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Bibliography on: Ecological Informatics

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ESP: PubMed Auto Bibliography 05 Dec 2024 at 01:46 Created: 

Ecological Informatics

Wikipedia: Ecological Informatics Ecoinformatics, or ecological informatics, is the science of information (Informatics) in Ecology and Environmental science. It integrates environmental and information sciences to define entities and natural processes with language common to both humans and computers. However, this is a rapidly developing area in ecology and there are alternative perspectives on what constitutes ecoinformatics. A few definitions have been circulating, mostly centered on the creation of tools to access and analyze natural system data. However, the scope and aims of ecoinformatics are certainly broader than the development of metadata standards to be used in documenting datasets. Ecoinformatics aims to facilitate environmental research and management by developing ways to access, integrate databases of environmental information, and develop new algorithms enabling different environmental datasets to be combined to test ecological hypotheses. Ecoinformatics characterize the semantics of natural system knowledge. For this reason, much of today's ecoinformatics research relates to the branch of computer science known as Knowledge representation, and active ecoinformatics projects are developing links to activities such as the Semantic Web. Current initiatives to effectively manage, share, and reuse ecological data are indicative of the increasing importance of fields like Ecoinformatics to develop the foundations for effectively managing ecological information. Examples of these initiatives are National Science Foundation Datanet projects, DataONE and Data Conservancy.

Created with PubMed® Query: ( "ecology OR ecological" AND ("data management" OR informatics) NOT "assays for monitoring autophagy" ) NOT pmcbook NOT ispreviousversion

Citations The Papers (from PubMed®)

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RevDate: 2024-12-03

Peltier DMP, Carbone MS, Ogle K, et al (2024)

Decades-old carbon reserves are widespread among tree species, constrained only by sapwood longevity.

The New phytologist [Epub ahead of print].

Carbon reserves are distributed throughout plant cells allowing past photosynthesis to fuel current metabolism. In trees, comparing the radiocarbon (Δ[14]C) of reserves to the atmospheric bomb spike can trace reserve ages. We synthesized Δ[14]C observations of stem reserves in nine tree species, fitting a new process model of reserve building. We asked how the distribution, mixing, and turnover of reserves vary across trees and species. We also explored how stress (drought and aridity) and disturbance (fire and bark beetles) perturb reserves. Given sufficient sapwood, young (< 1 yr) and old (20-60+ yr) reserves were simultaneously present in single trees, including 'prebomb' reserves in two conifers. The process model suggested that most reserves are deeply mixed (30.2 ± 21.7 rings) and then respired (2.7 ± 3.5-yr turnover time). Disturbance strongly increased Δ[14]C mean ages of reserves (+15-35 yr), while drought and aridity effects on mixing and turnover were species-dependent. Fire recovery in Sequoia sempervirens also appears to involve previously unobserved outward mixing of old reserves. Deep mixing and rapid turnover indicate most photosynthate is rapidly metabolized. Yet ecological variation in reserve ages is enormous, perhaps driven by stress and disturbance. Across species, maximum reserve ages appear primarily constrained by sapwood longevity, and thus old reserves are probably widespread.

RevDate: 2024-12-04
CmpDate: 2024-12-04

Yao M, Ren A, Yang X, et al (2025)

Unveiling the influence of heating temperature on biofilm formation in shower hoses through multi-omics.

Water research, 268(Pt B):122704.

Shower systems provide unique environments that are conducive to biofilm formation and the proliferation of pathogens. The water heating temperature is a delicate decision that can impact microbial growth, balancing safety and energy consumption. This study investigated the impact of different heating temperatures (39 °C, 45 °C, 51 °C and 58 °C) on the shower hose biofilm (exposed to a final water temperature of 39 °C) using controlled full-scale shower setups. Whole metagenome sequencing and metaproteomics were employed to unveil the microbial composition and protein expression profiles. Overall, the genes and enzymes associated with disinfectant resistance and biofilm formation appeared largely unaffected. However, metagenomic analysis revealed a sharp decline in the number of total (86,371 to 34,550) and unique genes (32,279 to 137) with the increase in hot water temperature, indicating a significant reduction of overall microbial complexity. None of the unique proteins were detected in the proteomics experiments, suggesting smaller variation among biofilms on the proteome level compared to genomic data. Furthermore, out of 43 pathogens detected by metagenomics, only 5 could actually be detected by metaproteomics. Most interestingly, our study indicates that 45 °C heating temperature may represent an optimal balance. It minimizes active biomass (ATP) and reduces the presence of pathogens while saving heating energy. Our study offered new insights into the impact of heating temperature on shower hose biofilm formation and proposed optimal parameters that ensure biosafety while conserving energy.

RevDate: 2024-12-03

Tian T, Zhang X, Zhang F, et al (2024)

Harnessing AI for advancing pathogenic microbiology: a bibliometric and topic modeling approach.

Frontiers in microbiology, 15:1510139.

INTRODUCTION: The integration of artificial intelligence (AI) in pathogenic microbiology has accelerated research and innovation. This study aims to explore the evolution and trends of AI applications in this domain, providing insights into how AI is transforming research and practice in pathogenic microbiology.

METHODS: We employed bibliometric analysis and topic modeling to examine 27,420 publications from the Web of Science Core Collection, covering the period from 2010 to 2024. These methods enabled us to identify key trends, research areas, and the geographical distribution of research efforts.

RESULTS: Since 2016, there has been an exponential increase in AI-related publications, with significant contributions from China and the USA. Our analysis identified eight major AI application areas: pathogen detection, antibiotic resistance prediction, transmission modeling, genomic analysis, therapeutic optimization, ecological profiling, vaccine development, and data management systems. Notably, we found significant lexical overlaps between these areas, especially between drug resistance and vaccine development, suggesting an interconnected research landscape.

DISCUSSION: AI is increasingly moving from laboratory research to clinical applications, enhancing hospital operations and public health strategies. It plays a vital role in optimizing pathogen detection, improving diagnostic speed, treatment efficacy, and disease control, particularly through advancements in rapid antibiotic susceptibility testing and COVID-19 vaccine development. This study highlights the current status, progress, and challenges of AI in pathogenic microbiology, guiding future research directions, resource allocation, and policy-making.

RevDate: 2024-12-02
CmpDate: 2024-12-02

Jeong D, Hyun JY, Marchenkova T, et al (2024)

Genetic insights and conservation strategies for Amur tigers in Southwest Primorye Russia.

Scientific reports, 14(1):29985.

Southwest Primorye hosts approximately 9% of the remaining wild Amur tiger population and represents hope for the revival of tigers in Northeast China and the Korean peninsula. Decades of conservation efforts have led to a significant increase in population size, from less than 10 individuals surviving in the region in 1996 to multiple folds today. However, while the population size has recovered since the mid-1900s, the effects of genetic depletion on evolutionary potential are not easily reversed. In this study, a non-invasive genetic analysis of the Amur tiger subpopulation in Southwest Primorye was conducted using microsatellite loci and mitochondrial genes to estimate genetic diversity, relatedness, and determine the impact of historical demographic dynamics. A total of 32 individuals (16 males, 15 females, and 1 unidentified sex) were identified, and signs of bottlenecks were detected, reflecting past demographic events. Low genetic variation observed in mitochondrial DNA also revealed genetic depletion within the population. Most individuals were found to be closely related to each other, raising concerns about inbreeding given the small population size and somewhat isolated environment from the main population in Sikhote-Alin. These findings emphasize the urgent need to establish ecological corridors to neighboring areas to restore genetic diversity and ensure the conservation of the Amur tiger population in Southwest Primorye.

RevDate: 2024-12-03
CmpDate: 2024-12-03

Tinsley E, Froidevaux JSP, G Jones (2024)

The location of solar farms within England's ecological landscape: Implications for biodiversity conservation.

Journal of environmental management, 372:123372.

A global energy transition to using sustainable renewable sources is being driven by global agreements. Simultaneously there is a call for increased biodiversity conservation. This creates a green-green dilemma, where the expansion of renewables could lead to the demise of biodiversity if not carefully assessed, managed and monitored. Recognition of the dilemma is central to the development of Sustainable Development Goals. It is therefore important to understand whether renewable energy sources such as solar farms are being sited in areas where they have minimal impact on biodiversity. If solar farms were sited with minimal impacts on biodiversity, we hypothesised that they would be less likely to be sited close to ecologically sensitive areas than near random points. We used Geographic Information System methods to explore the density of solar photovoltaic (PV) farms in England and assessed their siting relative to sensitive ecological features, including priority habitat types, designated sites, and land conservation initiatives. We compared the area of 25 sensitive ecological features around solar farms and random points across three spatial scales (100 m, 1000 m, and 6000 m radius scales). Solar farms were distributed throughout England, with the highest concentration in South West England. Solar sites were primarily surrounded by habitats with anthropogenic influences, such as agricultural and urban settings. Priority habitats, such as woodland, grassland, wetland and heathland, were more extensive around random points across spatial scales (except for woodland at the largest scale). Most designated sites were significantly more extensive around random points. We conclude that, under current planning regulations, solar sites in England are being placed appropriately with regard to sensitive ecological habitats, and are often sited in areas already impacted by farming and development. Adaptive planning should be implemented to ensure that the evolving research around biodiversity and solar farms is incorporated into decision making, and monitoring is completed across the lifespan of solar farms to assess impacts and effective mitigation.

RevDate: 2024-12-03
CmpDate: 2024-12-03

Konzen E, Delahay RJ, Hodgson DJ, et al (2024)

Efficient modelling of infectious diseases in wildlife: A case study of bovine tuberculosis in wild badgers.

PLoS computational biology, 20(11):e1012592 pii:PCOMPBIOL-D-24-00702.

Bovine tuberculosis (bTB) has significant socio-economic and welfare impacts on the cattle industry in parts of the world. In the United Kingdom and Ireland, disease control is complicated by the presence of infection in wildlife, principally the European badger. Control strategies tend to be applied to whole populations, but better identification of key sources of transmission, whether individuals or groups, could help inform more efficient approaches. Mechanistic transmission models can be used to better understand key epidemiological drivers of disease spread and identify high-risk individuals and groups if they can be adequately fitted to observed data. However, this is a significant challenge, especially within wildlife populations, because monitoring relies on imperfect diagnostic test information, and even under systematic surveillance efforts (such as capture-mark-recapture sampling) epidemiological events are only partially observed. To this end we develop a stochastic compartmental model of bTB transmission, and fit this to individual-level data from a unique > 40-year longitudinal study of 2,391 badgers using a recently developed individual forward filtering backward sampling algorithm. Modelling challenges are further compounded by spatio-temporal meta-population structures and age-dependent mortality. We develop a novel estimator for the individual effective reproduction number that provides quantitative evidence for the presence of superspreader badgers, despite the population-level effective reproduction number being less than one. We also infer measures of the hidden burden of infection in the host population through time; the relative likelihoods of competing routes of transmission; effective and realised infectious periods; and longitudinal measures of diagnostic test performance. This modelling framework provides an efficient and generalisable way to fit state-space models to individual-level data in wildlife populations, which allows identification of high-risk individuals and exploration of important epidemiological questions about bTB and other wildlife diseases.

RevDate: 2024-12-03
CmpDate: 2024-12-03

Li G, Wu M, Xiao Y, et al (2024)

Multi-omics reveals the ecological and biological functions of Enterococcus mundtii in the intestine of lepidopteran insects.

Comparative biochemistry and physiology. Part D, Genomics & proteomics, 52:101309.

Insect guts offer unique habitats for microbial colonization, with gut bacteria potentially offering numerous benefits to their hosts. Although Enterococcus has emerged as one of the predominant gut commensal bacteria in insects, its establishment in various niches within the gut has not been characterized well. In this study, Enterococcus mundtii was inoculated into the silkworm (Bombyx mori L.) to investigate its biological functions. Genome-based analysis revealed that its successful colonization is related to adherence genes (ebpA, ebpC, efaA, srtC, and scm). This bacterium did not alter the activities of related metabolic enzymes or the intestinal barrier function. However, significant changes in the gene expressions levels of Att2, CecA, and Lys suggest potential adaptive mechanisms of host immunity to symbiotic E. mundtii. Moreover, 16S metagenomics analysis revealed a significant increase in the relative abundance of E. mundtii in the intestines of silkworms following inoculation. The intestinal microbiome displayed marked heterogeneity, an elevated gut microbiome health index, a reduced microbial dysbiosis index, and low potential pathogenicity in the treatment group. Additionally, E. mundtii enhanced the breakdown of carbohydrates in host intestines. Overall, E. mundtii serves as a beneficial microbe for insects, promoting intestinal homeostasis by providing competitive advantage. This characteristic helps E. mundtii dominate complex microbial environments and remain prevalent across Lepidoptera, likely fostering long-term symbiosis between the both parties. The present study contributes to clarifying the niche of E. mundtii in the intestine of lepidopteran insects and further reveals its potential roles in their insect hosts.

RevDate: 2024-12-02
CmpDate: 2024-12-02

Monadjem A, Montauban C, Webala PW, et al (2024)

African bat database: curated data of occurrences, distributions and conservation metrics for sub-Saharan bats.

Scientific data, 11(1):1309.

Accurate knowledge of species distributions is foundational for effective conservation efforts. Bats are a diverse group of mammals, with important roles in ecosystem functioning. However, our understanding of bats and their ecological importance is hindered by poorly defined ranges, mostly as a result of under-recording. This issue is exacerbated in Africa by the ongoing rapid discovery of new species, both de novo and splits of existing species, and by inaccessibility to museum specimens that are mostly hosted outside of the continent. Here we present the African bat database - a curated set of 17,285 unique locality records of all 266 species of bats from sub-Saharan Africa, vouched for by specimens and/or genetic sequencing, and aligned with current taxonomy. Based on these records, we also present Maxent-based distribution models and calculate the IUCN Red List metrics for Extent of Occurrence and Area of Occupancy. This database and online visualization tool provide an important open-source resource and is expected to significantly advance studies in ecology, and aid in bat conservation.

RevDate: 2024-12-02

Nishimura H, Nawa N, Ogawa T, et al (2024)

Projections of future heat-related emergency hospitalizations for asthma under climate and demographic change scenarios: a Japanese nationwide time-series analysis.

Environmental research pii:S0013-9351(24)02405-8 [Epub ahead of print].

BACKGROUND: There is growing concern about climate impacts on human health. However, empirical evidence is lacking regarding future projections of heat-related asthma hospitalizations. This study aimed to project excess emergency hospitalizations for heat-related asthma exacerbation in Japan.

METHODS: Using Japanese nationwide administrative data from 2011 to 2019, we conducted an ecological time-series quasi-Poisson regression analysis to estimate the heat-related relative risk of emergency hospitalization for asthma over a lag of 0-3 days during the warm season (June to September). Heat exposure was defined as the region-specific daily mean temperature exceeding the locally defined minimum morbidity temperature percentile (MMP). Heat-related excess hospitalizations for asthma were projected under future climate and demographic change scenarios based on Shared Socioeconomic Pathways (SSPs).

RESULTS: We identified 75,829 emergency hospitalizations for asthma. The heat-related relative risk of hospitalization was 1.22 (95% confidence interval (CI): 1.12-1.33) at the 99th percentile temperature relative to the MMP, with the highest estimates for cases aged 0-14 years. Heat-related excess hospitalizations were projected to increase by 6.78 (95%CI: 5.84-7.67) times in 2091-2099 versus 2011-2019 along SSP5-8.5 when constant population structure was assumed. The increasing trend persisted even when the future population decline was considered (4.19 (95%CI: 3.53-4.85) times in 2091-2099 versus 2011-2019 under SSP5-8.5).

CONCLUSION: Future heat-related impacts on asthma exacerbation are expected to increase in Japan toward the end of this century, even when the future demographic change is considered. Our projections will contribute to resilient health systems adapting to ongoing climate change.

RevDate: 2024-12-02
CmpDate: 2024-12-02

Alfaro-Sánchez R, Richardson AD, Smith SL, et al (2024)

Permafrost instability negates the positive impact of warming temperatures on boreal radial growth.

Proceedings of the National Academy of Sciences of the United States of America, 121(50):e2411721121.

Climate warming can alleviate temperature and nutrient constraints on tree growth in boreal regions, potentially enhancing boreal productivity. However, in permafrost environments, warming also disrupts the physical foundation on which trees grow, leading to leaning trees or "drunken" forests. Tree leaning might reduce radial growth, undermining potential benefits of warming. Here, we found widespread radial growth reductions in southern latitude boreal forests since the 1980s. At mid latitudes, radial growth increased from ~1980 to ~2000 but showed recent signs of decline afterward. Increased growth was evident since the 1980 s at higher latitudes, where radial growth appears to be temperature limited. However, recent changes in permafrost stability, and the associated increased frequency of tree leaning events, emerged as a significant stressor, leading to reduced radial growth in boreal trees at the highest latitudes, where permafrost is extensive. We showed that trees growing in unstable permafrost sites allocated more nonstructural carbohydrate reserves to offset leaning which compromised radial growth and potential carbon uptake benefits of warming. This higher allocation of resources in drunken trees is needed to build the high-density reaction wood, rich in lignin, that is required to maintain a vertical position. With continued climate warming, we anticipate widespread reductions in radial growth in boreal forests, leading to lower carbon sequestration. These findings enhance our understanding of how climate warming and indirect effects, such as ground instability caused by warming permafrost, will affect boreal forest productivity in the future.

RevDate: 2024-12-02

Boyes D, Young MR, University of Oxford and Wytham Woods Genome Acquisition Lab, et al (2024)

The genome sequence of the Straw Grass-veneer moth, Agriphila straminella (Denis & Schiffermüller), 1775.

Wellcome open research, 9:433.

We present a genome assembly from an individual male Straw Grass-veneer moth, Agriphila straminella (Arthropoda; Insecta; Lepidoptera; Crambidae). The genome sequence has a length of 511.50 megabases. Most of the assembly is scaffolded into 26 chromosomal pseudomolecules, including the Z sex chromosome. The mitochondrial genome has also been assembled and is 15.36 kilobases in length. Gene annotation of this assembly on Ensembl identified 12,087 protein-coding genes.

RevDate: 2024-11-30

Asaaga FA, Shakeer I, Sriram A, et al (2024)

Ties that bind: understanding One Health networks and participation for zoonoses prevention and control in India.

One health outlook, 6(1):24.

BACKGROUND: Cross-sectoral collaborations as exemplified by the One Health approach, are widely endorsed as pragmatic avenues for addressing zoonotic diseases, but operationalisation remain limited in low-and-middle income countries (LMICs). Complexities and competing interests and agendas of key stakeholders and the underlying politico-administrative context can all shape outcomes of collaborative arrangements. Evidence is building that organised collaborations are complex political initiatives where different objectives; individual and institutional agendas need to be reconciled to incentivise collaborations.

METHODS: Drawing on a qualitative network analysis of published sources on 'One Health' stakeholders supplemented with 26 multi-scale (national-state-district level) key-informant interviews (including policymakers, disease managers and public health experts), this paper characterises the fragmented and complex characteristics of institutional networks involved in zoonoses prevention and control in India.

RESULTS: Our results highlight how the local socio-political and institutional contexts interact to modulate how and when collaborations occur (or not), the associated contingencies and stakeholder innovations in circumventing existing barriers (e.g. competing interests, distrust between actors, departmental bureaucracy) to cross-sector collaborations and zoonoses management. Aside from principal actors negotiating common ground in some instance, they also capitalised on political/institutional pressure to subtly 'manipulate' their subordinates as a way of fostering collaboration, especially in instances when the institutional and political stakes are high.

CONCLUSION: Altogether our findings suggest that cross-sectoral collaborations are by-product of political and institutional tinkering as long as individual actors and institutional interests converge and these dynamics must be embraced to embed meaningful and sustainable collaborations in local socio-political and administrative contexts.

RevDate: 2024-12-02
CmpDate: 2024-12-01

Wu Y, Wei C, Zhang Y, et al (2024)

Investigating intrinsic and situational predictors of depression among older adults: An analysis of the CHARLS database.

Asian journal of psychiatry, 102:104279.

BACKGROUND: This study aimed to investigate the intrinsic and situational predictors of depression under the health ecological model.

METHODS: Two waves (2011 and 2013) of survey data were collected from the CHARLS. A total of 5845 older adults (≧60) were included, and depression was defined as CESD-10 score ≧10. Random forest combined with interpretable methods were utilized to select important predictors of depression. Multilevel logit model was used to examine the associations of intrinsic and situational predictors with depression.

RESULTS: After a 2-year follow up, 1822 individuals (31.17 %) developed depression. Interpretable analyses showed that both intrinsic and situational variables were predictive for depression. Multilevel logit model showed that age, gender, number of chronic diseases, number of pain areas, life satisfaction, and toilet distance were significantly associated with depression.

CONCLUSION: Both intrinsic and situational factors were found to be associated with depression among community older population, highlighting their significance for early prevention from the perspective of public health.

RevDate: 2024-12-02
CmpDate: 2024-12-02

Burger J, Gochfeld M, Brown KG, et al (2025)

Using the National Land Cover Database as an indicator of shrub-steppe habitat: comparing two large United States federal lands with surrounding regions.

Journal of toxicology and environmental health. Part A, 88(1):1-19.

There is a need to assess whether ecological resources are being protected on large, federal lands. The aim of this study was to present a methodology which consistently and transparently determines whether two large Department of Energy (U.S. DOE) facilities have protected valuable ecological lands on their sites compared to the surrounding region. The National Land Cover Database (2019) was used to examine the % shrub-scrub (shrub-steppe) and other habitats on the DOE's Hanford Site (HS, Washington) and on the Idaho National Laboratory (INL), compared to a 10-km and 30-km diameter band of land surrounding each site. On both sites, over 95% is in shrub-scrub or grassland, compared to the surrounding region. Approximately 70% of 10 km and 30-km bands around INL, and less than 50% of land surrounding HS is located in these two habitat types. INL has preserved a significantly higher % shrub/scrub habitat than HS, but INL allows grazing on 60% of its land. HS has preserved a significantly higher % grassland than INL but no grazing on site is present. The methodology presented may be used to compare key ecological habitat types such as grasslands, forest, and desert among sites in different parts of the country. This methodology enables managers, resource trustees, and the public to (1) make remediation decisions that protect resources, (2) assess whether landowners and managers have adequately characterized and protected environmental resources on their sites, and (3) whether landowners and managers have protected the integrity of that land as well as its climax vegetation.

RevDate: 2024-11-29
CmpDate: 2024-11-29

Ma D, Huang Q, Wang Q, et al (2024)

Detection of spatiotemporal changes in eco-environmental quality based on RSEI and SG filtering and its driving force analysis: a case study in Sichuan Province, China.

Environmental monitoring and assessment, 196(12):1274.

Landsat images were extracted using Google Earth Engine (GEE) platform and optimized by Savitzky-Golay (SG) filtering. The Remote Sensing Ecological Index (RSEI) method was used to analyze the eco-environmental quality in Sichuan Province in recent 20 years. In addition, Theil-Sen median method and Mann-Kendall (MK) test were used to test the change trend of eco-environmental quality. Furthermore, drivers were evaluated by partial correlation analysis, 2D scatter plots, and t tests. The results showed that (1) in the past 20 years, the eco-environmental quality of Sichuan Province was on the rise, and the eco-environmental quality in the western region was better than that in the eastern region. The eco-environmental quality was positively correlated with forest and grassland types, and negatively correlated with cultivated land and urban and rural construction land types. (2) The eco-environmental quality of Sichuan Province is linearly correlated with the digital elevation model, but poorly correlated with slope and slope direction. In the range of slope 0° ~ 9° and southeast direction, the eco-environmental quality is the worst. (3) The eco-environmental quality of Sichuan Province was most significantly affected by soil moisture and sunshine hours. The study can help us to understand and assess the health of ecosystems in Sichuan Province, provide a scientific basis for protecting and improving the environment, and guide the formulation and implementation of environmental protection policies.

RevDate: 2024-11-28
CmpDate: 2024-11-28

Alvarez-Mamani E, Buettner F, Beltran-Castanon CA, et al (2024)

Exploratory analysis of metabolic changes using mass spectrometry data and graph embeddings.

Scientific reports, 14(1):29570.

Mass spectrometry (MS)-based metabolomics analysis is a powerful tool, but it comes with its own set of challenges. The MS workflow involves multiple steps before its interpretation in what is denominate data mining. Data mining consists of a two-step process. First, the MS data is ordered, arranged, and presented for filtering before being analyzed. Second, the filtered and reduced data are analyzed using statistics to remove further variability. This holds true particularly for MS-based untargeted metabolomics studies, which focused on understanding fold changes in metabolic networks. Since the task of filtering and identifying changes from a large dataset is challenging, automated techniques for mining untargeted MS-based metabolomic data are needed. The traditional statistics-based approach tends to overfilter raw data, which may result in the removal of relevant data and lead to the identification of fewer metabolomic changes. This limitation of the traditional approach underscores the need for a new method. In this work, we present a novel deep learning approach using node embeddings (powered by GNNs), edge embeddings, and anomaly detection algorithm to analyze the data generated by mass spectrometry (MS)-based metabolomics called GEMNA (Graph Embedding-based Metabolomics Network Analysis), for example for an untargeted volatile study on Mentos candy, the data clusters produced by GEMNA were better than the ones used traditional tools, i.e., GEMNA has [Formula: see text], vs. the traditional approach has [Formula: see text].

RevDate: 2024-11-28
CmpDate: 2024-11-28

Whyte M, Wambui KM, E Musenge (2024)

Nigeria's malaria prevalence in 2015: a geospatial, exploratory district-level approach.

Geospatial health, 19(2):.

This study used data from the second Nigeria Malaria Indicator Survey (NMIS) conducted in 2015 to investigate the spatial distribution of malaria prevalence in the country and identify its associated factors. Nigeria is divided into 36 states with 109 senatorial districts, most of which are affected by malaria, a major cause of morbidity and mortality in children under five years of age. We carried out an ecological study with analysis at the senatorial district level. A malaria prevalence map was produced combining geographic information systems data from the Nigeria Malaria Indicator Survey (NMIS) of 2015 with shape files from an open data-sharing platform. Spatial autoregressive models were fitted using a set of key covariates. Malaria prevalence in children under-five was highest in Kebbi South senatorial district (70.6%). It was found that poorest wealth index (β = 0.10 (95% CI: 0.01, 0.20), p = 0.04), mothers having only secondary level of education (β = 0.78 (95% CI: 0.05, 1.51), p = 0.04) and households without mosquito bed nets (β = 0.21 (95% CI: 0.02, 0.39), p = 0.03) were all significantly associated with higher malaria prevalence. Moran's I (54.81, p<0.001) showed spatial dependence of malaria prevalence across contiguous districts and spatial autoregressive modelling demonstrated significant spill-over effect of malaria prevalence. Maps produced in this study provide a useful graphical representation of the spatial distribution of malaria prevalence based on NMIS-2015 data. Clustering of malaria prevalence in certain areas further highlights the need for sustained malaria elimination interventions across affected regions in order to break the chain of transmission.

RevDate: 2024-11-27

Soares R, Azevedo L, Vasconcelos V, et al (2024)

Machine Learning-Driven Discovery and Database of Cyanobacteria Bioactive Compounds: A Resource for Therapeutics and Bioremediation.

Journal of chemical information and modeling [Epub ahead of print].

Cyanobacteria strains have the potential to produce bioactive compounds that can be used in therapeutics and bioremediation. Therefore, compiling all information about these compounds to consider their value as bioresources for industrial and research applications is essential. In this study, a searchable, updated, curated, and downloadable database of cyanobacteria bioactive compounds was designed, along with a machine-learning model to predict the compounds' targets of newly discovered molecules. A Python programming protocol obtained 3431 cyanobacteria bioactive compounds, 373 unique protein targets, and 3027 molecular descriptors. PaDEL-descriptor, Mordred, and Drugtax software were used to calculate the chemical descriptors for each bioactive compound database record. The biochemical descriptors were then used to determine the most promising protein targets for human therapeutic approaches and environmental bioremediation using the best machine learning (ML) model. The creation of our database, coupled with the integration of computational docking protocols, represents an innovative approach to understanding the potential of cyanobacteria bioactive compounds. This resource, adhering to the findability, accessibility, interoperability, and reuse of digital assets (FAIR) principles, is an excellent tool for pharmaceutical and bioremediation researchers. Moreover, its capacity to facilitate the exploration of specific compounds' interactions with environmental pollutants is a significant advancement, aligning with the increasing reliance on data science and machine learning to address environmental challenges. This study is a notable step forward in leveraging cyanobacteria for both therapeutic and ecological sustainability.

RevDate: 2024-11-27

Boyes D, Crowley LM, University of Oxford and Wytham Woods Genome Acquisition Lab, et al (2021)

The genome sequence of the harlequin ladybird, Harmonia axyridis (Pallas, 1773).

Wellcome open research, 6:300.

We present a genome assembly from an individual female Harmonia axyridis (the harlequin ladybird; Arthropoda; Insecta; Coleoptera; Coccinellidae). The genome sequence is 426 megabases in span. The majority (99.98%) of the assembly is scaffolded into 8 chromosomal pseudomolecules, with the X sex chromosome assembled.

RevDate: 2024-11-27

Toghan A, Alduaij OK, Sanad MMS, et al (2024)

Scalable Engineering of 3D Printing Filaments Derived from Recycling of Plastic Drinking Water Bottle and Glass Waste.

Polymers, 16(22): pii:polym16223195.

The most significant challenge that the world is currently facing is the development of beneficial industrial applications for solid waste. A novel strategy was implemented to produce a composite with varying loadings of glass waste nanoparticles (GWNP) in 5, 10, and 15 wt.% with recycled polyethylene terephthalate drinking water bottle waste (RPET). This strategy was based on glass and drinking water bottle waste. An analysis was conducted to evaluate the performance of the composite as filaments for 3D printer applications. This study evaluated the effect of GWNP addition on the chemical structure, thermal and mechanical characteristics of the composite. The Fourier Transform Infrared (FTIR) spectra of the filament composites and RPET composites exhibited similarities. However, the mechanical strength and thermal stability of the filament composites were enhanced due to the increased GWNP content. Furthermore, the results indicated that the filament developed could be utilized for 3D printing, as demonstrated by the successful fabrication of the filament composite, including 5 wt.% GWNP, using a 3D printer pen. The production of filaments using GWNP and RPET matrix presents a cost-effective, high-yield, and ecologically beneficial alternative. The present study may pave the way for the future advancement and utilization of 3D printing filaments by treating hazardous waste and using more ecologically friendly materials in design applications.

RevDate: 2024-11-27

Maślanka P, R Korycki (2024)

Material, Aerodynamic, and Operational Aspects of Single-Skin Paraglider.

Materials (Basel, Switzerland), 17(22): pii:ma17225553.

The operating comfort of a paraglider is created by the aerodynamic parameters as well as the mass and packing volume of the wing. A classic paraglider has upper and lower covers. To reduce the material and manufacturing costs as well as protect the environment, it is possible to introduce a single-skin wing. This article conducts an analysis of a single-skin paraglider covered only with upper panels, whereas the lower cover is applied only at the leading and trailing edges. The analysis is theoretically oriented; aerodynamic and structural calculations were performed using the ANSYS environment. The single-skin structure was evaluated in terms of the predicted behavior during flight and the material's deformation under the influence of a specified pressure and the overloads acting on it. The results show that developing these structures may influence the creation of models with comparable aerodynamic characteristics to traditional ones. Additionally, the reduced masses and packing volumes of difficult-to-degrade materials are strongly correlated with saving costs and an ecological approach. No corresponding studies were found in the available literature. Thus, this presented analysis may result in a greater understanding and application of this paraglider type.

RevDate: 2024-11-27
CmpDate: 2024-11-27

Signore IA, Donoso G, Bocchieri P, et al (2024)

The Chilean COVID-19 Genomics Network Biorepository: A Resource for Multi-Omics Studies of COVID-19 and Long COVID in a Latin American Population.

Genes, 15(11): pii:genes15111352.

Although a lack of diversity in genetic studies is an acknowledged obstacle for personalized medicine and precision public health, Latin American populations remain particularly understudied despite their heterogeneity and mixed ancestry. This gap extends to COVID-19 despite its variability in susceptibility and clinical course, where ethnic background appears to influence disease severity, with non-Europeans facing higher hospitalization rates. In addition, access to high-quality samples and data is a critical issue for personalized and precision medicine, and it has become clear that the solution lies in biobanks. The creation of the Chilean COVID-19 Biorepository reported here addresses these gaps, representing the first nationwide multicentric Chilean initiative. It operates under rigorous biobanking standards and serves as one of South America's largest COVID cohorts. A centralized harmonization strategy was chosen and included unified standard operating procedures, a sampling coding system, and biobanking staff training. Adults with confirmed SARS-CoV-2 infection provided broad informed consent. Samples were collected to preserve blood, plasma, buffy coat, and DNA. Quality controls included adherence to the standard preanalytical code, incident reporting, and DNA concentration and absorbance ratio 260/280 assessments. Detailed sociodemographic, health, medication, and preexisting condition data were gathered. In five months, 2262 participants were enrolled, pseudonymized, and sorted by disease severity. The average Amerindian ancestry considering all participant was 44.0% [SD 15.5%], and this value increased to 61.2% [SD 19.5%] among those who self-identified as Native South Americans. Notably, 279 participants self-identified with one of 12 ethnic groups. High compliance (>90%) in all assessed quality controls was achieved. Looking ahead, our team founded the COVID-19 Genomics Network (C19-GenoNet) focused on identifying genetic factors influencing SARS-CoV-2 outcomes. In conclusion, this bottom-up collaborative effort aims to promote the integration of Latin American populations into global genetic research and welcomes collaborations supporting this endeavor. Interested parties are invited to explore collaboration opportunities through our catalog, accessible online.

RevDate: 2024-11-27
CmpDate: 2024-11-27

Aras SG, Runyon JR, Kazman JB, et al (2024)

Is Greener Better? Quantifying the Impact of a Nature Walk on Stress Reduction Using HRV and Saliva Cortisol Biomarkers.

International journal of environmental research and public health, 21(11): pii:ijerph21111491.

The physiological impact of walking in nature was quantified via continuous heart rate variability (HRV), pre- and post-walk saliva cortisol measures, and self-reported mood and mindfulness scores for N = 17 participants who walked "The Green Road" at Walter Reed National Military Medical Center in Bethesda, Maryland. For N = 15 of the participants, HRV analysis revealed two main groups: group one individuals had a 104% increase (mean) in the root mean square standard deviation (RMSSD) and a 47% increase (mean) in the standard deviation of NN values (SDNN), indicating an overall reduction in physiological stress from walking the Green Road, and group two individuals had a decrease (mean) of 42% and 31% in these respective HRV metrics, signaling an increase in physiological stresses. Post-walk self-reported scores for vigor and mood disturbance were more robust for the Green Road than for a comparable urban road corridor and showed that a higher HRV during the walk was associated with improved overall mood. Saliva cortisol was lower after taking a walk for all participants, and it showed that walking the Green Road elicited a significantly larger reduction in cortisol of 53%, on average, when compared with 37% of walking along an urban road. It was also observed that the order in which individuals walked the Green Road and urban road also impacted their cortisol responses, with those walking the urban road before the Green Road showing a substantial reduction in cortisol, suggesting a possible attenuation effect of walking the Green Road first. These findings provide quantitative data demonstrating the stress-reducing effects of being in nature, thus supporting the health benefit value of providing access to nature more broadly in many settings.

RevDate: 2024-11-27

Alrhmoun M, Sulaiman N, Haq SM, et al (2024)

Is Boiling Bitter Greens a Legacy of Ancient Crete? Contemporary Foraging in the Minoan Refugium of the Lasithi Plateau.

Foods (Basel, Switzerland), 13(22):.

Wild greens (WGs) play a significant role in Mediterranean diets (MDs), reflecting botanical and cultural diversities, mainly influenced by a complex conglomerate of local human ecologies. This study investigates local ecological knowledge (LEK) linked to traditional gathering and consumption of WGs in the Lasithi Plateau of eastern Crete, where human genetic studies one decade ago showed very peculiar patterns, hypothesising that the Minoan civilisation took refuge there before it disappeared. A field ethnobotanical study was conducted to document the diversity of WGs and their detailed local culinary uses in the Lasithi area by interviewing 31 study participants. Fifty-nine folk taxa (species and subspecies) were recorded, corresponding to fifty-eight botanical taxa. A quotation index was measured to assess the cultural significance of WGs in the study areas; logistic regression analysis was adopted to understand the impact of sensory classifications of WGs and their local cooking methods. Lasithi's foraging showed a notable prevalence of bitter-tasting WGs, which play a central role in local cognition and culinary practices. This bitterness aspect of WGs, potentially influenced by cultural preferences and genetic factors, probably suggests a connection to the ancient Lasithi's inhabitants, i.e., Minoan dietary habits. We found that bitterness is the predominant sensory attribute in Lasithi, characterising 45.76% of the WGs. These findings underscore the complex interplay between local ecologies and biodiversity, LEK, and dietary traditions, highlighting the importance of WGs in understanding the evolution of foraging and plant culinary diversities across the Mediterranean.

RevDate: 2024-11-26
CmpDate: 2024-11-27

Das VA, Gautam B, Yadav PK, et al (2024)

Computational approach to identify novel genomic features conferring high fitness in Bacillus atrophaeus CNY01 and Bacillus velezensis AK-0 associated with plant growth promotion (PGP) in apple.

BMC plant biology, 24(1):1127.

A comparative genomic analysis approach provides valuable information about genetic variations and evolutionary relationships among microorganisms, aiding not only in the identification of functional genes responsible for traits such as pathogenicity, antibiotic resistance, and metabolic capabilities but also in enhancing our understanding of microbial genomic diversity and their ecological roles, such as supporting plant growth promotion, thereby enabling the development of sustainable strategies for agriculture. We used two strains from different Bacillus species, Bacillus velezensis AK-0 and Bacillus atrophaeus CNY01, which have previously been reported to have PGP activity in apple, and performed comparative genomic analysis to understand their evolutionary process and obtain a mechanistic understanding of their plant growth-promoting activity. We identified genomic features such as mobile genetic elements (MGEs) that encode key proteins involved in the survival, adaptation and growth of these bacterial strains. The presence of genomic islands and intact prophage DNA in Bacillus atrophaeus CNY01 and Bacillus velezensis AK-0 suggests that horizontal gene transfer has contributed to their diversification and acquisition of adaptive traits, enhancing their evolutionary advantage. We also identified novel DNA motifs that are associated with key physiological processes and metabolic pathways.

RevDate: 2024-11-26
CmpDate: 2024-11-26

Baradaran M, Salabi F, Mahdavinia M, et al (2024)

ScorpDb: A Novel Open-Access Database for Integrative Scorpion Toxinology.

Toxins, 16(11): pii:toxins16110497.

Scorpion stings are a significant public health concern globally, particularly in tropical and subtropical regions. Scorpion venoms contain a diverse array of bioactive peptides, and different scorpion species around the world typically exhibit varying venom profiles, resulting in a wide range of envenomation symptoms. Despite their harmful effects, scorpion venom peptides hold immense potential for drug development due to their unique characteristics. Therefore, the establishment of a comprehensive database that catalogs scorpions along with their known venom peptides and proteins is imperative in furthering research efforts in this research area. We hereby present ScorpDb, a novel database that offers convenient access to data related to different scorpion species, the peptides and proteins found in their venoms, and the symptoms they can cause. To this end, the ScorpDb database has been primarily advanced to accommodate data on the Iranian scorpion fauna. From there, we propose future community efforts to include a larger diversity of scorpions and scorpion venom components. ScorpDb holds the promise to become a valuable resource for different professionals from a variety of research fields, like toxinologists, arachnologists, and pharmacologists. The database is available at https://www.scorpdb.com/.

RevDate: 2024-11-27
CmpDate: 2024-11-27

Tayyab M, Hussain M, Zhang J, et al (2024)

Leveraging GIS-based AHP, remote sensing, and machine learning for susceptibility assessment of different flood types in peshawar, Pakistan.

Journal of environmental management, 371:123094.

Due to its diverse topography, Pakistan faces different types of floods each year, which cause substantial physical, environmental, and socioeconomic damage. However, the susceptibility of specific regions to different flood types remains unexplored. To the best of our knowledge for the first time, this study employed an integrated approach by leveraging a GIS-based Analytical Hierarchy Process (AHP), remote sensing, and machine learning (ML) algorithms, to assess susceptibility to three different types of flooding in Peshawar, Pakistan. The study first evaluated the degree of susceptibility to riverine, urban, and flash floods using the GIS-based AHP technique, and then employed ML models, (i.e., specifically Random Forest [RF] and Extreme Gradient Boosting [XG-Boost] to analyze multi-type flood susceptibility in the study region. The performance of the ML models was also evaluated, and the XG-Boost model outperforms RF, demonstrating a higher correlation coefficient (R[2] = 0.561-0.922) and lower mean absolute error (MAE = 0.042-0.354), and root-mean-square error (RMSE = 0.119-0.415) for both training and testing datasets. The superior performance of the XG-Boost was further confirmed by the higher value of the area under the curve (AUC) values, which is relatively higher (0.87) than that of the AHP (0.70) and RF (0.86) models. Based on the relative best performance, the XG-Boost model was chosen for further susceptibility assessment of different types of floods, and the generated flood susceptibility maps revealed that 20.9% of the total area is susceptible to riverine flooding, while 30.27% and 48.68% of the total area is susceptible to urban and flash flooding, respectively. The study's findings are significant, offering valuable insights for relevant stakeholders in guiding future flood risk management and sustainable land use plans in the study area.

RevDate: 2024-11-27
CmpDate: 2024-11-27

Li Z, Zhang Y, Peng B, et al (2024)

A novel interpretable deep learning-based computational framework designed synthetic enhancers with broad cross-species activity.

Nucleic acids research, 52(21):13447-13468.

Enhancers play a critical role in dynamically regulating spatial-temporal gene expression and establishing cell identity, underscoring the significance of designing them with specific properties for applications in biosynthetic engineering and gene therapy. Despite numerous high-throughput methods facilitating genome-wide enhancer identification, deciphering the sequence determinants of their activity remains challenging. Here, we present the DREAM (DNA cis-Regulatory Elements with controllable Activity design platforM) framework, a novel deep learning-based approach for synthetic enhancer design. Proficient in uncovering subtle and intricate patterns within extensive enhancer screening data, DREAM achieves cutting-edge sequence-based enhancer activity prediction and highlights critical sequence features implicating strong enhancer activity. Leveraging DREAM, we have engineered enhancers that surpass the potency of the strongest enhancer within the Drosophila genome by approximately 3.6-fold. Remarkably, these synthetic enhancers exhibited conserved functionality across species that have diverged more than billion years, indicating that DREAM was able to learn highly conserved enhancer regulatory grammar. Additionally, we designed silencers and cell line-specific enhancers using DREAM, demonstrating its versatility. Overall, our study not only introduces an interpretable approach for enhancer design but also lays out a general framework applicable to the design of other types of cis-regulatory elements.

RevDate: 2024-11-27
CmpDate: 2024-11-27

Sun Q, Zhang Z, Ping Q, et al (2024)

Insight into using multi-omics analysis to elucidate nitrogen removal mechanisms in a novel improved constructed rapid infiltration system: Functional gene and metabolite signatures.

Water research, 267:122502.

In this study, a laboratory-scale improved constructed rapid infiltration (imCRI) system with non-saturated and saturated layers was constructed, and corn cobs as solid carbon source were added to the saturated layer to enhance the removal of nitrogen. Combined analyses of metagenomics and metabolomics were conducted to elucidate the nitrogen removal mechanism in the imCRI system. The results showed that the hydraulic load significantly influenced the treatment performance of the imCRI system, and a hydraulic load of 1.25 m[3]/(m[2]⋅d) was recommended. Under optimal conditions, the imCRI system using simulated wastewater achieved average removal efficiencies of 97.8 % for chemical oxygen demand, 85.7 % for total nitrogen (TN), and 97.6 % for ammonia nitrogen. Metagenomic and metabolomic analyses revealed that besides nitrification and denitrification, dissimilatory nitrate reduction to ammonium (DNRA), anammox, etc., are also involved in nitrogen metabolism in the imCRI system. Although nitrification was the predominant pathway in the non-saturated layer, aerobic denitrification also occurred, accounting for 22.59 % of the TN removal. In the saturated layer, nitrogen removal was attributed to synergistic effects of denitrification, DNRA and anammox. Moreover, correlation analysis among nitrogen removal, functional genes and metabolites suggested that metabolites related to the tricarboxylic acid cycle generated from the glycolysis of corn cobs provided sufficient energy for denitrification. Our results can offer a promising technology for decentralized wastewater treatment with stringent nitrogen removal requirements, and provide a foundation for understanding the underlying nitrogen transformation and removal mechanism.

RevDate: 2024-11-27
CmpDate: 2024-11-27

Li D, Ping Q, Mo R, et al (2024)

Revealing synergistic mechanisms of biochar-assisted microbial electrolysis cells in enhancing the anaerobic digestion performance of waste activated sludge: Extracellular polymeric substances characterization, enzyme activity assay, and multi-omics analysis.

Water research, 267:122501.

Although biochar (BC)-assisted microbial electrolysis cells (MEC) has been shown to improve anaerobic digestion (AD) performance of waste activated sludge (WAS), the underlying mechanisms remain unclear. This study conducted an in-depth investigation into the mechanism based on analyses of extracellular polymeric substances (EPS) characteristics, enzyme activities and multi-omics. The results showed that compared with the control group, methane production improved by 16.73 %, 21.32 %, and 29.37 % in the BC, MEC, and BC-assisted MEC (BC-MEC) groups, respectively. The reconfiguration of the protein secondary structure increased the hydrophobicity of the EPS, thereby promoting microbial aggregation. In addition, partial least-squares path modeling (PLS-PM) and mantel test based on the enzyme activity and multi-omics analyses revealed that the promotional effect of MEC on the hydrolysis of WAS was superior to that of BC, while BC was more advantageous in promoting electron transfer and biofilm formation regulated by quorum sensing. The synergistic effects of BC and MEC were exemplified in the BC-MEC group. g_norank_Aminicenantales responsible for the hydrolysis of WAS was enriched (29.6 %), and the activities of hydrolytic enzymes including α-glucosidases and proteases were increased by 29.1 % and 43.6 %, respectively. Further, the expressions of genes related to acyl homoserine lactones (AHLs) and diffusible signal factor (DSF) in quorum sensing systems, as well as the genes related to hydrogenase involved in electron transfer (mbhJKL, hyfB-JR, hypA-F, and hoxFHUY), were up-regulated in the BC-MEC group. This facilitated electron transfer and microbial communication, consequently enhancing methane production. This research significantly advances the understanding of the mechanism by which BC-assisted MEC enhances AD performance and provides valuable insights into strategies for improving energy recovery from WAS.

RevDate: 2024-11-26
CmpDate: 2024-11-26

Roman-Ramos H, PL Ho (2024)

Current Technologies in Snake Venom Analysis and Applications.

Toxins, 16(11): pii:toxins16110458.

This comprehensive review explores the cutting-edge advancements in snake venom research, focusing on the integration of proteomics, genomics, transcriptomics, and bioinformatics. Highlighting the transformative impact of these technologies, the review delves into the genetic and ecological factors driving venom evolution, the complex molecular composition of venoms, and the regulatory mechanisms underlying toxin production. The application of synthetic biology and multi-omics approaches, collectively known as venomics, has revolutionized the field, providing deeper insights into venom function and its therapeutic potential. Despite significant progress, challenges such as the functional characterization of toxins and the development of cost-effective antivenoms remain. This review also discusses the future directions of venom research, emphasizing the need for interdisciplinary collaborations and new technologies (mRNAs, cryo-electron microscopy for structural determinations of toxin complexes, synthetic biology, and other technologies) to fully harness the biomedical potential of venoms and toxins from snakes and other animals.

RevDate: 2024-11-26

Arias M, Behrendt L, Dreßler L, et al (2024)

Testing the equivalency of human "predators" and deep neural networks in the detection of cryptic moths.

Journal of evolutionary biology pii:7908977 [Epub ahead of print].

Researchers have shown growing interest in using deep neural networks (DNNs) to efficiently test the effects of perceptual processes on the evolution of color patterns and morphologies. Whether this is a valid approach remains unclear, as it is unknown whether the relative detectability of ecologically relevant stimuli to DNNs actually matches that of biological neural networks. To test this, we compare image classification performance by humans and six DNNs (AlexNet, VGG-16, VGG-19, ResNet-18, SqueezeNet, and GoogLeNet) trained to detect artificial moths on tree trunks. Moths varied in their degree of crypsis, conferred by different sizes and spatial configurations of transparent wing elements. Like humans, four of six DNN architectures found moths with larger transparent elements harder to detect. However, humans and only one DNN architecture (GoogLeNet) found moths with transparent elements touching one side of the moth's outline harder to detect than moths with untouched outlines. When moths were small, the camouflaging effect of transparent elements touching the moth's outline was reduced for DNNs but enhanced for humans. Prey size can thus interact with camouflage type in opposing directions in humans and DNNs, which warrants a deeper investigation of size interactions with a broader range of stimuli. Overall, our results suggest that humans and DNNs responses had some similarities, but not enough to justify the widespread use of DNNs for studies of camouflage.

RevDate: 2024-11-25

Gianicolo E, Russo A, Di Staso R, et al (2024)

A municipality-specific analysis to investigate persistent increased incidence rates of childhood leukaemia near the nuclear power plant of Krümmel in Germany.

European journal of epidemiology [Epub ahead of print].

Increased incidence rates for childhood leukaemia have been reported in municipalities close to the nuclear power plant (NPP) Krümmel (Geesthacht, Germany). Methodological challenges arise when analysing this association at ecological level. They include the use of an appropriate reference population, unstable estimates of standardised incidence ratios (SIRs), and the potential role of prevailing winds. The aim of our study is to address these challenges. The German Childhood Cancer Registry provided data on leukaemia in children under 15 years (2004-2019). The German Federal Statistical Office provided the population data. The study region included all municipalities with ≥ 75% surface area within 50 kms from the Krümmel NPP. We calculated SIRs using national and regional reference rates. Smoothed incidence relative rates (IRRs) were calculated and mapped to check for potential patterns associated with prevailing winds. Overall 356 cases of childhood leukaemia were observed in the study region (321 municipalities) during 2004-2019. SIRs based on national reference rates show nearly no difference to those calculated using the regional rates as reference. Increased SIR and IRR were observed in Geesthacht (observed-cases = eight; SIR = 2.29; 95% confidence interval: 0.99-4.51. IRR = 1.80; 95% credibility interval: 0.88-2.79). The analysis of the IRR map does not show patterns associated with prevailing winds. Using a regional population as the reference, we found evidence that there may still be an increased risk for childhood leukaemia in Geesthacht. However, IRR estimates are uncertain and credibility intervals are compatible with the absence of elevated risk. The persistent evidence of risk of childhood leukaemia in Geesthacht warrants further epidemiological surveillance.

RevDate: 2024-11-25
CmpDate: 2024-11-25

Adderley-Heron K, P Chow-Fraser (2024)

Unsupervised classification of Blanding's turtle (Emydoidea blandingii) behavioural states from multi-sensor biologger data.

PloS one, 19(11):e0314291 pii:PONE-D-24-14991.

Classifying animal behaviors in their natural environments is both challenging and ecologically important, but the use of biologgers with multiple sensors has significantly advanced this research beyond the capabilities of traditional methods alone. Here, we show how biologgers containing an integrated tri-axial accelerometer, GPS logger and immersion sensor were used to infer behavioural states of a cryptic, freshwater turtle, the Blanding's turtle (Emydoidea blandingii). Biologgers were attached to three males and five females that reside in two undisturbed coastal marshes in northeastern Georgian Bay (Ontario, Canada) between May and July 2023. Raw acceleration values were separated into static and dynamic acceleration and subsequently used to calculate overall dynamic body acceleration (ODBA) and pitch. The unsupervised Hidden Markov Model (HMM) successfully differentiated five behavioural states as follows: active in water, resting in water, active out of water, resting in water, and nesting. Overall accuracy of the classification was 93.8%, and except for nesting (79%), all other behaviours were above 92%. There were significant differences in daily activity budgets between male and female turtles, with females spending a greater proportion of time active out of water, and inactive out of the water, while males spent a greater proportion of time active in water. These differences were likely a result of large seasonal life-history requirements such as nesting and mate finding. Accurate classification of behavioural states is important for researchers to understand fine-scale activities carried out during the active season and how environmental variables may influence the behaviours of turtles in their natural habitats.

RevDate: 2024-11-25
CmpDate: 2024-11-25

Sahak AS, Karsli F, MA Saraj (2024)

Evaluating the impact of urban sprawl on the urban ecological status using GIS and remote sensing from 2000 to 2021: a case study of Herat City, Afghanistan.

Environmental monitoring and assessment, 196(12):1246.

Urbanization often incurs environmental costs, as fertile agricultural and forested lands are converted into urban areas. Herat City is currently undergoing significant urban transformation. This research aims to assess the impact of urban sprawl on Herat City's urban ecological status during 2000, 2013, and 2021, using GIS and remote sensing. The urban expansion intensity index was used to measure urban sprawl. The Mean Remote Sensing Ecological Index (MRSEI), integrating known granulation entropy (KGE) and comprehensive distance-based ranking (COBRA) algorithms, was utilized to evaluate urban ecological status. The random forest (RF) supervised machine learning-based algorithm was used to classify the study area into four categories (Built-up, Bare-land, Water, and Vegetation). Findings indicate rapid development from 2000 to 2013, followed by moderate expansion until 2021. Urban ecological quality degradation is observed in various directions over time, with the southeast consistently demonstrating excellent status. Interestingly, while good and excellent urban ecological status decreases over two decades, poor and very poor conditions improve. The research underscores an inverse relationship between urban expansion intensity and ecological status, highlighting the need for improved strategies to mitigate environmental decline. These findings will inform Afghan governmental bodies and international organizations, enabling them to better address resource consumption, ecological disruptions, social inequalities, and foster sustainable development.

RevDate: 2024-11-25

Hakkenberg CR, Clark ML, Bailey T, et al (2024)

Ladder fuels rather than canopy volumes consistently predict wildfire severity even in extreme topographic-weather conditions.

Communications earth & environment, 5(1):721.

Drivers of forest wildfire severity include fuels, topography and weather. However, because only fuels can be actively managed, quantifying their effects on severity has become an urgent research priority. Here we employed GEDI spaceborne lidar to consistently assess how pre-fire forest fuel structure affected wildfire severity across 42 California wildfires between 2019-2021. Using a spatial-hierarchical modeling framework, we found a positive concave-down relationship between GEDI-derived fuel structure and wildfire severity, marked by increasing severity with greater fuel loads until a decline in severity in the tallest and most voluminous forest canopies. Critically, indicators of canopy fuel volumes (like biomass and height) became decoupled from severity patterns in extreme topographic and weather conditions (slopes >20°; winds > 9.3 m/s). On the other hand, vertical continuity metrics like layering and ladder fuels more consistently predicted severity in extreme conditions - especially ladder fuels, where sparse understories were uniformly associated with lower severity levels. These results confirm that GEDI-derived fuel estimates can overcome limitations of optical imagery and airborne lidar for quantifying the interactive drivers of wildfire severity. Furthermore, these findings have direct implications for designing treatment interventions that target ladder fuels versus entire canopies and for delineating wildfire risk across topographic and weather conditions.

RevDate: 2024-11-25
CmpDate: 2024-11-23

Li J, Weckwerth W, S Waldherr (2024)

Network structure and fluctuation data improve inference of metabolic interaction strengths with the inverse Jacobian.

NPJ systems biology and applications, 10(1):137.

Based on high-throughput metabolomics data, the recently introduced inverse differential Jacobian algorithm can infer regulatory factors and molecular causality within metabolic networks close to steady-state. However, these studies assumed perturbations acting independently on each metabolite, corresponding to metabolic system fluctuations. In contrast, emerging evidence puts forward internal network fluctuations, particularly from gene expression fluctuations, leading to correlated perturbations on metabolites. Here, we propose a novel approach that exploits these correlations to quantify relevant metabolic interactions. By integrating enzyme-related fluctuations in the construction of an appropriate fluctuation matrix, we are able to exploit the underlying reaction network structure for the inverse Jacobian algorithm. We applied this approach to a model-based artificial dataset for validation, and to an experimental breast cancer dataset with two different cell lines. By highlighting metabolic interactions with significantly changed interaction strengths, the inverse Jacobian approach identified critical dynamic regulation points which are confirming previous breast cancer studies.

RevDate: 2024-11-25
CmpDate: 2024-11-25

Zhao Y, Cordero OX, M Tikhonov (2024)

Linear-regression-based algorithms can succeed at identifying microbial functional groups despite the nonlinearity of ecological function.

PLoS computational biology, 20(11):e1012590 pii:PCOMPBIOL-D-24-00586.

Microbial communities play key roles across diverse environments. Predicting their function and dynamics is a key goal of microbial ecology, but detailed microscopic descriptions of these systems can be prohibitively complex. One approach to deal with this complexity is to resort to coarser representations. Several approaches have sought to identify useful groupings of microbial species in a data-driven way. Of these, recent work has claimed some empirical success at de novo discovery of coarse representations predictive of a given function using methods as simple as a linear regression, against multiple groups of species or even a single such group (the ensemble quotient optimization (EQO) approach). Modeling community function as a linear combination of individual species' contributions appears simplistic. However, the task of identifying a predictive coarsening of an ecosystem is distinct from the task of predicting the function well, and it is conceivable that the former could be accomplished by a simpler methodology than the latter. Here, we use the resource competition framework to design a model where the "correct" grouping to be discovered is well-defined, and use synthetic data to evaluate and compare three regression-based methods, namely, two proposed previously and one we introduce. We find that regression-based methods can recover the groupings even when the function is manifestly nonlinear; that multi-group methods offer an advantage over a single-group EQO; and crucially, that simpler (linear) methods can outperform more complex ones.

RevDate: 2024-11-25
CmpDate: 2024-11-25

Behera BP, Naik H, VB Konkimalla (2024)

Peptaloid: A Comprehensive Database for Exploring Peptide Alkaloid.

Journal of chemical information and modeling, 64(22):8387-8395.

Peptaloid is the first dedicated database for peptide alkaloid molecules, a unique class of naturally derived compounds known for their structural diversity and significant biological activities. Despite their promising potential in drug discovery and therapeutic development, research on peptide alkaloids has been limited by the absence of a comprehensive and centralized resource. Fragmented data across various sources have posed a significant challenge, underscoring the need for a specialized database to facilitate more efficient research and application. Peptaloid addresses this critical gap by providing a database with over 161,000 peptide alkaloid entries, each detailed with structural, physicochemical, and pharmacological properties. By leveraging advanced computational tools and machine learning, Peptaloid generates ADMET profiles, aiding in identifying and optimizing therapeutic candidates. Designed for versatility, the database supports various applications beyond drug discovery, including ecology and material sciences. Peptaloid (as a specialized database for peptide alkaloids) will play a crucial role in innovation and collaboration across scientific disciplines. Peptaloid is accessible at https://peptaloid.niser.ac.in.

RevDate: 2024-11-23
CmpDate: 2024-11-23

Ang'ang'o LM, Herren JK, Ö Tastan Bishop (2024)

Bioinformatics analysis of the Microsporidia sp. MB genome: a malaria transmission-blocking symbiont of the Anopheles arabiensis mosquito.

BMC genomics, 25(1):1132.

BACKGROUND: The use of microsporidia as a disease-transmission-blocking tool has garnered significant attention. Microsporidia sp. MB, known for its ability to block malaria development in mosquitoes, is an optimal candidate for supplementing malaria vector control methods. This symbiont, found in Anopheles mosquitoes, can be transmitted both vertically and horizontally with minimal effects on its mosquito host. Its genome, recently sequenced from An. arabiensis, comprises a compact 5.9 Mbp.

RESULTS: Here, we analyze the Microsporidia sp. MB genome, highlighting its major genomic features, gene content, and protein function. The genome contains 2247 genes, predominantly encoding enzymes. Unlike other members of the Enterocytozoonida group, Microsporidia sp. MB has retained most of the genes in the glycolytic pathway. Genes involved in RNA interference (RNAi) were also identified, suggesting a mechanism for host immune suppression. Importantly, meiosis-related genes (MRG) were detected, indicating potential for sexual reproduction in this organism. Comparative analyses revealed similarities with its closest relative, Vittaforma corneae, despite key differences in host interactions.

CONCLUSION: This study provides an in-depth analysis of the newly sequenced Microsporidia sp. MB genome, uncovering its unique adaptations for intracellular parasitism, including retention of essential metabolic pathways and RNAi machinery. The identification of MRGs suggests the possibility of sexual reproduction, offering insights into the symbiont's evolutionary strategies. Establishing a reference genome for Microsporidia sp. MB sets the foundation for future studies on its role in malaria transmission dynamics and host-parasite interactions.

RevDate: 2024-11-23
CmpDate: 2024-11-21

Cuesta-Aguirre DR, Malgosa A, C Santos (2024)

An easy-to-use pipeline to analyze amplicon-based Next Generation Sequencing results of human mitochondrial DNA from degraded samples.

PloS one, 19(11):e0311115.

Genome and transcriptome examinations have become more common due to Next-Generation Sequencing (NGS), which significantly increases throughput and depth coverage while reducing costs and time. Mitochondrial DNA (mtDNA) is often the marker of choice in degraded samples from archaeological and forensic contexts, as its higher number of copies can improve the success of the experiment. Among other sequencing strategies, amplicon-based NGS techniques are currently being used to obtain enough data to be analyzed. There are some pipelines designed for the analysis of ancient mtDNA samples and others for the analysis of amplicon data. However, these pipelines pose a challenge for non-expert users and cannot often address both ancient and forensic DNA particularities and amplicon-based sequencing simultaneously. To overcome these challenges, a user-friendly bioinformatic tool was developed to analyze the non-coding region of human mtDNA from degraded samples recovered in archaeological and forensic contexts. The tool can be easily modified to fit the specifications of other amplicon-based NGS experiments. A comparative analysis between two tools, MarkDuplicates from Picard and dedup parameter from fastp, both designed for duplicate removal was conducted. Additionally, various thresholds of PMDtools, a specialized tool designed for extracting reads affected by post-mortem damage, were used. Finally, the depth coverage of each amplicon was correlated with its level of damage. The results obtained indicated that, for removing duplicates, dedup is a better tool since retains more non-repeated reads, that are removed by MarkDuplicates. On the other hand, a PMDS = 1 in PMDtools was the threshold that allowed better differentiation between present-day and ancient samples, in terms of damage, without losing too many reads in the process. These two bioinformatic tools were added to a pipeline designed to obtain both haplotype and haplogroup of mtDNA. Furthermore, the pipeline presented in the present study generates information about the quality and possible contamination of the sample. This pipeline is designed to automatize mtDNA analysis, however, particularly for ancient samples, some manual analyses may be required to fully validate results since the amplicons that used to be more easily recovered were the ones that had fewer reads with damage, indicating that special care must be taken for poor recovered samples.

RevDate: 2024-11-22
CmpDate: 2024-11-22

Zhu J, Li Z, Yang J, et al (2024)

Ecological space management and control zoning of Giant Panda National Park from the perspective of ecosystem services and land use.

Scientific reports, 14(1):19951.

Since China proposed building a national park system in 2017, the establishment of a planning system for nature reserves, with national parks as the main body, is being actively promoted around the country. Among them, scientific ecological space management and control zoning (ESMCZ) is an important link in maintaining the ecological stability of national parks. How to zone national parks and how to improve the precision of zoning has become a new task for national parks. Therefore, this study takes the Giant Panda National Park as the study area, takes ecosystem services and land use/cover change as the research perspective, integrates the InVEST model, PLUS model and bayes belief network (BBN) model, and builds a set of ecological space management and control zoning (ESMCZ) spatial zoning framework based on raster scale, dividing the study area into strictly protected zone, ecological buffer zone, ecological control zone and controlled development zone. The results showed that: (1) The study area showed an increasing trend in water conservation, soil conservation and carbon storage from 2005 to 2020, and the habitat quality index was generally high. The spatial heterogeneity of ecosystem services in the study area was significant, and the effect of a single factor on ecosystem services was most pronounced. (2) Large variation in area for different land uses under natural development scenarios and ecological protection scenarios. In both scenarios, the area of cultivated land, the area of grassland and the area of unused land decrease relative to 2020, and the area of forested land, the area of water and the area of constructed land increase relative to 2020. (3) The Giant Panda National Park is divided into strictly protected zone, ecological buffer zone, ecological control zone and control development zone, of which the strictly protected zone have the largest area and the best ecosystem background condition, and the control development zone have the smallest area and the worst ecosystem background condition. (4) The ecological space management and control zoning (ESMCZ) framework provides a more refined method for the secondary zoning of nature reserves such as the Giant Panda National Park, which is valuable for the implementation of zoning and categorization management for ecological conservation in the Giant Panda National Park.

RevDate: 2024-11-21

Sung ML, León C, Reisman JI, et al (2024)

Disparities in Receipt of Medications for Opioid Use Disorder Before and During the COVID-19 Pandemic in the US Veterans Health Administration.

Substance use & addiction journal [Epub ahead of print].

BACKGROUND: Populations disproportionately impacted by the opioid epidemic are less likely to receive medications for opioid use disorder (MOUD; OUD). The COVID-19 pandemic exacerbated these disparities. We performed an ecological survey of subpopulations to compare differences in MOUD receipt among Veterans with OUD before versus during the pandemic.

METHODS: Using 2 cross-sections of 2 time periods of national Veterans Health Administration electronic health record data, we calculated proportions of Veterans with any MOUD receipt by demographics, Elixhauser comorbidity index, and natural language processing (NLP)-derived substance use and social determinants of health in each time period. We evaluated differences in MOUD receipt before and during the pandemic by patient characteristics using Chi-square and Cohen's h for effect size.

RESULTS: Among 62 195 patients with OUD before the pandemic, the proportion prescribed MOUD increased from 46.5% before to 47.5% (P = .0003) during the pandemic. Statistically significant increased receipt of MOUD was observed for patients who were ≥55 years, men, White, with Elixhauser comorbidity indices of 2 and ≥5, and with NLP-derived indicators of substance use. There was a decrease that did not achieve statistical significance in MOUD receipt from before to during the pandemic for patients who were women, Black, Latinx, and food insecure.

CONCLUSIONS: The proportions of patients with OUD prescribed MOUD increased from before to during the pandemic. However, Veterans who were women, Black, Latinx, and food insecure did not experience these increases. These patients may benefit from interventions such as targeted outreach efforts to improve MOUD engagement to reduce OUD harms.

RevDate: 2024-11-21

Yu Y, Edelson M, Pham A, et al (2024)

Distributed, immutable, and transparent biomedical limited data set request management on multi-capacity network.

Journal of the American Medical Informatics Association : JAMIA pii:7906102 [Epub ahead of print].

OBJECTIVE: Our study aimed to expedite data sharing requests of Limited Data Sets (LDS) through the development of a streamlined platform that allows distributed, immutable management of network activities, provides transparent and intuitive auditing of data access history, and systematically evaluated it on a multi-capacity network setting for meaningful efficiency metrics.

MATERIALS AND METHODS: We developed a blockchain-based system with six types of smart contracts to automate the LDS sharing process among major stakeholders. Our workflow included metadata initialization, access-request processing, and audit-log querying. We evaluated our system using synthetic data on three machines with varying specifications to emulate real-world scenarios. The data employed included ∼1000 researcher requests and ∼360 000 log queries.

RESULTS: On average, it took ∼2.5 s to register and respond to a researcher access request. The average runtime for an audit-log query with non-empty output was ∼3 ms. The runtime metrics at each institution showed general trends affiliated with their computational capacity.

DISCUSSION: Our system can reduce the LDS sharing request time from potentially hours to seconds, while enhancing data access transparency in a multi-institutional setting. There were variations in performance across sites that could be attributed to differences in hardware specifications. The performance gains became marginal beyond certain hardware thresholds, pointing to the influence of external factors such as network speeds.

CONCLUSION: Our blockchain-based system can potentially accelerate clinical research by strengthening the data access process, expediting access and delivery of data links, increasing transparency with clear audit trails, and reinforcing trust in medical data management. Our smart contracts are available at: https://github.com/graceyufei/LDS-Request-Management.

RevDate: 2024-11-21

Boyes D, Hutchinson F, Crowley LM, et al (2024)

The genome sequence of the Silver-barred Sober moth, Aproaerema taeniolella (Zeller, 1839).

Wellcome open research, 9:500.

We present a genome assembly of a female Silver-barred Sober moth Aproaerema taeniolella (Arthropoda; Insecta; Lepidoptera; Gelechiidae). The genome sequence has a length of 636.60 megabases. Most of the assembly is scaffolded into 31 chromosomal pseudomolecules, including the Z sex chromosome. The mitochondrial genome has also been assembled and is 15.19 kilobases in length. Gene annotation of this assembly on Ensembl identified 22,274 protein-coding genes.

RevDate: 2024-11-21

Zhang Y, Wang M, Huang M, et al (2024)

Innovative strategies and challenges mosquito-borne disease control amidst climate change.

Frontiers in microbiology, 15:1488106.

The revival of the transmission dynamics of mosquito-borne diseases grants striking challenges to public health intensified by climate change worldwide. This inclusive review article examines multidimensional strategies and challenges linked to climate change and the epidemiology of mosquito-borne diseases such as malaria, dengue, Zika, chikungunya, and yellow fever. It delves into how the biology, pathogenic dynamics, and vector distribution of mosquitoes are influenced by continuously rising temperatures, modified rainfall patterns, and extreme climatic conditions. We also highlighted the high likelihood of malaria in Africa, dengue in Southeast Asia, and blowout of Aedes in North America and Europe. Modern predictive tools and developments in surveillance, including molecular gears, Geographic Information Systems (GIS), and remote sensing have boosted our capacity to predict epidemics. Integrated data management techniques and models based on climatic conditions provide a valuable understanding of public health planning. Based on recent data and expert ideas, the objective of this review is to provide a thoughtful understanding of existing landscape and upcoming directions in the control of mosquito-borne diseases regarding changing climate. This review determines emerging challenges and innovative vector control strategies in the changing climatic conditions to ensure public health.

RevDate: 2024-11-21
CmpDate: 2024-11-21

Liu S, Gates KM, E Ferrer (2024)

Homogeneity Assumptions in the Analysis of Dynamic Processes.

Multivariate behavioral research, 59(6):1166-1176.

With the increased use of time series data in human research, ranging from ecological momentary assessments to data passively obtained, researchers can explore dynamic processes more than ever before. An important question researchers must ask themselves is, do I think all individuals have similar processes? If not, how different, and in what ways? Dr. Peter Molenaar's work set the foundation to answer these questions by providing insight into individual-level analysis for processes that are assumed to differ across individuals in at least some aspects. Currently, such assumptions do not have a clear taxonomy regarding the degree of homogeneity in the patterns of relations among variables and the corresponding parameter values. This paper provides the language with which researchers can discuss assumptions inherent in their analyses. We define strict homogeneity as the assumption that all individuals have an identical pattern of relations as well as parameter values; pattern homogeneity assumes the same pattern of relations but parameter values can differ; weak homogeneity assumes there are some (but not all) generalizable aspects of the process; and no homogeneity explicitly assumes no population-level similarities in dynamic processes across individuals. We demonstrate these assumptions with an empirical data set of daily emotions in couples.

RevDate: 2024-11-20

Sivell O, Hawkes WLS, Natural History Museum Genome Acquisition Lab, et al (2024)

The genome sequence of the silvery leafcutter bee, Megachile leachella Curtis, 1828.

Wellcome open research, 9:415.

We present a genome assembly from an individual female Megachile leachella (the silvery leafcutter bee; Arthropoda; Insecta; Hymenoptera; Megachilidae). The genome sequence is 573.0 megabases in span. Most of the assembly is scaffolded into 16 chromosomal pseudomolecules. The mitochondrial genome has also been assembled and is 21.04 kilobases in length.

RevDate: 2024-11-20
CmpDate: 2024-11-20

Toth AL, Wyatt CDR, Masonbrink RE, et al (2024)

New genomic resources inform transcriptomic responses to heavy metal toxins in the common Eastern bumble bee Bombus impatiens.

BMC genomics, 25(1):1106.

BACKGROUND: The common Eastern bumble bee Bombus impatiens is native to North America and is the main commercially reared pollinator in the Americas. There has been extensive research on this species related to its social biology, applied pollination, and genetics. The genome of this species was previously sequenced using short-read technology, but recent technological advances provide an opportunity for substantial improvements. This species is common in agricultural and urban environments, and heavy metal contaminants produced by industrial processes can negatively impact it. To begin to identify possible mechanisms underlying responses to these toxins, we used RNA-sequencing to examine how exposure to a cocktail of four heavy metals at field-realistic levels from industrial areas affected B. impatiens worker gene expression.

RESULTS: PacBio long-read sequencing resulted in 544x coverage of the genome, and HiC technology was used to map chromatin contacts. Using Juicer and manual curation, the genome was scaffolded into 18 main pseudomolecules, representing a high quality, chromosome-level assembly. The sequenced genome size is 266.6 Mb and BRAKER3 annotation produced 13,938 annotated genes. The genome and annotation show high completeness, with ≥ 96% of conserved Eukaryota and Hymenoptera genes present in both the assembly and annotated genes. RNA sequencing of heavy metal exposed workers revealed 603 brain and 34 fat body differentially expressed genes. In the brain, differentially expressed genes had biological functions related to chaperone activity and protein folding.

CONCLUSIONS: Our data represent a large improvement in genomic resources for this important model species-with 10% more genome coverage than previously available, and a high-quality assembly into 18 chromosomes, the expected karyotype for this species. The new gene annotation added 777 new genes. Altered gene expression in response to heavy metal exposure suggests a possible mechanism for how these urban toxins are negatively impacting bee health, specifically by altering protein folding in the brain. Overall, these data are useful as a general high quality genomic resource for this species, and provide insight into mechanisms underlying tissue-specific toxicological responses of bumble bees to heavy metals.

RevDate: 2024-11-18
CmpDate: 2024-11-18

Helgeson SA, Mudgalkar RM, Jacobs KA, et al (2024)

Association Between X/Twitter and Prescribing Behavior During the COVID-19 Pandemic: Retrospective Ecological Study.

JMIR infodemiology, 4:e56675 pii:v4i1e56675.

BACKGROUND: Social media has become a vital tool for health care providers to quickly share information. However, its lack of content curation and expertise poses risks of misinformation and premature dissemination of unvalidated data, potentially leading to widespread harmful effects due to the rapid and large-scale spread of incorrect information.

OBJECTIVE: We aim to determine whether social media had an undue association with the prescribing behavior of hydroxychloroquine, using the COVID-19 pandemic as the setting.

METHODS: In this retrospective study, we gathered the use of hydroxychloroquine in 48 hospitals in the United States between January and December 2020. Social media data from X/Twitter was collected using Brandwatch, a commercial aggregator with access to X/Twitter's data, and focused on mentions of "hydroxychloroquine" and "Plaquenil." Tweets were categorized by sentiment (positive, negative, or neutral) using Brandwatch's sentiment analysis tool, with results classified by date. Hydroxychloroquine prescription data from the National COVID Cohort Collaborative for 2020 was used. Granger causality and linear regression models were used to examine relationships between X/Twitter mentions and prescription trends, using optimum time lags determined via vector auto-regression.

RESULTS: A total of 581,748 patients with confirmed COVID-19 were identified. The median daily number of positive COVID-19 cases was 1318.5 (IQR 1005.75-1940.3). Before the first confirmed COVID-19 case, hydroxychloroquine was prescribed at a median rate of 559 (IQR 339.25-728.25) new prescriptions per day. A day-of-the-week effect was noted in both prescriptions and case counts. During the pandemic in 2020, hydroxychloroquine prescriptions increased significantly, with a median of 685.5 (IQR 459.75-897.25) per day, representing a 22.6% rise from baseline. The peak occurred on April 2, 2020, with 3411 prescriptions, a 397.6% increase. Hydroxychloroquine mentions on X/Twitter peaked at 254,770 per day on April 5, 2020, compared to a baseline of 9124 mentions per day before January 21, 2020. During this study's period, 3,823,595 total tweets were recorded, with 10.09% (n=386,115) positive, 37.87% (n=1,448,030) negative, and 52.03% (n=1,989,450) neutral sentiments. A 1-day lag was identified as the optimal time for causal association between tweets and hydroxychloroquine prescriptions. Univariate analysis showed significant associations across all sentiment types, with the largest impact from positive tweets. Multivariate analysis revealed only neutral and negative tweets significantly affected next-day prescription rates.

CONCLUSIONS: During the first year of the COVID-19 pandemic, there was a significant association between X/Twitter mentions and the number of prescriptions of hydroxychloroquine. This study showed that X/Twitter has an association with the prescribing behavior of hydroxychloroquine. Clinicians need to be vigilant about their potential unconscious exposure to social media as a source of medical knowledge, and health systems and organizations need to be more diligent in identifying expertise, source, and quality of evidence when shared on social media platforms.

RevDate: 2024-11-20
CmpDate: 2024-11-20

Smith SJ, Cummins SF, Motti CA, et al (2024)

A mass spectrometry database for the identification of marine animal saponin-related metabolites.

Analytical and bioanalytical chemistry, 416(29):6893-6907.

Saponins encompass a diverse group of naturally occurring glycoside molecules exhibiting amphiphilic properties and a broad range of biological activities. There is a resurgence of interest in those saponins produced by marine organisms based on their potential therapeutic benefits, application in food products and most recently their potential involvement in intra- and inter-species chemical communication. The continual advancements in liquid chromatography techniques and mass spectrometry technologies have allowed for greater detection rates, as well as improved isolation and elucidation of saponins. These factors have significantly contributed to the expansion in the catalogue of known saponin structures isolated from marine invertebrates; however, there currently exists no specific chemical library resource to accelerate the discovery process. In this study, a Marine Animal Saponin Database (MASD v1.0) has been developed to serve as a valuable chemical repository for known marine saponin-related data, including chemical formula, molecular mass and biological origin of nearly 1000 secondary metabolites associated with saponins produced by marine invertebrates. We demonstrate its application with an exemplar asteroid extract (Acanthaster cf. solaris, also known as crown-of-thorns starfish; COTS), identifying saponins from the MASD v1.0 that have been previously reported from COTS, as well as 21 saponins isolated from multiple other related asteroid species. This database will help facilitate future research endeavours, aiding researchers in exploring the vast chemical diversity of saponins produced by marine organisms and providing ecological insights, and the realisation of their potential for various applications, including as pharmaceuticals.

RevDate: 2024-11-19
CmpDate: 2024-11-19

Wang Y, Sun Y, Huang K, et al (2024)

Multi-omics analysis reveals the core microbiome and biomarker for nutrition degradation in alfalfa silage fermentation.

mSystems, 9(11):e0068224.

UNLABELLED: Alfalfa (Medicago sativa L.) is one of the most extensively cultivated forage crops globally, and its nutritional quality critically influences the productivity of dairy cows. Silage fermentation is recognized as a crucial technique for the preservation of fresh forage, ensuring the retention of its vital nutrients. However, the detailed microbial components and their functions in silage fermentation are not fully understood. This study integrated large-scale microbial culturing with high-throughput sequencing to thoroughly examine the microbial community structure in alfalfa silage and explored the potential pathways of nutritional degradation via metagenomic analysis. The findings revealed an enriched microbial diversity in silage, indicated by the identification of amplicon sequence variants. Significantly, the large-scale culturing approach recovered a considerable number of unique microbes undetectable by high-throughput sequencing. Predominant genera, such as Lactiplantibacillus, Leuconostoc, Lentilactobacillus, Weissella, and Liquorilactobacillus, were identified based on their abundance and prevalence. Additionally, genes associated with Enterobacteriaceae were discovered, which might be involved in pathways leading to the production of ammonia-N and butyric acid. Overall, this study offers a comprehensive insight into the microbial ecology of silage fermentation and provides valuable information for leveraging microbial consortia to enhance fermentation quality.

IMPORTANCE: Silage fermentation is a microbial-driven anaerobic process that efficiently converts various substrates into nutrients readily absorbable and metabolizable by ruminant animals. This study, integrating culturomics and metagenomics, has successfully identified core microorganisms involved in silage fermentation, including those at low abundance. This discovery is crucial for the targeted cultivation of specific microorganisms to optimize fermentation processes. Furthermore, our research has uncovered signature microorganisms that play pivotal roles in nutrient metabolism, significantly advancing our understanding of the intricate relationships between microbial communities and nutrient degradation during silage fermentation.

RevDate: 2024-11-18

Yang D, Hashizume M, Tobías A, et al (2024)

Temporal change in minimum mortality temperature under changing climate: A multicountry multicommunity observational study spanning 1986-2015.

Environmental epidemiology (Philadelphia, Pa.), 8(5):e334.

BACKGROUND: The minimum mortality temperature (MMT) or MMT percentile (MMTP) is an indicator of population susceptibility to nonoptimum temperatures. MMT and MMTP change over time; however, the changing directions show region-wide heterogeneity. We examined the heterogeneity of temporal changes in MMT and MMTP across multiple communities and in multiple countries.

METHODS: Daily time-series data for mortality and ambient mean temperature for 699 communities in 34 countries spanning 1986-2015 were analyzed using a two-stage meta-analysis. First, a quasi-Poisson regression was employed to estimate MMT and MMTP for each community during the designated subperiods. Second, we pooled the community-specific temporally varying estimates using mixed-effects meta-regressions to examine temporal changes in MMT and MMTP in the entire study population, as well as by climate zone, geographical region, and country.

RESULTS: Temporal increases in MMT and MMTP from 19.5 °C (17.9, 21.1) to 20.3 °C (18.5, 22.0) and from the 74.5 (68.3, 80.6) to 75.0 (71.0, 78.9) percentiles in the entire population were found, respectively. Temporal change was significantly heterogeneous across geographical regions (P < 0.001). Temporal increases in MMT were observed in East Asia (linear slope [LS] = 0.91, P = 0.02) and South-East Asia (LS = 0.62, P = 0.05), whereas a temporal decrease in MMT was observed in South Europe (LS = -0.46, P = 0.05). MMTP decreased temporally in North Europe (LS = -3.45, P = 0.02) and South Europe (LS = -2.86, P = 0.05).

CONCLUSIONS: The temporal change in MMT or MMTP was largely heterogeneous. Population susceptibility in terms of optimum temperature may have changed under a warming climate, albeit with large region-dependent variations.

RevDate: 2024-11-16

Rayamajhi N, Rivera-Colón AG, Minhas BF, et al (2024)

The genome of the cryopelagic Antarctic bald notothen, Trematomus borchgrevinki.

G3 (Bethesda, Md.) pii:7902048 [Epub ahead of print].

The Antarctic bald notothen, Trematomus borchgrevinki (family Nototheniidae) occupies a high latitude, ice-laden environment and represents an extreme example of cold-specialization among fishes. We present the first, high quality, chromosome-scale genome of a female T. borchgrevinki individual comprised of 23 putative chromosomes, the largest of which is 65 megabasepairs (Mbp) in length. The total length of the genome 935.13 Mbp, composed of 2,094 scaffolds, with a scaffold N50 of 42.67 Mbp. Annotation yielded 22,192 protein coding genes while 54.75% of the genome was occupied by repetitive elements; an analysis of repeats demonstrated that an expansion occurred in recent time. Conserved synteny analysis revealed that the genome architecture of T. borchgrevinki is largely maintained with other members of the notothenioid clade, although several significant translocations and inversions are present, including the fusion of orthologous chromosomes 8 and 11 into a single element. This genome will serve as a cold-specialized model for comparisons to other members of the notothenioid adaptive radiation.

RevDate: 2024-11-18
CmpDate: 2024-11-18

Amaral AS, DP Devos (2024)

The neglected giants: Uncovering the prevalence and functional groups of huge proteins in proteomes.

PLoS computational biology, 20(9):e1012459 pii:PCOMPBIOL-D-23-01891.

An often-overlooked aspect of biology is formed by the outliers of the protein length distribution, specifically those proteins with more than 5000 amino acids, which we refer to as huge proteins (HPs). By examining UniprotKB, we discovered more than 41 000 HPs throughout the tree of life, with the majority found in eukaryotes. Notably, the phyla with the highest propensity for HPs are Apicomplexa and Fornicata. Moreover, we observed that certain bacteria, such as Elusimicrobiota or Planctomycetota, have a higher tendency for encoding HPs, even more than the average eukaryote. To investigate if these macro-polypeptides represent "real" proteins, we explored several indirect metrics. Additionally, orthology analyses reveals thousands of clusters of homologous sequences of HPs, revealing functional groups related to key cellular processes such as cytoskeleton organization and functioning as chaperones or as E3-ubiquitin ligases in eukaryotes. In the case of bacteria, the major clusters have functions related to non-ribosomomal peptide synthesis/polyketide synthesis, followed by pathogen-host attachment or recognition surface proteins. Further exploration of the annotations for each HPs supported the previously identified functional groups. These findings underscore the need for further investigation of the cellular and ecological roles of these HPs and their potential impact on biology and biotechnology.

RevDate: 2024-11-16
CmpDate: 2024-11-16

Chen Y, Gao Y, Zhang Z, et al (2024)

Multi-Omics Inform Invasion Risks Under Global Climate Change.

Global change biology, 30(11):e17588.

Global climate change is exacerbating biological invasions; however, the roles of genomic and epigenomic variations and their interactions in future climate adaptation remain underexplored. Using the model invasive ascidian Botryllus schlosseri across the Northern Hemisphere, we investigated genomic and epigenomic responses to future climates and developed a framework to assess future invasion risks. We employed generalized dissimilarity modeling and gradient forest analyses to assess genomic and epigenomic offsets under climate change. Our results showed that populations with genomic maladaptation did not geographically overlap with those experiencing epigenomic maladaptation, suggesting that genomic and epigenomic variations play complementary roles in adaptation to future climate conditions. By integrating genomic and epigenomic offsets into the genome-epigenomic index, we predicted that populations with lower index values were less maladapted, indicating a higher risk of future invasions. Native populations exhibited lower offsets than invasive populations, suggesting greater adaptive potentials and higher invasion risks under future climate change scenarios. These results highlight the importance of incorporating multi-omics data into predictive models to study future climate (mal)adaptation and assess invasion risks under global climate change.

RevDate: 2024-11-15
CmpDate: 2024-11-16

Conrad RE, Brink CE, Viver T, et al (2024)

Microbial species and intraspecies units exist and are maintained by ecological cohesiveness coupled to high homologous recombination.

Nature communications, 15(1):9906.

Recent genomic analyses have revealed that microbial communities are predominantly composed of persistent, sequence-discrete species and intraspecies units (genomovars), but the mechanisms that create and maintain these units remain unclear. By analyzing closely-related isolate genomes from the same or related samples and identifying recent recombination events using a novel bioinformatics methodology, we show that high ecological cohesiveness coupled to frequent-enough and unbiased (i.e., not selection-driven) horizontal gene flow, mediated by homologous recombination, often underlie these diversity patterns. Ecological cohesiveness was inferred based on greater similarity in temporal abundance patterns of genomes of the same vs. different units, and recombination was shown to affect all sizable segments of the genome (i.e., be genome-wide) and have two times or greater impact on sequence evolution than point mutations. These results were observed in both Salinibacter ruber, an environmental halophilic organism, and Escherichia coli, the model gut-associated organism and an opportunistic pathogen, indicating that they may be more broadly applicable to the microbial world. Therefore, our results represent a departure compared to previous models of microbial speciation that invoke either ecology or recombination, but not necessarily their synergistic effect, and answer an important question for microbiology: what a species and a subspecies are.

RevDate: 2024-11-15

Kwon EJ, Lee H, Shin U, et al (2024)

Ionizing radiation inhibits zebrafish embryo hatching through induction of tissue inhibitors of metalloproteinases (TIMPs) expression.

The FEBS journal [Epub ahead of print].

Ionizing radiation (IR) has garnered growing attention because of its biological effects on aquatic organisms and humans. Here, we identify the most impacted organs and uncover the molecular mechanisms causing the changes in the context of vertebrate development using single-cell RNA sequencing. Alterations in cellular composition and biological functions were explored using transcriptomic profiling of zebrafish embryos exposed to 5 Gy. Single-cell RNA sequencing analyses unveiled notable shifts in the proportions of brain/central nervous system and hatching gland clusters. Although IR exposure led to increased expression of hatching enzymes, a significant but mild delay in hatching was observed following 5 Gy IR exposure. Gene Ontology analysis showed an increased expression of tissue inhibitors of metalloproteinases (TIMPs), known as matrix metalloproteinase inhibitors, which was confirmed via whole-mount in situ hybridization. Correlation analysis linked TIMPs to transcription factors cebpb and cebpd, which were significantly correlated post-IR exposure. Although no morphological changes were observed in some organs, including the brain, the study reveals substantial alterations in developing vertebrates. Notably, despite increased hatching enzymes, elevated TIMPs in the hatching gland suggest a regulatory mechanism impacting hatching activity. This research contributes to comprehending the ecological repercussions of IR exposure, emphasizing the importance of safety measures for aquatic ecosystems and overall environmental health.

RevDate: 2024-11-15

Meyer A, Ndiaye B, Larkins A, et al (2024)

Economic assessment of animal disease burden in Senegalese small ruminants.

Preventive veterinary medicine, 234:106382 pii:S0167-5877(24)00268-X [Epub ahead of print].

Small ruminant production in sub-Saharan Africa is limited by a range of constraints, including animal health issues. This study aimed at estimating the impact of these issues on the small ruminant production in Senegal in a holistic manner, using an approach developed by the Global Burden of Animal Diseases (GBADs) programme. The estimation focused on the mixed crop-livestock system, representing a large proportion (>60 %) of the small ruminant population in the country. It was based on existing data collected via a systematic literature review, acquisition of secondary datasets from local stakeholders, and expert elicitation. A dynamic population model was used to calculate the gross margin of the sector under both the current health constraints and an ideal health state, where animals are not exposed to causes of morbidity and mortality. The difference between the current and ideal health scenarios, termed the Animal Health Loss Envelope (AHLE), provides a quantitative measure of the farm-level cost of disease in the system. The all-cause AHLE was estimated at 292 billion FCFA (468 million USD, with 95 % prediction interval 216 - 366 billion FCFA) per year for 2022, for a population of 8.8 million animals. The contribution of Peste des Petits Ruminants (PPR) was modelled separately, as an example of attributing part of the AHLE to a specific disease cause. PPR was estimated to contribute 5 % of the total AHLE. The animal disease burden experienced by Senegalese livestock keepers was largely due to loss in animals and production, with relatively small amounts of animal health expenditure. Implementation of this study contributed to the further development of the GBADs approach. Such estimates can support decision making at all levels, from investment decisions at the international level to local disease awareness campaigns targeting livestock keepers.

RevDate: 2024-11-16
CmpDate: 2024-11-15

Heuck MK, Powell JR, Kath J, et al (2024)

Evaluating the Usefulness of the C-S-R Framework for Understanding AM Fungal Responses to Climate Change in Agroecosystems.

Global change biology, 30(11):e17566.

Arbuscular mycorrhizal (AM) fungi play a key role in terrestrial ecosystems by forming symbiotic relationships with plants and may confer benefits for sustainable agriculture, by reducing reliance on harmful fertiliser and pesticide inputs and enhancing plant resilience against insect herbivores. Despite their ecological importance, critical gaps in understanding AM fungal ecology limit predictions of their responses to global change in agroecosystems. However, predicting climate change impacts on AM fungi is important for maintaining crop productivity and ecosystem stability. Efforts to classify AM fungi based on functional traits, such as the competitor, stress-tolerator, ruderal (C-S-R) framework, aim to address these gaps but face challenges due to the obligate symbiotic nature of the fungi. As the framework is still widely used, we evaluate its applicability in predicting global change impacts on AM fungal communities in agroecosystems. Chagnon's adaptation of the C-S-R framework for AM fungi aligns with some study outcomes (e.g., under the context of water limitation) but faces challenges when used in complex climate change scenarios, varying agricultural conditions and/or extreme climatic conditions. The reliance on a limited dataset to classify AM fungal families further limits accurate predictions of AM fungal community dynamics. Trait data collection could support a nuanced understanding of AM fungi and leveraging AM fungal databases could streamline data management and analysis, enhancing efforts to clarify AM fungal responses to environmental change and guide ecosystem management practices. Thus, while the C-S-R framework holds promise, it requires additional AM fungal trait data for validation and improvement of its predictive power. Conclusively, before designing experiments based on life-history strategies and developing new frameworks tailored to AM fungi a critical first step is to gain a comprehensive understanding of their traits.

RevDate: 2024-11-16
CmpDate: 2024-11-15

Rzehak T, Praeg N, Galla G, et al (2024)

Comparison of commonly used software pipelines for analyzing fungal metabarcoding data.

BMC genomics, 25(1):1085.

BACKGROUND: Metabarcoding targeting the internal transcribed spacer (ITS) region is commonly used to characterize fungal communities of various environments. Given their size and complexity, raw ITS sequences are necessarily processed and quality-filtered with bioinformatic pipelines. However, such pipelines are not yet standardized, especially for fungal communities, and those available may produce contrasting results. While some pipelines cluster sequences based on a specified percentage of base pair similarity into operational taxonomic units (OTUs), others utilize denoising techniques to infer amplicon sequencing variants (ASVs). While ASVs are now considered a more accurate representation of taxonomic diversity for prokaryote communities based on 16S rRNA amplicon sequencing, the applicability of this method for fungal ITS sequences is still debated.

RESULTS: Here we compared the performance of two commonly used pipelines DADA2 (inferring ASVs) and mothur (clustering OTUs) on fungal metabarcoding sequences originating from two different environmental sample types (fresh bovine feces and pasture soil). At a 99% OTU similarity threshold, mothur consistently identified a higher fungal richness compared to DADA2. In addition, mothur generated homogenous relative abundances across multiple technical replicates (n = 18), while DADA2 results for the same replicates were highly heterogeneous.

CONCLUSIONS: Our study highlights a potential pipeline-associated bias in fungal metabarcoding data analysis of environmental samples. Based on the homogeneity of relative abundances across replicates and the capacity to detect OTUs/ASVs, we suggest using OTU clustering with a similarity of 97% as the most appropriate option for processing fungal metabarcoding data.

RevDate: 2024-11-16
CmpDate: 2024-11-16

Ibrahim AS, Kuuire V, T Kepe (2024)

On mapping urban community resilience: Land use vulnerability, coping and adaptive strategies in Ghana.

Journal of environmental management, 370:122426.

Cities across the globe are prioritizing resilience in the wake of increasing climate change-related disasters. About 44% of these disasters are floods and their manifestation in cities is more pronounced, threatening urban social, ecological, and economic systems. This study draws on community resilience and participatory GIS, to examine land use vulnerability to flooding and local coping and adaptive strategies to achieve resilience. Using Ghana as a case study, the results show that participatory mapping offers community resilience benefits by providing context to community resilience challenges and potentials, enabling a deeper understanding of socio-environmental coupling that contributes to flood vulnerability and builds on community adaptive strategies through harnessing local community knowledge. We identified that topography, poor drainage and road network, rainfall variability, residents' land use practices, and land use planning conundrum drive disparities in land use vulnerability to flooding. Participants underscored the necessity of critical urban infrastructure in facilitating community adaptability to floods. The findings indicate that socio-spatial inequities threaten urban community resilience, especially in increasingly cosmopolitan urban contexts, by putting the marginalized urban population in a more vulnerable position. We recommend the prioritization of recognitional equity in community resilience planning efforts to allow for the targeting of resilient interventions that reflect and respect social differentiation in the urban environment so that outcomes will not exacerbate or generate new urban socio-spatial inequalities.

RevDate: 2024-11-15

Rajovic N, Grubor N, Cirkovic A, et al (2024)

Insights into relationship of environmental inequalities and multimorbidity: a population-based study.

Environmental health : a global access science source, 23(1):99.

BACKGROUND: Substantial inequalities in the overall prevalence and patterns of multimorbidity have been widely reported, but the causal mechanisms are complex and not well understood. This study aimed to identify common patterns of multimorbidity in Serbia and assess their relationship with air pollutant concentrations and water quality indicators.

METHODS: This ecological study was conducted on a nationally representative sample of the Serbian population. Data were obtained from the European Health Interview (EHIS) Survey, a periodic study designed to assess population health using widely recognized standardized instruments. The study included 13,069 participants aged 15 and older, randomly selected through a multistage stratified sampling design. Multimorbidity was defined as having two or more self-reported diagnoses of chronic non-communicable diseases. Latent class analysis (LCA) was performed to identify clusters of multimorbidity. Concentrations of particulate matter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3), as well as water quality indicators, were obtained from the Serbian Environmental Protection Agency.

RESULTS: The overall prevalence of multimorbidity was 33.4% [32.6%-34.2%]. Six latent classes of multimorbidity were identified: Healthy, Multicondition, Cardiovascular, Metabolic syndrome, Respiratory, and Musculoskeletal. Annual increases in PM10 and SO2 concentrations, as well as daily increases in O3 concentrations, significantly raised the odds of having multimorbidity (OR = 1.02, 95% CI 1.02-1.03; OR = 1.01, 95% CI 1.00-1.02 and OR = 1.03, 95% CI 1.02-1.03, respectively). A pattern of increased risk was observed with rising levels of water contamination. Exposure to physico-chemical, microbiological and combined contamination was associated with a 3.92%, 5.17% and 5.54% higher probability, respectively, of having multiple chronic conditions. There was strong evidence that air pollutants, as well as chemical and microbial water contamination, were significantly associated with higher odds of the most common clusters of multimorbidity identified by LCA.

CONCLUSION: There is compelling evidence of an association between multimorbidity and environmental pollution, suggesting that exposure to air pollutants and water contaminants may contribute to disease accumulation and help explain geographically and socioeconomically patterned inequalities. These findings underscore the need for extensive studies that simultaneously measure both multimorbidity and pollution to explore their complex interrelationships.

RevDate: 2024-11-14

Wang G, Li X, Deng J, et al (2024)

Assessing soil cadmium quality standards for different land use types: A global synthesis.

Journal of hazardous materials, 480:136450 pii:S0304-3894(24)03029-2 [Epub ahead of print].

The contamination of cadmium (Cd) in soil has become an increasingly serious issue worldwide, presenting significant risks to human health, crop safety, and ecosystems. Despite its importance, there is a lack of standardized soil threshold values for use in regulating exposure to Cd-contaminated surface soil. By synthesizing soil environmental standards for Cd from 61 countries and 75 regions, this study analyzed and categorized these standards by land use types. The distribution of Cd quality standards among various countries was determined, based on available data primarily from the United States, Canada, Europe, Australia, and China. The established soil Cd quality standards were also determined for different land types, including lands for agricultural, residential, industrial, construction, commercial uses, and parks/green spaces. Using the ecological environment criteria - species sensitivity distribution (ECC-SSD) model, Cd levels were analyzed across different land use types, and it was determined that a log-logistic distribution was the best fitted model. Our findings indicated that soil Cd quality standards ranged from 0.11 to 5.20 mg/kg for agricultural land, 1.25 to 171.51 mg/kg for residential land, and 2.58 to 1845.26 mg/kg for industrial land, all within the 5-95 % percentile range. The 5 % hazard concentration (HC5) value was recommended as the latest national quality standards for each land type. This comprehensive assessment of global soil Cd quality standards provides valuable insight for decision-makers tasked with effectively managing and mitigating Cd pollution in soil.

RevDate: 2024-11-14
CmpDate: 2024-11-14

Pappa T, Rivas AL, Iandiorio MJ, et al (2024)

Personalized, disease-stage specific, rapid identification of immunosuppression in sepsis.

Frontiers in immunology, 15:1430972.

INTRODUCTION: Data overlapping of different biological conditions prevents personalized medical decision-making. For example, when the neutrophil percentages of surviving septic patients overlap with those of non-survivors, no individualized assessment is possible. To ameliorate this problem, an immunological method was explored in the context of sepsis.

METHODS: Blood leukocyte counts and relative percentages as well as the serum concentration of several proteins were investigated with 4072 longitudinal samples collected from 331 hospitalized patients classified as septic (n=286), non-septic (n=43), or not assigned (n=2). Two methodological approaches were evaluated: (i) a reductionist alternative, which analyzed variables in isolation; and (ii) a non-reductionist version, which examined interactions among six (leukocyte-, bacterial-, temporal-, personalized-, population-, and outcome-related) dimensions.

RESULTS: The reductionist approach did not distinguish outcomes: the leukocyte and serum protein data of survivors and non-survivors overlapped. In contrast, the non-reductionist alternative differentiated several data groups, of which at least one was only composed of survivors (a finding observable since hospitalization day 1). Hence, the non-reductionist approach promoted personalized medical practices: every patient classified within a subset associated with 100% survival subset was likely to survive. The non-reductionist method also revealed five inflammatory or disease-related stages (provisionally named 'early inflammation, early immunocompetence, intermediary immuno-suppression, late immuno-suppression, or other'). Mortality data validated these labels: both 'suppression' subsets revealed 100% mortality, the 'immunocompetence' group exhibited 100% survival, while the remaining sets reported two-digit mortality percentages. While the 'intermediary' suppression expressed an impaired monocyte-related function, the 'late' suppression displayed renal-related dysfunctions, as indicated by high concentrations of urea and creatinine.

DISCUSSION: The data-driven differentiation of five data groups may foster early and non-overlapping biomedical decision-making, both upon admission and throughout their hospitalization. This approach could evaluate therapies, at personalized level, earlier. To ascertain repeatability and investigate the dynamics of the 'other' group, additional studies are recommended.

RevDate: 2024-11-13

Noria SF, Pratt KJ, Abdel-Rasoul M, et al (2024)

The impact of social determinants of health (SDOH) on completing bariatric surgery at a single academic institution.

Surgical endoscopy [Epub ahead of print].

BACKGROUND: Underutilization of bariatric surgery is multifactorial. This study aimed to understand the association of SDOH on not achieving surgery.

METHODS: 1081 applications for primary MBS from January-December 2021 were stratified into those that completed surgery (COM; n = 415), in progress > 1-year (IP; n = 107), dropped out (DO; n = 379), and never started (NS; n = 180). Using the American-Community-Survey results (2015-2020) and patient zip-codes, population differences in 4-domains of SDOH (demographic/social/housing/economic) were examined between COM versus the other groups. Additionally, using institutional MBSAQIP and EMR data, patient-specific differences in comorbidities were evaluated for COM versus IP/DO. Univariate analysis using Kruskal-Wallis, chi-squared/Fisher's exact tests were used for continuous and/or categorical variables. For patient-level analysis multinomial logistic regression was used to determine predictors of not achieving surgery. Hypothesis testing was conducted at an overall 5 percent type-I error rate (alpha = 0.05) and Bonferroni's method was used to adjust for multiple comparisons.

RESULTS: Compared to COM, IP-patients resided in zip-codes characterized by fewer married people (43% vs 46%; p = 0.019), lower education levels (49% vs 43%; p = 0.048), more households where rent was > 50% of household income (10% vs 8%, p = 0.002), and households below the poverty line (17.6% vs 14.5%, p = 0.017). At the patient-level, IP were more likely to be male (27.9% vs 14.9%; p = 0.014), publicly insured (44.9% vs 28.4%; p = 0.004), Black (35.5% vs 22.2%; p = 0.006), an active smoker (8.9% vs 2.2%; p = 0.018), have a higher BMI (49.6 vs 47.6; p = 0.01), and coronary intervention (5.8% vs 1.7%, p = 0.034). Comparison of COM vs DO was similar for both phases. Multinomial multivariable logistic regression demonstrated higher BMI (OR = 1.03,[CI]:1.01-1.05, p = 0.001), males (OR = 1.9,[CI]:1.09-3.32, p = 0.024), smoking (OR = 4.58,[CI]:1.74-12.02, p = 0.002), and Medicaid (OR = 2.16,[CI]:1.33-3.49, p = 0.002) independently predicted not achieving surgery.

CONCLUSION: Patient-level data demonstrated social not clinical factors predicted surgery completion. Given zip-codes characterizing the IP/DO groups had a greater prevalence of social risk, more attention needs to be directed patient-level social risks.

RevDate: 2024-11-13
CmpDate: 2024-11-13

Ki J, Lee JM, Lee W, et al (2024)

Dual-encoder architecture for metal artifact reduction for kV-cone-beam CT images in head and neck cancer radiotherapy.

Scientific reports, 14(1):27907.

During a radiotherapy (RT) course, geometrical variations of target volumes, organs at risk, weight changes (loss/gain), tumor regression and/or progression can significantly affect the treatment outcome. Adaptive RT has become the effective methods along with technical advancements in imaging modalities including cone-beam computed tomography (CBCT). Planning CT (pCT) can be modified via deformable image registration (DIR), which is applied to the pair of pCT and CBCT. However, the artifact existed in both pCT and CBCT is a vulnerable factor in DIR. The dose calculation on CBCT is also suggested. Missing information due to the artifacts hinders the accurate dose calculation on CBCT. In this study, we aim to develop a deep learning-based metal artifact reduction (MAR) model to reduce the metal artifacts in CBCT for head and neck cancer RT. To train the proposed MAR model, we synthesized the kV-CBCT images including metallic implants, with and without metal artifacts (simulated image data pairs) through sinogram image handling process. We propose the deep learning architecture which focuses on both artifact removal and reconstruction of anatomic structure using a dual-encoder architecture. We designed four single-encoder models and three dual-encoder models based on UNet (for an artifact removal) and FusionNet (for a tissue restoration). Each single-encoder model contains either UNet or FusionNet, while the dual-encoder models have both UNet and FusionNet architectures. In the dual-encoder models, we implemented different feature fusion methods, including simple addition, spatial attention, and spatial/channel wise attention. Among the models, a dual-encoder model with spatial/channel wise attention showed the highest scores in terms of peak signal-to-noise ratio, mean squared error, structural similarity index, and Pearson correlation coefficient. CBCT images from 34 head and neck cancer patients were used to test the developed models. The dual-encoder model with spatial/channel wise attention showed the best results in terms of artifact index. By using the proposed model to CBCT, one can achieve more accurate synthetic pCT for head and neck patients as well as better tissue recognition and structure delineation for CBCT image itself.

RevDate: 2024-11-13

Di Battista V, Danielsen PH, Gajewicz-Skretna A, et al (2024)

Oxide-Perovskites for Automotive Catalysts Biotransform and Induce Multicomponent Clearance and Hazard.

ACS nano [Epub ahead of print].

Oxide-perovskites designed for automotive catalysts contain multiple metal elements whose presence is crucial to achieving the targeted performance. They are highly stable in exhaust operating conditions; however, little is known about their stability under physiological conditions. As some of the metallic components are hazardous to humans and the environment, perovskite benefits in cleaner air must be balanced with risks in a Safe and Sustainable Design (SSbD) approach. New approach methodologies (NAMs), including in chemico and in silico methods, were used for testing hazards and benefits, including catalytic activity and tolerance for temporary excess of oxygen under dynamic driving conditions. The composition and surface properties of six different lanthanum-based oxide-perovskites compromised their stability under lung physiological conditions, influencing the oxidative damage of the particles and the bioacessibility of leaching metals. We found consistent biotransformation of the oxide-perovskite materials at pH 4.5. The leached lanthanum ions, but not other metals, respeciated into lanthanum phosphate nanoparticles, which increased the overall oxidative damage in additive synergy. The NAM results in the presented SSbD approach were challenged by in vivo studies in rats and mice, which confirmed multicomponent clearance from lungs into urine and supported the comparative ranking of effects against well-characterized spinel materials. Among the perovskites, the version with reduced nickel content and doped with palladium offered the best SSbD balance, despite not improving the conventional benchmark catalytic performance and related sustainability benefits. Redesign by industry may be necessary to better fulfill all SSbD dimensions.

RevDate: 2024-11-13
CmpDate: 2024-11-13

Corrêa-do-Nascimento GS, Galvão C, GR Leite (2024)

Investigating the distribution of a rare Colombo-Venezuelan kissing bug, Rhodnius neivai, Lent, 1953, using geographical information system-based analyses.

Memorias do Instituto Oswaldo Cruz, 119:e240106 pii:S0074-02762024000101135.

BACKGROUND: Rhodnius neivai, a kissing bug found in the dry regions of Colombia and Venezuela, has limited documented occurrences. While it is not deemed a significant vector for Chagas disease, distributional and ecological studies are essential in monitoring species domiciliation and shedding light on the evolutionary aspects of the Rhodniini tribe.

OBJECTIVES: The study aims to provide a detailed revision of R. neivai distribution and evaluate general spatial data quality for ecological niche modelling (ENM). It will also provide the first published ENM for the species, which may aid species sampling and future analytical improvement.

METHODS: Registers and other spatial information were gathered by literature review; data georeferencing, preliminary geographical investigations, and model editing were conducted in GIS platforms; ENMs were built using R and explored the uncertainty of parameters and algorithms.

FINDINGS: Twenty four unique sites were identified, unearthing 17 previously uncovered records. Data lacks robust spatial and temporal precision; however, ENMs had acceptable validations. The models present some variation in suitability but with objective areas for sampling effort.

MAIN CONCLUSIONS: Rhodnius neivai distribution is better explained by conditions that characterise dry ecotypes, but further sampling is essential to improve modelling and advance with ecological and evolutive matters.

RevDate: 2024-11-11

Boyes D, Crowley LM, Boyes C, et al (2024)

The genome sequence of the Pale November moth, Epirrita christyi (Allen, 1906).

Wellcome open research, 9:540.

We present a genome assembly from an individual female Pale November moth, Epirrita christyi (Arthropoda; Insecta; Lepidoptera; Geometridae). The genome sequence has a total length of 474.20 megabases. Most of the assembly is scaffolded into 31 chromosomal pseudomolecules, including the Z sex chromosome. The mitochondrial genome has also been assembled and is 15.99 kilobases in length. Gene annotation of this assembly on Ensembl identified 16,983 protein-coding genes.

RevDate: 2024-11-12
CmpDate: 2024-11-08

Weistuch C, Murgas KA, Zhu J, et al (2024)

Normal tissue transcriptional signatures for tumor-type-agnostic phenotype prediction.

Scientific reports, 14(1):27230.

Cancer transcriptional patterns reflect both unique features and shared hallmarks across diverse cancer types, but whether differences in these patterns are sufficient to characterize the full breadth of tumor phenotype heterogeneity remains an open question. We hypothesized that these shared transcriptomic signatures reflect repurposed versions of functional tasks performed by normal tissues. Starting with normal tissue transcriptomic profiles, we use non-negative matrix factorization to derive six distinct transcriptomic phenotypes, called archetypes, which combine to describe both normal tissue patterns and variations across a broad spectrum of malignancies. We show that differential enrichment of these signatures correlates with key tumor characteristics, including overall patient survival and drug sensitivity, independent of clinically actionable DNA alterations. Additionally, we show that in HR+/HER2- breast cancers, metastatic tumors adopt transcriptomic signatures consistent with the invaded tissue. Broadly, our findings suggest that cancer often arrogates normal tissue transcriptomic characteristics as a component of both malignant progression and drug response. This quantitative framework provides a strategy for connecting the diversity of cancer phenotypes and could potentially help manage individual patients.

RevDate: 2024-11-08

Lewis JH, Kojima H, Suenaga M, et al (2024)

The era of cybertaxonomy: X-ray microtomography reveals cryptic diversity and concealed cuticular sculpture in Aphanerostethus Voss, 1957 (Coleoptera, Curculionidae).

ZooKeys, 1217:1-45.

Weevils represent one of the most speciose and economically important animal clades, but remain poorly studied across much of the Oriental Region. Here, an integrative revision of the Oriental, flightless genus Aphanerostethus Voss, 1957 (Curculionidae: Molytinae) based on X-ray microtomography, multi-gene DNA barcoding (CO1, Cytb, 16S), and traditional morphological techniques (light microscopy, dissections) is presented. Twelve new species, namely, A.armatus Lewis & Kojima, sp. nov., A.bifidus Kojima & Lewis, sp. nov., A.darlingi Lewis, sp. nov., A.decoratus Lewis & Kojima, sp. nov., A.falcatus Kojima, Lewis & Fujisawa, sp. nov., A.incurvatus Kojima & Lewis, sp. nov., A.japonicus Lewis & Kojima, sp. nov., A.magnus Lewis & Kojima, sp. nov., A.morimotoi Kojima & Lewis, sp. nov., A.nudus Lewis & Kojima, sp. nov., A.spinosus Lewis & Kojima, sp. nov., and A.taiwanus Lewis, Fujisawa & Kojima, sp. nov. are described from Japan, Taiwan, Vietnam, and Malaysia. A neotype is designated for A.vannideki Voss, 1957. The hitherto monotypic genus Darumazo Morimoto & Miyakawa, 1985, syn. nov. is synonymized under Aphanerostethus based on new morphological data and Aphanerostethusdistinctus (Morimoto & Miyakawa, 1985), comb. nov. is transferred accordingly. X-ray microtomography is successfully used to explore for stable interspecific differences in cuticular, internal and micro morphology. Remarkable species-specific sexual dimorphism in the metatibial uncus is described in seven of the newly described Aphanerostethus species and the evolution of this character is discussed.

RevDate: 2024-11-07
CmpDate: 2024-11-08

Tang Y, Tian C, Yao D, et al (2024)

Community assembly and potential function analysis of the endophyte in Eucommia ulmoides.

BMC microbiology, 24(1):460.

Endophytes play a pivotal role in protecting host plants from both biotic and abiotic stresses, promoting the production of active components (AC) and plant growth. However, the succession of the endophyte community in Eucommia ulmoides (E. ulmoides), particularly the community assembly and function, has not been extensively investigated. In this study, we employed high-throughput sequencing and bioinformatics tools to analyze endophyte diversity across different tree ages, parts, and periods. We examined the population differences, correlations, community assembly mechanisms, and functional roles of these endophytes. Functional predictions via PICRUSt2 revealed that most endophytic fungal functions were linked to biosynthesis, with significant differences in biosynthetic functional abundance across parts and periods. In contrast, the metabolic activity of endophytic bacteria remained stable across different periods and parts. Correlation analysis further confirmed a strong positive relationship between ACs and certain endophytic fungi. Among them, the fungal phyla Ascomycota and Basidiomycota were identified as key contributors to the metabolism of chlorogenic acid (CA), while Aucubin was significantly positively correlated with several endophytic bacteria. These findings provide valuable insights into the functional roles and community assembly mechanism of E. ulmoides endophytes, as well as their symbiotic relationships.

RevDate: 2024-11-12

Toledo MJL, Zawadzki MJ, Scott SB, et al (2024)

Exploring the Utility of a Real-Time Approach to Characterising Within-Person Fluctuations in Everyday Stress Responses.

Stress and health : journal of the International Society for the Investigation of Stress [Epub ahead of print].

Few studies have measured components of stress responses in real time-an essential step in designing just-in-time interventions targeting moments of risk. Using ecological momentary assessment (EMA), we characterised stress response components to everyday stressors, including reactivity (the response following a stressor), recovery (the return towards baseline), and pile-up (the accumulation of stressors) (RRPs) by quantifying the dynamics of response indicators (i.e., subjective stress, negative affect, and perseverative cognition). To determine the utility of these novel measures in capturing and characterising acute moments of the stress response, this study evaluated the proportion of variance in RRPs attributed to (1) between-person, (2) between-days, and (3) within-day (momentary) levels. Healthy adults (n = 123; aged 35-65, 79% women, 91% non-Hispanic White) participated in a 14-day study assessing stress response via EMA 6 times a day. RRPs were constructed from 10,065 EMA reports. Multilevel models with moments nested within days nested within persons were used to partition variance in the RRPs. Reactivity and recovery indicators captured the most variation within-days (i.e., across moments; range 76%-80% and 87%-89%, respectively), with small amounts of variance between-person. For pile-up, variation was mostly observed between-days (range 60%-63%) and between-persons (range 27%-31%). In contrast, raw measures of stress response reflected substantial between-person (range 32%-54%) and within-day (range 34%-53%) variance. These results demonstrated that a person-specific approach to measuring stress response components (i.e., RRPs) can capture the dynamic within-person variation in stress response, as it occurs in real time, making it well-suited for use in novel just-in-time interventions targeting moments of risk.

RevDate: 2024-11-11
CmpDate: 2024-11-11

Tan X, Xue F, Zhang C, et al (2024)

mbDriver: identifying driver microbes in microbial communities based on time-series microbiome data.

Briefings in bioinformatics, 25(6):.

Alterations in human microbial communities are intricately linked to the onset and progression of diseases. Identifying the key microbes driving these community changes is crucial, as they may serve as valuable biomarkers for disease prevention, diagnosis, and treatment. However, there remains a need for further research to develop effective methods for addressing this critical task. This is primarily because defining the driver microbe requires consideration not only of each microbe's individual contributions but also their interactions. This paper introduces a novel framework, called mbDriver, for identifying driver microbes based on microbiome abundance data collected at discrete time points. mbDriver comprises three main components: (i) data preprocessing of time-series abundance data using smoothing splines based on the negative binomial distribution, (ii) parameter estimation for the generalized Lotka-Volterra (gLV) model using regularized least squares, and (iii) quantification of each microbe's contribution to the community's steady state by manipulating the causal graph implied by gLV equations. The performance of nonparametric spline-based denoising and regularized least squares estimation is comprehensively evaluated on simulated datasets, demonstrating superiority over existing methods. Furthermore, the practical applicability and effectiveness of mbDriver are showcased using a dietary fiber intervention dataset and an ulcerative colitis dataset. Notably, driver microbes identified in the dietary fiber intervention dataset exhibit significant effects on the abundances of short-chain fatty acids, while those identified in the ulcerative colitis dataset show a significant correlation with metabolism-related pathways.

RevDate: 2024-11-10

Coelho LA, Gonzalez CLR, Tammurello C, et al (2024)

Hand and foot overestimation in visually impaired human adults.

Neuroscience, 563:74-83 pii:S0306-4522(24)00580-3 [Epub ahead of print].

Previous research has shown that visual impairment results in reduced audio, tactile and proprioceptive ability. One hypothesis is that these issues arise from inaccurate body representations. Few studies have investigated metric body representations in a visually impaired population. We designed an ecologically valid behavioural task in which visually impaired adults haptically explored various sized gloves or shoes. They were asked to indicate if they perceived each clothing item as bigger than the size of their hand or foot. In the post-hoc analyses we fit psychometric curves to the data to extract the point of subjective equality. We then compared the results to age/sex matched controls. We hypothesized the blind participants body representations should be more distorted. Because previous research has shown that females are more likely to overestimate body size, we predicted sex differences in the sighted participants. However, because blind adults have no exposure to visual ideals of body size, we predicted that there would be no sex differences. Our results showed thatblind participants overestimated their hands and feetto a similar degree. Sighted controls overestimated their hands significantly more than their feet. Taken together, our results partially support our hypothesis and suggest that visual deprivation, even for short periods result in hand size overestimation.

RevDate: 2024-11-09

Rodriguez-Caturla MY, Margalho LP, Graça JS, et al (2024)

Bacterial dynamics and volatile metabolome changes of vacuum-packaged beef with different pH during chilled storage.

International journal of food microbiology, 427:110955 pii:S0168-1605(24)00399-4 [Epub ahead of print].

This study aimed to assess the growth of spoilage bacteria in Brazilian vacuum-packed beef across different pH ranges (5.4-5.8, 5.8-6.1, ≥6.1) stored at temperatures of 0 °C, 4 °C, and 7 °C. Additionally, the research sought to identify predominant spoilage bacteria at the genus level using 16S rDNA gene sequencing and analyze the principal volatile organic compounds (VOCs) produced by this microbiota through HS-SPME/GC-MS. Lactic acid bacteria (LAB) consistently exhibited counts exceeding 6.0 Log CFU/g, regardless of temperature and pH conditions. The bacterial diversity in the meat samples reflected the influence of slaughterhouse environments, with Pseudomonas and Serratia remaining dominant across different cuts and pH levels. Post-storage, variations in pH and temperature modulated the initial bacterial diversity, leading to a reduction in diversity and an increase in LAB such as Lactobacillus, Lactococcus, Leuconostoc, and Carnobacterium. Notably, these changes were observed within pH ranges of 5.4-5.8 and 5.8-6.1, irrespective of beef cuts and storage temperatures. Based on high throughput sequencing and VOCS, correlation analysis revealed a relationship between the growth of specific spoilage microorganisms under vacuum conditions and the presence of VOCs such as alcohols (e.g., 1-propanol, 2-methyl-) and ketones (e.g., 2-nonanone, 2-octanone, 2-heptanone), identifying them as potential indicators of spoilage bacteria growth.

RevDate: 2024-11-13
CmpDate: 2024-11-12

Silva GAA, Harder AM, Kirksey KB, et al (2024)

Detectability of runs of homozygosity is influenced by analysis parameters and population-specific demographic history.

PLoS computational biology, 20(10):e1012566.

Wild populations are increasingly threatened by human-mediated climate change and land use changes. As populations decline, the probability of inbreeding increases, along with the potential for negative effects on individual fitness. Detecting and characterizing runs of homozygosity (ROHs) is a popular strategy for assessing the extent of individual inbreeding present in a population and can also shed light on the genetic mechanisms contributing to inbreeding depression. Here, we analyze simulated and empirical datasets to demonstrate the downstream effects of program selection and long-term demographic history on ROH inference, leading to context-dependent biases in the results. Through a sensitivity analysis we evaluate how various parameter values impact ROH-calling results, highlighting its utility as a tool for parameter exploration. Our results indicate that ROH inferences are sensitive to factors such as sequencing depth and ROH length distribution, with bias direction and magnitude varying with demographic history and the programs used. Estimation biases are particularly pronounced at lower sequencing depths, potentially leading to either underestimation or overestimation of inbreeding. These results are particularly important for the management of endangered species, as underestimating inbreeding signals in the genome can substantially undermine conservation initiatives. We also found that small true ROHs can be incorrectly lumped together and called as longer ROHs, leading to erroneous inference of recent inbreeding. To address these challenges, we suggest using a combination of ROH detection tools and ROH length-specific inferences, along with sensitivity analysis, to generate robust and context-appropriate population inferences regarding inbreeding history. We outline these recommendations for ROH estimation at multiple levels of sequencing effort, which are typical of conservation genomics studies.

RevDate: 2024-11-13
CmpDate: 2024-11-13

Manzanedo RD, Chin ARO, Ettinger AK, et al (2024)

Moving ecological tree-ring big data forwards: Limitations, data integration, and multidisciplinarity.

The Science of the total environment, 955:177244.

In recent years, tree-ring databases have emerged as a remarkable resource for ecological research, allowing us to address ecological questions at unprecedented temporal and spatial scales. However, concerns regarding big tree-ring data limitations and risks have also surfaced, leading to questions about their potential to be representative of long-term forest responses. Here, we highlight three paths of action to improve on tree-ring databases in ecology: 1) Implementing consistent bias analyses in large dendroecological databases and promoting community-driven data to address data limitations, 2) Encouraging the integration of tree-ring data with other ecological datasets, and 3) Promoting theory-driven, mechanistic dendroecological research. These issues are increasingly important for tackling pressing cross-disciplinary research questions. Finally, although we focus here on tree ring databases, these points apply broadly across many aggregative databases in ecology.

RevDate: 2024-11-11
CmpDate: 2024-11-11

Amenu K, Daborn C, Huntington B, et al (2024)

Prioritization, resource allocation and utilization of decision support tools in animal health: Results of qualitative interviews with experts.

Preventive veterinary medicine, 233:106333.

A follow up to an online questionnaire survey (in a kind of a sequential study design), qualitative assessment was made on the views of selected animal health experts on disease prioritization methods, resource allocation and use of decision-support tools. This was done through in-depth interviews with experts working for national or international organizations and sectors. A semi-structured question guide was formulated based on the information generated in the online questionnaire and a systematic content analysis of animal and human health manuals for disease prioritization and resource allocation. In-depth, one-on-one, online interviews on the process of disease prioritization, animal health decision-making, types of prioritization tools and aspects of improvements in the tools were conducted during March and April 2022 with 20 expert informants. Prioritization approaches reported by experts were either single criterion-based or multiple criteria-based. Experts appreciated the single-criterion-based approach (quantitative) for its objectivity in contrast to multicriteria prioritization approaches which were criticized for their subjectivity. Interviews with the experts revealed a perceived lack of quality and reliable data to inform disease prioritization, especially in smallholder livestock production systems. It was found that outputs of disease prioritization exercises do not generally directly influence resource allocation in animal health and highlighted the paucity of funding for animal health compared to other agricultural sectors. The experts considered that the available decision-support tools in animal health need improvement in terms of data visualization for interpretation, management decision making and advocacy. Further recommendations include minimizing subjective biases by increasing the availability and quality of data and improving the translation of disease prioritization outputs into actions and the resources to deliver those actions. DATA AVAILABILITY STATEMENT: The data can be obtained from the corresponding author upon request.

RevDate: 2024-11-07
CmpDate: 2024-11-07

Setyawati I, Husaini AF, Setiawan AG, et al (2024)

Structural Classification Insights Into the Plant Defensive Peptides.

Proteins, 92(12):1413-1427.

This study presents a structural phylogenetic analysis of plant defensive peptides, revealing their evolutionary relationships, structural diversification, and functional adaptations. Utilizing a robust dataset comprising both experimental and predicted structures sourced from the RCSB Protein Data Bank and AlphaFold DB, we constructed a detailed phylogenetic tree to elucidate the distinct evolutionary paths of plant defensive peptide families. Our findings showcase the evolutionary intricacies of defensive peptides, highlighting their diversity and the conservation of key structural motifs critical to their antimicrobial or defensive functions. The results also underscore the adaptive significance of defensive peptides in plant evolution, highlighting their roles in responding to ecological pressures and pathogen interactions.

RevDate: 2024-11-11

Xiao Y, Elmasry M, Bai JDK, et al (2024)

Eco-evolutionary Guided Pathomic Analysis to Predict DCIS Upstaging.

bioRxiv : the preprint server for biology.

Cancers evolve in a dynamic ecosystem. Thus, characterizing cancer's ecological dynamics is crucial to understanding cancer evolution and can lead to discovering novel biomarkers to predict disease progression. Ductal carcinoma in situ (DCIS) is an early-stage breast cancer characterized by abnormal epithelial cell growth confined within the milk ducts. In this study, we show that ecological habitat analysis of hypoxia and acidosis biomarkers can significantly improve prediction of DCIS upstaging. First, we developed a novel eco-evolutionary designed approach to define habitats in the tumor intraductal microenvironment based on oxygen diffusion distance. Then, we identify cancer cells with metabolic phenotypes attributed to their habitat conditions, such as the expression of CA9 indicating hypoxia responding phenotype, and LAMP2b indicating the acid adaptation. Traditionally these markers have shown limited predictive capabilities for DCIS upstaging, if any. However, when analyzed from an ecological perspective, their power to differentiate between pure DCIS and upstaged DCIS increased significantly. Second, using eco-evolutionary guided computational and digital pathology techniques, we discovered distinct niches with spatial patterns of these biomarkers and used the distribution of such niches to predict patient upstaging. The niches patterns were characterized by pattern analysis of both cellular and spatial features. With a 5-fold validation on the biopsy cohort, we trained a random forest classifier to achieve the area under curve (AUC) of 0.74. Our results affirm the importance of using eco-evolutionary-designed approaches in biomarkers discovery studies in the era of digital pathology by demonstrating the role of tumor ecological habitats and niches.

RevDate: 2024-11-07

Flores M, Ho E, Ly C, et al (2024)

Decreased accuracy of forensic DNA mixture analysis for groups with lower genetic diversity.

iScience, 27(11):111067 pii:S2589-0042(24)02292-2.

Forensic investigation of DNA samples from multiple contributors has become commonplace. These complex analyses use statistical frameworks accounting for multiple levels of uncertainty in allelic contributions from different individuals, particularly for samples containing few molecules of DNA. These methods have been thoroughly tested along some axes of variation, but less attention has been paid to accuracy across human genetic variation. Here, we quantify the accuracy of DNA mixture analysis over 83 human groups. We find higher false inclusion rates for mixtures with more contributors and for groups with lower genetic diversity. Even for three-contributor mixtures where two contributors are known and the reference group is correctly specified, false inclusion rates are 1e-5 or higher for 36 out of 83 groups. This means that, depending on multiple testing, some false inclusions may be expected. These false positives could be lessened with more selective and conservative use of DNA mixture analysis.

RevDate: 2024-11-06
CmpDate: 2024-11-06

Campelo F, de Oliveira ALG, Reis-Cunha J, et al (2024)

Phylogeny-aware linear B-cell epitope predictor detects targets associated with immune response to orthopoxviruses.

Briefings in bioinformatics, 25(6):.

We introduce a phylogeny-aware framework for predicting linear B-cell epitope (LBCE)-containing regions within proteins. Our approach leverages evolutionary information by using a taxonomic scaffold to build models trained on hierarchically structured data. The resulting models present performance equivalent or superior to generalist methods, despite using simpler features and a fraction of the data volume required by current state-of-the-art predictors. This allows the utilization of available data for major pathogen lineages to facilitate the prediction of LBCEs for emerging infectious agents. We demonstrate the efficacy of our approach by predicting new LBCEs in the monkeypox (MPXV) and vaccinia viruses. Experimental validation of selected targets using sera from infected patients confirms the presence of LBCEs, including candidates for the differential serodiagnosis of recent MPXV infections. These results point to the use of phylogeny-aware predictors as a useful strategy to facilitate the targeted development of immunodiagnostic tools.

RevDate: 2024-11-05
CmpDate: 2024-11-06

Sijm-Eeken M, Ossebaard HC, Čaluković A, et al (2024)

Linking theory and practice to advance sustainable healthcare: the development of maturity model version 1.0.

BMC health services research, 24(1):1350.

BACKGROUND: Climate change and increased awareness of planetary health have made reducing ecological footprints a priority for healthcare organizations. However, improving healthcare's environmental impact remains difficult. Numerous researchers argue these difficulties are caused by healthcare's environmental impact being multidimensional, influenced throughout the healthcare chain, and often has downstream consequences that are hard to identify or to measure. Even though existing research describes many successful approaches to reduce healthcare's environmental impact, a robust multidimensional framework to assess this impact is lacking. This research aims at developing a maturity model for sustainable healthcare that could be used for self-assessment by healthcare professionals to identify improvement actions and for sharing best practices in environmental sustainability.

METHODS: A design-oriented approach for maturity model development was combined with an expert panel and six case studies to develop, refine and expand the maturity model for environmentally sustainable healthcare.

RESULTS: A maturity model was developed containing four domains: 'Governance', 'Organization Structures', 'Processes', and 'Outcomes and Control'. Applying the model in real-world environments demonstrated the model's understandability, ease of use, usefulness, practicality and ability to identify improvement actions for environmental sustainability in healthcare organizations.

CONCLUSIONS: This study found that healthcare practitioners could apply the maturity model developed and tested in this study in several hours without training to help them gain valuable insights into the environment footprint of the healthcare setting they worked in. Systematically implementing the model developed in this study could help address the urgent need to mitigate the substantial environmental impact of healthcare. These implementations can help evaluate and improve the maturity model.

RevDate: 2024-11-06
CmpDate: 2024-11-05

Moeller AH, Dillard BA, Goldman SL, et al (2024)

Removal of sequencing adapter contamination improves microbial genome databases.

BMC genomics, 25(1):1033.

Advances in assembling microbial genomes have led to growth of reference genome databases, which have been transformative for applied and basic microbiome research. Here we show that published microbial genome databases from humans, mice, cows, pigs, fish, honeybees, and marine environments contain significant sequencing-adapter contamination that systematically reduces assembly accuracy and contiguousness. By removing the adapter-contaminated ends of contiguous sequences and reassembling MGnify reference genomes, we improve the quality of assemblies in these databases.

RevDate: 2024-11-06

Boyes D, Boyes C, University of Oxford and Wytham Woods Genome Acquisition Lab, et al (2024)

The genome sequence of the Case-bearing Clothes moth, Tinea pellionella (Linnaeus, 1758).

Wellcome open research, 9:119.

We present a genome assembly from an individual female Tinea pellionella (the Case-bearing Clothes moth; Arthropoda; Insecta; Lepidoptera; Tineidae). The genome sequence is 245.3 megabases in span. Most of the assembly is scaffolded into 30 chromosomal pseudomolecules, including the Z sex chromosome. The mitochondrial genome has also been assembled and is 25.86 kilobases in length. Gene annotation of this assembly on Ensembl identified 13,811 protein coding genes.

RevDate: 2024-11-05
CmpDate: 2024-11-04

Chakraborty H, Chakraborty HJ, Das BK, et al (2024)

Age-specific changes in the serum proteome of female anadromous, hilsa Tenualosa ilisha: a comparative analysis across developmental stages.

Frontiers in immunology, 15:1448627.

INTRODUCTION: The proteome profile of the female Tenualosa ilisha (Hamilton, 1822), a species of great ecological and economic importance, across various age groups was investigated to comprehend the functional dynamics of the serum proteome for conservation and aquaculture, as well as sustain the population.

METHODS: Advanced liquid chromatography-tandem mass spectrometry LC-MS/MS-based proteomic data were analysed and submitted to the ProteomeXchange Consortium via PRIDE (PRoteomics IDEntifications database). Bioinformatics analysis of serum proteome have been done and it showed different proteins associated with GO Gene Ontology () terms, and the genes associated with enriched KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways (such as phagosome, mTOR, Apelin signalling pathways, herpes simplex virus) implicated in immune responses.

RESULTS: The expression levels of important immunological proteins, such as those involved in cellular defence and inflammatory responses, were significantly different age-dependently. In this study, we annotated 952, 494, 415, and 282 proteins in year classes IV, III, II, and I Hilsa, respectively, and analysed their Protein-Protein Interaction (PPI) networks based on their functional characteristics. From year classes I to IV, new proteins appeared and were more than three-fold. Notably, class I hilsa displayed a lower abundance of proteins than class IV hilsa.

DISCUSSION: This is the first study, to the best of our knowledge, to report the analysis of the serum proteome of hilsa at different developmental stages, and the results can help improve the understanding of the mechanisms underlying the different changes in protein enrichment during migration in hilsa. This analysis also offers crucial insights into the immune system for hilsa conservation and management.

RevDate: 2024-11-05

Reuken PA, Besteher B, Bleidorn J, et al (2024)

Web-based telemedicine approach for treatment of post-COVID-19 in Thuringia (WATCH).

Digital health, 10:20552076241291748.

OBJECTIVE: After infection with SARS-CoV-2, a substantial proportion of patients develop long-lasting sequelae. These sequelae include fatigue (potentially as severe as that seen in ME/CFS cases), cognitive dysfunction, and psychiatric symptoms. Because the pathophysiology of these sequelae remains unclear, existing therapeutic concepts address the symptoms through pacing strategies, cognitive training, and psychological therapy.

METHODS: Here, we present a protocol for a digital multimodal structured intervention addressing common symptoms through three intervention modules: BRAIN, BODY, and SOUL. This intervention includes an assessment conducted via a mobile "post-COVID-19 bus" near the patient's home, as well as the use of wearable devices and mobile applications to support pacing strategies and collection of data, including ecological momentary assessment.

RESULTS: We will focus on physical component subscore of the SF36 as Quality of Life parameter as the primary outcome parameter for WATCH to take into account the holistic approach that is necessary for care of post-COVID patients.

CONCLUSION: In the current project, we present a protocol for a holistic and multimodal structured therapeutic concept which is easily accessible, and scalable for post-COVID patients.

RevDate: 2024-11-06
CmpDate: 2024-10-31

Goldshtein A, Chen X, Amichai E, et al (2024)

Acoustic cognitive map-based navigation in echolocating bats.

Science (New York, N.Y.), 386(6721):561-567.

Bats are known for their ability to use echolocation for obstacle avoidance and orientation. However, the extent to which bats utilize their highly local and directional echolocation for kilometer-scale navigation is unknown. In this study, we translocated wild Kuhl's pipistrelle bats and tracked their homing abilities while manipulating their visual, magnetic, and olfactory sensing and accurately tracked them using a new reverse GPS system. We show that bats can identify their location after translocation and conduct several-kilometer map-based navigation using solely echolocation. This proposition was further supported by a large-scale echolocation model disclosing how bats use environmental acoustic information to perform acoustic cognitive map-based navigation. We also demonstrate that navigation is improved when using both echolocation and vision.

RevDate: 2024-11-02
CmpDate: 2024-10-31

Ramesh S, Rapp S, Tapias Gomez J, et al (2024)

Reference Sequence Browser: An R application with a user-friendly GUI to rapidly query sequence databases.

PloS one, 19(10):e0309707.

Land managers, researchers, and regulators increasingly utilize environmental DNA (eDNA) techniques to monitor species richness, presence, and absence. In order to properly develop a biological assay for eDNA metabarcoding or quantitative PCR, scientists must be able to find not only reference sequences (previously identified sequences in a genomics database) that match their target taxa but also reference sequences that match non-target taxa. Determining which taxa have publicly available sequences in a time-efficient and accurate manner currently requires computational skills to search, manipulate, and parse multiple unconnected DNA sequence databases. Our team iteratively designed a Graphic User Interface (GUI) Shiny application called the Reference Sequence Browser (RSB) that provides users efficient and intuitive access to multiple genetic databases regardless of computer programming expertise. The application returns the number of publicly accessible barcode markers per organism in the NCBI Nucleotide, BOLD, or CALeDNA CRUX Metabarcoding Reference Databases. Depending on the database, we offer various search filters such as min and max sequence length or country of origin. Users can then download the FASTA/GenBank files from the RSB web tool, view statistics about the data, and explore results to determine details about the availability or absence of reference sequences.

RevDate: 2024-11-07
CmpDate: 2024-11-07

Ran J, Ditmar P, van den Broeke MR, et al (2024)

Vertical bedrock shifts reveal summer water storage in Greenland ice sheet.

Nature, 635(8037):108-113.

The Greenland ice sheet (GrIS) is at present the largest single contributor to global-mass-induced sea-level rise, primarily because of Arctic amplification on an increasingly warmer Earth[1-5]. However, the processes of englacial water accumulation, storage and ultimate release remain poorly constrained. Here we show that a noticeable amount of the summertime meltwater mass is temporally buffered along the entire GrIS periphery, peaking in July and gradually reducing thereafter. Our results arise from quantifying the spatiotemporal behaviour of the total mass of water leaving the GrIS by analysing bedrock elastic deformation measured by Global Navigation Satellite System (GNSS) stations. The buffered meltwater causes a subsidence of the bedrock close to GNSS stations of at most approximately 5 mm during the melt season. Regionally, the duration of meltwater storage ranges from 4.5 weeks in the southeast to 9 weeks elsewhere. We also show that the meltwater runoff modelled from regional climate models may contain systematic errors, requiring further scaling of up to about 20% for the warmest years. These results reveal a high potential for GNSS data to constrain poorly known hydrological processes in Greenland, forming the basis for improved projections of future GrIS melt behaviour and the associated sea-level rise[6].

RevDate: 2024-10-30

Chala D, Endresen D, Demissew S, et al (2024)

Stop using racist, unethical, and inappropriate names in taxonomy.

Proceedings of the National Academy of Sciences of the United States of America, 121(45):e2415490121.

RevDate: 2024-10-30

Ayadi H, Elbéji A, Despotovic V, et al (2024)

Digital Vocal Biomarker of Smoking Status Using Ecological Audio Recordings: Results from the Colive Voice Study.

Digital biomarkers, 8(1):159-170.

INTRODUCTION: The complex health, social, and economic consequences of tobacco smoking underscore the importance of incorporating reliable and scalable data collection on smoking status and habits into research across various disciplines. Given that smoking impacts voice production, we aimed to develop a gender and language-specific vocal biomarker of smoking status.

METHODS: Leveraging data from the Colive Voice study, we used statistical analysis methods to quantify the effects of smoking on voice characteristics. Various voice feature extraction methods combined with machine learning algorithms were then used to produce a gender and language-specific (English and French) digital vocal biomarker to differentiate smokers from never-smokers.

RESULTS: A total of 1,332‬ participants were included after propensity score matching (mean age = 43.6 [13.65], 64.41% are female, 56.68% are English speakers, 50% are smokers and 50% are never-smokers). We observed differences in voice features distribution: for women, the fundamental frequency F0, the formants F1, F2, and F3 frequencies and the harmonics-to-noise ratio were lower in smokers compared to never-smokers (p < 0.05) while for men no significant disparities were noted between the two groups. The accuracy and AUC of smoking status prediction reached 0.71 and 0.76, respectively, for the female participants, and 0.65 and 0.68, respectively, for the male participants.

CONCLUSION: We have shown that voice features are impacted by smoking. We have developed a novel digital vocal biomarker that can be used in clinical and epidemiological research to assess smoking status in a rapid, scalable, and accurate manner using ecological audio recordings.

RevDate: 2024-11-06
CmpDate: 2024-10-30

Wang Y, Chen J, Ni Y, et al (2024)

Exercise-changed gut mycobiome as a potential contributor to metabolic benefits in diabetes prevention: an integrative multi-omics study.

Gut microbes, 16(1):2416928.

BACKGROUND: The importance of gut microbes in mediating the benefits of lifestyle intervention is increasingly recognized. However, compared to the bacterial microbiome, the role of intestinal fungi in exercise remains elusive. With our established randomized controlled trial of exercise intervention in Chinese males with prediabetes (n = 39, ClinicalTrials.gov:NCT03240978), we investigated the dynamics of human gut mycobiome and further interrogated their associations with exercise-elicited outcomes using multi-omics approaches.

METHODS: Clinical variations and biological samples were collected before and after training. Fecal fungal composition was analyzed using the internal transcribed spacer 2 (ITS2) sequencing and integrated with paired shotgun metagenomics, untargeted metabolomics, and Olink proteomics.

RESULTS: Twelve weeks of exercise training profoundly promoted fungal ecological diversity and intrakingdom connection. We further identified exercise-responsive genera with potential metabolic benefits, including Verticillium, Sarocladium, and Ceratocystis. Using multi-omics approaches, we elucidated comprehensive associations between changes in gut mycobiome and exercise-shaped metabolic phenotypes, bacterial microbiome, and circulating metabolomics and proteomics profiles. Furthermore, a machine-learning algorithm built using baseline microbial signatures and clinical characteristics predicted exercise responsiveness in improvements of insulin sensitivity, with an area under the receiver operating characteristic (AUROC) of 0.91 (95% CI: 0.85-0.97) in the discovery cohort and of 0.79 (95% CI: 0.74-0.86) in the independent validation cohort (n = 30).

CONCLUSIONS: Our findings suggest that intense exercise training significantly remodels the human fungal microbiome composition. Changes in gut fungal composition are associated with the metabolic benefits of exercise, indicating gut mycobiome is a possible molecular transducer of exercise. Moreover, baseline gut fungal signatures predict exercise responsiveness for diabetes prevention, highlighting that targeting the gut mycobiome emerges as a prospective strategy in tailoring personalized training for diabetes prevention.

RevDate: 2024-10-29

Orr MC, Albert G, Hughes AC, et al (2024)

Dark data limit the biological sciences.

RevDate: 2024-11-01
CmpDate: 2024-10-29

Sandin P, Baard P, Bülow W, et al (2024)

Authorship and Citizen Science: Seven Heuristic Rules.

Science and engineering ethics, 30(6):53.

Citizen science (CS) is an umbrella term for research with a significant amount of contributions from volunteers. Those volunteers can occupy a hybrid role, being both 'researcher' and 'subject' at the same time. This has repercussions for questions about responsibility and credit, e.g. pertaining to the issue of authorship. In this paper, we first review some existing guidelines for authorship and their applicability to CS. Second, we assess the claim that the guidelines from the International Committee of Medical Journal Editors (ICMJE), known as 'the Vancouver guidelines', may lead to exclusion of deserving citizen scientists as authors. We maintain that the idea of including citizen scientists as authors is supported by at least two arguments: transparency and fairness. Third, we argue that it might be plausible to include groups as authors in CS. Fourth and finally, we offer a heuristic list of seven recommendations to be considered when deciding about whom to include as an author of a CS publication.

RevDate: 2024-10-29

Bağcı C, Nuhamunada M, Goyat H, et al (2024)

BGC Atlas: a web resource for exploring the global chemical diversity encoded in bacterial genomes.

Nucleic acids research pii:7848841 [Epub ahead of print].

Secondary metabolites are compounds not essential for an organism's development, but provide significant ecological and physiological benefits. These compounds have applications in medicine, biotechnology and agriculture. Their production is encoded in biosynthetic gene clusters (BGCs), groups of genes collectively directing their biosynthesis. The advent of metagenomics has allowed researchers to study BGCs directly from environmental samples, identifying numerous previously unknown BGCs encoding unprecedented chemistry. Here, we present the BGC Atlas (https://bgc-atlas.cs.uni-tuebingen.de), a web resource that facilitates the exploration and analysis of BGC diversity in metagenomes. The BGC Atlas identifies and clusters BGCs from publicly available datasets, offering a centralized database and a web interface for metadata-aware exploration of BGCs and gene cluster families (GCFs). We analyzed over 35 000 datasets from MGnify, identifying nearly 1.8 million BGCs, which were clustered into GCFs. The analysis showed that ribosomally synthesized and post-translationally modified peptides are the most abundant compound class, with most GCFs exhibiting high environmental specificity. We believe that our tool will enable researchers to easily explore and analyze the BGC diversity in environmental samples, significantly enhancing our understanding of bacterial secondary metabolites, and promote the identification of ecological and evolutionary factors shaping the biosynthetic potential of microbial communities.

RevDate: 2024-10-30

Bernstein JM, Bautista JB, Clores MA, et al (2024)

Using mangrove and field observation data to identify fine-scale species distributions: a case study in bockadams (Serpentes: Homalopsidae: Cerberus).

Royal Society open science, 11(10):240483.

Characterization of species distributions is a fundamental challenge in biodiversity science, with particular significance for downstream evolutionary studies, conservation efforts, field-based faunal studies and estimates of species diversity. Checklists and phylogenetic studies often focus on poorly known, rare taxa with limited ranges. However, studies of widely distributed, ecologically important species that are abundant in their preferred microhabitats are also important for systematics and local conservation efforts, but less often studied. We collected novel natural history data during fieldwork (2019-2023) for Philippine populations of bockadams (Homalopsidae: Cerberus), one of the most abundant vertebrates in Southeast Asian aquatic systems. Considered a coastal snake, many studies report Cerberus inland. We report the frequency of encounters of Cerberus schneiderii, and the IUCN data-deficient, Philippine-endemic Cerberus microlepis during six expeditions (62 days; 1041 person-hours). We report new occurrence data for 69 C. schneiderii and 6 C. microlepis for coastal and inland populations, water measurements and dietary observations. Regression analyses and ecological niche models show the importance of coastal and mangrove habitats for Cerberus. Our study is the most comprehensive assessment of Philippine Cerberus populations to date and provides critical baseline natural history data for downstream research on widespread and range-restricted species of Southeast Asian snakes.

RevDate: 2024-10-30

Chávez-Luzanía RA, Ortega-Urquieta ME, Aguilera-Ibarra J, et al (2024)

Transdisciplinary approaches for the study of cyanobacteria and cyanotoxins.

Current research in microbial sciences, 7:100289.

Cyanobacteria, ancient aerobic and photoautotrophic prokaryotes, thrive in diverse ecosystems due to their extensive morphological and physiological adaptations. They play crucial roles in aquatic ecosystems as primary producers and resource providers but also pose significant ecological and health risks through blooms that produce harmful toxins, called cyanotoxins. The taxonomic affiliation of cyanobacteria has evolved from morphology-based methods to genomic analysis, which offers detailed structural and physiological insights that are essential for accurate taxonomic affiliation and monitoring. However, challenges posed by uncultured species have been extrapolated to the detection and quantification of cyanotoxins. Current advances in molecular biology and informatics improve the precision of monitoring and allow the analysis of groups of genes related to toxin production, providing crucial information for environmental biosafety and public health. Unfortunately, public genomic databases heavily underrepresent cyanobacteria, which limits the understanding of their diversity and metabolic capabilities. Despite the increasing availability of cyanobacterial genome sequences, research is still largely focused on a few model strains, narrowing the scope of genetic and metabolic studies. The challenges posed by cyanobacterial blooms and cyanotoxins necessitate improved molecular, cultivation, and polyphasic techniques for comprehensive classification and quantification, highlighting the need for advanced genomic approaches to better understand and manage cyanobacteria and toxins. This review explores the application of transdisciplinary approaches for the study of cyanobacteria and cyanotoxins focused on diversity analysis, population quantification, and cyanotoxin monitoring, emphasizing their genomic resources and their potential in the genomic mining of toxin-related genes.

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In the early 1990's, Robert Robbins was a faculty member at Johns Hopkins, where he directed the informatics core of GDB — the human gene-mapping database of the international human genome project. To share papers with colleagues around the world, he set up a small paper-sharing section on his personal web page. This small project evolved into The Electronic Scholarly Publishing Project.

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In 1995, Robbins became the VP/IT of the Fred Hutchinson Cancer Research Center in Seattle, WA. Soon after arriving in Seattle, Robbins secured funding, through the ELSI component of the US Human Genome Project, to create the original ESP.ORG web site, with the formal goal of providing free, world-wide access to the literature of classical genetics.

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This is a must read book for anyone with an interest in invasion biology. The full title of the book lays out the author's premise — The New Wild: Why Invasive Species Will Be Nature's Salvation. Not only is species movement not bad for ecosystems, it is the way that ecosystems respond to perturbation — it is the way ecosystems heal. Even if you are one of those who is absolutely convinced that invasive species are actually "a blight, pollution, an epidemic, or a cancer on nature", you should read this book to clarify your own thinking. True scientific understanding never comes from just interacting with those with whom you already agree. R. Robbins

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Papers in Classical Genetics

The ESP began as an effort to share a handful of key papers from the early days of classical genetics. Now the collection has grown to include hundreds of papers, in full-text format.

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Along with papers on classical genetics, ESP offers a collection of full-text digital books, including many works by Darwin and even a collection of poetry — Chicago Poems by Carl Sandburg.

Timelines

ESP now offers a large collection of user-selected side-by-side timelines (e.g., all science vs. all other categories, or arts and culture vs. world history), designed to provide a comparative context for appreciating world events.

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