoonotic and veterinary importance in central Europe, stressing the need for continued surveillance in wild carnivores.},
}

@article {pmid42058737,
year = {2026},
author = {Liu, Q and Zhou, L and Yang, W and Liu, M and Liu, J},
title = {Associations between environmental exposure, lifestyle, and the risk of respiratory infections among 67890 adults: A population-based cohort analysis using UK Biobank data.},
journal = {Global health research and policy},
volume = {11},
number = {1},
pages = {43-50},
pmid = {42058737},
issn = {2397-0642},
mesh = {Humans ; Male ; Female ; *Life Style ; United Kingdom/epidemiology ; Middle Aged ; *Respiratory Tract Infections/epidemiology ; *Environmental Exposure/adverse effects/statistics & numerical data ; Adult ; Cohort Studies ; Biological Specimen Banks ; Aged ; Risk Factors ; Proportional Hazards Models ; UK Biobank ; },
abstract = {BACKGROUND: Respiratory infections pose a major global health burden. While green spaces are generally thought to benefit respiratory health, research often overlooks the roles of private gardens and the interaction between environmental exposures and lifestyle behaviors. This study uses UK Biobank data to examine the integrated associations of environmental exposures, lifestyle habits, and respiratory infections.

METHODS: We conducted a large-scale cohort analysis based on UK Biobank data. Environmental exposures were assessed using geospatial data linked to residential addresses, including green space and domestic garden percentage (within 300 m and 1000 m buffers), natural environment accessibility, and coastal proximity. Cox proportional hazards regression models were used to estimate hazard ratios (HRs), adjusting for demographic characteristics (sex, age, BMI), socioeconomic status, and lifestyle behaviors (insomnia, smoking status, alcohol consumption, and physical activity).

RESULTS: A total of 46,288 healthy individuals and 21,602 patients with respiratory infection were included. Results revealed a scale-dependent "dual effect" of green space: higher greenspace percentage within a 300 m buffer was protective (HR=0.93, 95% CI: 0.88-0.99), whereas within a 1000 m buffer, it was associated with an increased risk (HR=1.10, 95% CI: 1.02-1.19). Domestic gardens and natural environments at 1000 m were generally protective. Greater distance to the coast was associated with a lower risk of most respiratory infections but a potentially higher risk of tuberculosis. Male gender, older age, higher BMI, smoking, and insomnia were risk factors, while physical activity and alcohol consumption were associated with lower risks.

CONCLUSIONS: This study provides novel insights into the complex interplay between environmental exposures and lifestyle factors. The divergence between the protective effects of immediate greenness (300 m) and the risks associated with broader vegetation coverage (1000 m) suggests a trade-off between accessibility benefits and potential exposure to aeroallergens. Public health strategies should prioritize "low-allergen" urban planning and promote healthy lifestyles-particularly physical activity and smoking cessation-to mitigate respiratory infection risks.},
}

Humans
Male
Female
*Life Style
United Kingdom/epidemiology
Middle Aged
*Respiratory Tract Infections/epidemiology
*Environmental Exposure/adverse effects/statistics & numerical data
Adult
Cohort Studies
Biological Specimen Banks
Aged
Risk Factors
Proportional Hazards Models
UK Biobank

@article {pmid42018599,
year = {2026},
author = {Li, Y and Nielsen, BF and Levin, SA and Te Velthuis, AJW and Grenfell, BT},
title = {Spatio-temporal modelling of in vitro influenza A virus infection: The impact of defective interfering particles on the type I interferon response.},
journal = {PLoS computational biology},
volume = {22},
number = {4},
pages = {e1014198},
doi = {10.1371/journal.pcbi.1014198},
pmid = {42018599},
issn = {1553-7358},
mesh = {*Interferon Type I/immunology/metabolism ; *Influenza A virus/immunology/physiology/genetics/pathogenicity ; Humans ; *Defective Viruses/immunology ; Virus Replication/immunology ; *Influenza, Human/immunology/virology ; *Models, Biological ; Spatio-Temporal Analysis ; Computational Biology ; Animals ; Immunity, Innate ; Stochastic Processes ; },
abstract = {Defective interfering particles (DIPs) are incomplete viral genomes that modulate infection by competing with wild-type viruses and activating the innate immune response. Activation of the immune response leads to the production of cytokines and chemokines, including type I interferon (IFN), which restricts viral growth and may cause cell death. How DIPs interact with type I interferon (IFN) in spatially structured environments remains unclear. Focusing here on influenza A viruses, we developed a spatially explicit, stochastic model of in vitro viral infection that integrates virus and DIP replication, IFN signalling, and alternative dispersal modes. We find that: (1) our model captures the ring-like and patchy plaque morphologies observed experimentally; (2) IFN production peaks at an intermediate DIP ratio, reflecting a trade-off between early immune activation and sufficient co-infection; and (3) even a small fraction of long-range spread by virus and DIPs enables escape from the immune-based containment despite long-range IFN diffusion; this causes stronger antiviral responses but earlier peaks in virus egress at similar levels of cell loss. The model is available as an interactive platform: https://shiny-spatial-infection-app-production.up.railway.app/.},
}

*Interferon Type I/immunology/metabolism
*Influenza A virus/immunology/physiology/genetics/pathogenicity
Humans
*Defective Viruses/immunology
Virus Replication/immunology
*Influenza, Human/immunology/virology
*Models, Biological
Spatio-Temporal Analysis
Computational Biology
Animals
Immunity, Innate
Stochastic Processes

@article {pmid42025279,
year = {2026},
author = {Shen, A and Shen, W and Zhu, Y and Zeng, J},
title = {Multi-omics investigation of the molecular response of typical bloom-forming species Prorocentrum shikokuense to stoichiometric phosphorus limitation under a high nitrogen-to-phosphorus ratio.},
journal = {Marine environmental research},
volume = {218},
number = {},
pages = {108071},
doi = {10.1016/j.marenvres.2026.108071},
pmid = {42025279},
issn = {1879-0291},
mesh = {*Phosphorus/metabolism ; *Nitrogen/metabolism/analysis ; *Dinoflagellida/physiology/genetics ; *Eutrophication ; China ; Phytoplankton ; Transcriptome ; Multiomics ; },
abstract = {Nitrogen and phosphorus are essential nutrients for marine phytoplankton, with their ratio critically influencing ecosystem dynamics. The high nitrogen-to-phosphorus (N/P) ratio in the East China Sea (ECS) results in stoichiometric phosphorus limitation, which is a primary constraint on phytoplankton growth. Nevertheless, the dinoflagellate Prorocentrum shikokuense can form persistent, large-scale blooms even when dissolved inorganic phosphorus concentrations are low. The molecular mechanisms behind its adaptation to stoichiometric P limitation under high N/P ratios remain unclear. This study applied multi-omics analyses to investigate the response of P. shikokuense to stoichiometric P limitation under a high N/P ratio. We identified 431 differentially expressed genes (DEGs: 139 up, 292 down), 617 differentially expressed proteins (DEPs: 135 up, 482 down), and 217 differentially accumulated metabolites (DAMs: 51 up, 166 down). Integrated analysis revealed 61 metabolic pathways common to at least two omics layers. Key enriched pathways included photosynthesis, oxidative phosphorylation, nucleotide metabolism, and nitrogen metabolism. Pathways related to genetic information processing were downregulated, and energy metabolism was constrained. This subsequently suppressed nitrogen transport, assimilation, allocation, and secondary metabolism. In summary, these results elucidates the transcriptional, proteomic, and metabolic adjustments enabling P. shikokuense to thrive under stoichiometric P limitation based on a high N/P ratio. These findings provide a scientific basis for understanding its bloom dynamics in the ECS waters subject to stoichiometric P limitation under high N/P ratios.},
}

*Phosphorus/metabolism
*Nitrogen/metabolism/analysis
*Dinoflagellida/physiology/genetics
*Eutrophication
China
Phytoplankton
Transcriptome
Multiomics

@article {pmid42047788,
year = {2026},
author = {Gambetta Vianna, J and Ceccardi, E and Benedetti, B and Oh, JK and Di Carro, M and Pizzini, S and Magi, E},
title = {Assessing emerging contaminants in Antarctic benthic marine fauna: a dual mass spectrometry investigation combining targeted and suspect screening approaches.},
journal = {Analytical and bioanalytical chemistry},
volume = {},
number = {},
pages = {},
pmid = {42047788},
issn = {1618-2650},
support = {PNRA18_00216-B2//Ministero dell'Università e della Ricerca, National Program of Research in Antarctica, Italy/ ; },
abstract = {Antarctica hosts a highly endemic and diverse benthic marine fauna. Despite this biodiversity, the Antarctic marine food web remains structurally simple, rendering the ecosystem particularly vulnerable to environmental stressors. Benthic organisms, due to their sedentary nature, long lifespans, and close interaction with the sediment-water interface, are widely regarded as effective sentinels of ecological change. In this study, we extended a previously validated QuEChERS-based extraction protocol, originally developed for Adamussium colbecki organisms, to assess its applicability across additional Antarctic benthic taxa, including Sphaerotylus antarcticus, Odontaster validus, Trematomus bernacchii, and Laternula elliptica. The extraction method was used in combination with LC-MS/MS analysis for the determination of emerging contaminants in both targeted and suspect screening modes. Method performance was evaluated for 23 targeted emerging contaminants (ECs), yielding recovery rates of 58-116% and matrix effects between 62 and 108% for most compounds, confirming the method's suitability for taxonomically diverse matrices. Samples collected during Antarctic expeditions from 2018 to 2022 revealed the presence of multiple ECs, including perfluorooctanoic acid (PFOA), caffeine, pharmaceuticals and personal care products (PPCPs), and UV filters. Complementarily, a preliminary suspect screening via high-resolution mass spectrometry was attempted, revealing the potential presence of a broader spectrum of drugs, PPCPs, and lifestyle-related compounds in all studied species. This work represents one of the first applications of a QuEChERS-based analytical framework for ECs detection in Antarctic marine fauna, offering a reliable approach for long-term contaminant monitoring in one of the planet's most fragile ecosystems.},
}

@article {pmid42050104,
year = {2026},
author = {Rubin, L and Nowack, R and Lang, F and Stiasny, P and Puhlmann, H},
title = {Deadwood effects on dissolved organic carbon in forest soils depend on bedrock type, tree species, and microclimate.},
journal = {Scientific reports},
volume = {16},
number = {1},
pages = {},
pmid = {42050104},
issn = {2045-2322},
abstract = {Deadwood plays an important role in the forest carbon cycle by supplying dissolved organic carbon to the underlying soils. Yet, the extent to which this effect varies across different site conditions remains insufficiently understood. We monitored dissolved organic carbon at multiple soil depths beneath European beech and Norway spruce logs at sites with contrasting bedrock types over 2.5 years, comparing them with adjacent control plots. Concentrations were consistently elevated beneath deadwood, but the magnitude of the increase varied with bedrock type, tree species, and depth, and was influenced by soil temperature and moisture. Differences between deadwood and control were minor beneath the forest floor but pronounced in the upper mineral soil (15 cm), with the strongest increase (+ 90%) observed at the silicate site. When separating by tree species, this increase was driven by beech deadwood, while spruce showed little effect. At the silicate site, concentrations declined markedly between 15 and 30 cm, suggesting enhanced retention or processing in deeper layers. The effect of soil moisture on DOC was similar between deadwood and control plots, but temperature effects differed. These results indicate that the contribution of deadwood to soil carbon inputs is context-dependent, varying with tree species and soil properties.},
}

@article {pmid42053508,
year = {2026},
author = {Tandon, D and De Farias, TM and Allard, PM and Defossez, E},
title = {METRIN-KG: A knowledge graph integrating plant metabolites, traits, and biotic interactions.},
journal = {GigaScience},
volume = {},
number = {},
pages = {},
doi = {10.1093/gigascience/giag051},
pmid = {42053508},
issn = {2047-217X},
abstract = {BACKGROUND: In recent years, biodiversity data management has emerged as a critical pillar in global conservation efforts. Today, the ability to efficiently collect, structure, and analyze biodiversity data is central to breakthroughs in conservation, drug development, disease monitoring, ecological forecasting, and agri-tech innovation. However, due to the vastness and heterogeneity of biodiversity data, it is often confined to databases for specific research areas in isolated formats and disconnected from other relevant resources. Crucial components of such data in kingdom Plantae comprise of metabolomes-the vast array of compounds produced by plants; traits-measurable characteristics of plants that influence their growth, survival, and reproduction, and that affect ecosystem processes; and biotic interactions-relationships of plants with other living organisms, affecting the ecosystem functions.

RESULTS: In this work, we present METRIN-KG (MEtabolomes, TRaits, and INteractions-Knowledge Graph) a powerful data resource simplifying the integration of diverse and heterogeneous data resources such as plant metabolomes, traits, and biotic interactions.

CONCLUSIONS: The proposed knowledge graph provides an interface to interactively search for data relating plant metabolomes, traits, and interactions. This, in turn, will facilitate development of research questions in life-sciences. In this context, we provide representative case studies on how to frame queries that can be used to search for relevant data in the knowledge graph.},
}

@article {pmid42055456,
year = {2026},
author = {Bohling, SM and Musharoff, S and Gunn, LH},
title = {Advances and opportunities for computational interrogation of plant proteins.},
journal = {The Plant journal : for cell and molecular biology},
volume = {126},
number = {3},
pages = {e70899},
doi = {10.1111/tpj.70899},
pmid = {42055456},
issn = {1365-313X},
support = {DE-SC0024175//U.S. Department of Energy/ ; },
mesh = {*Plant Proteins/metabolism/genetics/chemistry ; *Computational Biology/methods ; *Plants/metabolism/genetics ; },
abstract = {Plants exhibit remarkable biochemical and physiological diversity, and are capable of adapting to a wide range of environmental conditions and stresses. This complexity makes them essential systems for understanding how life responds to a changing climate. Plant proteins are the molecular engines that carry out the reactions, signalling and regulation underlying these adaptive processes. However, studying plant proteins remains constrained by limited experimental throughput and the challenges of genetic manipulation, which vary widely across species. While synthetic biology and heterologous expression systems have expanded opportunities to investigate plant proteins, in planta studies are still limited by the availability and efficiency of genetic transformation methods. Computational approaches offer a powerful complement to experimental research by generating high-throughput, testable hypotheses that can accelerate discovery of plant protein function. In recent years, the power, versatility and ease of use of computational tools for protein research have expanded dramatically. These methods now enable detailed predictions of protein structure, dynamics and interactions, as well as insights into their evolutionary history and mechanistic function. In this review, we highlight the expanding computational toolkit for plant protein analysis, emphasising both established and emerging approaches. We summarise recent successes where computational methods have provided key biological insights into plant protein function and highlight the potential of such methods for scientific discovery in plant research. By integrating computation with experimentation, plant biology can overcome current limitations to studying plant proteins and move more rapidly toward a mechanistic understanding of plant processes, enabling advances in agriculture, ecology and climate resilience.},
}

*Plant Proteins/metabolism/genetics/chemistry
*Computational Biology/methods
*Plants/metabolism/genetics

@article {pmid42056177,
year = {2026},
author = {Agrawal, N and Mahrishi, M and Gupta, MK and Bohra, MK},
title = {Large scale multi-class pest image classification using structurally adapted DenseNet architecture.},
journal = {Scientific reports},
volume = {},
number = {},
pages = {},
doi = {10.1038/s41598-026-49685-8},
pmid = {42056177},
issn = {2045-2322},
abstract = {The United Nations' Sustainable Development Goals, SDG 12: Responsible Consumption and Production, and SDG 13: Climate Action highlight the importance of environmental conservation and reducing pesticide use. Early and accurate pest identification is essential for implementing targeted pest control measures, which helps reduce unnecessary and incorrect pesticide use. While effective pest recognition and classification are crucial for ecological research and biodiversity conservation, traditional methods remain labor-intensive, time-consuming, and dependent on experts. Several deep learning techniques have been introduced in recent years, leading to more efficient and accurate identification and classification of crop pests. This research presents a structurally adapted DenseNet model for multi-class pest image classification based on dense connections. The model is fine-tuned through hyperparameters involving dense blocks and transition layers to perform consistently across three different datasets, including the IP102 dataset, which contains over 75,000 images of 102 pest species. The study also addresses dataset imbalance to prevent biased outcomes by deep learning models. The proposed structurally adapted model for fine-grained classification achieves 82.69% accuracy and 81.45% F1 score on the IP102 dataset, complementing existing advanced methods.},
}

@article {pmid41373417,
year = {2025},
author = {Hu, Y and Jiang, G and Wang, J and He, H and Liu, L and Du, P and Li, H and Wang, F and Xie, Q},
title = {Genome-Wide Identification and Hormone-Induced Expression Analysis of the Anthocyanidin Reductase Gene Family in Sainfoin (Onobrychis viciifolia Scop.).},
journal = {International journal of molecular sciences},
volume = {26},
number = {23},
pages = {},
pmid = {41373417},
issn = {1422-0067},
support = {2022xjkkk0503//The third comprehensive scientific expedition project in Xinjiang/ ; 23CB008-01//Xinjiang Construction Corps Youth Science and Technology Innovation Talent Project/ ; 2024DA030//Xinjiang Construction Corps Science and Technology Plan Basic Research Project/ ; 2023AB070//Xinjiang Construction Corps Science and Technology Plan Key Areas of Science and Technology Research Plan./ ; },
mesh = {*Genome, Plant ; *Gene Expression Regulation, Plant/genetics ; *Anthocyanins/metabolism ; Oxylipins/chemistry ; Abscisic Acid/chemistry ; Cyclopentanes ; Gene Expression Profiling ; Protein Domains ; Amino Acid Motifs ; Plant Leaves ; Plant Stems ; Plant Roots ; Computational Biology ; *Hormones/chemistry ; *Fabaceae/enzymology ; Acetates ; },
abstract = {Sainfoin (Onobrychis viciifolia Scop.) is an important legume forage. Its anthocyanidin reductase (ANR) catalyzes the conversion of anthocyanins to epicatechins. This conversion reaction is not only a key step in the biosynthesis of proanthocyanidins (PAs) but also directly influences both forage quality and stress resistance. Here, we systematically identified 67 ANR gene family members in autotetraploid sainfoin for the first time. Using bioinformatics approaches, we analyzed gene structure, conserved domains, motifs, and cis-regulatory elements of the identified ANR genes. In this study, phylogenetic analysis revealed that the ANRs clustered into 11 distinct clades, with genes within the same clade predominantly originating from closely related species within the same family. Significant collinearity with Arabidopsis thaliana, Glycine max, Cicer arietinum, and Medicago truncatula further revealed the conserved evolutionary path of this gene family. RT-qPCR analysis showed differential expression patterns of OvANRs in root, stem, and leaf tissues. For instance, OvANR19 was significantly induced by abscisic acid (ABA) and methyl jasmonate (MeJA), with its expression upregulated by 79.7-fold and 3.8-fold in roots and by 16.2-fold and 31.3-fold in leaves. Furthermore, subcellular localization analysis confirmed that representative ANR proteins were localized in the cytoplasm. This study lays a foundation for molecular breeding aimed at enhancing stress resistance and forage quality in sainfoin.},
}

*Genome, Plant
*Gene Expression Regulation, Plant/genetics
*Anthocyanins/metabolism
Oxylipins/chemistry
Abscisic Acid/chemistry
Cyclopentanes
Gene Expression Profiling
Protein Domains
Amino Acid Motifs
Plant Leaves
Plant Stems
Plant Roots
Computational Biology
*Hormones/chemistry
*Fabaceae/enzymology
Acetates

@article {pmid41985106,
year = {2026},
author = {Sun, Q and Lin, Y and Ping, Q and Zhao, Y and Wang, X and Wang, L and Li, Y},
title = {Breaking the Pharmaceutical-ARG Nexus in Wastewater: Mechanistic Insights into Risk Mitigation by a Novel Riboflavin/Ultraviolet/Peracetic Acid Disinfection Process Unveiled by Multiomics.},
journal = {Environmental science & technology},
volume = {60},
number = {16},
pages = {12501-12513},
doi = {10.1021/acs.est.5c16102},
pmid = {41985106},
issn = {1520-5851},
mesh = {*Wastewater ; *Disinfection ; Riboflavin ; Peracetic Acid ; Ultraviolet Rays ; Water Pollutants, Chemical ; Drug Resistance, Microbial/genetics ; Water Purification ; Pharmaceutical Preparations ; Multiomics ; },
abstract = {Wastewater treatment plants (WWTPs) serve as critical reservoirs and dissemination hotspots for pharmaceuticals and antibiotic resistance genes (ARGs), posing significant threats to environmental and public health. In this study, a novel riboflavin/ultraviolet/peracetic acid (RF/UV/PAA) disinfection process was developed to enhance the removal of these emerging contaminants. The process achieved superior performance in degrading 29 pharmaceuticals and eliminating 106 ARGs and 13 mobile genetic elements (MGEs), attributed to the action of both radical and non-radical species. The underlying risk mitigation potential was further elucidated through multiomics analyses. The results revealed that the RF/UV/PAA process suppresses ARG dissemination through a triple-mechanism pathway, directly inactivating host bacteria; blocking vertical gene transfer; enhancing pharmaceutical removal, which alleviates the selection pressure for resistance; and disrupting horizontal gene transfer (HGT) through MGE destruction and alterations in membrane permeability, extracellular polymeric substance secretion, adenosine triphosphate synthesis, and cellular motility. Notably, our results also suggest that non-antibiotic pharmaceuticals promote the MGE-mediated HGT of ARGs, challenging the conventional antibiotic-centric paradigm. This study not only establishes RF/UV/PAA disinfection as an effective technology for the synergistic removal of pharmaceuticals and ARGs in wastewater but also provides critical mechanistic insights to mitigate ARG dissemination via WWTP effluents.},
}

*Wastewater
*Disinfection
Riboflavin
Peracetic Acid
Ultraviolet Rays
Water Pollutants, Chemical
Drug Resistance, Microbial/genetics
Water Purification
Pharmaceutical Preparations
Multiomics

@article {pmid42040854,
year = {2026},
author = {Kietzka, GJ and Pryke, JS and Gaigher, R and Samways, MJ and Hui, C},
title = {Evaluating Conservation Corridor Success for Rare and Common Dragonflies Using Zeta Diversity.},
journal = {Ecology and evolution},
volume = {16},
number = {4},
pages = {e73251},
pmid = {42040854},
issn = {2045-7758},
abstract = {Conservation corridors connect natural areas, aiming to mitigate the effects of land transformation. However, their influence on biodiversity, particularly species turnover, remains poorly understood. This study evaluates the impact of conservation corridors on riverine ecosystems and their associated dragonfly assemblages. We assessed species richness and applied the zeta diversity framework to evaluate species turnover across multiple sites, thereby providing insights into how these corridors influence dragonfly community composition relative to natural areas. The research was conducted in the KwaZulu-Natal Midlands of South Africa, covering 104 freshwater sites within natural grasslands and timber plantation corridors. At each site, a 100 m transect adjacent to a river was sampled twice, focusing on recording adult male dragonflies and six environmental variables. Drivers of species richness were analysed using generalised additive models and generalised linear models. Multi-site generalised dissimilarity models were run to examine changes in zeta diversity along environmental gradients and to partition the contributions of different factors to compositional turnover. A total of 37 species were recorded, with one species exclusive to natural areas and four unique to corridors. Dragonfly assemblages were influenced more by stochastic processes than by environmental gradients. Although factors such as site distance, differences in water temperature, dissolved oxygen, shade and rock cover affected turnover, they explained little variation in both rare and common species. Species richness was higher in corridors and consistently declined with increasing shade cover. Neither the presence of corridors nor invasive alien vegetation influenced species turnover, indicating that corridors function similarly to natural habitats. This study demonstrates the crucial role of conservation corridors in preserving dragonfly diversity in altered landscapes. Our findings support continued investment in corridor implementation and management for biodiversity conservation and demonstrate the utility of the zeta diversity framework for understanding species turnover dynamics.},
}

@article {pmid42041468,
year = {2026},
author = {Gerolimos, N and Kiskira, K and Sfyroera, E and Tsoumas, J and Alevizos, V and Plakantonaki, S and Foka, M and Priniotakis, G},
title = {Integrating Biomimetic Reasoning Into Early-Stage Design Thinking for Sustainable Textile Development.},
journal = {Biomimetics (Basel, Switzerland)},
volume = {11},
number = {4},
pages = {},
pmid = {42041468},
issn = {2313-7673},
abstract = {This study explores the potential of biomimetic reasoning to inform early-stage design thinking, with a focus on enhancing the consideration of material utilization and textile waste. While sustainability efforts within the field of textiles are often focused on recycling and end-of-life management strategies, it is important to recognize that a substantial proportion of final waste-related outcomes are determined during the conceptual design stage and the initial prototyping iterations. This study investigates the potential of organizational principles derived from natural systems to inform the definition of problems, the generation of ideas, and early conceptual prototyping. This is achieved by the introduction of ecological constraints and material life-cycle awareness in conjunction with user-centered requirements. To address the conceptual gap between biological forms and manufacturing, biomimicry is approached as a mode of systemic reasoning, utilizing topological skeletonization as a tool for logic extraction rather than formal imitation, with emphasis placed on continuity, modularity, and adaptive organization. This computational proof-of-concept employs a Particle Swarm Optimization (PSO) framework, utilizing biological venation as a topological guide to demonstrate how distinct organizational logics influence pattern configuration while incorporating manufacturing-inspired constraints (such as path continuity and density) as optimization penalties. The findings are exploratory in nature and are confined to the computational domain; while the study utilizes proxy indicators to simulate potential textile behaviors, it acknowledges the lack of direct experimental validation of physical fabrication as a current limitation. By framing waste as an outcome of upstream design choices, this paper contributes a methodological perspective. This perspective places biomimetic design thinking as a reflective tool within sustainable and regenerative design practice. It also supports earlier engagement with ecological considerations in textile development.},
}

@article {pmid42030493,
year = {2026},
author = {Wei, S and Van, S and Shia, C and Gancz, M and Camenga, D and Aneni, K and Marks, A and Hieftje, K},
title = {Psychophysiological Responses in Virtual Reality for Assessing Current Nicotine Use and Future Addiction Risk Among Young Adults: Protocol for a Mixed Methods Study.},
journal = {JMIR research protocols},
volume = {15},
number = {},
pages = {e89382},
pmid = {42030493},
issn = {1929-0748},
mesh = {Humans ; Young Adult ; Adolescent ; Pilot Projects ; *Virtual Reality ; Male ; Craving/physiology ; Female ; Heart Rate/physiology ; *Tobacco Use Disorder/psychology/diagnosis/physiopathology ; Galvanic Skin Response ; Cues ; *Vaping/psychology ; *Behavior, Addictive/psychology ; *Psychophysiology/methods ; },
abstract = {BACKGROUND: Nicotine addiction among youth is a continuing public health concern, and vaping serves as a major pathway to nicotine use. Conventional assessments of craving and addiction risk rely on self-reports, which are prone to bias and lack sensitivity to real-time processes. Virtual reality (VR) enables controlled cue exposure while capturing real-time multimodal data, including subjective experiences, behavioral patterns, and physiological responses, which offer a more implicit and dynamic approach to identifying addiction risk.

OBJECTIVE: This pilot study examines whether subjective craving and psychophysiological responses (eg, eye gaze, heart rate, and electrodermal activity) to vaping-related cues in VR can distinguish young adults who vape from those who do not. Our secondary objective is to explore associations between these multimodal biomarkers and self-reported measures of craving, dependence, motivation to quit, and susceptibility to initiate vaping.

METHODS: Bespoke VR scenes were developed with input from a youth advisory board to ensure ecological validity. Forty young adults aged 18 to 21 years (20 vapers and 20 nonvapers) will complete a single laboratory session. Participants will experience 3 VR scenes (neutral baseline, vaping cues without social pressure, and vaping cues with social pressure in counterbalanced order). Eye gaze, heart rate, and electrodermal activity will be recorded continuously. Participants will complete standardized assessments of craving, sense of presence, and social presence in VR after each cue scene, followed by a short interview at the end. Quantitative data will be analyzed using mixed-model ANOVAs, correlation metrics, and exploratory regularized regression analyses to examine relationships between physiological responses, behavioral measures, and vaping status.

RESULTS: The project received institutional review board approval in August 2025 and was registered publicly in the Open Science Framework in November 2025. Development of the VR stimuli was completed in December 2025. Participant recruitment and data collection began in February 2026, and 7 participants have been enrolled as of March 2026.

CONCLUSIONS: This protocol outlines a pilot study integrating immersive VR and multimodal biometrics to examine vaping cue reactivity in young adults. The findings will guide the development and evaluation of VR-based psychophysiological tools for identifying early markers of nicotine use risk. This work will also lay the foundation for adapting the approach to younger adolescents to support scalable early detection and prevention of nicotine addiction and initiation.},
}

Humans
Young Adult
Adolescent
Pilot Projects
*Virtual Reality
Male
Craving/physiology
Female
Heart Rate/physiology
*Tobacco Use Disorder/psychology/diagnosis/physiopathology
Galvanic Skin Response
Cues
*Vaping/psychology
*Behavior, Addictive/psychology
*Psychophysiology/methods

@article {pmid42032815,
year = {2026},
author = {Min, J and Ning, Y and Pope, NS and Baumdicker, F and Kern, AD},
title = {Neural posterior estimation for population genetics.},
journal = {Genetics},
volume = {},
number = {},
pages = {},
doi = {10.1093/genetics/iyag107},
pmid = {42032815},
issn = {1943-2631},
abstract = {Simulation-based inference methods are increasingly being used in population genetics due to their flexibility and ability to be applied in settings where likelihood-based methods are intractable. Perhaps the best known such method is Approximate Bayesian Computation (ABC); however, its popularity is offset by its shortcomings which include computational expense and an unfortunate inability to efficiently fit models to high-dimensional summaries of the data. An alternative approach that solves these issues is supervised machine learning (ML); however, ML methods generally do not yield Bayesian uncertainty estimates of the quantities they predict. Here, we apply a recently introduced method, neural posterior estimation (NPE), that combines the best facets of ABC and supervised ML by training a neural network to estimate the posterior distribution of a population genetics model. We first compare neural posterior estimation with other inference methods for a variety of population genetic tasks, and show that neural posterior estimators yield posterior distributions with high accuracy and efficiency. We compare learned posterior distributions given raw genotypes and various summary statistics as input data. Additionally, we apply neural posterior estimation for demographic inference for simple and more complex models to highlight its application, including an analysis of demographic history in Drosophila melanogaster. Finally, we provide a user friendly workflow that enables others to perform neural posterior estimation on their own genetic data.},
}

@article {pmid42037082,
year = {2026},
author = {Spöri, Y and Flot, JF},
title = {Champuru 2: Improved Scoring of Alignments and a User-Friendly Graphical Interface.},
journal = {Molecular ecology resources},
volume = {26},
number = {4},
pages = {e70110},
doi = {10.1111/1755-0998.70110},
pmid = {42037082},
issn = {1755-0998},
mesh = {*Software ; *Computational Biology/methods ; *Sequence Alignment/methods ; User-Computer Interface ; Computer Graphics ; *Sequence Analysis, DNA/methods ; Internet ; Algorithms ; },
abstract = {Champuru is a web-based software tool that helps determine the two sequences present in mixed Sanger chromatograms obtained by simultaneously sequencing two DNA templates of unequal lengths. A previous version (Champuru 1.0) was published as a simple Perl CGI (Common Gateway Interface) application, but the server hosting it was decommissioned, which prompted us to update Champuru and develop it further. The new Champuru 2, implemented in Haxe and hosted at GitHub Pages, offers an improved graphical user interface as well as more sophisticated algorithms to compute alignment scores, making it more efficient at detecting the most likely alignment positions between forward and reverse traces. It also compares the distribution of alignment scores to the theoretical expectation for the comparison of two random sequences and uses this comparison to calculate p-values for the offset pairs it detects. Moreover, Champuru 2 now makes it possible to analyse other offset pairs than the one detected as most likely by the selected algorithm. Champuru 2 is freely accessible at https://eeg-ebe.github.io/Champuru/, including both a graphical user interface (running a JavaScript version transpiled from the Haxe source code) and a compiled command-line version (obtained by transpiling the Haxe source code into C++).},
}

*Software
*Computational Biology/methods
*Sequence Alignment/methods
User-Computer Interface
Computer Graphics
*Sequence Analysis, DNA/methods
Internet
Algorithms

@article {pmid42038460,
year = {2026},
author = {Li, J and Wang, QY},
title = {Multi-omics insights into mosquito insecticide resistance for integrated vector management.},
journal = {PeerJ},
volume = {14},
number = {},
pages = {e21083},
pmid = {42038460},
issn = {2167-8359},
mesh = {*Insecticide Resistance/genetics ; Animals ; *Mosquito Vectors/genetics/drug effects ; *Mosquito Control/methods ; *Insecticides/pharmacology ; Genomics ; Multiomics ; },
abstract = {Escalating insecticide resistance in mosquito vectors threatens the durability of vector-borne disease control and increasingly constrains the effectiveness of core interventions. This resistance is a multilayered adaptive phenotype arising from the combined action of target-site substitutions that reduce insecticide sensitivity, transcriptional and enzymatic upregulation of detoxification systems that enhance xenobiotic metabolism, cuticular and behavioral changes that limit exposure and penetration, and transporter-mediated efflux, with additional modulation by microbiota and local environmental conditions that shape phenotypic expression in the field. Current integrated vector management (IVM) strategies aim to mitigate resistance through operationally guided deployment of dual-active-ingredient or synergist-treated nets, indoor residual spraying with rotations or mixtures, integration of larval source management and habitat modification, and incorporation of nonchemical tools such as Wolbachia releases and genetic control, supported by routine resistance surveillance. However, much of the existing evidence remains fragmented, with an overreliance on a narrow set of insecticide classes and a limited number of genetic markers, variable phenotyping and performance metrics across settings, and insufficient prospective linkage between molecular signals and intervention impact under real transmission ecologies. Multi-omics frameworks provide a route to move beyond single-locus screening toward network-level reconstruction of resistance biology, enabling discovery of predictive biomarkers, pathway signatures, and metabolic readouts that can be translated into actionable diagnostics and locally optimized decision rules. Looking forward, omics-enabled precision surveillance integrated with field-deployable assays, standardized benchmarks, and model-informed adaptive management could support closed-loop resistance mitigation in which operational choices are continuously refined to preserve long-term intervention efficacy within IVM programs.},
}

*Insecticide Resistance/genetics
Animals
*Mosquito Vectors/genetics/drug effects
*Mosquito Control/methods
*Insecticides/pharmacology
Genomics
Multiomics

@article {pmid41990455,
year = {2026},
author = {James, SH and Galvan, T and Raugh, IM and Allen, DN and Condray, R and Strauss, GP},
title = {Ethnoracially incongruent environments predict state increases in negative symptoms of schizophrenia:Evidence from geocoding and digital phenotyping.},
journal = {Journal of psychiatric research},
volume = {198},
number = {},
pages = {294-300},
doi = {10.1016/j.jpsychires.2026.04.007},
pmid = {41990455},
issn = {1879-1379},
mesh = {Humans ; Male ; *Schizophrenia/physiopathology/ethnology/diagnosis ; Female ; Adult ; *Ecological Momentary Assessment ; Middle Aged ; Geographic Information Systems ; *Social Environment ; *Schizophrenic Psychology ; },
abstract = {BACKGROUND: Cultural contexts, such as whether one's immediate environment is ethnoracially congruent, are known to influence emotional expression, emotional experience, motivation, and social behavior in healthy individuals. However, it is unclear whether such cultural factors play a role in state exacerbations in negative symptoms that occur in schizophrenia (SZ).

AIMS: The current study combined GPS data, environmental geocoding, and ecological momentary assessment (EMA) to test the hypothesis that ethnoracial incongruence encountered in daily-life situations predicts state increases in negative symptoms in SZ.

METHOD: Participants included outpatients with SZ (n = 37) and healthy controls (CN: n = 41) with marginalized ethnoracial identities who completed EMA and passive digital phenotyping recordings. Geolocation was used to pair participant GPS location at the time of completing EMA symptom surveys with geocoded measures of that location's ethnoracial density based on government census records. Ethnoracial congruence was determined in relation to the match between a participant's identified ethnoracial identity and the ethnoracial density of their location at the time of EMA survey.

RESULTS: Results indicated that ethnoracially incongruent contexts were associated with state increases in negative symptoms in individuals with SZ, but not CN.

CONCLUSIONS: These findings suggest that interactions between one's own ethnoracial identity and the ethnoracial context of the current environment contributes to negative symptom exacerbations in SZ. Identity factors are not typically considered in the assessment and treatment of negative symptoms in SZ, but it would be beneficial to do so.},
}

Humans
Male
*Schizophrenia/physiopathology/ethnology/diagnosis
Female
Adult
*Ecological Momentary Assessment
Middle Aged
Geographic Information Systems
*Social Environment
*Schizophrenic Psychology

@article {pmid42027768,
year = {2026},
author = {Ylinampa, TA and Kõljalg, U},
title = {The Orbitoscope, a six-axis macro-imaging robot for photogrammetric 3D-digitization of insects and other small specimens.},
journal = {ZooKeys},
volume = {1277},
number = {},
pages = {137-155},
pmid = {42027768},
issn = {1313-2989},
abstract = {Natural history collections contain vast numbers of small, fragile specimens whose morphology is difficult to capture using conventional 2D-imaging. Photogrammetric 3D-reconstruction from multi-view photographs can preserve surface colour and enable scaled measurement, but at macro magnification it typically requires dense viewpoint coverage with high overlap and extended depth-of-field (EDOF) imagery. Existing robotic systems often achieve viewpoint variation by rotating and tilting the specimen, which can be limiting for elongated, heavy, or fragile mounts and for objects whose geometry may change when reoriented. We present the Orbitoscope, an open-source six-axis macro-imaging robot that keeps the specimen stationary while moving the camera in translation (X-Y-Z) and orientation (A-B) around it, with a dedicated stacking axis (C) to acquire focus stacks automatically. We demonstrate the workflow by digitizing six insect specimens and generating scaled, textured 3D models suitable for preservation, measurement, and online dissemination. Basic measurement validation on one specimen showed a mean absolute percent error of 0.52% (max. 0.88%) relative to calibrated microscope reference measurements. Hardware, software, and documentation are openly released, with detailed build and operation instructions archived separately as a technical package.},
}

@article {pmid41805696,
year = {2026},
author = {Veith, T and Beck, RJ and Brown, JS and Andor, N},
title = {Inverse game theory characterizes frequency-dependent selection driven by karyotypic diversity in triple-negative breast cancer.},
journal = {PLoS computational biology},
volume = {22},
number = {3},
pages = {e1013897},
doi = {10.1371/journal.pcbi.1013897},
pmid = {41805696},
issn = {1553-7358},
mesh = {*Triple Negative Breast Neoplasms/genetics ; Humans ; Female ; *Game Theory ; Cell Line, Tumor ; Animals ; DNA Copy Number Variations/genetics ; Mice ; Computational Biology ; Karyotyping ; Karyotype ; },
abstract = {Chromosomal instability, characterized by pervasive copy number alterations (CNAs), significantly contributes to cancer progression and therapeutic resistance. CNAs drive intratumoral genetic heterogeneity, creating distinct subpopulations whose interactions shape tumor evolution through frequency-dependent selection. Here, we introduce ECO-K (Ecological-Karyotypes), an inverse game theory framework that quantifies frequency-dependent interaction coefficients among karyotypically defined subpopulations under the assumption that their fitness is frequency-dependent. Applying this approach to serially-passaged, triple-negative breast cancer cell lines and patient-derived xenografts (PDXs), we estimated interaction matrices consistent with the observed time-series dynamics. In one PDX lineage, the inferred matrices consistently assigned large interaction coefficients to a subpopulation characterized by chromosome 1 loss and chromosome 14p gain, suggesting it may act as an ecological hub within the frequency-dependent model. Our framework provides testable predictions of intratumoral ecological dynamics, highlighting opportunities to strategically target key subpopulations to disrupt tumor evolution.},
}

*Triple Negative Breast Neoplasms/genetics
Humans
Female
*Game Theory
Cell Line, Tumor
Animals
DNA Copy Number Variations/genetics
Mice
Computational Biology
Karyotyping
Karyotype

@article {pmid41920852,
year = {2026},
author = {Kim, H and Kim, S and Kimbrel, JA and Morris, MM and Mayali, X and Buie, CR},
title = {Multidimensional scaling informed by F-statistic: Visualizing grouped microbiome data with inference.},
journal = {PLoS computational biology},
volume = {22},
number = {4},
pages = {e1014102},
doi = {10.1371/journal.pcbi.1014102},
pmid = {41920852},
issn = {1553-7358},
mesh = {*Microbiota ; *Computational Biology/methods ; Algorithms ; Humans ; Multivariate Analysis ; },
abstract = {Multidimensional scaling (MDS) is a widely used dimensionality reduction technique in microbial ecology data analysis that captures the multivariate structure of the data while preserving pairwise distances between samples. While improvements in MDS have enhanced the ability to reveal group-specific data patterns, these MDS-based methods require prior assumptions for inference, limiting their application in general microbiome analysis. In this study, we introduce a new MDS-based ordination method, "F-informed MDS," which configures the data distribution based on the F-statistic, the ratio of dispersion between groups sharing common and different characteristics. Using semisynthetic datasets, we demonstrate that the proposed method is robust to hyperparameter selection while maintaining statistical significance throughout the ordination process. Various quality metrics for evaluating dimensionality reduction confirm that F-informed MDS is comparable to state-of-the-art methods in preserving both local and global data structures. Its application to a diatom-associated bacterial community suggests the role of this new method in interpreting the community's response to the host. Our approach offers a well-founded refinement of MDS that aligns with statistical test results, which can be beneficial for broader multidimensional data analyses in microbiology and ecology. This new visualization tool can be incorporated into standard microbiome data analyses.},
}

*Microbiota
*Computational Biology/methods
Algorithms
Humans
Multivariate Analysis

@article {pmid41959181,
year = {2026},
author = {Yuan, H and Mandava, A and Samart, K and Ganz, J and Krishnan, A},
title = {Linking Genetic Risk to Disease-Relevant Cellular States via Metacell-Informed Modeling with ICePop.},
journal = {bioRxiv : the preprint server for biology},
volume = {},
number = {},
pages = {},
pmid = {41959181},
issn = {2692-8205},
abstract = {Genome-wide association studies (GWAS) have implicated thousands of loci in complex diseases, but translating these population-level signals into specific cellular contexts remains a central challenge. Integrating GWAS with single-cell transcriptomics data has enabled systematic identification of disease-relevant cell types, yet existing methods face a fundamental tradeoff: approaches like seismic that optimized for statistical power operate at the annotated cell-type level and miss heterogeneous disease signals concentrated in specific cellular states, while single-cell-resolution approaches like scDRS that capture such heterogeneity often lack sufficient power to detect subtle associations. Here we present ICePop (Informative Cell Populations), a framework that resolves this tradeoff by performing disease-cell type association at metacell resolution, thus achieving statistical power comparable to cell-type-level methods while detecting heterogeneous disease signals within cell types. In simulations against seismic and scDRS, ICePop maintains appropriate false positive rates and demonstrates superior power when disease effects are concentrated in cellular subpopulations. Applied to Tabula Muris across 81 traits and 120 cell types, ICePop identifies 2,178 disease-cell type associations, including the preferential vulnerability of differentiated gut epithelial cells in ulcerative colitis and loss of cell identity in immune-stressed lung capillary endothelial cells underlying their association with lung function. Clustering diseases by metacell association profiles reveals groupings that diverge from genetic risk-based clustering, including separation of blood cell count traits from immune diseases despite shared genetic architecture, reflecting differences in cellular rather than genetic etiology. In autism spectrum disorder, ICePop identifies preferential enrichment of genetic risk in specific enteric neuron subtypes, implicating dysfunction of the enteric nervous system in gastrointestinal comorbidities. ICePop's resolution of disease-relevant cell states within annotated cell types enables generation of testable, cell-state-specific hypotheses about disease mechanisms and therapeutic targets.},
}

@article {pmid42022432,
year = {2026},
author = {Hanf-Dressler, T and Nouioua, R and Thomisch, K and Cazau, D and de Selys Longchamps, S and Darras, KFA},
title = {Software Tools for Passive Acoustic Monitoring in Aquatic and Terrestrial Bio- and Ecoacoustics: A Living Systematic Review.},
journal = {F1000Research},
volume = {15},
number = {},
pages = {48},
pmid = {42022432},
issn = {2046-1402},
mesh = {*Software ; *Acoustics ; *Environmental Monitoring/methods ; Ecosystem ; Biodiversity ; },
abstract = {Biodiversity monitoring is crucial for understanding species trends and their responses to anthropogenic change. Passive acoustic monitoring (PAM) offers a scalable, non-invasive approach to capture ecological information across large spatial and temporal scales. However, it generates vast amounts of audio recordings, whose management and analysis present technical challenges. To support diverse user needs in ecoacoustic research, a growing number of software tools have emerged, but the landscape remains fragmented and difficult to navigate. We provide a systematic overview of software tools used for soundscape assessment across terrestrial, freshwater, and marine environments. We screened peer-reviewed literature and complemented it with database cross-checking to identify and categorize tools according to four PAM data workflow components: data management, signal pre-processing, visualisation and navigation, and acoustic analysis. We found 221 available tools of which 174 were explicitly designed for PAM. Most tools were freely accessible (83%) with only a smaller fraction being commercial (12%) or limited access (5%). Terrestrial research accounted for most software mentions (476 studies), followed by aquatic (319) and cross-realm (64) studies. Nearly half (45%) were package-based frameworks within R, Python, or MATLAB. Acoustic analysis was the most represented workflow component, while only 40 tools covered all four of them. This diversity illustrates the field's rapid technical growth but also its redundancy and methodological fragmentation: to date, many tools target only a subset of workflow components and replicate similar functionalities. Despite this, the prevalence of PAM-dedicated software indicates increasing specialization and technical maturity within ecoacoustics. Our structured inventory underscores the need for greater collaboration and continuity in software development, promoting the improvement and accessibility of existing tools rather than further proliferation. This living systematic review, provides a practical, biannually updated reference for tool selection and fosters transparency, comparability, and cooperation across bioacoustic and ecoacoustic research communities.},
}

*Software
*Acoustics
*Environmental Monitoring/methods
Ecosystem
Biodiversity

@article {pmid42022830,
year = {2026},
author = {Agbajelola, V and Raghavan, RK},
title = {A systematic review and meta-analysis of population-based anthrax prevalence in Africa with a one health narrative synthesis of outbreak surveillance.},
journal = {Frontiers in public health},
volume = {14},
number = {},
pages = {1792476},
pmid = {42022830},
issn = {2296-2565},
mesh = {*Anthrax/epidemiology ; Humans ; Africa/epidemiology ; Prevalence ; *Disease Outbreaks/statistics & numerical data/veterinary ; Animals ; *One Health ; *Population Surveillance ; Cross-Sectional Studies ; },
abstract = {BACKGROUND: Anthrax remains a persistent public health, veterinary, and ecological challenge in Africa, sustained by fragmented surveillance systems characterized by underreporting, limited diagnostic capacity, and weak cross-sectoral coordination. The absence of integrated surveillance across human, livestock, wildlife, and environmental interfaces constrains accurate burden estimation and timely outbreak response.

METHODS: We conducted a systematic review and meta-analysis following PRISMA guidelines to synthesize available evidence on anthrax epidemiology in Africa. Studies published between January 2000 and February 2025 were identified from PubMed and Web of Science. Observational studies reporting primary epidemiological data in humans, livestock, wildlife, or environmental samples were eligible. Quantitative synthesis was restricted to cross-sectional studies reporting extractable prevalence data. Pooled estimates were generated using a logit-transformed random-effects model (REML), with heterogeneity assessed using I [2] and τ[2] statistics. Studies not meeting meta-analytic criteria were synthesized narratively within a One Health framework.

RESULTS: Ten cross-sectional studies comprising 19,955 samples and 2,079 confirmed anthrax cases were included in the meta-analysis. The crude aggregated prevalence was 9.88% (95% CI: 9.46%-10.30%). The pooled prevalence from the logit-transformed random-effects model was 20% (95% CI: 8%-44%). Substantial heterogeneity was observed (I [2] = 98.2%), indicating marked epidemiological variability across ecological settings, host populations, and surveillance systems. Narrative synthesis further highlighted wildlife outbreaks and environmental persistence of Bacillus anthracis, though such studies remain comparatively scarce.

CONCLUSION: The available evidence on anthrax in Africa is limited, geographically uneven, and highly heterogeneous. The pooled estimate should therefore be interpreted as a summary measure of reported prevalence rather than a precise continental burden estimate. These findings underscore persistent transmission within fragmented surveillance systems and support strengthened One Health-based approaches integrating human, animal, wildlife, and environmental health sectors to improve surveillance, early detection, and coordinated response across Africa.},
}

*Anthrax/epidemiology
Humans
Africa/epidemiology
Prevalence
*Disease Outbreaks/statistics & numerical data/veterinary
Animals
*One Health
*Population Surveillance
Cross-Sectional Studies

@article {pmid42026820,
year = {2026},
author = {Melendez, D and Şapcı, AOB and Bafna, V and Mirarab, S},
title = {SPrUCE: Utilizing Ultraconserved Elements of DNA for Population-Level Genetic Diversity Estimation.},
journal = {Molecular ecology resources},
volume = {26},
number = {3},
pages = {e70145},
doi = {10.1111/1755-0998.70145},
pmid = {42026820},
issn = {1755-0998},
support = {//Minderoo Foundation/ ; },
mesh = {*Genetic Variation ; Animals ; *Genetics, Population/methods ; *Conserved Sequence ; *DNA/genetics ; Invertebrates/genetics/classification ; *Computational Biology/methods ; Vertebrates/genetics/classification ; },
abstract = {Ultraconserved elements (UCEs) provide ideal candidates for targeted sequencing and cost-effective acquisition of genome-wide data. While UCEs have been widely used in phylogenetic studies to reconstruct evolutionary relationships, their use in population-level research has been limited. This limited application stems from uncertainty over whether UCEs can capture the levels of genetic variation needed to answer population genomic questions central to ecology and biodiversity research. The concern is that, by definition, UCEs are highly conserved and may therefore lack sufficient within-species variation. The more variable flanking regions (400-750 bp from the UCE core) contain informative polymorphisms, though diversity decreases near the core. Thus, any naive estimator of genetic diversity that ignores this conservation will have an underestimation bias. In this paper, we introduce SPrUCE: Sigmoid Pi requiring UCEs, a reference-free method that estimates nucleotide diversity π $$ \pi $$ from aligned UCE data. SPrUCE corrects underestimation bias by modelling the change in diversity away from the UCE core using a Gompertz function. The model accounts for the bias introduced by the conserved core and allows for more accurate per-site diversity estimates. We tested SPrUCE on UCE alignments from a range of taxa, including invertebrates and vertebrates (finches, honeybees, sheep and smelt). SPrUCE produces diversity values consistent with whole-genome derived estimates that require an assembled reference. It is fast, scalable, and effective even with missing data. Its modelling approach enables accurate population-level assessments of genetic diversity, offering a new and reliable option for conservation and population genetics.},
}

*Genetic Variation
Animals
*Genetics, Population/methods
*Conserved Sequence
*DNA/genetics
Invertebrates/genetics/classification
*Computational Biology/methods
Vertebrates/genetics/classification

@article {pmid41719082,
year = {2026},
author = {Gao, M and Liu, KJ},
title = {A REsampling and Visual EvALuation Method to Detect and Map Local Model Violations During Biomolecular Sequence Analysis.},
journal = {Journal of computational biology : a journal of computational molecular cell biology},
volume = {33},
number = {4},
pages = {482-498},
doi = {10.1177/15578666261424921},
pmid = {41719082},
issn = {1557-8666},
mesh = {Phylogeny ; Animals ; *Sequence Alignment/methods ; Algorithms ; *Computational Biology/methods ; Evolution, Molecular ; *Models, Genetic ; Computer Simulation ; },
abstract = {A fundamental assumption in phylogenetics and phylogenomics is that a single, global evolutionary model can adequately characterize the substitution processes operating across all sites in a molecular sequence alignment. However, this assumption is frequently violated in practice due to heterogeneity in evolutionary processes, leading to local model mis-specification and potential bias in downstream inference. While a variety of statistical and machine learning-based approaches have been developed to address this issue, these methods often rely on restrictive model assumptions or are designed for narrowly scoped applications, limiting their generalizability across diverse datasets and evolutionary contexts. Here, we present REVEAL ("REsampling and Visual EvALuation"), a general-purpose statistical framework for detecting and localizing model mis-specification in biomolecular sequence data. REVEAL operates without introducing additional assumptions beyond those inherent to standard global model-based analyses. It employs sequence-aware statistical resampling to construct a local support matrix along the sequence alignment, facilitating the identification of site-level model violations. Through extensive simulation experiments, we demonstrate that REVEAL achieves robust control of both type I and type II errors, with precision of 90% or greater and recall of 85% or greater across diverse evolutionary scenarios involving different sources of model heterogeneity, varying dataset sizes in terms of sequence length and number of taxa, and other experimental factors. We further apply REVEAL to genomic data from mouse and mosquito, uncovering localized model violations that are consistent with previously reported biological signals. These results establish REVEAL as a flexible and effective tool for evaluating model adequacy in phylogenetic and phylogenomic analyses.},
}

Phylogeny
Animals
*Sequence Alignment/methods
Algorithms
*Computational Biology/methods
Evolution, Molecular
*Models, Genetic
Computer Simulation

@article {pmid41985608,
year = {2026},
author = {Guo, Q and Ding, C and Ding, Z and Luan, J and Meng, Q and Cai, M and Dong, C and Pan, Y and Yu, J and Liang, F},
title = {A data mining-based screening and prioritization of PFAS in wastewater treatment plants across China.},
journal = {Environmental pollution (Barking, Essex : 1987)},
volume = {398},
number = {},
pages = {128129},
doi = {10.1016/j.envpol.2026.128129},
pmid = {41985608},
issn = {1873-6424},
mesh = {China ; *Wastewater/chemistry ; *Water Pollutants, Chemical/analysis ; *Fluorocarbons/analysis ; *Environmental Monitoring/methods ; *Waste Disposal, Fluid ; Data Mining ; Risk Assessment ; Humans ; },
abstract = {Numerous per- and polyfluoroalkyl substances (PFAS) existed in effluent of wastewater treatment plants (WWTP) generate potential risk to ecosystem and human health. It is imperative to evaluate the characteristic and potential risk of PFAS from WWTP comprehensively. The risk prioritization based on data mining method was established to compile the reference PFAS and corresponding concentrations in municipal WWTP (M-WWTP) and industrial WWTP (I-WWTP) across China over 17 years. The annual publication frequency of PFAS increased significantly, indicating the major concern over time. Totally, 370 PFAS compounds were identified from 960 publications, of which 107 PFAS with concentrations were detected from M-WWTP, and 55 PFAS with concentrations were identified in I-WWTP. Most PFAS categories from M-WWTP and I-WWTP were concentrated on PFCA and PFSA. It's worth noting that there existed negative removal for PFAS contaminants from WWTP, suggesting the precursors in influent could be transformed into PFAS by biodegradation in following treatment processes. The ecological and human health risk of PFAS, including PFOS, PFOA and FOSA, etc., with risk quotient (RQ) > 0.3 and exposure activity ratio (EAR) > 0.001, in effluent from WWTPs could be generated to the receiving water environment. PFAS, including PFOS, PFOA, 6:2 FESA, FOSA, PFHpA, PFTrDA, MeFBSAA, have high prioritization index based on environmental health (EHPI) scores in effluent of M-WWTP, while 6:2 Cl-PFESA, PFDA, 8:2 Cl-PFESA, FOSA, PFOS, 6:2 diPAP have high EHPI scores in effluent of I-WWTP, indicating that these PFAS should be focused on and further prioritized for removal and control. Finally, the PFAS from M-WWTP and I-WWTP in China over the past 17 years were comprehensively compiled by text mining, which provides the reference for screening and identifying PFAS in WWTP. The prioritization of PFAS also offered the foundation for following goal analysis, supervision and administration.},
}

China
*Wastewater/chemistry
*Water Pollutants, Chemical/analysis
*Fluorocarbons/analysis
*Environmental Monitoring/methods
*Waste Disposal, Fluid
Data Mining
Risk Assessment
Humans

@article {pmid42017006,
year = {2026},
author = {Bai, Y and Song, P and Wen, S and Zhu, H and Wang, Y and Wang, H and Feng, X and Ma, B and Ergu, D and Liu, F},
title = {A Hybrid Machine Learning Framework to Improve Morphological Trait Recovery in Avian Datasets.},
journal = {Ecology and evolution},
volume = {16},
number = {3},
pages = {e73173},
pmid = {42017006},
issn = {2045-7758},
abstract = {Missing data in morphological trait datasets pose a persistent challenge to ecological and evolutionary research, frequently compromising model inference and predictive accuracy. We propose THORBFNN, a three-stage hybrid imputation framework that integrates regularized K-means clustering, Radial Basis Function Neural Networks (RBFNNs), and hierarchical Bayesian optimization to accurately recover missing avian morphological traits. The framework partitions species into clusters using regularized K-means, enhancing the preservation of local morphological structure through inter-cluster separation. Within each cluster, RBFNNs model nonlinear dependencies among traits using input features selected by Pearson correlation with the target trait. Key hyperparameters such as the number of clusters and RBF width are optimized via hierarchical Bayesian optimization to balance generalization and model complexity. When applied to a global avian trait dataset comprising over 10,000 individuals and 11 morphological traits, THORBFNN outperforms K-nearest neighbors and Random Forest imputation across four focal traits, achieving higher R [2] and lower errors (THORBFNN: R [2] = 0.9003, RMSE = 0.1652, MAE = 0.1096; KNN: R [2] = 0.8864, RMSE = 0.1668, MAE = 0.1248; Random Forest: R [2] = 0.8573, RMSE = 0.2134, MAE = 0.1584). Ablation experiments comparing models trained on complete cases versus mean-imputed data confirm that THORBFNN captures genuine trait covariation rather than statistical artifacts. THORBFNN requires no phylogenetic information and scales efficiently to datasets with thousands of individuals, offering a practical pathway for integrating machine learning into biodiversity trait analysis.},
}

@article {pmid42019450,
year = {2026},
author = {Guo, Z and Wang, Z and Liu, Y and Wang, M and Ma, H and Wang, Z and Zhang, S and Chang, Y and Ge, H and Li, C and Yang, H and Miao, H and Zhang, X and Cui, P},
title = {Early-life and lifelong exposure to environmentally relevant enrofloxacin reorganizes a proteobacteria-centered gut-lipid-resistome steady state in marine medaka.},
journal = {Journal of hazardous materials},
volume = {510},
number = {},
pages = {142146},
doi = {10.1016/j.jhazmat.2026.142146},
pmid = {42019450},
issn = {1873-3336},
abstract = {Environmental fluoroquinolone residues such as enrofloxacin (ENR) are increasingly detected in coastal waters, yet the persistence of low-dose effects on gut ecosystem organization remains unclear. We compared an early-life window exposure (5 μg/L ENR, 20-35 days post-hatch; depurated to 150 dph) with a lifelong exposure (5 μg/L ENR from fertilization to 150 dph) in marine medaka (Oryzias melastigma), using an environmentally realistic upper-bound concentration reflecting aquaculture-impacted conditions. We integrated intestinal histology and ultrastructure, inflammatory and lipid-metabolic transcriptional programs, intestinal fatty-acid profiles, 16S rRNA and 2bRAD-M characterization of the gut microbiota and antibiotic-resistance genes. Both regimens increased intestinal hypertrophy or densification and rewired communities into more positively connected, Proteobacteria-centered networks. Lifelong exposure produced a pronounced shift in intestinal lipid programming, marked by enhanced lipogenesis and reduced fatty-acid catabolism, together with selective changes in fatty-acid composition and desaturation balance. Early-life window exposure left persistent, albeit weaker, adult signatures in intestinal morphology, microbial network topology, and lipid-related transcription after prolonged withdrawal. Across cohorts, Proteobacteria indicator taxa covaried with inflammatory and lipid gene modules and with coordinated resistance-gene modules, consistent with a Proteobacteria-rich gut-lipid-resistome steady state. These findings indicate that ENR at an environmentally realistic upper-bound concentration reflecting aquaculture-impacted and hotspot contamination scenarios can durably reorganize host-microbe-resistome linkages, supporting re-evaluation of "no-effect" thresholds for antibiotic pollution from a One Health perspective.},
}

@article {pmid42021765,
year = {2026},
author = {Boyes, D and Crowley, LM and McCulloch, J and Boyes, C and , and , and , and , and , and , and , },
title = {The genome sequence of the Acorn Weevil, Curculio glandium (T.Marsham, 1802) (Coleoptera: Curculionidae).},
journal = {Wellcome open research},
volume = {11},
number = {},
pages = {178},
pmid = {42021765},
issn = {2398-502X},
abstract = {We present a genome assembly from an individual female Curculio glandium (Acorn Weevil; Arthropoda; Insecta; Coleoptera; Curculionidae). The genome sequence has a total length of 1 121.34 megabases. Most of the assembly (97.77%) is scaffolded into 13 chromosomal pseudomolecules, including the X sex chromosome. The mitochondrial genome has also been assembled, with a length of 21.61 kilobases. This assembly was generated as part of the Darwin Tree of Life project, which produces reference genomes for eukaryotic species found in Britain and Ireland.},
}

@article {pmid42012361,
year = {2026},
author = {Jiang, Y and Wang, X and Wei, M and Zhu, W and Liu, L and Zheng, H and Tang, S},
title = {Indirect reciprocity with environmental feedback.},
journal = {Chaos (Woodbury, N.Y.)},
volume = {36},
number = {4},
pages = {},
doi = {10.1063/5.0334029},
pmid = {42012361},
issn = {1089-7682},
abstract = {Indirect reciprocity maintains cooperation in stranger societies by mapping individual behaviors onto reputation signals via social norms. Existing theoretical frameworks assume static environments with constant resources and fixed payoff structures. However, in real-world systems, individuals' strategic behaviors not only shape their reputation but also induce collective-level resource changes in ecological, economic, or other external environments, which, in turn, reshape the incentives governing future individual actions. To overcome this limitation, we establish a co-evolutionary framework that couples moral assessment, strategy updating, and environmental dynamics, allowing the payoff structure to dynamically adjust in response to the ecological consequences of collective actions. We find that this environmental feedback mechanism helps lower the threshold for the emergence of cooperation, enabling the system to spontaneously transition from a low-cooperation state to a stable high-cooperation regime, thereby reducing the dependence on specific initial conditions. Furthermore, while lenient norms demonstrate adaptability in static environments, norms with strict discrimination are shown to be crucial for curbing opportunism and maintaining evolutionary resilience in dynamic settings. Our results reveal the evolutionary dynamics of coupled systems involving reputation institutions and environmental constraints, offering a new theoretical perspective for understanding collective cooperation and social governance in complex environments.},
}

@article {pmid42014086,
year = {2026},
author = {Martins, BH and Franco, AMA and Soriano-Redondo, A and Acácio, M and Catry, I},
title = {From inexperience to proficiency: age-related improvements shape the use of novel anthropogenic food subsidies in a long-lived bird.},
journal = {Proceedings. Biological sciences},
volume = {293},
number = {2069},
pages = {},
doi = {10.1098/rspb.2025.1884},
pmid = {42014086},
issn = {1471-2954},
support = {//InBIO/ ; //Natural Environment Research Council/ ; //Fundação para a Ciência e a Tecnologia/ ; },
mesh = {Animals ; *Birds/physiology ; *Feeding Behavior ; Waste Disposal Facilities ; Age Factors ; Anthropogenic Effects ; Geographic Information Systems ; },
abstract = {Worldwide, humans have altered ecosystems not only by reducing and changing the distribution of resources but also by providing new foraging opportunities to wildlife. However, little is known about the early-life development and maintenance of new foraging behaviours, which are crucial for species to adapt to human-induced environmental changes. Using a longitudinal global positioning system (GPS)-tracking dataset from 71 adult and 147 juvenile white storks (Ciconia ciconia) tracked for up to 6 years, this study investigates shifts in the exploitation of landfill resources during ontogeny and explores whether selective survival, within-individual improvements or both shape the emergence of this behaviour. Landfill use was found to increase with age. From their second year of life onwards, white storks visit landfills more often than in their first year, forage more in areas with abundant organic waste and reduce their foraging energy expenditure. Overall, this study reveals that the age-related increase in the use of anthropogenic food sources is driven primarily by within-individual improvements operating most strongly in early life, rather than by selective survival of individuals that most frequently and proficiently use landfill sites. As more species rely on anthropogenic food subsidies, this work highlights how opportunistic species cope with and adapt to human-driven environmental change, influencing individual lifetime decisions and potentially impacting population dynamics.},
}

Animals
*Birds/physiology
*Feeding Behavior
Waste Disposal Facilities
Age Factors
Anthropogenic Effects
Geographic Information Systems

@article {pmid41801038,
year = {2026},
author = {Manninen, J and Korhonen, A and Johnson, KL and Tahvonen, O and Luukkonen, A and Saarenpää, M and Puhakka, R and Uimonen, L and Kummola, L and Skevaki, C and Renz, H and Rajaniemi, J and Laitinen, OH and Roslund, MI},
title = {Playgrounds as microbial interfaces: strategies to enhance soil microbiomes and support healthy childhoods.},
journal = {mSystems},
volume = {11},
number = {4},
pages = {e0166225},
doi = {10.1128/msystems.01662-25},
pmid = {41801038},
issn = {2379-5077},
support = {346136//Strategic Research Council/ ; //Stiftung für Pathobiochemie und Molekulare Diagnostik/ ; CALM-QE project MIRACUM consortium of the Medical Informatics Initiative//Bundesministerium für Bildung und Forschung/ ; Hospital Partnership Programme//Deutscher Akademischer Austauschdienst/ ; //Deutsche Gesellschaft für Internationale Zusammenarbeit/ ; //Deutsche Forschungsgemeinschaft/ ; 346137//Strategic Research Council/ ; 346138//Strategic Research Council/ ; //Universities of Giessen and Marburg Lung Center (UGMLC)/ ; //Deutsches Zentrum für Lungenforschung/ ; //Uniklinikum Giessen und Marburg/ ; //Stiftung für Pathobiochemie und Molekulare Diagnostik/ ; //Bundesministerium für Gesundheit/ ; //State of Hesse/ ; },
mesh = {Humans ; *Soil Microbiology ; *Microbiota ; Child ; *Play and Playthings ; },
abstract = {Emerging evidence suggests that reduced exposure to biodiversity, including rich environmental microbiota, is associated with negative outcomes in the health and well-being of children. Biodiversity loss not only impacts individual health but also poses significant threats to planetary health. It destabilizes systems that regulate climate, purify air and water, maintain soil fertility, and support plant and microbial life essential for environmental health. Here, we review the scientific evidence on microbiome-supportive strategies in eco-centric, child-friendly playground environments. Investigating how environmental features influence soil microbiomes and exposure pathways could provide insights into how playgrounds function as living interfaces. These are places where environmental microbes shape children's microbial colonization patterns, immune and endocrine regulatory systems, while also contributing to ecosystem services such as biodiversity support and pollutant mitigation-particularly relevant given that many pollutants are known to disrupt immune and endocrine functions in children. These dynamics have far-reaching implications for child well-being, preventive health strategies, physical activity, environmental literacy, and broader sustainability. A multi-omic systems approach offers a critical pathway to uncover the ecological and health-related impacts of nature-associated microbial exposure and characterize host-microbiome interactions underlying immune and endocrine regulation, brain development, cognition, and stress-related disorders. Our review highlights a lack of such integrative studies, underscoring the need to advance this line of research to inform evidence-based, sustainable, and health-promoting urban design.},
}

Humans
*Soil Microbiology
*Microbiota
Child
*Play and Playthings

@article {pmid41959754,
year = {2026},
author = {Nande, A and Levy, MZ and Hill, AL},
title = {Understanding patterns of variant emergence and spread in an ongoing epidemic.},
journal = {medRxiv : the preprint server for health sciences},
volume = {},
number = {},
pages = {},
pmid = {41959754},
abstract = {The COVID-19 pandemic saw successive emergence and global spread of novel viral variants, exhibiting enhanced transmissibility or evasion of immunity. While the genotypic and phenotypic basis of SARS-CoV-2 variants have been extensively characterized, the evolutionary factors governing their patterns of emergence are less well understood. In this study we systematically investigated how the invasion dynamics of viral variants depend on variant phenotype (increased transmissibility or immune evasion), source (local evolution vs importation), the timing of introduction, the distribution of population susceptibility, and the contact network structure. Using a stochastic multi-strain epidemic model, we find that strains with only a transmission advantage are more likely to emerge earlier in the epidemic, and rapidly and predictably dominate the viral population. In contrast, immune-escape variants tend to linger at low prevalence for extended time periods after emergence, avoiding detection, until a critical amount of immunity has built up in the population and they begin to rapidly outcompete existing strains. We find that two common features of realistic human contact networks-heterogeneity in contacts (overdispersion) and clustering-lead to more punctuated evolutionary dynamics. This work provides insight into past dynamics of SARS-CoV-2 variants and can help define planning scenarios for future epidemic modeling efforts.},
}

@article {pmid41973730,
year = {2026},
author = {Dahlin, KJ and Ebey, K and Vinson, JE and Drake, JM},
title = {Nonlinear effects of noise on outbreaks of mosquito-borne diseases.},
journal = {PLoS computational biology},
volume = {22},
number = {4},
pages = {e1013466},
pmid = {41973730},
issn = {1553-7358},
mesh = {*Disease Outbreaks/statistics & numerical data ; Animals ; Humans ; *Vector Borne Diseases/epidemiology/transmission ; Mosquito Vectors ; *Culicidae ; Stochastic Processes ; Basic Reproduction Number ; Nonlinear Dynamics ; *Noise ; Models, Biological ; Computational Biology ; Climate Change ; Mosquito-Borne Diseases ; },
abstract = {Mosquito-borne diseases are a significant and growing public health burden globally. Predictions about the spread and impact of mosquito-borne disease outbreaks can help inform direct control and prevention measures. However, climate change is expected to increase weather variability, potentially shaping the future of mosquito-borne disease outbreaks globally. In this study, we sought to determine the effects of demographic and environmental noise (stochasticity) on the duration and size of outbreaks predicted by models of mosquito-borne disease. We developed a demographically and environmentally stochastic Ross-Macdonald model to assess how noise affects the probability of an outbreak, the peak number of cases, and the duration of outbreaks at increasing levels of the basic reproduction number (R0) and environmental noise strength. Increasing environmental noise reduces the risk of endemic disease from 100% down to almost 0%, but the largest outbreaks occur at intermediate environmental noise levels. In this case, if an outbreak dies out, it ends quickly. In the presence of noise, R0 alone is insufficient to definitively predict whether an outbreak occurs. Surprisingly, our modelling results suggest that the dramatic effect on mosquito populations from increases in the frequency of extreme environmental conditions could reduce the risk of endemic disease and epidemics in some settings.},
}

*Disease Outbreaks/statistics & numerical data
Animals
Humans
*Vector Borne Diseases/epidemiology/transmission
Mosquito Vectors
*Culicidae
Stochastic Processes
Basic Reproduction Number
Nonlinear Dynamics
*Noise
Models, Biological
Computational Biology
Climate Change
Mosquito-Borne Diseases

@article {pmid42003557,
year = {2026},
author = {Zu, B and Zhang, Y and Yu, Z and Li, B and Cheng, S and Du, M and Li, R and Liu, C and Zhou, B},
title = {miR-184/hamp-Mediated Cardiotoxicity and Hepatotoxicity in Offspring Zebrafish Following Paternal Exposure to Environmentally Relevant Concentrations of Tris(1,3-dichloro-2-propyl) Phosphate.},
journal = {Environmental science & technology},
volume = {},
number = {},
pages = {},
doi = {10.1021/acs.est.6c00486},
pmid = {42003557},
issn = {1520-5851},
abstract = {Recently, increasing attention has been focused on the intergenerational toxicity of environmental contaminants. Tris(1,3-dichloro-2-propyl)phosphate (TDCIPP) is a widely detected contaminant in aquatic environments, but its paternally mediated intergenerational toxicity in vertebrates has remained insufficiently elucidated. In this study, zebrafish at 50 days postfertilization (dpf) were exposed to environmentally relevant concentrations (55, 550, and 5500 ng/L) of TDCIPP for 150 days. Following exposure, the males were paired with unexposed females, and cardiotoxicity and hepatotoxicity were assessed in the offspring larvae. It was found that TDCIPP accumulated in F0 testes but not in the offspring embryos. Furthermore, paternal exposure to TDCIPP led to an increased heart rate, abnormal cardiac morphology, and significantly elevated ventricular wall thickness in the offspring zebrafish. Additionally, lipid metabolism disorders, abnormal liver morphology, and functional impairment were also observed in the offspring. Moreover, paternal exposure to TDCIPP down-regulated the expression of the hepcidin antimicrobial peptide gene (hamp) in the offspring larvae, leading to iron overload, which might contribute to the observed cardiotoxicity and lipid metabolism disorders in the offspring, as well as the subsequent development of hepatotoxicity. Furthermore, the up-regulation of miR-184 in F0 testes and offspring larvae accounted for the suppression of hamp expression following paternal exposure to TDCIPP. Our findings reveal that paternal exposure to TDCIPP induces up-regulation of miR-184 in F0 testes, and this overexpressed microRNA can be transmitted to the offspring, subsequently inhibiting hamp expression, leading to iron overload and consequently contributing to cardiotoxicity and hepatotoxicity in the offspring.},
}

@article {pmid42004444,
year = {2026},
author = {Ossendorf, G and Tekelemariam, MG and Taipale, N and Groos, AR and Negash, A and Cnuts, D and Akçar, N and Vockenhuber, C and Tariku, ZK and Kahsay, TH and Rots, V and Vogelsang, R},
title = {Human occupation of the Afroalpine Bale Mountains at the onset of the African Humid Period.},
journal = {Landscape ecology},
volume = {41},
number = {4},
pages = {75},
pmid = {42004444},
issn = {0921-2973},
abstract = {CONTEXT: The reasons for the intermittent human use of harsh Afroalpine environments in prehistory remain unclear. High-resolution glacial and archaeological chronologies from Ethiopia's Bale Mountains now offer insights into landscape change and human adaptations at high altitudes.

OBJECTIVES: This study investigates the behavioral signatures of human occupation in Africa's largest alpine environment around 15,000 years ago, focusing on local site use and integration into regional networks amid deglaciation and the abrupt onset of African Humid Period wet conditions.

METHODS: This research integrates surface exposure dating of moraine boulders and radiocarbon dating of archaeological rock shelter deposits with detailed analyses of lithic materials from three stratified sites in the Bale Mountains. We use multivariate statistical analyses of electron microprobe data to determine the geochemical provenance of obsidian artifacts. Lithic technological analysis is based on systematic recording of artifact attributes to reconstruct key stages of production. Functional analyses include use-wear and residue studies conducted using stereomicroscopy, reflected light microscopy, and scanning electron microscopy (SEM-EDX).

RESULTS: This study provides a detailed reconstruction of the final deglaciation phase in the Bale Mountains and identifies distinct patterns of lithic acquisition, production, and use across three contemporaneous sites. Dimtu, located on the formerly glaciated plateau and representing the highest known stratified archaeological site in Africa, is distinguished by a focus on the production of rare but specific pointed flakes. Simbero exhibits standardized backed tool production and evidence of hafting, while the Webi Gestro assemblage includes bladelets and notched tools; wear on unretouched bladelets indicates their use in transverse and longitudinal motions for processing activities and possibly as projectile elements. Geochemical results reveal obsidian exchange between high altitudes and lowlands, suggesting extensive social networks reinforced by technological and behavioral parallels.

CONCLUSIONS: Human strategies at high altitudes closely mirror contemporaneous lowland behavior, revealing synchronous patterns across ecological zones. Similar patterns during other periods point to broader systemic dynamics. Conventional refugium-based explanations fail to fully capture these patterns, highlighting the need to examine diachronic shifts in the scale, connectivity, and intensity of prehistoric networks across ecozones.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10980-026-02337-8.},
}

@article {pmid42007577,
year = {2026},
author = {Cai, ZF and Liu, B and Yin, TT and Ma, C and Han, ZT and Gu, LH and Zhang, C and Wu, F and Liu, LS and Shi, X and Wang, XQ and Wu, RN and Xie, LZ and Bai, Y and Zhang, YC and Zhang, SR and Gu, LJ and Wang, MS and Xie, GL and Cheng, WK and Lu, JG and Luo, Y and Li, SB and Ashari, H and Zein, MSA and Han, JL and Singchat, W and Srikulnath, K and Zhang, YP and Peng, MS},
title = {Harnessing Deep Learning in Searching Wild Relatives of Domestic Animals.},
journal = {Molecular ecology resources},
volume = {26},
number = {3},
pages = {e70133},
doi = {10.1111/1755-0998.70133},
pmid = {42007577},
issn = {1755-0998},
support = {2022YFC2602500//National Key Research and Development Program of China/ ; 2024YFD1200700//National Key Research and Development Program of China/ ; 202503AP140028//Yunnan International Joint Laboratory for Conservation and Gene Mining of Genetic Resources/ ; 2021FY100200//Science and Technology Basic Resources Investigation Program of China: "Wild Germplasm Collection and Preservation in the Greater Gaoligong Mountains"/ ; 32001091//National Natural Science Foundation of China/ ; //Ministry of Higher Education, Science, Research and Innovation, Thailand/ ; RUP_Climate68_No.9//Thailand Science Research and Innovation/ ; //Chinese Academy of Sciences/ ; //Kunming Institute of Zoology, Chinese Academy of Sciences,/ ; },
mesh = {Animals ; *Deep Learning ; *Animals, Domestic/genetics/classification ; *Chickens/genetics/classification ; Polymorphism, Single Nucleotide ; *Animals, Wild/genetics/classification ; Sus scrofa/genetics ; Genomics/methods ; Genetic Variation ; Swine/genetics ; *Computational Biology/methods ; },
abstract = {Wild relatives of domestic animals are crucial reservoirs of genetic diversity, yet pervasive hybridization with domestic animals poses significant conservation challenges. Here, we developed a deep learning-based pipeline, consisting of a multi-layer perceptron for SNP panel selection and a Deep & Cross Network for model training, to discern wild relatives from their closely related domestic animals using genomic SNP data. Leveraging the 1960 genomes from 164 red jungle fowl (RJF; Gallus gallus) and 1796 domestic chicken samples, we applied this pipeline to yield the RJF identification model based on a 285-SNP panel. We employed this model to characterize domestic chickens, RJF, and hybrids in the independent genomic datasets from contemporary samples and historical specimens, respectively. The accuracy was 97.8% for historical samples with missing genotypes. The benchmarking multiple hybrid detection tools indicated that the RJF identification model was effective and practical. The further application to the genomic data from wild boar (Sus scrofa), domestic pigs, and their hybrids validated the pipeline. Our method has potential in not only monitoring genetic diversity in wild relatives of domestic animals but also supporting animal genetic resource conservation and management.},
}

Animals
*Deep Learning
*Animals, Domestic/genetics/classification
*Chickens/genetics/classification
Polymorphism, Single Nucleotide
*Animals, Wild/genetics/classification
Sus scrofa/genetics
Genomics/methods
Genetic Variation
Swine/genetics
*Computational Biology/methods

@article {pmid42008016,
year = {2026},
author = {Yoneda, K},
title = {Comprehensive identification and subcellular localization prediction of carbonic anhydrases in the marine haptophyte Tisochrysis lutea based on a refined genome annotation.},
journal = {Archives of microbiology},
volume = {208},
number = {7},
pages = {},
pmid = {42008016},
issn = {1432-072X},
support = {23K14001//Japan Society for the Promotion of Science/ ; },
mesh = {*Carbonic Anhydrases/genetics/metabolism/chemistry ; *Haptophyta/genetics/enzymology ; Molecular Sequence Annotation ; Proteome/genetics ; Genome ; Computational Biology ; Photosynthesis ; },
abstract = {The marine haptophyte Tisochrysis lutea is a commercially important microalga known for its production of high-value lipids and carotenoids. While the CO2-concentrating mechanism (CCM) is essential for efficient photosynthesis in marine environments, its molecular basis in haptophytes remains poorly understood despite their ecological and industrial importance. In the present study, I first assessed proteome completeness of the latest gene models of T. lutea and subsequently re-annotated the reference genome to refine these models. I then identified the complete repertoire of carbonic anhydrases (CAs). The re-annotated models significantly improved the proteome-level BUSCO completeness from 76.7% to 89.9% and resolved previously fragmented sequences, resulting in 17,205 protein-coding genes with markedly reduced fragmentation. Within this refined proteome, I identified 16 CA genes across six distinct classes: one α-, five β-, three γ-, two δ-, one θ-, and four ι-type CAs. Subcellular localization was predicted using an integrated bioinformatic pipeline (SignalP, TargetP, ASAFind2, HECTAR, and DeepLoc-2), which suggested a complex compartmentalization of inorganic carbon interconversion. Notably, TlδCA1 and TlιCA3 exhibited high expression levels and were predicted to localize to the plasma membrane and plastid, respectively, indicating their pivotal roles in the CCM of T. lutea. Furthermore, structural analysis revealed unique features in haptophyte CAs, such as specific transmembrane domain configuration in δ-CA and conserved domain repeats in ι-CAs. These findings provide a molecular framework for understanding the CCM machinery in T. lutea, offering a robust genomic platform for future metabolic engineering aimed at enhancing carbon fixation efficiency in marine haptophytes.},
}

*Carbonic Anhydrases/genetics/metabolism/chemistry
*Haptophyta/genetics/enzymology
Molecular Sequence Annotation
Proteome/genetics
Genome
Computational Biology
Photosynthesis

@article {pmid42009284,
year = {2026},
author = {Macrina, L and Terraneo, TI and McFadden, CS and Sabino, A and Oury, N and Barreca, F and Vicario, S and Samimi-Namin, K and Knop, D and Rodrigue, M and Pieribone, V and Baird, AH and Berumen, ML and Reimer, JD and Paulay, G and Benzoni, F},
title = {Beyond Tubipora musica: Phylogenomics unveils the overlooked diversity and endemism of the hermatypic octocoral genus Tubipora.},
journal = {Molecular phylogenetics and evolution},
volume = {},
number = {},
pages = {108622},
doi = {10.1016/j.ympev.2026.108622},
pmid = {42009284},
issn = {1095-9513},
abstract = {Although scleractinians are typically considered the main reef-building corals, a few octocoral taxa also contribute to coral reef framework formation. The genus Tubipora deposits hard calcareous skeletons organised in tubes connected by horizontal stolonic platforms constituted of fused sclerites. The genus is broadly distributed across the tropical Indo-Pacific, but its diversity and evolutionary history remain poorly understood. Most recent treatments have recognized only the type species Tubipora musica, albeit historically ten species have been named. Here, using an integrative approach combining morphological and phylogenomic (based on Ultra-Conserved Element and exon loci) analyses of 136 Tubipora colonies collected across six marine provinces in the Indo-Pacific, we delimited 15 morphologically distinct and genetically strongly supported lineages. All lineages retrieved in our results exhibited restricted geographic distributions, limited to single areas, highlighting potential regional endemism. Endemic diversification is suggested by sister species restricted to the Red Sea, Madagascar, and Eastern Australia, as well as regional diversification in Arabia, the Western Indian Ocean, and the Western Pacific. Our results reveal deep diversification within the Western Pacific and are consistent with colonization of the Western Indian Ocean by a single clade that subsequently diversified there. Accordingly, these findings underscore the need for broader sampling across the Indo-Pacific to assess Tubipora diversity and diversification and highlight the power of genomics in clarifying species boundaries and evolutionary relationships, providing a foundation towards the taxonomic revision of Tubipora. Accurate species definition is essential for biodiversity assessment and conservation planning, particularly for reef-building taxa that may include geographically restricted lineages vulnerable to environmental change, ultimately enhancing our ability to monitor and mitigate such impacts on these organisms.},
}

@article {pmid42011984,
year = {2026},
author = {Chelaru, IA and Ciausu, RA and Savuca, A and Ureche, C and Nicoara, MN and Ciobica, AS and Andronic, GA and Ambrosie, RM and Ureche, D},
title = {Effects of environmentally relevant ibuprofen and valproic acid exposure on zebrafish behavior.},
journal = {Biomolecules & biomedicine},
volume = {},
number = {},
pages = {},
doi = {10.17305/bb.2026.14030},
pmid = {42011984},
issn = {2831-090X},
abstract = {Active pharmaceutical ingredients (APIs) are increasingly entering aquatic environments due to human and veterinary use, wastewater discharges, and inadequate waste containment, raising significant concerns for both ecosystems and human health. Ibuprofen and valproic acid are among the pharmaceuticals detected in surface waters, primarily due to incomplete metabolism and the limited removal efficiency of conventional wastewater treatment systems. Ibuprofen, readily available over the counter, is frequently found in high concentrations, while valproic acid, which is available only by prescription, is detected less often, likely reflecting its more restricted use. This study employed the established behavioral ecotoxicology model, Danio rerio, to investigate the effects of environmentally relevant concentrations of ibuprofen (20 µg L-1) and valproic acid (3 µg L-1) on zebrafish (8 months old) after 96 hours of exposure. Both compounds influenced locomotor and anxiety-related endpoints, with changes in social preference primarily associated with valproic acid exposure. Single compound exposures resulted in reduced total distance traveled and average velocity, while combined exposure did not differ from the control group, indicating no additive locomotor impairment. Inactivity duration decreased in both individual treatments, most significantly with valproic acid, whereas the mixture produced no significant effect. Only ibuprofen reduced counterclockwise rotations, suggesting a mild anxiolytic-like response. Given the ecological importance of social cohesion and locomotor performance in predator avoidance, foraging, and reproduction, such behavioral disruptions may compromise population stability. These findings highlight the necessity of integrating behavioral endpoints and considerations of mixture toxicity into ecological risk assessments of pharmaceutical contaminants in aquatic systems.},
}

@article {pmid41998806,
year = {2026},
author = {Tang, R and Wang, J and Zhang, Z and Li, Y and Lan, Y and Fan, Z},
title = {Temporal Shifts in Gut Microbiota and Host Immunity During Chronic Diarrhea in an Infant Rhesus Macaque: A Longitudinal Case Study Based on Multi-Omics.},
journal = {Journal of medical primatology},
volume = {55},
number = {3},
pages = {e70074},
doi = {10.1111/jmp.70074},
pmid = {41998806},
issn = {1600-0684},
support = {2023NSFSC1935//Sichuan Province Science and Technology Support Program/ ; 32370450//National Natural Science Foundation of China/ ; },
mesh = {Animals ; *Macaca mulatta/immunology ; *Gastrointestinal Microbiome ; *Diarrhea/veterinary/microbiology/immunology ; *Monkey Diseases/immunology/microbiology ; Longitudinal Studies ; Transcriptome ; Male ; Anti-Bacterial Agents/therapeutic use ; Female ; Chronic Disease ; Multiomics ; },
abstract = {Diarrhea remains a major health challenge in captive rhesus macaques (RMs; Macaca mulatta), particularly among infants, yet the dynamic interplay between gut microbiota and host immune responses during disease progression remains poorly understood. Here, we conducted a longitudinal multi-omics study on a captive infant RM, analyzing 25 fecal metagenomes and 18 blood transcriptomes across diarrheal, antibiotic treatment, and recovery phases. Our results demonstrated that disease state was the primary driver of gut microbiota variation. The diarrheal phase was characterized by a significant reduction in microbial α-diversity and marked expansion of multidrug-resistant Enterobacteriaceae, including Escherichia, Shigella, and Salmonella, accompanied by severe depletion of probiotic genera such as Lactobacillus and Bifidobacterium. Correspondingly, antibiotic resistance genes targeting fluoroquinolones and cephalosporins accumulated substantially during diarrhea, explaining the limited efficacy of empirical antibiotic therapy. Blood transcriptome analysis revealed heightened innate immune activation, evidenced by upregulation of interferon-related genes, alongside suppression of adaptive immune pathways including interleukin-5 signaling. Integrated correlation analysis uncovered synchronized host-microbiome interactions, with inflammatory gene expression positively associated with opportunistic pathogens and negatively correlated with beneficial commensals. Clinical recovery coincided with re-establishment of probiotic populations, reduction in resistance gene burden, and normalization of immune function. These findings demonstrate that infant macaque diarrhea profoundly disrupts both gut microbial ecology and systemic immunity, supporting management strategies that prioritize targeted antimicrobial intervention and microbiome restoration over prolonged empirical antibiotic use in captive primates.},
}

Animals
*Macaca mulatta/immunology
*Gastrointestinal Microbiome
*Diarrhea/veterinary/microbiology/immunology
*Monkey Diseases/immunology/microbiology
Longitudinal Studies
Transcriptome
Male
Anti-Bacterial Agents/therapeutic use
Female
Chronic Disease
Multiomics

@article {pmid41999115,
year = {2026},
author = {Zhang, Y and Zhang, H and Akashi, H and Albouy, CP and Andres, KJ and Barquín, J and Brantschen, J and Connon, RE and Craine, JM and Gleeson, D and Goldenberg-Vilar, A and González-Ferreras, AM and Hatzenbuhler, C and Hupało, K and Hyde, J and Iwasaki, W and Johnson, MD and Katz, AD and Kuzovlev, VV and Larson, CE and Lecaudey, LA and Leese, F and Leray, M and Li, F and Macher, TH and Mauvisseau, Q and Morán-Luis, M and Nester, G and Quintero, H and Ravelomanana, T and Chacko, MR and Saccò, M and Sales, N and Schenekar, T and Schletterer, M and Schmidt, S and Schulte, NO and Schütz, R and Sperry, JH and Stevens, ER and Stinson, SA and Weiss, S and Xia, F and Zhang, H and Zhang, S and Zhong, W and Zong, S and Pellissier, L and Zhang, X and Altermatt, F},
title = {Integrated Reanalysis of Global Riverine Fish eDNA Datasets Shows Robustness and Congruence of Biodiversity Conclusions.},
journal = {Molecular ecology},
volume = {35},
number = {8},
pages = {e70340},
pmid = {41999115},
issn = {1365-294X},
support = {2022YFC32021001//National Key Research and Development Program of China/ ; 2021YFC3201003//National Key Research and Development Program of China/ ; 42507382//National Natural Science Foundation of China/ ; 310030_197410//Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung/ ; 31003A_173074//Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung/ ; },
mesh = {*Biodiversity ; Animals ; *Fishes/genetics/classification ; *DNA, Environmental/genetics ; DNA Barcoding, Taxonomic ; Rivers ; Computational Biology ; Ecosystem ; },
abstract = {The analysis of environmental DNA (eDNA) has revolutionized biodiversity assessments in aquatic ecosystems, enabling non-invasive monitoring of fish communities across diverse regions. However, the global comparability of these eDNA datasets remains ambiguous due to heterogeneous sampling protocols and bioinformatic workflows across studies, making it difficult to assess how robust and comparable the biodiversity patterns inferred from these datasets actually are. Here, we conducted a meta-analysis of 58 riverine fish eDNA metabarcoding studies, covering 1818 sampling sites worldwide, to evaluate the robustness of eDNA-derived biodiversity patterns. We found that species richness estimates and metrics of community structure derived under a common bioinformatic workflow were overall consistent with those of original analyses, despite the relatively high variability in bioinformatic analyses in the respective original studies. Contrastingly, congruence of species identity varied more extensively across datasets, mostly reflecting different completeness and regional relevance of reference databases. Restricting taxonomic assignment to basin-specific species pools improved species identification accuracy, while datasets lacking publicly accessible or well-curated reference data were more prone to mismatches. Year of sampling had a positive effect on taxonomic congruence, such that more recent studies showed increased robustness, also reflecting improved reference database coverage and enhanced species-level identification over time and overall method congruence in more recent years. Overall, the suitability and potential of eDNA for global biodiversity monitoring is corroborating overall robust biodiversity estimates, irrespective of the bioinformatic approaches. Our study underlines the effectiveness and need for further harmonization of bioinformatic workflows and strengthened region-specific reference databases for improved taxonomic resolution and comparability across studies.},
}

*Biodiversity
Animals
*Fishes/genetics/classification
*DNA, Environmental/genetics
DNA Barcoding, Taxonomic
Rivers
Computational Biology
Ecosystem

@article {pmid42002290,
year = {2026},
author = {Jadin, RC and Orlofske, SA},
title = {AN ACTIVE LEARNING PROJECT FOR TEACHING BIOINFORMATICS, PHYLOGENETICS, AND PARASITOLOGY.},
journal = {The Journal of parasitology},
volume = {112},
number = {2},
pages = {203-208},
doi = {10.1645/25-19},
pmid = {42002290},
issn = {1937-2345},
mesh = {*Phylogeny ; *Parasitology/education ; *Computational Biology/education ; *Problem-Based Learning ; Humans ; Animals ; Curriculum ; },
abstract = {This article describes an active learning project designed for implementation in general biology, ecology, evolution, and parasitology courses. It involves individual or group-based tasks in which students role-play as various types of biologists to solve real-world parasitology problems through molecular data analysis. Specifically, students are provided with a scenario and a molecular data set to analyze, which involves performing bioinformatic tasks to construct a phylogenetic tree. Students use MEGA software to explore, create, and illustrate a phylogenetic analysis of parasites with GenBank sequences. The resulting phylogenetic tree helps identify an "unknown" taxon and provides the evidence required to address the scenario and answer the posed question. By fostering a deeper understanding of evolutionary processes and bioinformatics tools, this project not only enhances students' knowledge of parasitology but also prepares them to tackle complex, interdisciplinary challenges in global health, biodiversity conservation, and beyond, shaping the next generation of scientists capable of addressing the urgent issues facing our world.},
}

*Phylogeny
*Parasitology/education
*Computational Biology/education
*Problem-Based Learning
Humans
Animals
Curriculum

@article {pmid41995560,
year = {2026},
author = {Demirtaş, Y and Şahinöz, T},
title = {Trends and determinants of tuberculosis incidence in Turkey: A secondary data analysis.},
journal = {Medicine},
volume = {105},
number = {16},
pages = {e48278},
doi = {10.1097/MD.0000000000048278},
pmid = {41995560},
issn = {1536-5964},
mesh = {Humans ; Turkey/epidemiology ; Incidence ; *Tuberculosis/epidemiology ; Longitudinal Studies ; Female ; Male ; Adult ; Socioeconomic Factors ; Linear Models ; Social Determinants of Health ; Risk Factors ; Secondary Data Analysis ; },
abstract = {Tuberculosis remains a major public health concern, with incidence rates influenced by social determinants of health. Although tuberculosis incidence in Turkey has declined markedly in recent decades, the factors associated with this decline have not been comprehensively evaluated at the country-level. This study aimed to examine trends in tuberculosis incidence in Turkey from 1982 to 2021 and to identify determinants of tuberculosis incidence rates between 2000 and 2021, considering variables categorized under composite development, economic indicators, population, and health services. A longitudinal ecological study was conducted using secondary data to examine trends and determinants of tuberculosis incidence in Turkey. Univariate and multivariable linear regression were employed to evaluate the associations between tuberculosis incidence rates and 10 selected variables. Tuberculosis incidence in Turkey declined substantially over the 40-year period analyzed, with an overall decrease of 86.6% and sharper reductions observed in certain intervals. In multivariable linear regression, only the Human Development Index remained independently associated with tuberculosis incidence (β = -1.041, P < .001), indicating that higher Human Development Index values were associated with lower tuberculosis incidence rates in Turkey. These findings indicate that tuberculosis incidence in Turkey has declined alongside changes in human development, as reflected by the composite Human Development Index.},
}

Humans
Turkey/epidemiology
Incidence
*Tuberculosis/epidemiology
Longitudinal Studies
Female
Male
Adult
Socioeconomic Factors
Linear Models
Social Determinants of Health
Risk Factors
Secondary Data Analysis

@article {pmid41997124,
year = {2026},
author = {Shi, M and Patti, GJ and Gunter, MJ and Govindan, R and Lansdorp-Vogelaar, I and Wang, T and Townsend, JP and Colditz, GA and Belkaid, Y and Cao, Y},
title = {Accelerating discovery of cancer causes for prevention in the era of rising early-onset cancers.},
journal = {Cell},
volume = {189},
number = {8},
pages = {2232-2253},
doi = {10.1016/j.cell.2026.03.019},
pmid = {41997124},
issn = {1097-4172},
mesh = {Humans ; *Neoplasms/prevention & control/epidemiology/etiology/genetics ; Age of Onset ; Risk Assessment ; },
abstract = {Cancer in younger adults is rising globally, with notable birth-cohort effects. This epidemiological shift underscores the urgent need to accelerate the identification of novel causes and underlying biological networks, with the aim of translating these insights into prevention and interception strategies. In this perspective, we revisit the major milestones in the discovery of cancer causes and outline challenges that hinder progress. To address these challenges, we advocate closer integration of epidemiologic and mechanistic studies and propose three interconnected frameworks that extend current epidemiologic approaches: a tissue ecosystem-anchored framework for cancer cause discovery, a biological state-based framework for precision cancer risk assessment, and a dynamic framework to characterize cancer preventability. This roadmap aims to stimulate conceptual, resource, and methodological advances to accelerate cancer etiology research and prevention in the era of rising early-onset cancers.},
}

Humans
*Neoplasms/prevention & control/epidemiology/etiology/genetics
Age of Onset
Risk Assessment

@article {pmid41990227,
year = {2026},
author = {Parween, S and Nagarajan, AP and Alghamdi, AK and Eida, AA and Lafi, FF and Albanna, L and Salem, N and Abu-Irmaileh, B and Pirzada, ZA and Siddique, S and Garrido-Oter, R and Schulze-Lefert, P and Saad, MM and Hirt, H},
title = {Desert Plant Endophyte Genome Database: a curated repository of endophytic bacterial genomes across arid ecosystems.},
journal = {Database : the journal of biological databases and curation},
volume = {2026},
number = {},
pages = {},
doi = {10.1093/database/baag020},
pmid = {41990227},
issn = {1758-0463},
support = {BAS/1/1062-01-01//KAUST/ ; },
mesh = {*Endophytes/genetics ; *Desert Climate ; *Genome, Bacterial ; *Databases, Genetic ; *Plants/microbiology ; *Ecosystem ; *Bacteria/genetics ; },
abstract = {Microbial communities associated with desert plants play a pivotal role in enhancing host survival under extreme environmental stressors, including drought, salinity, and nutrient limitation. The Desert Plant Endophyte Microbial Collection is one of the largest curated repositories of 2500 cultivable endophytic bacteria isolated from 23 native desert plant species across Saudi Arabia, Jordan, and Pakistan. Representing a broad spectrum of arid microhabitats from inland deserts and mountain wadis to coastal mangroves and date palm oases, the collection supports integrative studies on microbial ecology and plant-microbe interactions in water-limited ecosystems. A central component of this initiative is the Desert Plant Endophyte Genome Database, which currently hosts whole-genome sequences of 534 endophytic bacterial isolates annotated with extensive ecological metadata, assembly statistics, functional traits, and host associations. The database interface provides tools for genome exploration, metadata filtering, and functional gene mining, enabling users to identify taxa and traits of agronomic interest, particularly for applications in sustainable agriculture and sustainable desert revegetation. By combining genomic, ecological, and functional data, the Desert Plant Endophyte Genome Database serves as a foundational platform for the development of targeted microbial inoculants and fosters data-driven research into desert microbiomes and plant resilience mechanisms.},
}

*Endophytes/genetics
*Desert Climate
*Genome, Bacterial
*Databases, Genetic
*Plants/microbiology
*Ecosystem
*Bacteria/genetics

@article {pmid41991539,
year = {2026},
author = {Lionello, P and Di Fant, V and Pasquier, U and Tosi, L and Cozannet, GL and Nicholls, RJ and Cramer, W and Cremades, R and Giupponi, C and Hinkel, J and Sfriso, A and Teatini, P and Vafeidis, AT and Umgiesser, G and Haasnoot, M},
title = {Long-term adaptation pathways for Venice and its lagoon under sea-level rise.},
journal = {Scientific reports},
volume = {16},
number = {1},
pages = {},
pmid = {41991539},
issn = {2045-2322},
support = {Pathways2Resilience project (101093942)//European Union's Horizon 2020/ ; Adapt@Ve Programme//Fondazione Eni Enrico Mattei/ ; },
abstract = {The substantial risks posed to Venice and its lagoon by ongoing and projected sea-level rise (SLR) require unprecedented long-term adaptation strategies. We map the evolution of development pathways and the progressive shrinking of the solution space as SLR advances, identifying adaptation tipping points and analysing the relative pros and cons of alternative measures. The analysis highlights trade-offs among environmental quality, heritage preservation, social well-being and relevant Sustainable Development Goals, and costs increasing with SLR. With present insufficient greenhouse gas mitigation policies, the current open lagoon strategy, with mobile barriers and multiple accommodation measures, is likely to encounter hard limits within the current century. Follow-up strategies include ring-dikes isolating the city from the rest of the lagoon, or a closed lagoon with permanent coastal dams, each preserving different combinations of values while entailing major ecological and socio-cultural transitions. Under extreme SLR, relocation of monuments to suitable inland areas and abandonment would be the only remaining strategy, which might become unavoidable in the 22nd century under current climate policies and an Antarctic ice-sheet collapse. Rapid mitigation could still avoid the most disruptive long-term outcomes.},
}

@article {pmid41992918,
year = {2026},
author = {Luijten, M and Herzler, M and Affourtit, F and Allen, D and Ashraf, MW and Ball, N and Berggren, E and Berndt, S and Billat, PA and Cöllen, E and Colbourne, J and Marco, M and Currie, R and Diemar, MG and Dirven, H and Dreser, N and Escher, SE and Gardner, I and Gozalbes, R and Hahn, S and Heiland, A and Hempt, C and Hendriks, G and Henschel, O and Husøy, T and Islam, B and Jensen, KA and Kamp, H and Karakitsios, S and Kass, GEN and Kumar, V and Landsiedel, R and Loret, T and Lundquist, P and Mahony, C and Marx-Stoelting, P and Moné, MJ and Ottenbros, I and Ouédraogo, G and Pastor, M and Sachana, M and Schmeisser, S and Scholz, S and Schütte, K and Sullivan, K and Tangianu, S and Tristram, A and Turner, J and Vinken, M and Vlaanderen, J and van de Water, B and White, A and Leist, M},
title = {Stakeholder input towards further refinement and consolidation of the alternative safety profiling algorithm (ASPA) for next generation risk assessment (NGRA).},
journal = {ALTEX},
volume = {},
number = {},
pages = {},
doi = {10.14573/altex.2603121},
pmid = {41992918},
issn = {1868-8551},
abstract = {Next-generation risk assessment (NGRA) aims to enable transparent, reproducible chemical safety assessments based on human-relevant, animal-free new approach methodologies (NAMs). The Alternative Safety Profiling Algorithm (ASPA) was developed within the ASPIS cluster to provide an algorithmic workflow that structures problem formulation, evidence integration, and decision-making across three main pillars-hazard, ADME (toxicokinetics), and exposure. To refine ASPA, a stakeholder workshop was organized. Four breakout groups systematically reviewed corresponding workflow sections, identifying strengths, conceptual gaps, and opportunities for harmonization. Across groups, participants endorsed ASPA's modular, technology-neutral nature and its focus on standardizing processes rather than prescribing specific test batteries. The hazard pillar discussions emphasized a sensitive, hypothesis-generating Tier 1, complemented by a specific, mechanistic Tier 2, capable of deriving points of departure (PoDs). ADME experts supported a physiology-based kinetic (PBK) modelling strategy, advancing from generic towards more complex models, using mechanistic information and experimental data. The exposure group proposed refinements for transparent, tiered exposure modelling, with emphasis on realistic worst-case scenarios and explicit uncertainty communication. Cross-pillar discussions highlighted the importance of feedback loops between all pillars, and the documentation of decision points to achieve consistency and defensibility. The workshop outcomes informed three parallel developments: (i) algorithmic refinement and re-design toward the next ASPA version, (ii) the creation of detailed guidance for each building block, and (iii) the establishment of practical case studies to demonstrate workflow implementation. This report already contains a first case study (developmental neurotoxicity assessment of desnitro-imidacloprid). These advances increase the operability, transparency, and regulatory readiness of ASPA.},
}

@article {pmid41993749,
year = {2026},
author = {Malik, V and AlJarullah, A and Alsubait, T and Ikram, A and Goyal, SB and Khan, M},
title = {Explainable artificial-intelligence-based hyperspectral image analysis for leaf disease detection in intercropping system.},
journal = {Frontiers in plant science},
volume = {17},
number = {},
pages = {1789542},
pmid = {41993749},
issn = {1664-462X},
abstract = {INTRODUCTION: Intercropping regimes enhance the efficiency of land use and ecological sustainability but present serious problems to automated disease analysis since the overlapping canopy and the similarity of symptoms in crop species are visually indistinguishable.

METHODS: This work presents an explainable artificial intelligence (XAI)-based hyperspectral analysis on leaf disease in intercropping systems. The framework combines the spectral-spatial feature generators that utilize transformers including vision transformer (ViT), Swin transformer, pyramid vision transformer (PVT), and detection transformer (DETR) to identify nuanced biochemical and structural changes in crop combinations for maize-soybean and pea-cucumber. In order to reduce spectral redundancy and high dimensionality, an enhanced greedy political optimization (EGPO) algorithm is used as a wrapper-based feature selection strategy. A capsule spatial shift neural network (CSSNet) is used to predict the classification of diseases. Explainable AI methods, such as Local Interpretable Model-agnostic Explanations (LIME) and SHapley Additive exPlanations (SHAP) feature attribution analysis and gradient-weighted class activation mapping (Grad-CAM) visualization of disease-relevant regions, provide model transparency. The DETR + EGPO + CSSNet framework is tested on the conventional feature selection methods.

RESULTS AND DISCUSSION: The results or findings on publicly available hyperspectral datasets on intercropping show an average recall of 99.998% with high region consistency (Dice score: 99.997%) of activation maps and expert-marked disease regions. These findings affirm that the proposed framework is highly accurate, stable, and interpretable to identify subtle and overlapping disease in leaves in a complex system of intercropping.},
}

@article {pmid41994308,
year = {2026},
author = {van Gerrevink, MJ and Veraverbeke, S and Cooperdock, S and Potter, S and Zhong, Q and Moubarak, M and Virkkala, AM and Goetz, SJ and Mack, MC and Randerson, JT and Schutgens, N and Turetsky, MR and van der Werf, GR and Rogers, BM},
title = {Climate impacts from North American boreal forest fires.},
journal = {Nature geoscience},
volume = {19},
number = {4},
pages = {455-461},
pmid = {41994308},
issn = {1752-0894},
abstract = {The boreal forest biome is warming rapidly, impacting disturbance regimes and global climate. Boreal forest fires have intensified, initiating both climate warming (positive) and climate cooling (negative) impacts across spatial and temporal scales. Here we estimate climate impacts from boreal fires in Alaska and western Canada between 2001 and 2019 using integrated net radiative forcing metrics combining greenhouse gas and aerosol emissions from combustion, vegetation recovery, greenhouse gas emissions from fire-induced permafrost thaw and changes in surface albedo over a 70-year period. We find that fires across Alaska contributed, on average, to net climate warming (0.35 ± 4.66 W m[-2] of burned area; one standard deviation), while fires across Canada contributed to net cooling (-2.88 ± 4.17 W m[-2] of burned area; one standard deviation). Climate-warming fires occur preferentially in dry, high-elevation, steep permafrost landscapes with high pre-fire black spruce coverage and combust more carbon per unit area. Climate-cooling fires are driven by longer spring snow exposure and occur more frequently in continental regions near the treeline. This fine-scale characterization of component and net radiative forcing advances our understanding of the biogeophysical impacts of fires on high-latitude climate and highlights the need to prioritize fire management in carbon-rich permafrost regions to curb long-term warming.},
}

@article {pmid41994310,
year = {2023},
author = {Boyes, D and Holland, PWH and , and , and , and , and , and , },
title = {The genome sequence of the Water Carpet, Lampropteryx suffumata (Denis & Schiffermiiller, 1775).},
journal = {Wellcome open research},
volume = {8},
number = {},
pages = {304},
doi = {10.12688/wellcomeopenres.19654.2},
pmid = {41994310},
issn = {2398-502X},
abstract = {We present a genome assembly from an individual male Lampropteryx suffumata (the Water Carpet; Arthropoda; Insecta; Lepidoptera; Geometridae). The genome sequence is 581.6 megabases in span. Most of the assembly is scaffolded into 31 chromosomal pseudomolecules, including the Z sex chromosome. The mitochondrial genome has also been assembled and is 16.48 kilobases in length. Gene annotation of this assembly on Ensembl identified 18,663 protein coding genes. This assembly was generated as part of the Darwin Tree of Life project, which produces reference genomes for eukaryotic species found in Britain and Ireland.},
}

@article {pmid41090561,
year = {2026},
author = {Zhang, T and Luo, D and Li, G and Wang, H and Cao, Q and Zhang, R and Li, Y and Zhu, Y and Ma, C and Liston, A and Sun, H and Qiao, Q},
title = {Multi-omics analyses shed lights on the evolution and fruit development of Chinese raspberries (Rubus spp.).},
journal = {Journal of integrative plant biology},
volume = {68},
number = {4},
pages = {1032-1048},
doi = {10.1111/jipb.70052},
pmid = {41090561},
issn = {1744-7909},
support = {202301AS070071//Yunnan Fundamental Research Projects/ ; 202505AS350015//Yunnan Fundamental Research Projects/ ; 202501AS070177//Yunnan Fundamental Research Projects/ ; 32260094//National Natural Science Foundation of China/ ; 32372655//National Natural Science Foundation of China/ ; 82260739//National Natural Science Foundation of China/ ; 2024YFF1306702//National Key Research and Development Program of China/ ; },
mesh = {*Rubus/genetics/growth & development/metabolism ; *Fruit/growth & development/genetics/metabolism ; Genome, Plant/genetics ; *Genomics ; Phylogeny ; Transcriptome/genetics ; Multiomics ; },
abstract = {Rubus (raspberries and blackberries) is a large genus of over 700 species well known for its taxonomic challenges. Many of its species hold significant economic value as important edible and medicinal plants. Here, near-complete genomes for four wild diploid raspberry species were assembled, including R. ellipticus, R. niveus, as well as the highly heterozygous diploid red raspberry (R. idaeus), and its closely related species R. sachalinensis. Pan-genome analysis of Rubus identified 10,243 core gene families (64% of total), and highlights expansions of flavonoid/terpenoid pathways in Rubus, correlating with fruit bioactive compound diversity. Our discovery of shared ancestral components between R. idaeus and R. sachalinensis subgenomes provides evidence for their homoploid hybrid origin. The centromere sequence characteristics could serve as markers for subgenome assignment in R. idaeus and R. sachalinensis. Moreover, population genomic studies of 125 accessions from ca. 80 species uncovered widespread genetic introgression, particularly in red raspberries, with centromeric haplotype signatures tracing ancestral contributions to cultivated varieties. By integrating metabolome and transcriptome data, we explore the fruit quality regulatory network of Chinese raspberries. We identified a glutathione S-transferase gene that may inhibit the successful transport of anthocyanins into the vacuole and appears to be a limiting factor for the anthocyanin pigmentation in R. ellipticus fruits. In summary, this research sheds new light on the genetic intricacies of raspberry species and their cultivars, and provides a robust foundation for horticultural improvement and genomic selection in raspberry breeding.},
}

*Rubus/genetics/growth & development/metabolism
*Fruit/growth & development/genetics/metabolism
Genome, Plant/genetics
*Genomics
Phylogeny
Transcriptome/genetics
Multiomics

@article {pmid41978890,
year = {2026},
author = {Pereira Belúcio, L and Reyes Flores, CA and Leão de Oliveira, L and Frederico Mortati, A and Batista Rodrigues, D and Vieira Feitoza, G and André, T and Schöngart, J and Fernandez Piedade, MT and Cavalcanti da Cunha, A},
title = {Soil physicochemical gradient from headwaters to flooded riparian zones in the Falsino River, Eastern Amazonia.},
journal = {PeerJ},
volume = {14},
number = {},
pages = {e20882},
pmid = {41978890},
issn = {2167-8359},
mesh = {*Rivers/chemistry ; *Soil/chemistry ; *Floods ; Brazil ; Geographic Information Systems ; Environmental Monitoring/methods ; Hydrology ; },
abstract = {This study investigates the edaphic-hydrological gradients of riparian zones in the Falsino River basin, Eastern Amazon. We defined 21 sampling units based on water body order (2nd to 4th) to capture edaphic and hydrological variation. Maximum river level values (MRL) were represented using limnimetric rulers as proxy of flood pulse intensity, and physicochemical analysis was performed on 378 soil samples. The topographic measurements by Global Positioning System (GPS) and Shuttle Radar Topography Mission (SRTM) quantified basin levels and the results were compared. Results reveal a clear spatial pattern, with MRL increasing with tributary order and decreasing elevation. Flood pulse intensity strongly influenced soil texture and acidity, while variables such as organic matter and phosphorus were weakly associated. The inverse relationship between elevation and MRL highlights the topographic control on hydrological dynamics, although elevation alone did not explain most soil variations. Both GPS and SRTM showed strong agreement, validating their use in low-relief Amazonian landscapes. Sample plot delimitation along the basin's longitudinal profile facilitated the evaluation of abiotic attribute relationships. This research provides novel insights into how hydro-topographic interactions shape riparian soil properties, offering a practical framework for hydropedological assessments in remote tropical basins.},
}

*Rivers/chemistry
*Soil/chemistry
*Floods
Brazil
Geographic Information Systems
Environmental Monitoring/methods
Hydrology

@article {pmid41983802,
year = {2026},
author = {Rudgers, JA and Gherardi, LA and Yogi, P and Bacigalupa, M and Miller, TEX and Blais, JJ and Bolin, L and Collins, SL and Hou, E and Luo, Y and Morales, JO and Pockman, WT and Richardson, AD and Villatoro-Castañeda, M and Wesely, NK and Whitney, KD and Zhou, Y},
title = {Precipitation variability interacts with mean precipitation to restructure a semiarid grassland community.},
journal = {Ecology},
volume = {107},
number = {4},
pages = {e70365},
doi = {10.1002/ecy.70365},
pmid = {41983802},
issn = {1939-9170},
support = {1655499//Division of Environmental Biology/ ; 2425290//Division of Environmental Biology/ ; },
mesh = {*Grassland ; *Rain ; *Plants/classification ; Biodiversity ; Climate Change ; Time Factors ; },
abstract = {Climate forecasts project change not only in the mean of climate variables but also in their variance. If these dual changes interact, then future ecological dynamics will be difficult to predict using current experimental approaches, which typically change the mean or impose a single extreme event, such as drought. We designed a new field experiment to factorially reduce mean precipitation and increase its interannual variability. Across 4 years, drier, more variable precipitation additively reduced aboveground primary productivity by 48%-69% and interactively reduced the dominant plant species, but had no effect on the plant species predicted to dominate in the future, which could lead to state transition. Drier, more variable precipitation also interactively reduced biodiversity more than either climate factor alone, with 37%-42% fewer plant species than under ambient conditions, a pattern that matched declining richness during the past 20 years of ongoing climate change. Drier, more variable precipitation restructured the composition and spatiotemporal variation of the plant community. Altered precipitation mean or variance affected 14% of plant species, with eight species sensitive to the mean × variance interaction. Results suggest that future forecasts of plant community structure may be inadequate if they fail to incorporate climate mean × variance interactions.},
}

*Grassland
*Rain
*Plants/classification
Biodiversity
Climate Change
Time Factors

@article {pmid41989469,
year = {2026},
author = {Shchyogolev, S and Muratova, A and Turkovskaya, O and Matora, L},
title = {The Rieske dioxygenase system in Achromobacter: in silico studies of the protein structure and substrate interactions.},
journal = {Archives of microbiology},
volume = {208},
number = {7},
pages = {},
pmid = {41989469},
issn = {1432-072X},
mesh = {*Achromobacter/enzymology/genetics/chemistry ; *Bacterial Proteins/chemistry/metabolism/genetics ; Substrate Specificity ; *Dioxygenases/chemistry/metabolism/genetics ; Protein Conformation ; Computational Biology ; Computer Simulation ; Models, Molecular ; Amino Acid Sequence ; },
abstract = {Using a set of protein sequences of the class IIB Rieske dioxygenase system of the Achromobacter insolitus LCu2 strain, known for its ability to degrade pollutants, large-scale bioinformatic assessments of the potential of Achromobacter as an effective tool for bioremediation were performed. More than 100 homologues and isoforms of proteins in this system have been identified in various species of the genus Achromobacter. The reproducibility and stability of their 3D structures with ions and coenzymes, predicted using the AlphaFold 3 program, were established despite significant changes in protein sequences with a percentage identity of ≈ 20-99% within the genus. Using AlphaFold 3 and DeepPeptide programs and considering the experimental 3D structures of Rieske dioxygenase proteins of various bacterial classes from the PDB database, presumable propeptides were identified for the first time in achromobacteria at the N- and C-termini of the protein precursors. Their possible functions include participation in the folding, maturation, stabilization of proteins, and regulation of their activity. The genomic context of the proteins in the type strains of Achromobacter species revealed a conservative clustering pattern. Along with the stability of the protein 3D structures, this may contribute to the conservation of the functional activity of the enzymes as the strains adapt to their respective ecological niches. The interactions of the substrates with the enzyme and isoenzyme in the catalytic domain of the dioxygenase were characterized Using AutoDock Vina, which showed that their substrate specificity remained virtually unchanged. Overall, a wide range of Achromobacter strains suitable for biodegradation (bioremediation) was identified.},
}

*Achromobacter/enzymology/genetics/chemistry
*Bacterial Proteins/chemistry/metabolism/genetics
Substrate Specificity
*Dioxygenases/chemistry/metabolism/genetics
Protein Conformation
Computational Biology
Computer Simulation
Models, Molecular
Amino Acid Sequence

@article {pmid41975475,
year = {2026},
author = {Floridia, T and Mendoza, JN and Fantinato, E and Zocchi, DM and Barbasetti di Prun, L and Sõukand, R and Mattalia, G},
title = {Local farmers, custodians of wild food plant knowledge and uses in the touristified Venice Lagoon.},
journal = {Journal of ethnobiology and ethnomedicine},
volume = {},
number = {},
pages = {},
doi = {10.1186/s13002-026-00888-3},
pmid = {41975475},
issn = {1746-4269},
abstract = {BACKGROUND: The islands of Sant'Erasmo and Vignole, nestled in the Venice Lagoon, are biocultural refugia, where local ecological knowledge (LEK) of local communities, vital for wetland conservation, is being eroded by factors such as rural depopulation, globalization and touristification. This study investigates Local Gastronomic Knowledge (LGK) of Wild Food Plants (WFPs) among farmers and fishers to determine how occupation specialization influences knowledge distribution. It also investigates the ability of farmers to transform LGK into an economic resource by creating (or entering) niche economies, even though being immersed in a touristified and globalized context.

METHODS: From 2022 to 2025, semi-structured interviews were conducted with 18 farmers (Sant'Erasmo and Vignole) and 31 fishers of the Venice lagoon.

RESULTS: We documented 39 wild plant taxa, focusing on folk taxonomy, culinary preparations, and sale of WFPs. A significant occupational knowledge gap was identified: 94% of farmers utilized wild plants (with 70% of them also involved in their sale), naming 39 taxa, whereas fishers reported minimal knowledge representing only 10% of the sample (three out of 31 interviewed) and naming 2 out of the 39 documented taxa, confirming that LGK is tied to everyday contact with specific resources. Farmers demonstrated a very specialized knowledge, including 35% of uses previously unrecorded at the regional or national level.

CONCLUSIONS: The findings of this study reveal that LGK among farmers, thus people who live in close connection with the soil and vegetation of the Venice lagoon, is still vivid and it is increasingly economically valued. The study also shows a sharp distinction in the LGK on WFPs between farmers and fishers, revealing a strong knowledge specialization tied to their primary occupation, essential in a context of rural depopulation and touristification, for identifying knowledge hotspots and supporting the resilience of local economies. Furthermore, the economic valorization of WFPs (through their incorporation into local short food supply chains) may further encourage their continued use and LGK transmission. We believe this may empower farmers and facilitate the expansion of WFP markets, shedding light on a positive narrative that sees farmers as active custodians of LGK, rather than as passively subjected to globalization, especially in tourist areas as the Venice lagoon is.},
}

@article {pmid41791164,
year = {2026},
author = {Ding, Y and Wang, W and Luo, T and Song, Y and Gao, Y and Zhang, Z and Zhao, H and Wang, H and Li, H},
title = {Multi-omics evaluation of grape microbial diversity and natural wine flavor metabolites under extra-simplified eco-viticulture.},
journal = {Food chemistry},
volume = {510},
number = {},
pages = {148671},
doi = {10.1016/j.foodchem.2026.148671},
pmid = {41791164},
issn = {1873-7072},
mesh = {*Wine/analysis/microbiology ; *Vitis/microbiology/metabolism/chemistry/growth & development ; *Flavoring Agents/metabolism/chemistry/analysis ; Microbiota ; *Bacteria/classification/isolation & purification/genetics/metabolism ; Volatile Organic Compounds/metabolism/chemistry/analysis ; Metabolomics ; Fruit/microbiology/chemistry/metabolism ; Fermentation ; Biodiversity ; Taste ; *Fungi/classification/isolation & purification/metabolism/genetics ; Odorants/analysis ; Soil Microbiology ; Multiomics ; },
abstract = {Ecological viticulture with minimal intervention is increasingly emphasized for sustainable wine production, but its effects on grape microbial communities and wine flavor metabolism remain insufficiently understood. This study investigated vineyard soil/grape-associated microbiota and wine flavor metabolites under conventional management (CM) and extra-simplified eco-viticulture (ES) across 2023-2025 vintages. Results showed that ES positively influenced soil microbial diversity and grape epidermal bacterial diversity, while reducing epidermal fungal diversity relative to CM. Spontaneous fermentation (SF) enriched organic acids, amino acids, and their derivatives, whereas inoculated fermentation (IF) accumulated glycolysis/TCA cycle intermediates and nucleosides. Volatile metabolomics revealed that ES-S natural wine had higher levels of terpenoids, aldehydes, and heterocyclic compounds with distinct floral/fruity aromas (rOAV>1), while IF wines were dominated by alcohols, esters, and ketones with homogeneous ripe fruit/mushroom notes. Collectively, extra-simplified eco-viticulture enhanced microbial diversity and drove more complex flavor metabolites in natural wines, providing a sustainable strategy for high-quality wine production.},
}

*Wine/analysis/microbiology
*Vitis/microbiology/metabolism/chemistry/growth & development
*Flavoring Agents/metabolism/chemistry/analysis
Microbiota
*Bacteria/classification/isolation & purification/genetics/metabolism
Volatile Organic Compounds/metabolism/chemistry/analysis
Metabolomics
Fruit/microbiology/chemistry/metabolism
Fermentation
Biodiversity
Taste
*Fungi/classification/isolation & purification/metabolism/genetics
Odorants/analysis
Soil Microbiology
Multiomics

@article {pmid41930519,
year = {2026},
author = {Han, L and Gu, H and Chen, M and He, Z and Jia, Y and Feng, Y and Li, J and Zhu, Y and Zou, Y},
title = {Text mining and machine learning based health risk prediction for soil polycyclic aromatic hydrocarbons at typical coal-fired industrial sites in china.},
journal = {Journal of hazardous materials},
volume = {508},
number = {},
pages = {141934},
doi = {10.1016/j.jhazmat.2026.141934},
pmid = {41930519},
issn = {1873-3336},
mesh = {*Polycyclic Aromatic Hydrocarbons/analysis/toxicity ; China ; Risk Assessment ; *Machine Learning ; *Soil Pollutants/analysis/toxicity ; Data Mining ; Humans ; Coal ; Environmental Monitoring ; },
abstract = {Polycyclic aromatic hydrocarbons (PAHs) are persistent organic pollutants posing significant threats to the environment and human health, particularly at active coal-fired industrial sites (coking, steel smelting, and thermal electric power generation) in China. However, for active industrial enterprises, effectively predicting PAHs exposure risks at the national scale remains challenging due to spatial uncertainty of contamination distribution and difficulties in the acquisition of large-scale monitoring data. This study introduces a multidisciplinary framework integrating text mining, probabilistic risk assessment, and machine learning to predict and assess health risks of PAHs in soils at these active industrial sites. Text mining extracted comprehensive PAHs-related data from literature, forming a national database with over 1600 entries. Probabilistic risk assessment with Monte Carlo simulation (1000 iterations per sample) revealed that 32% of historically reported sites in the text-mined database exceeded the acceptable target risk (ATR = 1 ×10[-6]), with benzo[a]pyrene (BaP) and dibenzo[a,h]anthracene (DahA) emerging as primary risk drivers, while non-carcinogenic risks were mostly below safety thresholds (hazard quotient < 1). Four machine learning algorithms including Support Vector Machine (SVM), Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM) were evaluated for risk classification, with LightGBM achieving optimal performance (accuracy: 98.88%, ROC-AUC: 1.0000). Feature importance analysis identified enterprise insured population, regional atmospheric CO concentration, and particulate emission limits as key predictors. National-scale prediction for 1263 sites identified 15.30% exceeding the ATR, predominantly concentrated in eastern and central China. Industry-specific analysis showed coking plants (39.40%) and steel smelting facilities (38.00%) exhibited higher proportions of sites exceeding the ATR than thermal power plants (22.60%), reflecting process-specific PAHs generation patterns. This framework provides an efficient, scalable approach for PAHs risk assessment and management at coal-fired sites in China, offering a replicable model for similar environmental challenges globally.},
}

*Polycyclic Aromatic Hydrocarbons/analysis/toxicity
China
Risk Assessment
*Machine Learning
*Soil Pollutants/analysis/toxicity
Data Mining
Humans
Coal
Environmental Monitoring

@article {pmid41974379,
year = {2026},
author = {Weseman, CE and Siegle, E and Boxrud, B and Shankman, SA and Reddy, M and Griffith, JW and Ashaie, SA},
title = {Validating an aphasia-accessible ecological momentary assessment for daily depressive affect: A preliminary investigation.},
journal = {Journal of affective disorders},
volume = {},
number = {},
pages = {121783},
doi = {10.1016/j.jad.2026.121783},
pmid = {41974379},
issn = {1573-2517},
abstract = {BACKGROUND: Up to 60% of individuals with aphasia have post-stroke depression, resulting in worse quality of life. However, extant measures of depression in aphasia are insufficient, and people with aphasia are often excluded from studies of depression due to a lack of valid assessment tools. Ecological momentary assessment (EMA) involves brief, repeated surveys that capture fluctuations in the real world, and may be adapted for individuals with communication impairments. We created a novel, aphasia-accessible EMA of affective depressive symptoms and evaluated its feasibility and usability in a sample of people with aphasia.

METHODS: 27 people with aphasia (Western Aphasia Battery-Aphasia Quotient (WAB-AQ) range: 32.9-97.4) completed a six-item EMA survey assessing positive and negative affect through the app m-Path four times per day for 14 days (up to 56 assessments). We analyzed feasibility, validity, and user experience of the app and surveys.

RESULTS: Participants completed 89.6% of the EMA surveys, indicating strong compliance and feasibility. EMA items correlated strongly with the Center for Epidemiologic Scale-Revised and Patient-Reported Outcomes Measure Information System (PROMIS) Depression measures, reflecting high convergent validity. Participants gave positive feedback about their experience using the app and answering the survey questions.

CONCLUSIONS: These results suggest that EMA is a useful tool for identifying affective symptoms of depression symptoms in people with aphasia and could be a way to address the gap in mental health care for people with aphasia. Future research should include more diverse samples as well as add passive, ecologically valid measures of depression.},
}

@article {pmid41974724,
year = {2026},
author = {Lydon, EC and Deosthale, P and Glascock, A and Phan, HV and Osborne, CM and Leroue, MK and Allen, J and Mick, E and Wagner, BD and DeRisi, JL and Ambroggio, L and Mourani, PM and Langelier, CR},
title = {Host-microbiome archetypes differentiate infection from pathogen carriage in the human lower airway.},
journal = {Nature communications},
volume = {},
number = {},
pages = {},
doi = {10.1038/s41467-026-71863-5},
pmid = {41974724},
issn = {2041-1723},
support = {R01HL155418//U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)/ ; R01HL124103//U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)/ ; R01AI182308//Division of Intramural Research, National Institute of Allergy and Infectious Diseases (Division of Intramural Research of the NIAID)/ ; },
abstract = {Distinguishing lower respiratory tract infection (LRTI) from incidental pathogen carriage (IPC) is clinically challenging. The immunologic and microbial factors defining the states of LRTI and IPC are poorly understood. Here, we perform host-microbe metatranscriptomic profiling of tracheal aspirates from 326 mechanically ventilated children with clinically adjudicated LRTI (n = 207), IPC (n = 70), or non-infectious respiratory failure (n = 49). In the airway microbiome, LRTI shows reduced alpha diversity and taxonomic richness, while IPC displays greater bacterial abundance, enrichment in respiratory anaerobes, and increased metabolic activity. At the host level, patients with LRTI exhibit a distinct lower airway transcriptional signature of innate and adaptive immune activation compared to those with IPC, who have similar transcriptional profiles to uninfected controls. Mediation analyses suggest the airway microbiome influences the host response to pathogens. An integrated host-microbe metatranscriptomic classifier accurately discriminates LRTI from IPC and controls (AUC = 0.89, 95% confidence interval (CI) 0.85-0.92). The single gene FABP4, encoding a macrophage-associated lipid chaperone and recently described pneumonia biomarker, performs similarly when combined with alpha diversity; FABP4 protein alone achieves an AUC = 0.88 (95% CI 0.82-0.93). Together, our findings reveal distinct ecological and immunologic archetypes defining LRTI and IPC, and support data-driven, biology-informed LRTI diagnostics incorporating host and microbial features.},
}

@article {pmid41714862,
year = {2026},
author = {McInerney, AM and Schmitz, N and Matthews, M and Deschênes, SS},
title = {The impact of sleep and movement behaviour on daily mood in people with type 2 diabetes: A smartphone-based digital phenotyping study.},
journal = {Diabetic medicine : a journal of the British Diabetic Association},
volume = {43},
number = {5},
pages = {e70269},
doi = {10.1111/dme.70269},
pmid = {41714862},
issn = {1464-5491},
support = {//Ad Astra Fellows PhD Studentship/ ; },
mesh = {Humans ; *Diabetes Mellitus, Type 2/psychology/physiopathology ; Male ; Female ; *Smartphone ; Middle Aged ; *Affect/physiology ; *Sleep/physiology ; Ecological Momentary Assessment ; Aged ; *Exercise/physiology/psychology ; Accelerometry ; Geographic Information Systems ; Adult ; Phenotype ; Movement/physiology ; Sleep Quality ; Actigraphy ; },
abstract = {OBJECTIVE: To examine how sleep and movement behaviours, measured on smartphones via ecological momentary assessment (EMA), GPS and accelerometer, impact subsequent daily mood in people with type 2 diabetes (T2D) compared to those without.

METHODS: Sixty-one participants with (n = 32) and without (n = 29) T2D underwent 2 months of smartphone-based data collection through phone sensors (GPS, accelerometer) and EMAs. Daily sleep, movement and mood (happiness, sadness, stress, anger) were assessed. Dynamic structural equation modelling examined the impact of sleep and movement on subsequent mood, adjusted for age, gender and employment status.

RESULTS: We found 18 significant within-person effects between smartphone-derived behaviour and subsequent mood, with 17 within-person effects indicating behaviour had a positive effect on mood. For people with and without T2D, higher physical activity, better sleep quality and visiting more locations predicted increased happiness, and higher physical activity predicted lower sadness. However, unique behaviour-mood effects were also found for each group, such as greater actigraphy-derived step count predicting greater anger in people with T2D (0.13 [0.05, 0.2]) but having no effect for those without.

CONCLUSIONS: Though effects were small, results indicate smartphone-derived behaviour influences daily mood for both people with and without T2D, but that the nuances of these relationships may differ. If daily mood correlates differ between people with and without T2D, digital phenotyping for early detection and intervention may need to be tailored to those with T2D.},
}

Humans
*Diabetes Mellitus, Type 2/psychology/physiopathology
Male
Female
*Smartphone
Middle Aged
*Affect/physiology
*Sleep/physiology
Ecological Momentary Assessment
Aged
*Exercise/physiology/psychology
Accelerometry
Geographic Information Systems
Adult
Phenotype
Movement/physiology
Sleep Quality
Actigraphy

@article {pmid41890999,
year = {2026},
author = {Suez, E and Fox, SJ},
title = {Basic Baseline model design choices can substantially influence performance in collaborative forecast hubs.},
journal = {medRxiv : the preprint server for health sciences},
volume = {},
number = {},
pages = {},
pmid = {41890999},
abstract = {Over the past decade, outbreak forecasting has become an increasingly used tool to assist public health decision-making during epidemics. Collaborative forecast hubs, where multiple teams submit predictions in real-time, are the gold standard for such efforts. For each hub, a Baseline model is used as a performance benchmark for other models. Although the Baseline is understood as a naïve forecast, its design is subjective, and the impact of model design decisions remains understudied. We evaluated how three Baseline specification decisions influence forecast performance on trend models that forecast based on historically observed dynamics: (1) the amount of historical data used for training, (2) whether the data are transformed, and (3) whether forecasts follow a flatline variant (constant predictions) or a drift variant (allowing a slope). Retrospective forecasts were generated for multiple years across four surveillance targets: COVID-19, influenza and RSV hospital admissions, and weighted influenza-like illness percentage. For wILI, we additionally compared trend baselines with a seasonal baseline model leveraging long-term historical patterns. Model specification significantly altered performance. The optimal performing model across targets was a flatline model that used the most recent 6-12 transformed observations. The optimal model outperforms the current standard Baseline used in many forecast hubs by an average of 9.6% (range: 3.7-12.9%) across forecast targets, and it outperformed the seasonal baseline model by 32.3% across nine influenza seasons. Our results demonstrate that subjective Baseline design decisions can materially influence forecast accuracy and, consequently, the perceived rankings of models within collaborative forecast hubs. Based on the varying approaches and their performance differences, these findings highlight the need for increased transparency in Baseline model specifications and support the routine inclusion of multiple benchmark models within collaborative forecast hubs.},
}

@article {pmid41964702,
year = {2026},
author = {Bouzada, N and Ababou, A and Senouci, F and Chenaoui, A and Bouthiba, A},
title = {Influence of water quality on the composition and distribution of riparian vegetation in the Cheliff River, Algeria.},
journal = {Environmental monitoring and assessment},
volume = {198},
number = {5},
pages = {},
pmid = {41964702},
issn = {1573-2959},
mesh = {Algeria ; *Rivers/chemistry ; *Environmental Monitoring ; *Water Quality ; *Plants/classification ; *Water Pollutants, Chemical/analysis ; Ecosystem ; },
abstract = {This ecological study was conducted along the Cheliff River in northwestern Algeria to evaluate how water quality shapes riparian plant communities. Floristic surveys and water quality analyses were performed at ten stations across the upstream and downstream sections. The hierarchical classification distinguished four main vegetation units: the Centaurium-Sonchus (CS) unit, associated with downstream sites affected by urban wastewater; the Plantago-Medicago-Lolium (PML) unit, linked to upstream agricultural runoff; the Solanum-Melissa-Bryonia (SMB) unit, reflecting industrial influence with high sulfates and nitrates; and the Aster-Atriplex-Nicotiana (AAN) unit, indicating alkaline conditions. Redundancy analysis (RDA) confirmed that these assemblages were strongly correlated with environmental gradients, explaining 60.6% of the species-environment variation. Key drivers included pH, conductivity, nitrates, orthophosphates, and iron, which successfully differentiated pollution gradients from urban, agricultural, and industrial sources. The dominance of nitrophilous and ruderal species in highly disturbed areas signals advanced ecological degradation, while several taxa demonstrated strong tolerance to pollutants, highlighting their bioindicator potential. These findings validate the use of macrophyte communities for monitoring water quality and provide a scientific basis for managing Mediterranean river ecosystems.},
}

Algeria
*Rivers/chemistry
*Environmental Monitoring
*Water Quality
*Plants/classification
*Water Pollutants, Chemical/analysis
Ecosystem

@article {pmid41966053,
year = {2026},
author = {Hu, H and Qu, Z and Liu, Y and Zhu, L and Mei, Z and Chen, XL},
title = {AI-driven fungicide design: From target identification to field application.},
journal = {Plant communications},
volume = {},
number = {},
pages = {101850},
doi = {10.1016/j.xplc.2026.101850},
pmid = {41966053},
issn = {2590-3462},
abstract = {Plant pathogenic fungi severely threaten global agriculture, causing substantial yield losses in staple crops and endangering food safety through mycotoxin contamination. Conventional fungicide development suffers from high costs, lengthy timelines, and rapid evolution of fungal resistance that outpaces traditional discovery workflows. While artificial intelligence (AI) offers transformative potential to address these bottlenecks, its application in plant pathology remains fragmented, lacking integration of agricultural-specific constraints such as field stability, ecological safety, and resistance management. This review presents the AI-driven fungicide design (AIFD) platform, a comprehensive framework comprising four interdependent components: a plant pathogen-specific data ecosystem, a modular microservice technical architecture, a linear multi-phased development workflow, and a specialized resistance prediction workflow. We synthesize key technological progress across the fungicide development pipeline, from target identification and virtual screening to molecular optimization and field validation, emphasizing AI methodologies adapted to agrochemical requirements rather than pharmaceutical standards. Despite significant advances, critical challenges persist, including scarce high-quality training data for understudied pathogens, limited model adaptability across diverse agroecosystems, poor interpretability hindering stakeholder trust, and accessibility barriers for resource-constrained researchers. Future directions emphasize real-time field data integration, explainable AI for regulatory acceptance, and inclusive design strategies to bridge the lab-to-field gap. By aligning computational innovation with agricultural priorities, AIFD platforms accelerate the discovery of resistance-breaking, environmentally benign fungicides, offering a viable pathway toward sustainable crop protection and enhanced global food security.},
}

@article {pmid41968734,
year = {2026},
author = {Sandin, MM and Walde, M and Henry, N and Forn, I and Simon, N and Berney, C and Massana, R and Richter, DJ},
title = {OligoN-Design: A Simple and Versatile Tool to Design Specific Probes and Primers From Large Heterogeneous Datasets.},
journal = {Molecular ecology resources},
volume = {26},
number = {3},
pages = {e70140},
doi = {10.1111/1755-0998.70140},
pmid = {41968734},
issn = {1755-0998},
support = {2021BP00068//Generalitat de Catalunya/ ; 101103530//H2020 Marie Skłodowska-Curie Actions/ ; 464344344//Deutsche Forschungsgemeinschaft/ ; 101082304//European Union under the Horizon Europe Programme/ ; PID2023-152955NA-I00/ERC_/European Research Council/International ; PID2022-137508NB-I00/ERC_/European Research Council/International ; 2021 SGR 00751//Departament de Recerca i Universitats de la Generalitat de Catalunya/ ; },
mesh = {*DNA Primers/genetics ; *Computational Biology/methods ; *Software ; High-Throughput Nucleotide Sequencing/methods ; *Oligonucleotide Probes/genetics ; },
abstract = {High-throughput environmental DNA sequencing has ushered ecological and evolutionary studies into the big data era. With thousands to millions of DNA sequences, designing taxon-specific oligonucleotides is a current bottleneck of molecular studies that rely on primers for Polymerase Chain Reactions (PCRs) or probes for Fluorescence in situ Hybridization (FISH). No software currently exists to design specific oligonucleotides starting from a custom set of sequences. Existing tools rely on specific databases, alignments or phylogenetic trees, or cannot accommodate increasingly large molecular environmental datasets. Here we present oligoN-design, a versatile tool to design oligonucleotides specific to a set of target sequences while minimizing predicted binding to non-target sequences. OligoN-design is simple, reproducible and adaptable to high-throughput sequencing data analyses. It requires only two fasta files as input, one containing target taxa and the other containing non-target taxa. Using standard bioinformatic formats, it integrates easily with other tools such as BLAST, VSEARCH or MAFFT. OligoN-design allows a range of strategies that we present in detail, from an unsupervised end-to-end usage all the way to a detailed and thorough expert usage. Starting with large, comprehensive ribosomal databases that are widely used by the community (i.e., PR2, SILVA) and the unsupervised function, we were able to replicate known taxa-specific oligonucleotides in under 30 min and up to 6 GB of RAM on a personal laptop. OligoN-design, available at github.com/MiguelMSandin/oligoN-design under GNU General Public Licence version 3.0, is easily installed via bioconda bioconda.github.io/recipes/oligon-design/README.html.},
}

*DNA Primers/genetics
*Computational Biology/methods
*Software
High-Throughput Nucleotide Sequencing/methods
*Oligonucleotide Probes/genetics

@article {pmid41969650,
year = {2026},
author = {Zhu, H and Ma, P and Yuan, Y and Chen, Y and Shi, H and Huang, C and Zhou, Y and Jing, R and Cao, M and Zhang, D and Luo, Y},
title = {Integrated mechanistic and bioinformatics analysis of a traditional Chinese medicine compound MangHuang solution against Candida albicans.},
journal = {Frontiers in cellular and infection microbiology},
volume = {16},
number = {},
pages = {1737769},
pmid = {41969650},
issn = {2235-2988},
mesh = {*Candida albicans/drug effects/genetics ; Biofilms/drug effects/growth & development ; *Antifungal Agents/pharmacology ; Computational Biology/methods ; Staphylococcus aureus/drug effects ; *Drugs, Chinese Herbal/pharmacology/chemistry ; Microbial Sensitivity Tests ; Medicine, Chinese Traditional ; Escherichia coli/drug effects ; Anti-Bacterial Agents/pharmacology ; Tannins/pharmacology ; },
abstract = {INTRODUCTION: The growing prevalence of drug-resistant pathogens urgently calls for new treatment strategies. Traditional Chinese medicine (TCM) formulas, with their multi-targeted mechanisms of action, offer promising alternative options for antimicrobial therapy. This study aims to evaluate the antimicrobial activity of the TCM formula MangHuang solution (MH) after content detection of tannin, composed of Rhei Radix et Rhizoma, Natrii Sulfas, and Galla Chinensis, and to elucidate its antifungal mechanism against Candida albicans through integrated multi-omics analysis.

METHODS: MH and its individual or combined components were prepared and evaluated for their inhibitory effects on Staphylococcus aureus, Escherichia coli, and Candida albicans, and their antimicrobial activity was assessed. Transmission electron microscopy (TEM), biofilm formation experiments, and multi-omics analysis were used to investigate the antifungal mechanism of MH against C. albicans.

RESULTS: MH demonstrated potent and rapid antibacterial activity. Biofilm formation was significantly inhibited, manifested by reduced cell surface hydrophobicity, weakened initial adhesion capacity, and impaired biofilm maturation processes. Transcriptome and metabolome analyses revealed significant alterations in key metabolic pathways, particularly ABC transporters, amino acid biosynthesis, and protein-related pathways.

DISCUSSION: MH exhibits potent antifungal activity against C. albicans through a multi-target mechanism, primarily affecting biofilm formation and intracellular metabolic processes. The integration of multi-omics approaches provides strong evidence for the potential clinical application of MH as an effective antifungal agent.},
}

*Candida albicans/drug effects/genetics
Biofilms/drug effects/growth & development
*Antifungal Agents/pharmacology
Computational Biology/methods
Staphylococcus aureus/drug effects
*Drugs, Chinese Herbal/pharmacology/chemistry
Microbial Sensitivity Tests
Medicine, Chinese Traditional
Escherichia coli/drug effects
Anti-Bacterial Agents/pharmacology
Tannins/pharmacology

@article {pmid41972477,
year = {2026},
author = {Mammides, C and Gu, H and Nimalrathna, TS and Avicena, NR and Papadopoulos, H and Campos-Arceiz, A},
title = {Emerging applications of large language models in ecology and conservation science.},
journal = {Conservation biology : the journal of the Society for Conservation Biology},
volume = {},
number = {},
pages = {e70287},
doi = {10.1111/cobi.70287},
pmid = {41972477},
issn = {1523-1739},
support = {CAS-SEABRI: #Y4ZK111B05//Southeast Asia Biodiversity Research Institute, Chinese Academy of Sciences/ ; 202503AM140014//The Wisdom Yunnan Project/ ; E3ZKFF9B//4th Five-Year Plan of the Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences/ ; //High-End Foreign Experts Program of the Yunnan Revitalization Talents Support Plan/ ; H20250434//National Foreign Expert Project/ ; 202505AO120035//Yunnan Provincial Foreign Expert Project/ ; },
abstract = {Large language models (LLMs) mark a major development in artificial intelligence, with potentially transformative implications for ecology and conservation science. Built on advanced deep-learning architectures, these models can support a wide range of tasks. We reviewed emerging applications of LLMs, drawing on the wider scientific literature and practical use cases. We found that LLMs can streamline ecological workflows and accelerate evidence-based conservation by supporting the extraction of ecological information from unstructured sources, enabling natural-language interaction with structured databases and facilitating large-scale literature syntheses. They can also be used to leverage publicly available data for ecological insights, for example, through automated monitoring of news reports. They can enhance biodiversity monitoring through integration with edge devices, such as camera traps, and can assist with analytical tasks, such as code generation, and improve scientific communication and support outreach, for example, through custom models trained on domain-specific information. Other potential applications include policy analysis and decision support, such as simulating interactions among stakeholders with multiagent systems. However, the rapid adoption of LLMs also raises technical and ethical challenges, including inaccurate or biased outputs caused by hallucinations and imbalances in training data. Such limitations can also contribute to poor out-of-distribution performance and the underrepresentation of minority viewpoints. Additional concerns include limited transparency and reproducibility due to their black-box nature, high technical complexity, and computational demands, which may exacerbate access inequalities, the risk of deskilling, and environmental impacts. To mitigate these challenges, we recommend a set of best practices, including careful model selection, effective prompt engineering, retrieval-augmented generation to improve factual accuracy and representation, human-in-the-loop validation, and broader efforts to promote inclusive development, capacity building, and appropriate governance. When applied thoughtfully, LLMs can serve as a valuable addition to the ecologists' toolkit, enhancing scientific capacity and supporting efforts toward achieving global biodiversity goals.},
}

@article {pmid41973532,
year = {2026},
author = {Devasahayam, BRF and Poeschl, Y and Uthe, H and Rennert, R and Hartmann, L and Deising, HB},
title = {Confrontations between Aspergillus nidulans and microbial biocontrol agents cause differential regulation of secondary metabolism and synthesis of chemicals toxic to human kidney and colon cells.},
journal = {Applied and environmental microbiology},
volume = {},
number = {},
pages = {e0218025},
doi = {10.1128/aem.02180-25},
pmid = {41973532},
issn = {1098-5336},
abstract = {Microbial interactions in agricultural ecosystems are chemically dynamic, with significant implications for ecological balance and crop protection. As synthetic fungicides face increasing regulatory and resistance challenges, applying microbial biological control agents (MBCAs) presents a potential alternative crop-protection strategy. However, the chemical and toxicological consequences of such applications remain poorly understood. Using the model ascomycete Aspergillus nidulans, the response to confrontations with twelve microbial partners, including bacterial and fungal MBCAs, plant pathogens, and phylloplane isolates was studied. Dual-culture assays revealed distinct interaction patterns, and transcriptome profiling showed confrontation-specific activation of secondary metabolite biosynthetic gene clusters (SMBGCs), with up to 50 SMBGCs differentially expressed in A. nidulans. Complementary untargeted LC-MS/MS identified hundreds of unique secondary metabolites (SMs), including compounds structurally resembling synthetic fungicides, including azoles and piperidines. Notably, cytotoxicity assays using human HEK-293 and HCT-116 cell lines revealed that SM mixtures from confrontations of A. nidulans with Bacillus subtilis or Trichothecium roseum exhibited significant toxicity, with IC50 values as low as 52 µg/mL. These findings demonstrate that microbial confrontations can trigger the production of diverse and specific sets of SMs, including compounds representing potential human health risks. This study underscores the need for confrontation-informed toxicological assessments in MBCA regulation and highlights the importance of developing safer biocontrol strategies in agriculture.IMPORTANCEThis study shows fundamental changes at the transcriptome and metabolome level in the ubiquitous fungus Aspergillus nidulans confronting various microorganisms, including microbial biological control agents. Strong modulations of transcript abundances of genes belonging to secondary metabolism gene clusters correlated with the formation of a vast array of novel secondary metabolites. Compounds formed in some confrontations were toxic to human cells, questioning the consumer safety of applying microbial biological control agents.},
}

@article {pmid41819291,
year = {2026},
author = {Kalimuthu, S and Muthusamy, A},
title = {MobiRes: An integrative pipeline for resistome risk prediction through mobilome profiling.},
journal = {Journal of microbiological methods},
volume = {244},
number = {},
pages = {107448},
doi = {10.1016/j.mimet.2026.107448},
pmid = {41819291},
issn = {1872-8359},
mesh = {Humans ; *Metagenomics/methods ; DNA Transposable Elements/genetics ; Anti-Bacterial Agents/pharmacology ; Plasmids/genetics ; Animals ; *Bacteria/genetics/drug effects ; Interspersed Repetitive Sequences/genetics ; *Drug Resistance, Bacterial/genetics ; Microbiota/genetics ; Machine Learning ; *Computational Biology/methods ; Metagenome ; Bacteriophages/genetics ; Risk Assessment ; Feces/microbiology ; },
abstract = {Antimicrobial resistance (AMR) poses a significant global health challenge, with the environment serving as a crucial reservoir and conduit for resistance determinants. Although antibiotic resistance genes (ARGs) have been extensively studied in environmental contexts, systematic approaches for assessing and prioritizing the risks associated with mobile genetic elements (MGEs), such as plasmids, phages, transposons, and integrative elements (IEs), remain unclear. To address this gap, we present MobiRes, an open-source computational framework designed to predict resistome risk by integrating information from the mobilome and microbiome. The pipeline was evaluated using a wide range of publicly available metagenomic datasets spanning diverse environments, including wastewater, poultry, soil, sediments, and human fecal samples. To validate the framework, statistical analyses and machine learning models were applied to evaluate the role of MGEs in driving ARG dissemination. The pipeline identified transposons as the dominant MGE class while capturing environment-specific variation in plasmid, phage, and IE -associated ARGs. Transposon-associated ARGs showed the most consistent environmental differentiation (ANOVA p = 0.0017; Kruskal-Wallis p = 0.018), whereas plasmid and phage-associated ARGs varied moderately (p = 0.015-0.040) and IE-associated ARGs remained comparatively stable across environments (p > 0.05). The Random Forest (RF) model achieved an AUC of 0.82, and subsequent feature importance and SHapley Additive exPlanations (SHAP) analyses revealed that transposon abundance is the primary factor driving ARG dissemination across diverse environments. By integrating host, mobility, and ecological factors, MobiRes provides a scalable and One Health-oriented framework for comprehensive AMR risk assessment. This pipeline is publicly available at https://github.com/santhiyakc17/MobiRes_Pipeline.},
}

Humans
*Metagenomics/methods
DNA Transposable Elements/genetics
Anti-Bacterial Agents/pharmacology
Plasmids/genetics
Animals
*Bacteria/genetics/drug effects
Interspersed Repetitive Sequences/genetics
*Drug Resistance, Bacterial/genetics
Microbiota/genetics
Machine Learning
*Computational Biology/methods
Metagenome
Bacteriophages/genetics
Risk Assessment
Feces/microbiology

@article {pmid41896196,
year = {2026},
author = {He, W and Bolnick, DI and Scarpino, SV and Eliassi-Rad, T},
title = {Hypergraph representations of single-cell RNA sequencing data for improved cell clustering.},
journal = {Bioinformatics (Oxford, England)},
volume = {42},
number = {4},
pages = {},
pmid = {41896196},
issn = {1367-4811},
support = {#2133740//National Science Foundation/ ; },
mesh = {*Single-Cell Analysis/methods ; Algorithms ; Cluster Analysis ; *Sequence Analysis, RNA/methods ; Humans ; Computational Biology/methods ; Gene Expression Profiling ; Gene Regulatory Networks ; },
abstract = {MOTIVATION: Single-cell RNA sequencing (scRNA-seq) data analysis is often performed using network projections that produce co-expression networks. These network-based algorithms are attractive because regulatory interactions are fundamentally network-based and there are many tools available for downstream analysis. However, most network-based approaches have two major limitations. First, they are typically unipartite and therefore fail to capture higher-order information. Second, scRNA-seq data are often sparse, so most algorithms for constructing unipartite network projections are inefficient and may overestimate co-expression relationships, or may under-utilize the sparsity when clustering (e.g. with cosine distance). To address these limitations, we propose representing scRNA-seq expression data as hypergraphs, which are generalized graphs where a hyperedge can connect more than two nodes. In this context, hypergraph nodes represent cells, and hyperedges represent genes. Each hyperedge connects all cells in which its corresponding gene is actively expressed, indicating the expression of that gene across different cells. The resulting hypergraph can capture higher-order information and appropriately handle varying levels of data sparsity. This representation enables clustering algorithms to leverage higher-order relationships for improved cell-type differentiation.

RESULTS: To distinguish cell types using hypergraph representations of scRNA-seq data, we introduce two novel clustering algorithms: (i) Dual-Importance Preference Hypergraph Walk (DIPHW) and (ii) Co-expression and Memory-Integrated Dual-Importance Preference Hypergraph Walk (CoMem-DIPHW). DIPHW is a new hypergraph-based random walk algorithm that computes cell embeddings by considering the relative importance of genes to cells and cells to genes, incorporating a preference exponent to facilitate clustering. CoMem-DIPHW integrates two unipartite projections, the gene co-expression and cell co-expression networks, along with the cell-gene expression hypergraph derived from single-cell abundance count data into the random walk model. The advantage of CoMem-DIPHW is that it accounts for both local information from single-cell gene expression and global information from pairwise similarity in the two co-expression networks. We benchmark the performance of our algorithms against established and state-of-the-art deep learning approaches using both real-world and simulated scRNA-seq data. Real-world datasets include cells from the human pancreas, mouse pancreas, human brain, and mouse brain tissues. We also use a ground-truth labeled cell-type annotation dataset based on human lung adenocarcinoma cell lines. Quantitative evaluation shows that CoMem-DIPHW consistently outperforms established algorithms and state-of-the-art deep learning algorithms for cell-type clustering. Our proposed algorithms show the greatest improvement on scRNA-seq data with weak modularity. Moreover, CoMem-DIPHW successfully annotates clusters with biologically relevant cell types. Our results highlight the utility of hypergraph representations in the analysis of scRNA-seq data.

Our methods are implemented in Python and available on GitHub (https://github.com/wanhe13/CoMem-DIPHW) and archived at Zenodo (https://doi.org/10.5281/zenodo.18927437).},
}

*Single-Cell Analysis/methods
Algorithms
Cluster Analysis
*Sequence Analysis, RNA/methods
Humans
Computational Biology/methods
Gene Expression Profiling
Gene Regulatory Networks

@article {pmid41921320,
year = {2026},
author = {Huang, DQ and Zhou, S and Jia, Y and Yan, Y and Lu, H},
title = {Deciphering pharmaceutical resistance in sulfur-driven autotrophic denitrification: an integrated multi-omics artificial intelligence-driven structural biology approach.},
journal = {Water research},
volume = {298},
number = {},
pages = {125834},
doi = {10.1016/j.watres.2026.125834},
pmid = {41921320},
issn = {1879-2448},
mesh = {*Denitrification ; *Sulfur/metabolism ; Autotrophic Processes ; *Artificial Intelligence ; Ibuprofen ; Multiomics ; },
abstract = {Sulfur-driven autotrophic denitrification (SdAD) is a promising low-carbon technology for nitrogen removal; however, its stability and adaptive mechanisms under pharmaceutical stress remain poorly understood. In this study, ibuprofen (IBU) was used as a representative pharmaceutical to investigate the response of an SdAD system. Throughout the 210-day operational period, the system demonstrated exceptional functional robustness, maintaining high sulfide (97.46 ± 3.18%) and inorganic nitrogen (99.17 ± 4.34%) removal efficiencies across IBU concentrations ranging from environmentally relevant levels to elevated shock loads (100-2000 μg/L). Underpinning this macroscopic stability, community-level analyses revealed that instead of succumbing to inhibition, the SdAD microbiome actively reorganized its composition and topological structure to accommodate the selective pressure. This adaptation was characterized by enhanced microbial diversity and stress-induced network modularity (particularly at 100-500 μg/L), alongside strengthened cooperative interactions between sulfur-oxidizing bacteria and denitrifiers. To unravel the specific molecular drivers of this resilience, we integrated AlphaFold-based structural modeling with machine learning-coupled molecular docking. This enabled us to resolve the three-dimensional structure of sulfide: quinone oxidoreductase (SQR) and perform the first structure-function analysis of SQR within an SdAD context under pharmaceutical stress, revealing that arginine residues serve as key interaction hotspots for IBU binding. Consistent with this binding mechanism, multi-omics data further corroborated a systemic adjustment involving the coordinated regulation of sulfur oxidation genes and the transcriptional upregulation of arginine biosynthesis pathways. Overall, these findings shed light on how the SdAD community mitigates pharmaceutical toxicity through a multi-tiered strategy involving ecological network reorganization and metabolic compensation. Methodologically, this work highlights the value of integrating artificial intelligence-driven structural biology with multi-omics analyses to decode the mechanisms of contaminant resistance in biological wastewater treatment systems.},
}

*Denitrification
*Sulfur/metabolism
Autotrophic Processes
*Artificial Intelligence
Ibuprofen
Multiomics

@article {pmid41957200,
year = {2026},
author = {Spiliotis, K and Russo, L and Siettos, C and Giannino, F},
title = {Numerical bifurcation analysis of turing and symmetry broken patterns of a PDE model for vegetation dynamics.},
journal = {Journal of mathematical biology},
volume = {92},
number = {5},
pages = {},
pmid = {41957200},
issn = {1432-1416},
mesh = {*Models, Biological ; Mathematical Concepts ; Biomass ; *Ecosystem ; *Plant Development ; Water/metabolism ; Computer Simulation ; },
abstract = {We study the mechanisms of pattern formation for vegetation dynamics in water-limited regions. Our analysis is based on a set of two partial differential equations (PDEs) of reaction-diffusion type for the biomass and water, and one ordinary differential equation (ODE) describing the dependence of the toxicity on the biomass. We perform a linear stability analysis in the one-dimensional finite space, we derive analytically the conditions for the appearance of Turing instability that gives rise to spatio-temporal patterns emanating from the homogeneous solution, and provide its dependence with respect to the size of the domain. Furthermore, we perform a numerical bifurcation analysis in order to study the pattern formation of the inhomogeneous solution, with respect to the precipitation rate, thus analyzing the stability and symmetry properties of the emanating patterns. Based on the numerical bifurcation analysis, we have found new patterns, which form due to the onset of secondary bifurcations from the primary Turing instability, thus giving rise to a multistability of asymmetric solutions.},
}

*Models, Biological
Mathematical Concepts
Biomass
*Ecosystem
*Plant Development
Water/metabolism
Computer Simulation

@article {pmid41959695,
year = {2026},
author = {Celeste, J and Sevilleja, JE and Bongolan, VP and Rivera, RL and Caoili, SE and de Castro, R},
title = {COVID-19 mortality in the Philippines: province-level ecological analysis, 2020-2023.},
journal = {Western Pacific surveillance and response journal : WPSAR},
volume = {17},
number = {1},
pages = {1-12},
pmid = {41959695},
issn = {2094-7313},
mesh = {Humans ; Philippines/epidemiology ; *COVID-19/mortality ; Aged ; SARS-CoV-2 ; Middle Aged ; Incidence ; Male ; Adult ; Female ; },
abstract = {OBJECTIVE: To investigate COVID-19 mortality in Philippine provinces from 2020 to 2023.

METHODS: Crude mortality rate (CMR), age-standardized mortality rate (ASMR) and age-specific mortality rate were computed for 84 areas (82 provinces and 2 cities) using COVID-19 surveillance data from the Philippine Department of Health, which captured data about confirmed deaths occurring between 20 January 2020 and 9 May 2023. Provinces were ranked by their ASMR. A correlation analysis was conducted to identify possible predictors of COVID-19 mortality. Among the factors investigated were the incidence of poverty, population density, proportion of the population considered elderly (aged ≥ 65 years), hospital bed density and COVID-19 testing rates.

RESULTS: Eight of the 10 provinces that had the highest COVID-19 ASMRs were located in the Luzon island group. The province with the highest ASMR was Benguet in Northern Luzon (207.83 deaths/100 000 population), and the lowest rate was in Tawi-Tawi in Southwestern Mindanao (2.22 deaths/100 000 population). The incidence of poverty was negatively correlated with COVID-19 mortality, while hospital bed density and COVID-19 testing rates were positively correlated with CMRs and ASMRs.

DISCUSSION: This analysis provides a starting point for investigating COVID-19 mortality in Philippine provinces. The ranking of provinces by their ASMR is useful for directing future epidemiological investigations and, coupled with the results of the correlation analysis, provides insight into the factors that may have impacted COVID-19 mortality in the Philippines. Our analysis suggests that COVID-19 mortality patterns can partly be explained by the streetlight effect and factors linked to the availability of and access to health care.},
}

Humans
Philippines/epidemiology
*COVID-19/mortality
Aged
SARS-CoV-2
Middle Aged
Incidence
Male
Adult
Female

@article {pmid41931472,
year = {2026},
author = {Kim, Y and Faivre, B and Boulinier, T and Sineau, C and Galon, C and Moutailler, S and Bournez, L and Métras, R},
title = {A Bayesian modelling framework for estimating tick-borne pathogen transmission dynamics at the host-tick interface.},
journal = {PLoS computational biology},
volume = {22},
number = {4},
pages = {e1014146},
doi = {10.1371/journal.pcbi.1014146},
pmid = {41931472},
issn = {1553-7358},
mesh = {Bayes Theorem ; Animals ; *Tick-Borne Diseases/transmission/microbiology ; *Ticks/microbiology ; *Models, Biological ; Birds/parasitology ; Computational Biology ; Host-Pathogen Interactions ; },
abstract = {Understanding the transmission dynamics of tick-borne pathogens at the host-tick interface is challenged by the presence of multiple pathways for tick infection, including (i) host-to-tick transmission, (ii) tick-to-tick (cofeeding) transmission, and (iii) pre-existing infection through vertical transmission or prior feeding. Assessing parameters governing these pathways is critical for identifying the main transmission drivers and, consequently, key prevention and control points. Here, we developed a Bayesian modelling framework that estimates key parameters describing the probability of each transmission pathway and assesses associated factors, including bird species, tick life stage and engorgement level, by jointly modelling transmission at the host-tick interface using data collected in field studies that sample hosts and their ticks. First, by fitting the model to simulated host-tick infection data, we demonstrated the framework's ability to recover the parameter values underlying these data. Model performance improved significantly when more information was available on variability in cofeeding probability among individual ticks, highlighting the value of testing all collected ticks and recording their spatial distribution on the host in relation to each other. Second, we fitted the model to field data collected at the bird-tick interface in Northeast France in 2023, focusing on Borrelia garinii, B. valaisiana, and Anaplasma phagocytophilum as case pathogens. For all three pathogens studied, models including cofeeding transmission explained the data significantly better than models that did not. Engorgement level was significantly and positively associated with the probability of bird-to-tick transmission for A. phagocytophilum. Finally, the estimated parameters, such as the probability of A. phagocytophilum infection in birds and the probability of Borrelia or Anaplasma infection in ticks before feeding, were comparable to values from an external dataset, not used for model fitting. Our framework provides a valuable foundation for future research to understand tick-borne pathogen transmission dynamics based on epidemiological and ecological field data collected at the host-tick interface.},
}

Bayes Theorem
Animals
*Tick-Borne Diseases/transmission/microbiology
*Ticks/microbiology
*Models, Biological
Birds/parasitology
Computational Biology
Host-Pathogen Interactions

@article {pmid41956682,
year = {2026},
author = {Cao, R and Yan, X and Ma, Y and Li, A and Du, H and Zhou, Q and Xu, Y},
title = {Coupling ensemble learning with multi-omics: a novel data-driven strategy for Daqu quality assessment and validation.},
journal = {Food research international (Ottawa, Ont.)},
volume = {233},
number = {Pt 2},
pages = {119028},
doi = {10.1016/j.foodres.2026.119028},
pmid = {41956682},
issn = {1873-7145},
mesh = {Fermentation ; *Fermented Foods/microbiology/analysis ; *Machine Learning ; *Food Microbiology ; Quality Control ; Taste ; Food Quality ; Odorants/analysis ; Ensemble Learning ; Multiomics ; },
abstract = {Daqu, a fermentation starter for traditional fermented foods, is produced by complex microbial communities; it is generally evaluated using conventional methods based on subjective sensory perception and limited physicochemical indicators. These approaches have several limitations, including poor consistency and low repeatability, making it challenging to meet industrial demands for a transition from "experience-driven" to "science-driven" quality control. In this study, medium-high temperature Daqu for strong-aroma-type Baijiu was selected as the research object, and we aimed to establish a quality evaluation model for it by the integration of multidimensional fermentation data. Additionally, multi-omics analysis was combined to validate key functional microorganisms, thereby revealing their mechanisms of action. The results indicate that the fermentation functions of Daqu are predominantly driven by eukaryotic microorganisms characterized by "low abundance and high expression." Rhizomucor and Saccharomycopsis were identified as core contributors to hydrolases. An ensemble learning model (temperature-based Gradient Boosting + physicochemical XGBoost + flavor-based Linear Regression) was established to achieve rapid quality grading of Daqu. Daqu quality was substantially improved by targeted inoculation with core functional fungi, thereby verifying the effectiveness of the model. Accordingly, in this study, a systematic research paradigm of "multi-omics analysis → machine learning modeling → microbial targeted validation" was established, allowing the transformation of experience-dependent "ecological art" into interpretable, quantifiable, and predictable "synthetic ecological engineering." The study findings are expected to provide a generalizable methodology for addressing quality evaluation issues in traditional fermented foods.},
}

Fermentation
*Fermented Foods/microbiology/analysis
*Machine Learning
*Food Microbiology
Quality Control
Taste
Food Quality
Odorants/analysis
Ensemble Learning
Multiomics

@article {pmid41628813,
year = {2026},
author = {Gasser, RB},
title = {Biotechnology advances and the parasitology paradigm: From genomes to multi-omics and translation.},
journal = {Biotechnology advances},
volume = {89},
number = {},
pages = {108813},
doi = {10.1016/j.biotechadv.2026.108813},
pmid = {41628813},
issn = {1873-1899},
mesh = {*Biotechnology ; Humans ; *Genomics ; Animals ; *Parasitology ; Proteomics ; *Parasitic Diseases/genetics/parasitology ; Metabolomics ; *Genome ; Host-Parasite Interactions ; Multiomics ; },
abstract = {Parasitic diseases impose a substantial and often underestimated burden on human and animal health, food security and economic development. Over recent decades, advances in biotechnology have expanded parasitology into a genomics-enabled field. Early progress stemmed from the use of molecular markers, PCR and immunological assays, followed by draft genomes generated through high-throughput sequencing and bioinformatics. The advent of long-read sequencing and chromosome conformation capture (Hi-C) mapping technologies subsequently enabled chromosome-scale assemblies, providing robust frameworks for comparative analyses across parasitic taxa. Building on this progress, multi-omics platforms - including transcriptomics, proteomics, lipidomics and metabolomics - have been applied to characterise developmental trajectories, host-parasite interactions and parasite-specific pathways, and the integration of these datasets is facilitating the construction of systems-level models linking genetic variation to phenotype and disease processes. More recently, artificial intelligence (AI), including machine learning, has been applied to predict essential genes, accelerate structure-based drug discovery, guide reverse vaccinology and integrate heterogeneous datasets, thereby establishing new approaches for genome-guided identification of diagnostic markers and candidate vaccine and therapeutic targets. Importantly, perspectives within the discipline have emphasised that taxonomy, ecology and field parasitology remain critical for contextualising molecular findings. The future of molecular parasitology will depend on integrating breadth with depth; genomic and multi-omics resources should align with the FAIR (findable, accessible, interoperable and reusable) principles and be embedded within a One Health framework, enabling fundamental discoveries to translate into improved diagnostics, novel therapeutics and sustainable strategies for parasite control.},
}

*Biotechnology
Humans
*Genomics
Animals
*Parasitology
Proteomics
*Parasitic Diseases/genetics/parasitology
Metabolomics
*Genome
Host-Parasite Interactions
Multiomics

@article {pmid41946726,
year = {2026},
author = {Funosas, D and Massol, E and Bas, Y and Schmidt, S and Bennett, D and Arend, D and Gebhard, A and Barbaro, L and König, S and Font, RC and Sannier, D and Deroussen, F and Sueur, J and Trilar, T and Forstmeier, W and Roger, L and Matheu, E and Guzik, P and Barataud, J and Pelozuelo, L and Puissant, S and Mueller, S and Schuller, B and Montoya, JM and Triantafyllopoulos, A and Cauchoix, M},
title = {A finely annotated dataset for the automated acoustic identification of European Orthoptera and Cicadidae.},
journal = {Scientific data},
volume = {},
number = {},
pages = {},
doi = {10.1038/s41597-026-07150-1},
pmid = {41946726},
issn = {2052-4463},
support = {ANR-23-CPJ1-0174-01//Association Nationale de la Recherche et de la Technologie (National Association for Research and Technology)/ ; ANR-21-CE03-0002//Association Nationale de la Recherche et de la Technologie (National Association for Research and Technology)/ ; ANR-21-ESRE-0014//Association Nationale de la Recherche et de la Technologie (National Association for Research and Technology)/ ; ANR-23-CPJ1-0174-01//Association Nationale de la Recherche et de la Technologie (National Association for Research and Technology)/ ; P1-0255//The Slovenian Research and Innovation Agency (ARIS)/ ; },
abstract = {Mounting evidence points to widespread declines in insect abundance and diversity across European terrestrial ecosystems, highlighting an urgent need for effective large-scale monitoring methods. Passive acoustic monitoring enables the monitoring of sound-producing insects at an unprecedented temporal and spatial scale by remotely capturing sounds such as orthopteran stridulations and cicada timbalizations. However, current automated recognition tools for European insect sounds remain limited, and developing algorithms capable of reliably identifying diverse species requires large, ecologically heterogeneous acoustic datasets. Here we present a dataset of 11,224 recordings covering 193 orthopteran and 24 cicada species from North, Central, and temperate Western Europe. It combines coarsely labeled recordings, for which we can only infer the presence, at some point, of their target species (weak labeling), with finely annotated recordings that specify the time and frequency range of each insect sound (strong labeling). This dataset complements existing online resources and supports the advancement of automated acoustic classification for orthopterans and cicadas, aiding biodiversity monitoring efforts across Europe.},
}