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Bibliography on: Ecological Informatics

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ESP: PubMed Auto Bibliography 14 Feb 2025 at 01:47 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: 2025-02-13

Rakshasa-Loots AM, Steyn C, Swiffen D, et al (2025)

Metabolic biomarkers of clinical outcomes in severe mental illness (METPSY): protocol for a prospective observational study in the Hub for metabolic psychiatry.

BMC psychiatry, 25(1):122.

People with severe mental illness have high rates of obesity, type 2 diabetes, and cardiovascular disease. Emerging evidence suggests that metabolic dysfunction may be causally linked to the risk of severe mental illness. However, more research is needed to identify reliable metabolic markers which may have an impact on mental health outcomes, and to determine the mechanisms behind their impact. In the METPSY research study, we will investigate the relationship between metabolic markers and clinical outcomes of severe mental illness in young adults. We will recruit 120 young adults aged 16-25 years living in Scotland with major depressive disorder, bipolar disorder, schizophrenia, or no severe mental illness (controls) for a prospective observational study. We will assess clinical symptoms at three in-person visits (baseline, 6 months, and 12 months) using the Structured Clinical Interview for DSM-5, and collect blood samples at each of these visits for agnostic profiling of metabolic biomarkers through an untargeted metabolomic screen, using the rapid hydrophilic interaction liquid chromatography ion mobility mass spectrometry method (RHIMMS). Participants will also complete remote assessments at 3 and 9 months after the baseline visit: Ecological Momentary Assessments to measure mental health, wrist actigraphy to measure rhythms of rest and activity, and continuous glucose monitoring to measure metabolic changes. Throughout the 12-month enrolment period, we will also measure objective markers of sleep using a radar sleep monitor (Somnofy). Using advanced statistical techniques and machine learning analysis, we will seek to better understand the mechanisms linking metabolic health with mental health in young adults with schizophrenia, bipolar disorder, and severe depression. Clinical trial number: Not applicable.

RevDate: 2025-02-13
CmpDate: 2025-02-13

Tittes S, Lorant A, McGinty SP, et al (2025)

The population genetics of convergent adaptation in maize and teosinte is not locally restricted.

eLife, 12: pii:92405.

What is the genetic architecture of local adaptation and what is the geographic scale over which it operates? We investigated patterns of local and convergent adaptation in five sympatric population pairs of traditionally cultivated maize and its wild relative teosinte (Zea mays subsp. parviglumis). We found that signatures of local adaptation based on the inference of adaptive fixations and selective sweeps are frequently exclusive to individual populations, more so in teosinte compared to maize. However, for both maize and teosinte, selective sweeps are also frequently shared by several populations, and often between subspecies. We were further able to infer that selective sweeps were shared among populations most often via migration, though sharing via standing variation was also common. Our analyses suggest that teosinte has been a continued source of beneficial alleles for maize, even after domestication, and that maize populations have facilitated adaptation in teosinte by moving beneficial alleles across the landscape. Taken together, our results suggest local adaptation in maize and teosinte has an intermediate geographic scale, one that is larger than individual populations but smaller than the species range.

RevDate: 2025-02-13
CmpDate: 2025-02-13

Cleveland P, A Morrison (2025)

Sông Sài Gòn: Extreme Plastic Pollution Pathways in Riparian Waterways.

Sensors (Basel, Switzerland), 25(3): pii:s25030937.

Plastic pollution in waterways poses a significant global challenge, largely stemming from land-based sources and subsequently transported by rivers to marine environments. With a substantial percentage of marine plastic waste originating from land-based sources, comprehending the trajectory and temporal experience of single-use plastic bottles assumes paramount importance. This project designed, developed, and released a plastic pollution tracking device, coinciding with Vietnam's annual Plastic Awareness Month. By mapping the plastic tracker's journey through the Saigon River, this study generated high-fidelity data for comprehensive analysis and bolstered public awareness through regular updates on the Re-Think Plastics Vietnam website. The device, equipped with technologies such as drone flight controller, open-source software, embedded computing, and cellular networking effectively captured GPS position, track, and localized conditions experienced by the plastic bottle tracker on its journey. This amalgamation of data contributes to the understanding of plastic pollution behaviors and serves as a data set for future initiatives aimed at plastic prevention in the ecologically sensitive Mekong Delta. By illuminating the transportation of single-use plastic bottles in the riparian waterways of Ho Chi Minh City and beyond, this study plays a role in collective efforts to understand plastic pollution and preserve aquatic ecosystems. By deploying a GPS-enabled plastic tracker, this study provides novel, high-resolution empirical data on plastic transport in urban tidal systems. These findings contribute to improving waste interception strategies and informing environmental policies aimed at reducing plastic accumulation in critical retention zones.

RevDate: 2025-02-12
CmpDate: 2025-02-13

Lorková Z, Cimermanová M, Piknová M, et al (2025)

Environmental impact on the genome shaping of putative new Streptomyces species.

BMC microbiology, 25(1):72.

BACKGROUND: The bacterial evolution and the emergence of new species are likely influenced by multiple forces, including long-term environmental pressure such as living in extreme conditions. In this study, the genomes of two potentially new Streptomyces species isolated from a former mine heap in Tarnowskie Góry in Poland, were analyzed.

RESULTS: A bioinformatic approach revealed notable phylogenetic and metabolic differences between the studied Streptomyces strains, despite originating from the same environment. While both strains are characterized by genetic features common to actinomycetes, additional unique biosynthetic gene clusters were also predicted in their genomes. The comparative genomic analysis with other Streptomyces spp. revealed a high conservation in heavy metal adaptive mechanisms, indicating a preadaptation to extreme conditions. The difference observed in the cad and mer operons could be attributed to the specific adaptations to heavy metal contamination. The high metal tolerance of examined strains was also confirmed by an agar dilution assay in the presence of several heavy metals. The confirmed siderophore production represents an additional mechanism allowing streptomycetes to survive in extreme conditions. On the other hand, both of studied genomes show significant differences in energy acquisition processes and the production of putative novel secondary metabolites. The isolates showed these differences not only among themselves but also compared to other Streptomyces species, indicating their uniqueness.

CONCLUSIONS: Our results demonstrate that extreme environmental conditions can lead to the development of various adaptation mechanisms in the Streptomyces spp. Furthermore, the results indicate that diverse Streptomyces species have developed conserved adaptation mechanisms against the heavy metals under extreme conditions, indicating the emergence of preadaptations that allow bacteria to respond rapidly to polluted environments and evolve their genomes accordingly up to the evolution of new species.

RevDate: 2025-02-13
CmpDate: 2025-02-13

Vacchi L, Zirone E, Strina V, et al (2024)

Mobile Applications to Support Multiple Sclerosis Communities: The Post-COVID-19 Scenario.

Telemedicine journal and e-health : the official journal of the American Telemedicine Association, 30(6):e1615-e1628.

Introduction: The increase in the use of mobile apps since the COVID-19 pandemic, even among people with multiple sclerosis (PwMS) and health care providers (HCPs), has enabled access to reliable information, symptoms monitoring and management, and social connections. The pandemic has undoubtedly contributed to the acceleration of the "digital revolution." But how far has it progressed for the MS communities? Methods: Italian Google Play and App Store were queried, selecting MS-specific apps in English or Italian language and usable by a wide public. Results: Fifty-four (n = 54) MS-specific apps were identified; most were PwMS-oriented (83%), free of charge (94%), and in English language (76%). The 45 PwMS-oriented apps focused on increasing MS knowledge (71%), tracking symptoms (33%), and promoting networking with peers or HCPs (38%). The 13 HCPs-oriented tools addressed education and updates on MS (62%), disease assessment and management (54%), and research (15%). Google Search tool was also queried to find non-MS-specific apps to fulfill some unmet domains (as sleep, pain, sexual or mental health). Twenty-four additional apps were listed to provide a valuable contribution. Conclusion: The "digital revolution" led to increasingly customized tools for PwMS, especially as m-health or social-networking apps. However, apps to support other specific MS-relevant domains, appealing HCPs-oriented apps, and specific mobile tools for MS caregivers are still lacking. The absence of data assessing the usability and quality of MS apps in ecologically contexts leads to not reliable conclusions about potential benefits. A strong dialogue between MS communities and the digital industry is encouraged to fill this gap.

RevDate: 2025-02-12

Zhuo W, Wu N, Shi R, et al (2025)

Assessing the impacts of reclamation and invasion on ecological dynamics of coastal wetland vegetation in the Yangtze Estuary from 1985 to 2019:A case study of Chongming Island, China.

Journal of environmental management, 376:124505 pii:S0301-4797(25)00481-5 [Epub ahead of print].

The distribution of coastal wetland vegetation is influenced by biological invasions, human reclamations and climate changes, which continually reshape vegetation structures. However, limited attention has been given to the impact of biological invasion on native vegetation and tidal wetlands. This study focuses on the wetlands of Chongming Island, employing a multi-feature dataset combining spectral, phenological, and temporal information on the Google Earth Engine (GEE) platform. Using the Random Forest (RF) classification method, we analyzed annual vegetation distribution changes and examined the distinct effects of natural and anthropogenic factors. The research results indicate that: (1) From 1985 to 2019, the total area of Chongming Island expanded, while wetland vegetation decreased due to embankment construction and island connection projects. (2) The total area of wetland vegetation on Chongming Island dropped to its lowest point in 2002 (3812.76 ha), and then gradually recovered. (3) Human reclamation was the primary driver of vegetation changes from 1985 to 1995. (4) Vegetation distribution in Dongtan was influenced by both human and natural factors, whereas Beiliuyao affected by the invasion and expansion of the S. alterniflor. These findings provide valuable insights into the drivers of long-term vegetation distribution changes, offering essential data and theoretical support for sustainable development and management of Chongming Island's ecosystems.

RevDate: 2025-02-12

Kim KK, U Backonja (2025)

Digital health equity frameworks and key concepts: a scoping review.

Journal of the American Medical Informatics Association : JAMIA pii:8010284 [Epub ahead of print].

OBJECTIVES: Digital health equity, the opportunity for all to engage with digital health tools to support good health outcomes, is an emerging priority across the world. The field of digital health equity would benefit from a comprehensive and systematic understanding of digital health, digital equity, and health equity, with a focus on real-world applications. We conducted a scoping review to identify and describe published frameworks and concepts relevant to digital health equity interventions.

MATERIALS AND METHODS: We conducted a scoping review of published peer-reviewed literature guided by the PRISMA Extension for Scoping Reviews. We searched 5 databases for frameworks related to or applied to digital health or equity interventions. Using deductive and inductive approaches, we analyzed frameworks and concepts based on the socio-ecological model.

RESULTS: Of the 910 publications initially identified, we included 44 (4.8%) publications in our review that described 42 frameworks that sought to explain the ecosystem of digital and/or health equity, but none were comprehensive. From the frameworks we identified 243 concepts grouped into 43 categories including characteristics of individuals, communities, and organizations; societal context; perceived value of the intervention by and impacts on individuals, community members, and the organization; partnerships; and access to digital health services, in-person services, digital services, and data and information, among others.

DISCUSSION: We suggest a consolidated definition of digital health equity, highlight illustrative frameworks, and suggest concepts that may be needed to enhance digital health equity intervention development and evaluation.

CONCLUSION: The expanded understanding of frameworks and relevant concepts resulting from this study may inform communities and stakeholders who seek to achieve digital inclusion and digital health equity.

RevDate: 2025-02-12
CmpDate: 2025-02-12

Krefer LT, WF Oliveira (2025)

[Reformulations in the national mental health policy: analysis of assistance data in the period from 2012 to 2022].

Ciencia & saude coletiva, 30(2):e13372023.

This article aims to analyze data on care in the field of public mental healthcare in Brazil from 2012 to 2022, corresponding to the years before and after the implementation of the New Mental Health Policy. For this purpose, quantitative methodology, of the longitudinal ecological study type, was used. Data was extracted for the period from 2012 to 2022. The sources used were Health Information Systems. The data was compiled into time series and analyzed using descriptive statistical techniques. The results pointed to the enhancement of outpatient services and a decrease in the expansion of Psychosocial Care Centers and Primary Care facilities after 2017, indicating compliance with the New Policy guidelines to deprioritize territorial and community-based services. The number of psychiatric hospitals showed little variation for the entire period, indicating not only alignment with the strengthening of hospital institutions indicated in the New Policy, but also weaknesses in the deinstitutionalization policy of the period prior to 2017. This study concludes that the effects of the changes in national policies on the organization, management and execution of the health system can be seen, but at the same time there is continuity in various aspects.

RevDate: 2025-02-12
CmpDate: 2025-02-12

Shukla S, Khan R, Chrzanowski Ł, et al (2025)

Advancing sustainable agriculture through multi-omics profiling of biosolids for safe application: A review.

Journal of environmental management, 375:124292.

Biosolids, derived from wastewater treatment processes, are valuable resources for soil amendment in agriculture due to their nutrient-rich composition. However, various contaminants of concern (CEC) such as pharmaceuticals, per-and poly-fluoroalkyl substances, endocrine disruptive chemicals, surfactants, pathogens, nanoplastics, and microplastics, are also reported in biosolids. The use of biosolids for agriculture may introduce these CEC into the soil, which raises concerns about their environmental and human health impacts. Moreover, the presence of pathogens (Escherichia coli, Salmonella sp., Shigella, Giardia, Rotavirus, etc.) even after treatment calls for microbial profiling of biosolids, especially in developing countries. Multi-omics approaches can be used as powerful tools for characterizing microbial communities and highlighting metabolic pathways. Moreover, these approaches also help in predicting the ecological and agronomic effects of biosolids application in agricultural soils. This review discusses the advantages and challenges of using biosolids in agriculture, considering the range of different CEC reported in biosolids. Moreover, the current legislation for the use of biosolids in agriculture is also presented, highlighting the limitations with respect to guidelines for emerging contaminants in biosolids. Furthermore, the role of the multi-omics approach in biosolids management, focusing on genomics, transcriptomics, proteomics, and metabolomics is also assessed. Multi-omics also allows for real-time monitoring, ensuring continuous optimization of biosolids towards changing environmental conditions. This dynamic approach not only enhances the safe use, but also enhances the sustainability of waste management practices, minimizing the negative effects. Finally, the future research directions for integrating the multi-omics approach into biosolid management practices are also suggested. The need for updating the legislative framework, continued innovation to promote sustainable and robust agricultural systems, bringing the process closer to the principles of a circular bioeconomy is also empahasized.

RevDate: 2025-02-12
CmpDate: 2025-02-12

Ghimire SR, Schumacher B, Swanson S, et al (2025)

Assessing riparian functioning condition for improved ecosystem services: A case study of the Back Creek watershed (Virginia, USA).

Journal of environmental management, 375:124154.

Riparian functioning condition refers to a rating and description of the current ecological status of a reach of a riparian ecosystem in consideration of its potential hydrology, vegetation, and geomorphology. Reach rating options are Proper Functioning Condition (PFC), Functional-At-Risk (FAR), Non-Functional, and apparent or monitored trends. We assessed the functioning condition of flowing riverbank areas of Back Creek located in Virginia (USA) following a PFC protocol developed by the U.S. Department of the Interior and the U.S. Department of Agriculture. The PFC protocol involves 17 qualitative assessment items that address three categories of attributes (hydrology, vegetation, and geomorphology); each is answered as "yes", "no," or "not applicable" with an explanation. We discussed key PFC items driving stream water quality contextualizing the previously modeled riparian buffer zones and ecosystem services tradeoffs in the Back Creek watershed published by U.S. Environmental Protection Agency. Using the remote sensing data in the Geographic Information System, we delineated and characterized 26 Back Creek reaches of 41.1 km length. We also analyzed the 38-year (1981-2018) daily datasets of the precipitation, surface runoff, temperature, soil moisture pattern, and vegetation types for the watershed. Then, we conducted the PFC assessments using field reconnaissance of 10 reaches, 19.3 km of the Back Creek. The field assessments concluded that 52% of the assessed length of Back Creek was in PFC, attributed to diverse vegetation, maintained channel characteristics, floodplain accessibility (where appropriate), and balanced water and sediment loading supplied by individual headwater streams to the Back Creek. 48% of the assessed length was in FAR condition due to land use changes and urban road network. This study provides an exemplar of nonpoint source (diffused pollution generated by land runoff) methodology for identifying key riparian functioning issues and assessing effectiveness of the non-point source best management practice programs.

RevDate: 2025-02-12
CmpDate: 2025-02-12

Wang S, Liping Y, M Arif (2025)

Evolutionary analysis of ecological-production-living space-carrying capacity in tourism-centric traditional villages in Guangxi, China.

Journal of environmental management, 375:124182.

The carrying capacity of ecological-production-living space (EPLS) is pivotal to the development of traditional villages and the optimization of their tourism industries. However, research on tourism-centric traditional villages in China remains limited. This study addresses this gap by examining EPLS carrying capacity in tourism-focused villages in Guangxi, China. Using remote sensing imagery of Chengyang Bazhai (CYBZ) along with data on local tourism and socio-economic development, the study classifies different types of EPLS and establishes a comprehensive indicator system. Geographic information system spatial analysis, combined with grey correlation analysis, was employed to assess the evolution of EPLS carrying capacity and its influencing factors in CYBZ. The findings indicate that between 2006 and 2015, the overall carrying capacity of EPLS experienced a decline. While the carrying capacity of production spaces remained relatively stable, ecological and living spaces saw notable decreases. However, from 2015 to 2021, EPLS carrying capacity increased substantially. The most substantial growth was observed in Pingyan Village, followed by Chengyang Village, with Pingfu Village exhibiting the smallest improvement. The expansion of the tourism industry has significantly influenced the evolution of EPLS carrying capacity in CYBZ, creating a greater need for strategic future planning. Optimal EPLS and durable tourism development require continuous enhancements in EPLS capacity, reductions in negative interactions between carrying capacity and tourism growth, as well as ecological revitalization. This study contributes to the existing literature by enhancing EPLS carrying capacity understanding. It offers theoretical guidance for its optimization in Chengyang and practical insights into sustainable tourism development in similar regions.

RevDate: 2025-02-12
CmpDate: 2025-02-12

Zhang WH, Gao JW, Lau CC, et al (2024)

Effects of different trophic conditions on total fatty acids, amino acids, pigment and gene expression profiles in Euglena gracilis.

World journal of microbiology & biotechnology, 40(10):325.

Euglena gracilis is a unique microalga that lacks a cell wall and is able to grow under different trophic culture conditions. In this study, cell growth, biomass production, and changes in the ultrastructure of E. gracilis cells cultivated photoautotrophically, mixotrophically, and under sequential-heterotrophy-photoinduction (SHP) were assessed. Mixotrophy induced the highest cell growth and biomass productivity (6.27 ± 0.59 mg/L/d) in E. gracilis, while the highest content of fatty acids, 2.69 ± 0.04% of dry cell weight (DCW) and amino acids, 38.16 ± 0.08% of DCW was obtained under SHP condition. E. gracilis also accumulated significantly higher saturated fatty acids and lower unsaturated fatty acids when cultivated under SHP condition. Transcriptomic analysis showed that the expression of photosynthetic genes (PsbA, PsbC, F-type ATPase alpha and beta) was lower, carbohydrate and protein synthetic genes (glnA, alg14 and fba) were expressed higher in SHP-culture cells when compared to other groups. Different trophic conditions also induced changes in the cell ultrastructure, where paramylon and starch granules were more abundant in SHP-cultured cells. The findings generated in this study illustrated that aerobic SHP cultivation of E. gracilis possesses great potential in human and animal feed applications.

RevDate: 2025-02-11

Wang L, Simopoulos CMA, Serrana JM, et al (2025)

PhyloFunc: phylogeny-informed functional distance as a new ecological metric for metaproteomic data analysis.

Microbiome, 13(1):50.

BACKGROUND: Beta-diversity is a fundamental ecological metric for exploring dissimilarities between microbial communities. On the functional dimension, metaproteomics data can be used to quantify beta-diversity to understand how microbial community functional profiles vary under different environmental conditions. Conventional approaches to metaproteomic functional beta-diversity often treat protein functions as independent features, ignoring the evolutionary relationships among microbial taxa from which different proteins originate. A more informative functional distance metric that incorporates evolutionary relatedness is needed to better understand microbiome functional dissimilarities.

RESULTS: Here, we introduce PhyloFunc, a novel functional beta-diversity metric that incorporates microbiome phylogeny to inform on metaproteomic functional distance. Leveraging the phylogenetic framework of weighted UniFrac distance, PhyloFunc innovatively utilizes branch lengths to weigh between-sample functional distances for each taxon, rather than differences in taxonomic abundance as in weighted UniFrac. Proof of concept using a simulated toy dataset and a real dataset from mouse inoculated with a synthetic gut microbiome and fed different diets show that PhyloFunc successfully captured functional compensatory effects between phylogenetically related taxa. We further tested a third dataset of complex human gut microbiomes treated with five different drugs to compare PhyloFunc's performance with other traditional distance methods. PCoA and machine learning-based classification algorithms revealed higher sensitivity of PhyloFunc in microbiome responses to paracetamol. We provide PhyloFunc as an open-source Python package (available at https://pypi.org/project/phylofunc/), enabling efficient calculation of functional beta-diversity distances between a pair of samples or the generation of a distance matrix for all samples within a dataset.

CONCLUSIONS: Unlike traditional approaches that consider metaproteomics features as independent and unrelated, PhyloFunc acknowledges the role of phylogenetic context in shaping the functional landscape in metaproteomes. In particular, we report that PhyloFunc accounts for the functional compensatory effect of taxonomically related species. Its effectiveness, ecological relevance, and enhanced sensitivity in distinguishing group variations are demonstrated through the specific applications presented in this study. Video Abstract.

RevDate: 2025-02-11

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

The genome sequence of the Bird-cherry Ermine moth, Yponomeuta evonymella (Linnaeus, 1758).

Wellcome open research, 9:618.

We present a genome assembly from an individual female Yponomeuta evonymella (the Bird-cherry Ermine; Arthropoda; Insecta; Lepidoptera; Yponomeutidae). The genome sequence has a total length of 572.70 megabases. Most of the assembly is scaffolded into 32 chromosomal pseudomolecules, including the trivalent sex chromosomes Z 1, Z 2 and W. The mitochondrial genome has also been assembled and is 16.16 kilobases in length.

RevDate: 2025-02-11
CmpDate: 2025-02-11

McKenzie-Smith GC, Wolf SW, Ayroles JF, et al (2025)

Capturing continuous, long timescale behavioral changes in Drosophila melanogaster postural data.

PLoS computational biology, 21(2):e1012753 pii:PCOMPBIOL-D-23-01766.

Animal behavior spans many timescales, from short, seconds-scale actions to daily rhythms over many hours to life-long changes during aging. To access longer timescales of behavior, we continuously recorded individual Drosophila melanogaster at 100 frames per second for up to 7 days at a time in featureless arenas on sucrose-agarose media. We use the deep learning framework SLEAP to produce a full-body postural dataset for 47 individuals resulting in nearly 2 billion pose instances. We identify stereotyped behaviors such as grooming, proboscis extension, and locomotion and use the resulting ethograms to explore how the flies' behavior varies across time of day and days in the experiment. We find distinct daily patterns in all stereotyped behaviors, adding specific information about trends in different grooming modalities, proboscis extension duration, and locomotion speed to what is known about the D. melanogaster circadian cycle. Using our holistic measurements of behavior, we find that the hour after dawn is a unique time point in the flies' daily pattern of behavior, and that the behavioral composition of this hour tracks well with other indicators of health such as locomotion speed and the fraction of time spend moving vs. resting. The method, data, and analysis presented here give us a new and clearer picture of D. melanogaster behavior across timescales, revealing novel features that hint at unexplored underlying biological mechanisms.

RevDate: 2025-02-11
CmpDate: 2025-02-11

Ji G, Wang Y, Lu Z, et al (2025)

Associations between ambient benzene and stroke, and the mediating role of accelerated biological aging: Findings from the UK biobank.

Environmental pollution (Barking, Essex : 1987), 367:125656.

Benzene can cause respiratory diseases. However, the associations between benzene and stroke are unclear. A total of 13,116 patients with stroke and 377,120 controls from the UK Biobank were included. The benzene exposure concentrations were matched on the basis of the address information of each participant via a data form from the UK Department for Environment, Food and Rural Affairs. Weighted Cox regression was used to investigate the association between benzene and stroke risk. The polygenic risk score (PRS) was used to observe the joint effects of benzene exposure and genetic factors on stroke risk. We conducted a mediation analysis to investigate the mediating role of accelerated biological aging in this cohort study. After adjusting for covariates, every 1 μg/m[3] increase in benzene exposure increased the risk of stroke by 70%, which may be mediated by accelerated biological aging. The population with high benzene exposure concentrations and high PRSs had a 44% greater risk of stroke than did those with low benzene exposure concentrations and low PRSs. Benzene exposure and the PRS have joint effects on the risk of stroke. Benzene exposure was associated with stroke risk, possibly through increased biological aging, and the PRS modified this association.

RevDate: 2025-02-10

Song J, Zhou S, Kwan MP, et al (2025)

The time-lagged effect of noise exposure on noise annoyance: The role of temporal, spatial and social contexts.

Social science & medicine (1982), 368:117817 pii:S0277-9536(25)00146-7 [Epub ahead of print].

While some research has examined the time-lagged effect of restorative soundscape in specific contexts (e.g., parks), how the time-lagged effect of noise annoyance during people's daily activities may vary across different temporal, spatial, and social contexts remains largely unknown. To address this research gap, we utilized Ecological Momentary Assessment (EMA) data to measure people's real-time noise annoyance and activity diary data to assess their time-lagged noise annoyance. Real-time noise exposure was captured by portable noise sensors. We employed fixed effects ordered panel logistic regression to examine the effects of different thresholds of noise levels on people's time-lagged noise annoyance, and how it varied across different temporal, spatial, and social contexts. The results indicated that: (1) there were significant time-lagged effects between participants' real-time noise exposure and their time-lagged noise annoyance; (2) participants' time-lagged noise annoyance associated with an activity was influenced by its temporal, spatial, and social contexts, particularly on weekdays; (3) participants' time-lagged noise annoyance was significantly associated with measured noise levels, with the highest coefficient for 65 dB, followed by 70 dB; and (4) there were significant interaction effects between noise levels and temporal-spatial-social contexts on participants' time-lagged noise annoyance (particularly when noise levels exceeded 70 dB). These findings enhance our understanding and have crucial implications for the implementation of noise control policies, which should consider not only noise levels but also the time-lagged effects of noise, particularly on weekdays, at outdoor recreational activity sites, as well as the potential vulnerabilities of individuals experiencing noise exposure in isolation.

RevDate: 2025-02-10

Güneri FD, Karaarslan F, Özen H, et al (2025)

Medical mud-pack treatment with different temperatures in patients with knee osteoarthritis.

International journal of biometeorology [Epub ahead of print].

To compare the effects of medical mud-pack (MMP) treatments applied at different temperatures on the pain and joint functions of patients with knee osteoarthritis (KOA). Kellgren Lawrence (KL) stage 3 or 4 KOA patients were included and randomized into three groups. Patients in groups 1, 2, and 3 took MMP treatment to both knees at 39 °C, 42 °C, and 45 °C, respectively. The treatment was performed for 12 days (only weekdays) and was 30 min long per day. The same blinded physician evaluated the patients at baseline and at the end of the treatment. The assessments were done before and after the intervention. The primary outcome was to achieve a minimal clinically important improvement (MCII) for KOA (decrease of at least 19 mm (-40.8%) on the VAS for pain, a decrease of 18.3 mm (-39%) on the patient's global assessment (PGA), and/or a decrease of at least 9.1 points (-26%) on the Western Ontario and McMaster Universities Osteoarthritis Index function subscale (WOMAC-FS). Secondary outcomes were pain (VAS), patient's global assessment (VAS), physician's global assessment (VAS), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Patient's health state, Patient Acceptable Symptom State (PASS). 217 patients were analyzed. Groups 1, 2, and 3 had 68, 81,68 patients, respectively. The MCII measurement revealed that MMP treatment did not show a significant difference between groups 2 and 3 (p > 0.05). Also, it was observed that more patients in groups 2 and 3 reached the MCII compared to group 1 (p < 0.001). For the secondary outcomes, significant improvements were observed within-group evaluations for each of the three groups (p < 0.001). Between groups comparisons, the improvements at the end of the treatment were found to be superior for group 2 and group 3 compared to group 1 (p < 0.001). There was no statistically significant difference between groups 2 and 3 for any parameters (p > 0.05). The number of patients who achieved the PASS was statistically lower for group 1 compared to groups 2 and 3 (p < 0.001). We observed significant improvements in all groups after treatment. The main result, as measured by MCII, suggests that MMP treatments at 42-45 °C is more effective than at 39 °C in managing severe KOA patients' pain and functional status. We found no significant difference in pain and joint function improvement between 42 °C and 45 °C after MMP.

RevDate: 2025-02-10
CmpDate: 2025-02-10

Hozé N, Pons-Salort M, Metcalf CJE, et al (2025)

RSero: A user-friendly R package to reconstruct pathogen circulation history from seroprevalence studies.

PLoS computational biology, 21(2):e1012777 pii:PCOMPBIOL-D-24-00337.

Population-based serological surveys are a key tool in epidemiology to characterize the level of population immunity and reconstruct the past circulation of pathogens. A variety of serocatalytic models have been developed to estimate the force of infection (FOI) (i.e., the rate at which susceptible individuals become infected) from age-stratified seroprevalence data. However, few tool currently exists to easily implement, combine, and compare these models. Here, we introduce an R package, Rsero, that implements a series of serocatalytic models and estimates the FOI from age-stratified seroprevalence data using Bayesian methods. The package also contains a series of features to perform model comparison and visualise model fit. We introduce new serocatalytic models of successive outbreaks and extend existing models of seroreversion to any transmission model. The different features of the package are illustrated with simulated and real-life data. We show we can identify the correct epidemiological scenario and recover model parameters in different epidemiological settings. We also show how the package can support serosurvey study design in a variety of epidemic situations. This package provides a standard framework to epidemiologists and modellers to study the dynamics of past pathogen circulation from cross-sectional serological survey data.

RevDate: 2025-02-10
CmpDate: 2025-02-10

Brock MT, Morrison HG, Maignien L, et al (2024)

Impacts of sample handling and storage conditions on archiving physiologically active soil microbial communities.

FEMS microbiology letters, 371:.

Soil microbial communities are fundamental to ecosystem processes and plant growth, yet community composition is seasonally and successionally dynamic, which interferes with long-term iterative experimentation of plant-microbe interactions. We explore how soil sample handling (e.g. filtering) and sample storage conditions impact the ability to revive the original, physiologically active, soil microbial community. We obtained soil from agricultural fields in Montana and Oklahoma, USA and samples were sieved to 2 mm or filtered to 45 µm. Sieved and filtered soil samples were archived at -20°C or -80°C for 50 days and revived for 2 or 7 days. We extracted DNA and the more transient RNA pools from control and treatment samples and characterized microbial communities using 16S amplicon sequencing. Filtration and storage treatments significantly altered soil microbial communities, impacting both species richness and community composition. Storing sieved soil at -20°C did not alter species richness and resulted in the least disruption to the microbial community composition in comparison to nonarchived controls as characterized by RNA pools from soils of both sites. Filtration significantly altered composition but not species richness. Archiving sieved soil at -20°C could allow for long-term and repeated experimentation on preserved physiologically active microbial communities.

RevDate: 2025-02-09

Lucca E, Kofinas D, Avellán T, et al (2025)

Integrating "nature" in the water-energy-food Nexus: Current perspectives and future directions.

The Science of the total environment, 966:178600 pii:S0048-9697(25)00234-7 [Epub ahead of print].

Integrated approaches for managing natural resources are said to meet increasing demand for water, energy, and food, while maintaining the integrity of ecosystems, and ensuring equitable access to resources. The Water-Energy-Food (WEF) Nexus has been proposed as a cross-sectoral approach to manage trade-offs and exploit synergies that arise among these sectors. Although not initially included as a component of the Nexus, the role of nature in sustaining the water, energy, and food sectors and in regulating their interrelationships is increasingly recognised by Nexus researchers and practitioners. To converge existing approaches that integrate nature into the WEF Nexus and suggest a common framework, we - an interdisciplinary group of natural resources management researchers and systems thinkers from the European research network NEXUSNET COST Action - followed a collaborative process of knowledge creation combining literature review, elicitation of expert opinion and collaborative writing. Our results reveal a multiplicity of concepts utilised in the literature to represent, partially or fully, "nature" in the Nexus, such as "environment", "ecosystems", "ecosystem services", "social-ecological systems", and "biodiversity". Disparity was also found in the role attributed to nature, represented by three key paradigms: (1) ecosystems as the fourth component of an expanded Nexus, i.e., the WEF-Ecosystems (WEFE) Nexus; (2) ecosystems as a foundational layer to the Nexus; and (3) the WEF Nexus as a central component of social-ecological systems (SES). By creating a hybrid approach that brings together the benefits of the respective paradigms, we present a forward-looking WEFE Nexus conceptualisation. This paradigm expands the mutual interlinkages among water, energy and food to the entirety of SES, thus acknowledging the social-ecological processes that are affected by and affect the WEF Nexus. The results of this collaborative research effort intend to provide researchers and stakeholders with means to better understand and ultimately manage Nexus issues towards a transformative change.

RevDate: 2025-02-09

de Melo LRS, Dos Santos Pereira J, Melo MS, et al (2025)

Spatial and temporal dynamic of colorectal cancer mortality in Brazil: A nationwide population-based study of four decades (1980-2021).

Cancer epidemiology, 95:102766 pii:S1877-7821(25)00025-6 [Epub ahead of print].

BACKGROUND: Regardless of being preventable through screening strategies and prompt diagnosis, deaths from colorectal cancer (CRC) still represent a serious public health concern in Brazil, with more than 20 thousand deaths annually. Herein, we aimed to assess the temporal trends and spatiotemporal patterns of CRC mortality in all Brazilian states.

METHODS: An ecological study using temporal and spatial analysis techniques on deaths due to CRC as the underlying cause in Brazil from 1980 to 2021 was conducted. Death certificate and population data were provided by the Department of Informatics of the Unified Health System (DATASUS) and by the Brazilian Institute of Geography and Statistics (IBGE), respectively.

RESULTS: A total of 395,782 deaths from CRC were recorded in this period and most of them were in female (205,479; 51.92 %), ≥ 65 years old (233,059; 58.89 %), diagnosed with malignant neoplasm of the colon (212,277; 53.63 %), with 1-7 years of education (157.564; 39.81 %), married (192.276; 48.58 %), hospital as place of death (331.393; 83.73 %) and white (212.666; 65.07 %). Moreover, there was an increasing temporal trend in the Northeast region (APC: 2.6; p < 0.05), men (APC: 1.5; p < 0.05) and 45-64 years old (APC: 1.2; p < 0.05). Also, the spatial analysis showed positive spatial autocorrelation in all periods, with the South and Southeast regions presenting the highest concentration of high-risk clusters CRC deaths. Nevertheless, high-risk clusters were also observed in capitals and municipalities in metropolitan regions in the Northeast region.

CONCLUSIONS: In general, a temporal and spatial expansion of CRC mortality has been observed in Brazil over the last few decades.

RevDate: 2025-02-08
CmpDate: 2025-02-08

Asuako PAG, Stojan R, Bock O, et al (2025)

Multitasking: does task-switching add to the effect of dual-tasking on everyday-like driving behavior?.

Cognitive research: principles and implications, 10(1):5.

It is well established that performing multiple tasks simultaneously (dual-tasking) or sequentially (task-switching) degrades performance on one or both tasks. However, it is unknown whether task-switching adds to the effects of dual-tasking in a single setup. We investigated this in a simulated everyday-like car driving scenario. We expected an additive effect of task-switching on dual-tasking, leading to a stronger deterioration of driving performance due to the increased cognitive load required to handle multiple task-sets. Forty-five young adults aged 18 to 30 years (age: 23.62 ± 2.51, 28 females) were instructed to follow a lead car driving at a constant speed of 70 km/h through a rural landscape while concurrently performing additional tasks. The additional tasks were typing and arguing, in response to stimuli presented visually or auditorily. The tasks were presented either in separate blocks or in intermixed order (conditions: repetitive vs. switching). Driving performance was assessed by use of the average velocity and the standard deviation of lateral position, and performance in the additional tasks was assessed by reaction time. Linear-mixed effect models revealed better performance in the repetitive, compared to the switch condition only for the standard deviation of the lateral lane position while performing the additional typing task. This provides limited evidence for the view that task-switching adds to the challenges of dual-tasking. We therefore posit that already dual-tasking alone involves processing demands that are not substantially increased by adding switching demands.

RevDate: 2025-02-08
CmpDate: 2025-02-08

Sha J, Liu X, Wang H, et al (2025)

Status and habitat suitability evaluation: A case study of the typical temperate seagrass beds in the Bohai Sea, China.

Marine environmental research, 204:106873.

Seagrass beds serve crucial ecological functions, yet they are facing a severe decline necessitating immediate conservation and restoration efforts. Current assessments of seagrass habitat suitability are insufficient, thus hindering the restoration effects. This study used a combination of field surveys and satellite remote sensing to conduct a three-year monitoring of typical temperate seagrass beds in the Caofeidian and Xingcheng areas of the Bohai Sea. The relationships between seagrass community factors and environmental factors were investigated using Spearman correlation analysis, BIOENV analysis, and redundancy analysis (RDA). Subsequently, the weights of each environmental factor were determined using the Analytic Hierarchy Process (AHP), leading to the development of the Habitat Suitability Index (HSI). Seagrass habitat suitability maps for Caofeidian and Xingcheng areas were then generated using Geographic Information System (GIS). The results indicate that both seagrass ecosystems degraded during the study period, which coincided with a decreasing trend in habitat suitability shown by the suitability maps. This study provides a methodology for seagrass bed habitat suitability assessment, thereby contributing to the conservation and restoration of these vital ecosystems.

RevDate: 2025-02-07

Lysholm S, Chaters GL, Di Bari C, et al (2025)

A framework for quantifying the multisectoral burden of animal disease to support decision making.

Frontiers in veterinary science, 12:1476505.

Animal diseases have wide-ranging impacts in multiple societal arenas, including agriculture, public health and the environment. These diseases cause significant economic losses for farmers, disrupt food security and present zoonotic risks to human populations. Additionally, they contribute to antimicrobial resistance and a range of environmental issues such as greenhouse gas emissions. The societal and ecological costs of livestock diseases are frequently underrepresented or unaddressed in policy decisions and resource allocations. Social cost-benefit analysis (SCBA) offers a comprehensive framework to evaluate the broad impacts of animal diseases across different sectors. This approach aligns with the One Health concept, which seeks to integrate and optimize the health of humans, animals and the environment. Traditional economic evaluations often focus narrowly on profit maximization within the livestock sector, neglecting wider externalities such as public health and environmental impacts. In contrast, SCBA takes a multi-sectoral whole-system view, considering multiple factors to guide public and private sector investments toward maximizing societal benefits. This paper discusses three separate sector specific (Animal health, Human health, Environmental health) methodologies for quantifying the burden of animal diseases. It then discusses how these estimates can be combined to generate multisectoral estimates of the impacts of animal diseases on human societies and the environment using monetary values. Finally this paper explores how this framework can support the evaluation of interventions from a One Health perspective though SCBA. This integrated assessment framework supports informed decision-making and resource allocation, ultimately contributing to improved public health outcomes, enhanced animal welfare, and greater environmental sustainability.

RevDate: 2025-02-07
CmpDate: 2024-12-23

Borton MA, McGivern BB, Willi KR, et al (2025)

A functional microbiome catalogue crowdsourced from North American rivers.

Nature, 637(8044):103-112.

Predicting elemental cycles and maintaining water quality under increasing anthropogenic influence requires knowledge of the spatial drivers of river microbiomes. However, understanding of the core microbial processes governing river biogeochemistry is hindered by a lack of genome-resolved functional insights and sampling across multiple rivers. Here we used a community science effort to accelerate the sampling, sequencing and genome-resolved analyses of river microbiomes to create the Genome Resolved Open Watersheds database (GROWdb). GROWdb profiles the identity, distribution, function and expression of microbial genomes across river surface waters covering 90% of United States watersheds. Specifically, GROWdb encompasses microbial lineages from 27 phyla, including novel members from 10 families and 128 genera, and defines the core river microbiome at the genome level. GROWdb analyses coupled to extensive geospatial information reveals local and regional drivers of microbial community structuring, while also presenting foundational hypotheses about ecosystem function. Building on the previously conceived River Continuum Concept[1], we layer on microbial functional trait expression, which suggests that the structure and function of river microbiomes is predictable. We make GROWdb available through various collaborative cyberinfrastructures[2,3], so that it can be widely accessed across disciplines for watershed predictive modelling and microbiome-based management practices.

RevDate: 2025-02-06

Gould E, Fraser HS, Parker TH, et al (2025)

Same data, different analysts: variation in effect sizes due to analytical decisions in ecology and evolutionary biology.

BMC biology, 23(1):35.

Although variation in effect sizes and predicted values among studies of similar phenomena is inevitable, such variation far exceeds what might be produced by sampling error alone. One possible explanation for variation among results is differences among researchers in the decisions they make regarding statistical analyses. A growing array of studies has explored this analytical variability in different fields and has found substantial variability among results despite analysts having the same data and research question. Many of these studies have been in the social sciences, but one small "many analyst" study found similar variability in ecology. We expanded the scope of this prior work by implementing a large-scale empirical exploration of the variation in effect sizes and model predictions generated by the analytical decisions of different researchers in ecology and evolutionary biology. We used two unpublished datasets, one from evolutionary ecology (blue tit, Cyanistes caeruleus, to compare sibling number and nestling growth) and one from conservation ecology (Eucalyptus, to compare grass cover and tree seedling recruitment). The project leaders recruited 174 analyst teams, comprising 246 analysts, to investigate the answers to prespecified research questions. Analyses conducted by these teams yielded 141 usable effects (compatible with our meta-analyses and with all necessary information provided) for the blue tit dataset, and 85 usable effects for the Eucalyptus dataset. We found substantial heterogeneity among results for both datasets, although the patterns of variation differed between them. For the blue tit analyses, the average effect was convincingly negative, with less growth for nestlings living with more siblings, but there was near continuous variation in effect size from large negative effects to effects near zero, and even effects crossing the traditional threshold of statistical significance in the opposite direction. In contrast, the average relationship between grass cover and Eucalyptus seedling number was only slightly negative and not convincingly different from zero, and most effects ranged from weakly negative to weakly positive, with about a third of effects crossing the traditional threshold of significance in one direction or the other. However, there were also several striking outliers in the Eucalyptus dataset, with effects far from zero. For both datasets, we found substantial variation in the variable selection and random effects structures among analyses, as well as in the ratings of the analytical methods by peer reviewers, but we found no strong relationship between any of these and deviation from the meta-analytic mean. In other words, analyses with results that were far from the mean were no more or less likely to have dissimilar variable sets, use random effects in their models, or receive poor peer reviews than those analyses that found results that were close to the mean. The existence of substantial variability among analysis outcomes raises important questions about how ecologists and evolutionary biologists should interpret published results, and how they should conduct analyses in the future.

RevDate: 2025-02-05

Fatima M, Butt I, MohammadEbrahimi S, et al (2025)

Spatiotemporal clusters of acute respiratory infections associated with socioeconomic, meteorological, and air pollution factors in South Punjab, Pakistan.

BMC public health, 25(1):469.

BACKGROUND: In Pakistan, acute respiratory infections (ARI) continue to be a major public health problem. However, there is still a lack of scholarly work regarding different environmental and socioeconomic influencing factors and how they interact with respiratory infections. Furthermore, we do not know much about geographic variation in this context. Therefore, our study examines the ecological-level spatial and temporal patterns of acute respiratory infection incidence (ARI) and their geographic relationship with selected socio-economic, meteorological, and air pollution factors in Pakistan.

METHODS: We applied the spatiotemporal scan statistics to examine the purely temporal, spatial, and spatiotemporal clusters of ARI in South Punjab, Pakistan for five years (2016-2020). Generalized Linear Model (GLM) and geographically weighted regression (GWR) were also applied to model the linear and non-linear spatial relationships between selected variables and ARI.

RESULTS: Our results indicate that in the central and northern regions of Pakistan, two spatial clusters of ARI were present, accounting for 28.5% of the total cases. A spatiotemporal cluster with a relative risk of 1.57 was discovered in the northeastern area. The results obtained from the season-based GLM highlighted the significance of climatic factors (temperature, fog, dust storms) and air pollutants (NO2) in influencing ARI incidence, while socio-economic variables (rural population, literacy) had limited impact. In addition, GWR revealed that the relationships between predictors and ARI incidence varied across locations, emphasizing the importance of considering local settings. Season-based non-stationary GLM revealed a multifaceted interaction among socio-economic, meteorological, and air pollution factors.

CONCLUSIONS: Our study provides evidence about environmental and socio-economic factors significantly associated with ARI incidence. In addition, this study provides the first baseline of ARI cases in Pakistan to plan for intervention and adaptation strategies and may be replicated in other regions of comparable settings worldwide.

RevDate: 2025-02-05

Hebert JD, Tang YJ, Szamecz M, et al (2025)

Combinatorial in vivo genome editing identifies widespread epistasis and an accessible fitness landscape during lung tumorigenesis.

Molecular biology and evolution pii:8002229 [Epub ahead of print].

Lung adenocarcinoma, the most common subtype of lung cancer, is genomically complex, with tumors containing tens to hundreds of non-synonymous mutations. However, little is understood about how genes interact with each other to enable the evolution of cancer in vivo, largely due to a lack of methods for investigating genetic interactions in a high-throughput and quantitative manner. Here, we employed a novel platform to generate tumors with inactivation of pairs of ten diverse tumor suppressor genes within an autochthonous mouse model of oncogenic KRAS-driven lung cancer. By quantifying the fitness of tumors with every single and double mutant genotype, we show that most tumor suppressor genetic interactions exhibited negative epistasis, with diminishing returns on tumor fitness. In contrast, Apc inactivation showed positive epistasis with the inactivation of several other genes, including synergistic effects on tumor fitness in combination with Lkb1 or Nf1 inactivation. Sign epistasis was extremely rare, suggesting a surprisingly accessible fitness landscape during lung tumorigenesis. These findings expand our understanding of the evolutionary interactions that drive tumorigenesis in vivo.

RevDate: 2025-02-05

Palande S, Arsenault J, Basurto-Lozada P, et al (2025)

Expression-based machine learning models for predicting plant tissue identity.

Applications in plant sciences, 13(1):e11621.

PREMISE: The selection of Arabidopsis as a model organism played a pivotal role in advancing genomic science. The competing frameworks to select an agricultural- or ecological-based model species were rejected, in favor of building knowledge in a species that would facilitate genome-enabled research.

METHODS: Here, we examine the ability of models based on Arabidopsis gene expression data to predict tissue identity in other flowering plants. Comparing different machine learning algorithms, models trained and tested on Arabidopsis data achieved near perfect precision and recall values, whereas when tissue identity is predicted across the flowering plants using models trained on Arabidopsis data, precision values range from 0.69 to 0.74 and recall from 0.54 to 0.64.

RESULTS: The identity of belowground tissue can be predicted more accurately than other tissue types, and the ability to predict tissue identity is not correlated with phylogenetic distance from Arabidopsis. k-nearest neighbors is the most successful algorithm, suggesting that gene expression signatures, rather than marker genes, are more valuable to create models for tissue and cell type prediction in plants.

DISCUSSION: Our data-driven results highlight that the assertion that knowledge from Arabidopsis is translatable to other plants is not always true. Considering the current landscape of abundant sequencing data, we should reevaluate the scientific emphasis on Arabidopsis and prioritize plant diversity.

RevDate: 2025-02-05
CmpDate: 2025-02-05

Andorf CM, Ross-Ibarra J, Seetharam AS, et al (2025)

A unified VCF dataset from nearly 1,500 diverse maize accessions and resources to explore the genomic landscape of maize.

G3 (Bethesda, Md.), 15(2):.

Efforts to capture and analyze maize nucleotide diversity have ranged widely in scope, but differences in reference genome version and software algorithms used in these efforts inhibit comparison, and these data are generally not available in an easy-to-use visualization platform for quick access and analysis. To address these issues, The Maize Genetics and Genomics Database has collaborated with maize researchers to offer variant data from a diverse set of 1,498 inbred lines, traditional varieties, and teosintes through a standardized variant-calling pipeline against version 5 of the B73 reference genome. The output was filtered for mapping quality, completeness, and linkage disequilibrium, and annotated based on variant effects relative to the B73 RefGen_v5 gene annotations. MaizeGDB has also updated a web tool, SNPversity 2.0, to filter, visualize, and download genotype sets based on genomic locations and accessions of interest, and added external datasets to demonstrate SNPversity 2.0's broad usage. MaizeGDB plans to host annual updates of these resources as additional resequencing data become available, with plans to expand to all publicly available sequence data.

RevDate: 2025-02-04
CmpDate: 2025-02-04

Mihaljevic JR, DJ Páez (2025)

Systematic shifts in the variation among host individuals must be considered in climate-disease theory.

Proceedings. Biological sciences, 292(2040):20242515.

To make more informed predictions of host-pathogen interactions under climate change, studies have incorporated the thermal performance of host, vector and pathogen traits into disease models to quantify effects on average transmission rates. However, this body of work has omitted the fact that variation in susceptibility among individual hosts affects disease spread and long-term patterns of host population dynamics. Furthermore, and especially for ectothermic host species, variation in susceptibility is likely to be plastic, influenced by variables such as environmental temperature. For example, as host individuals respond idiosyncratically to temperature, this could affect the population-level variation in susceptibility, such that there may be predictable functional relationships between variation in susceptibility and temperature. Quantifying the relationship between temperature and among-host trait variation will therefore be critical for predicting how climate change and disease will interact to influence host-pathogen population dynamics. Here, we use a model to demonstrate how short-term effects of temperature on the distribution of host susceptibility can drive epidemic characteristics, fluctuations in host population sizes and probabilities of host extinction. Our results emphasize that more research is needed in disease ecology and climate biology to understand the mechanisms that shape individual trait variation, not just trait averages.

RevDate: 2025-02-04

Thomas GWC, Hughes JJ, Kumon T, et al (2025)

The genomic landscape, causes, and consequences of extensive phylogenomic discordance in murine rodents.

Genome biology and evolution pii:7998737 [Epub ahead of print].

A species tree is a central concept in evolutionary biology whereby a single branching phylogeny reflects relationships among species. However, the phylogenies of different genomic regions often differ from the species tree. Although tree discordance is widespread in phylogenomic studies, we still lack a clear understanding of how variation in phylogenetic patterns is shaped by genome biology or the extent to which discordance may compromise comparative studies. We characterized patterns of phylogenomic discordance across the murine rodents - a large and ecologically diverse group that gave rise to the laboratory mouse and rat model systems. Combining recently published linked-read genome assemblies for seven murine species with other available rodent genomes, we first used ultra-conserved elements (UCEs) to infer a robust time-calibrated species tree. We then used whole genomes to examine finer-scale patterns of discordance across ∼12 million years of divergence. We found that proximate chromosomal regions tended to have more similar phylogenetic histories. There was no clear relationship between local tree similarity and recombination rates in house mice, but we did observe a correlation between recombination rates and average similarity to the species tree. We also detected a strong influence of linked selection whereby purifying selection at UCEs led to appreciably less discordance. Finally, we show that assuming a single species tree can result in substantial deviation from the results with gene trees when testing for positive selection under different models. Collectively, our results highlight the complex relationship between phylogenetic inference and genome biology and underscore how failure to account for this complexity can mislead comparative genomic studies.

RevDate: 2025-02-04
CmpDate: 2025-02-04

Gulyaeva A, Liu L, Garmaeva S, et al (2025)

Identification and characterization of Faecalibacterium prophages rich in diversity-generating retroelements.

Microbiology spectrum, 13(2):e0106624.

Metagenomics has revealed the incredible diversity of phages within the human gut. However, very few of these phages have been subjected to in-depth experimental characterization. One promising method of obtaining novel phages for experimental characterization is through induction of the prophages integrated into the genomes of cultured gut bacteria. Here, we developed a bioinformatic approach to prophage identification that builds on prophage genomic properties, existing prophage-detecting software, and publicly available virome sequencing data. We applied our approach to 22 strains of bacteria belonging to the genus Faecalibacterium, resulting in identification of 15 candidate prophages, and validated the approach by demonstrating the activity of five prophages from four of the strains. The genomes of three active phages were identical or similar to those of known phages, while the other two active phages were not represented in the Viral RefSeq database. Four of the active phages possessed a diversity-generating retroelement (DGR), and one retroelement had two variable regions. DGRs of two phages were active at the time of the induction experiments, as evidenced by nucleotide variation in sequencing reads. We also predicted that the host range of two active phages may include multiple bacterial species. Finally, we noted that four phages were less prevalent in the metagenomes of inflammatory bowel disease patients compared to a general population cohort, a difference mainly explained by differences in the abundance of the host bacteria. Our study highlights the utility of prophage identification and induction for unraveling phage molecular mechanisms and ecological interactions.IMPORTANCEWhile hundreds of thousands of phage genomes have been discovered in metagenomics studies, only a few of these phages have been characterized experimentally. Here, we explore phage characterization through bioinformatic identification of prophages in genomes of cultured bacteria, followed by prophage induction. Using this approach, we detect the activity of five prophages in four strains of commensal gut bacteria Faecalibacterium. We further note that four of the prophages possess diversity-generating retroelements implicated in rapid mutation of phage genome loci associated with phage-host and phage-environment interactions and analyze the intricate patterns of retroelement activity. Our study highlights the potential of prophage characterization for elucidating complex molecular mechanisms employed by the phages.

RevDate: 2025-02-03
CmpDate: 2025-02-03

Vysakh VG, Sukumaran S, Sebastian W, et al (2025)

The transcriptomic footprint of Mytella strigata: de novo transcriptome assembly of a major invasive species.

Scientific data, 12(1):201.

Mytella strigata, a potentially invasive species native to South America, is rapidly spreading across various aquatic ecosystems around the globe, posing a threat to native mussels. This study presents the first comprehensive de novo transcriptome assembly of M. strigata. We generated 254 million reads, which were processed and assembled using the Trinity assembler, resulting in 60362 transcripts with an N50 of 1,578 bp and over 93-98% completeness, as confirmed by BUSCO analysis with multiple ortho-datasets. A number of databases were used for functional annotation, including UniProt, KEGG, Reactome, InterPro, and eggNOG. Gene Ontology and pathway analyses identified transcripts associated with key biological processes, including those associated with cell signalling, metabolism, stress responses, cancer pathways, and immune regulation. This dataset enriches the bivalve database by advancing the understanding of the adaptive success and evolutionary resilience of this invasive species. The present study provides a fundamental framework for future research on the ecological and evolutionary impacts of this invasive species.

RevDate: 2025-02-03
CmpDate: 2025-02-03

Sheen JK, Kennedy-Shaffer L, Levy MZ, et al (2025)

Design of field trials for the evaluation of transmissible vaccines in animal populations.

PLoS computational biology, 21(2):e1012779 pii:PCOMPBIOL-D-23-01443.

Vaccines which can transmit from vaccinated to unvaccinated animals may be especially useful for increasing immunity in hard to reach populations or in populations where achieving high coverage is logistically infeasible. However, gauging the public health utility for future use of such transmissible vaccines and assessing their risk-benefit tradeoff, given their potential for unintended evolution, hinges on accurate estimates of their indirect protective effect. Here, we establish the conditions under which a two-stage randomized field trial can characterize the protective effects of a transmissible vaccine relative to a traditional vaccine. We contrast the sample sizes required to adequately power these trials when the vaccine is weakly and strongly transmissible. We also identify how required sample sizes change based on the characteristics of host ecology such as the overdispersion of the contact structure of the population, as well as the efficacy of the vaccine and timing of vaccination. Our results indicate the range of scenarios where two-stage randomized field trial designs are feasible and appropriate to capture the protective effects of transmissible vaccines. Our estimates identify the protective benefit of using transmissible vaccines compared to traditional vaccines, and thus can be used to weigh against evolutionary risks.

RevDate: 2025-02-03

Doshi P, Klas M, Kyzek S, et al (2025)

Investigating the effect of plasma activated water on entomopathogenic nematodes under laboratory conditions.

Heliyon, 11(2):e42038.

Entomopathogenic nematodes are currently being tested for their efficiency in controlling several insect pests. In recent years, non-thermal plasma has been investigated as a state-of-the-art technology for its disinfection/decontamination properties on the seed surface. In addition, it is also used to induce seed germination. In this investigation, the effect of plasma activated water (PAW) was tested on three EPN species, namely Steinernema feltiae Filipjev (1934), S. carpocapsae Weiser (1955), and Heterorhabditis bacteriophora Poinar (1976). Seven different PAW prepared at different treatment times, that is, (1s, 3s, 5s, 10s, 20s, 60s, 90s) were tested directly on the three selected nematode species. Distilled water was used as a control treatment (0s). In the case of H. bacteriophora, significantly higher mortality was observed in PAW preparation times of 5, 10, 20, 60 and 90s compared to the control. In the case of S. feltiae, significantly high mortality was observed for PAW preparation times of 10, 20, 60 and 90s. However, S. carpocapsae was found to have the least sensitivity against all PAW treatments, with a maximum mortality of 14 % (<20 %), indicating the potential synergy between PAW and EPNs. The possibility of combined treatments in the context of integrated pest management is presented and discussed.

RevDate: 2025-02-03

Loukili I, Laamrani A, El Ghorfi M, et al (2025)

Monitoring land changes at an open mine site using remote sensing and multi-spectral indices.

Heliyon, 11(2):e41845.

This study investigates the growth of mining activities in Benguerir, one of Morocco's largest and fastest-growing phosphate mines and a global leader in phosphate production, using remote sensing and ancillary data. The study examines spatio-temporal changes in land use and land cover (LULC) within this phosphate mining city to analyze the impacts of mining on agricultural areas, built-up lands, and water bodies over time. A series of images from 1984 to 2021 were processed in to assess patterns of change within the city. Five LULC maps were generated using supervised classification with the maximum likelihood method, providing detailed insights into both urban and non-urban transformations during the study period. Classification quality was evaluated using accuracy assessment and the Kappa index. Additionally, multi-spectral indices, including the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), and Normalized Difference Built-up Index (NDBI), were simulated and analyzed across four intervals. The results reveal significant variations in LULC and ecological indices over time, which are associated with mining activities, water stress, urban sprawl, and socio-economic changes in the region.These results provide a valuable means for decision-makers and planners to effectively manage the spaces and lands in the future.

RevDate: 2025-02-03

Milling M, Rampp SDN, Triantafyllopoulos A, et al (2025)

Automating airborne pollen classification: Identifying and interpreting hard samples for classifiers.

Heliyon, 11(2):e41656.

Deep-learning-based classification of pollen grains has been a major driver towards automatic monitoring of airborne pollen. Yet, despite an abundance of available datasets, little effort has been spent to investigate which aspects pose the biggest challenges to the (often black-box- resembling) pollen classification approaches. To shed some light on this issue, we conducted a sample-level difficulty analysis based on the likelihood for one of the largest automatically-generated datasets of pollen grains on microscopy images and investigated the reason for which certain airborne samples and specific pollen taxa pose particular problems to deep learning algorithms. It is here concluded that the main challenges lie in A) the (partly) co-occurring of multiple pollen grains in a single image, B) the occlusion of specific markers through the 2D capturing of microscopy images, and C) for some taxa, a general lack of salient, unique features. Our code is publicly available under https://github.com/millinma/SDPollen.

RevDate: 2025-02-03
CmpDate: 2025-02-03

Fuster-Calvo A, Valentin S, Tamayo WC, et al (2025)

Evaluating the feasibility of automating dataset retrieval for biodiversity monitoring.

PeerJ, 13:e18853.

AIM: Effective management strategies for conserving biodiversity and mitigating the impacts of global change rely on access to comprehensive and up-to-date biodiversity data. However, manual search, retrieval, evaluation, and integration of this information into databases present a significant challenge to keeping pace with the rapid influx of large amounts of data, hindering its utility in contemporary decision-making processes. Automating these tasks through advanced algorithms holds immense potential to revolutionize biodiversity monitoring.

INNOVATION: In this study, we investigate the potential for automating the retrieval and evaluation of biodiversity data from Dryad and Zenodo repositories. We have designed an evaluation system based on various criteria, including the type of data provided and its spatio-temporal range, and applied it to manually assess the relevance for biodiversity monitoring of datasets retrieved through an application programming interface (API). We evaluated a supervised classification to identify potentially relevant datasets and investigate the feasibility of automatically ranking the relevance. Additionally, we applied the same appraoch on a scientific literature source, using data from Semantic Scholar for reference. Our evaluation centers on the database utilized by a national biodiversity monitoring system in Quebec, Canada.

MAIN CONCLUSIONS: We retrieved 89 (55%) relevant datasets for our database, showing the value of automated dataset search in repositories. Additionally, we find that scientific publication sources offer broader temporal coverage and can serve as conduits guiding researchers toward other valuable data sources. Our automated classification system showed moderate performance in detecting relevant datasets (with an F-score up to 0.68) and signs of overfitting, emphasizing the need for further refinement. A key challenge identified in our manual evaluation is the scarcity and uneven distribution of metadata in the texts, especially pertaining to spatial and temporal extents. Our evaluative framework, based on predefined criteria, can be adopted by automated algorithms for streamlined prioritization, and we make our manually evaluated data publicly available, serving as a benchmark for improving classification techniques.

RevDate: 2025-02-03
CmpDate: 2025-02-03

Fonseca LL, Böttcher L, Mehrad B, et al (2025)

Optimal control of agent-based models via surrogate modeling.

PLoS computational biology, 21(1):e1012138.

This paper describes and validates an algorithm to solve optimal control problems for agent-based models (ABMs). For a given ABM and a given optimal control problem, the algorithm derives a surrogate model, typically lower-dimensional, in the form of a system of ordinary differential equations (ODEs), solves the control problem for the surrogate model, and then transfers the solution back to the original ABM. It applies to quite general ABMs and offers several options for the ODE structure, depending on what information about the ABM is to be used. There is a broad range of applications for such an algorithm, since ABMs are used widely in the life sciences, such as ecology, epidemiology, and biomedicine and healthcare, areas where optimal control is an important purpose for modeling, such as for medical digital twin technology.

RevDate: 2025-01-31

Weeks F, Myerson R, Gangnon R, et al (2025)

Racial disparities in intrapartum care experiences and birth hospital characteristics.

Social science & medicine (1982), 367:117720 pii:S0277-9536(25)00049-8 [Epub ahead of print].

Policymakers and researchers have posited intrapartum care as a potential mediator of racial inequities in perinatal outcomes. However, few studies have measured patient-centered quality of intrapartum care or explored differences by race. To address this gap, we developed a survey supplement using cognitive interviewing and administered it to a probability-based race-stratified random sample of people who recently gave birth in Wisconsin in 2020, including oversamples of non-Hispanic Black and Indigenous birthing people. We estimate overall and race-specific prevalences of intrapartum care experiences and use survey-weighted mixed effects ordinal and logistic regression to estimate differences in intrapartum care experiences by race/ethnicity and hospital characteristics. We find significant racial differences in the population prevalence of negative experiences of intrapartum care providers, including disrespect, lack of responsiveness, inclusion in decision-making about care, and pressure to use epidural analgesia. In unadjusted models, both non-Hispanic Indigenous (American Indian/Alaska Native) and non-Hispanic Black respondents had higher odds (than non-Hispanic White birthing people) of reporting several negative intrapartum experiences, including feeling disrespected by providers and experiencing a lower level of care team responsiveness. In adjusted models, Indigenous respondents had significantly higher odds of reporting that intrapartum care providers withheld information, showed disrespect, and were less responsive. Giving birth at a low birth-volume hospital was associated with higher odds of reporting greater participation in decision-making. CONCLUSION: While all birthing people are entitled to respectful and person-centered care, in practice, Indigenous and Black birthing persons are more likely than their white counterparts to endure negative intrapartum experiences including disrespect and lack of responsiveness to their needs. Equitable implementation of person-centered care principles will require concerted efforts to institutionalize practices that preserve patient dignity and autonomy.

RevDate: 2025-01-31

Giles EC, González VL, Carimán P, et al (2025)

Comparative Genomics Points to Ecological Drivers of Genomic Divergence Among Intertidal Limpets.

Molecular ecology resources [Epub ahead of print].

Comparative genomic studies of closely related taxa are important for our understanding of the causes of divergence on a changing Earth. This being said, the genomic resources available for marine intertidal molluscs are limited and currently, there are few publicly available high-quality annotated genomes for intertidal species and for molluscs in general. Here we report transcriptome assemblies for six species of Patellogastropoda and genome assemblies and annotations for three of these species (Scurria scurra, Scurria viridula and Scurria zebrina). Comparative analysis using these genomic resources suggest that and recently diverging lineages (10-20 Mya) have experienced similar amounts of contractions and expansions but across different gene families. Furthermore, differences among recently diverged species are reflected in variation in the amount of coding and noncoding material in genomes, such as amount of repetitive elements and lengths of transcripts and introns and exons. Additionally, functional ontologies of species-specific and duplicated genes together with demographic inference support the finding that recent divergence among members of the genus Scurria aligns with their unique ecological characteristics. Overall, the resources presented here will be valuable for future studies of adaptation in molluscs and in intertidal habitats as a whole.

RevDate: 2025-01-31
CmpDate: 2025-01-31

Moody NM, Williams CM, Ramachandran S, et al (2025)

Social mates dynamically coordinate aggressive behavior to produce strategic territorial defense.

PLoS computational biology, 21(1):e1012740 pii:PCOMPBIOL-D-24-00073.

Negotiating social dynamics among allies and enemies is a complex problem that often requires individuals to tailor their behavioral approach to a specific situation based on environmental and/or social factors. One way to make these contextual adjustments is by arranging behavioral output into intentional patterns. Yet, few studies explore how behavioral patterns vary across a wide range of contexts, or how allies might interlace their behavior to produce a coordinated response. Here, we investigate the possibility that resident female and male downy woodpeckers guard their breeding territories from conspecific intruders by deploying defensive behavior in context-specific patterns. To study whether this is the case, we use correlation networks to reveal how suites of agonistic behavior are interrelated. We find that residents do organize their defense into definable patterns, with female and male social mates deploying their behaviors non-randomly in a correlated fashion. We then employ spectral clustering analyses to further distill these responses into distinct behavioral motifs. Our results show that this population of woodpeckers adjusts the defensive motifs deployed according to threat context. When we combine this approach with behavioral transition analyses, our results reveal that pair coordination is a common feature of territory defense in this species. However, if simulated intruders are less threatening, residents are more likely to defend solo, where only one bird deploys defensive behaviors. Overall, our study supports the hypothesis that nonhuman animals can pattern their behavior in a strategic and coordinated manner, while demonstrating the power of systems approaches for analyzing multiagent behavioral dynamics.

RevDate: 2025-01-31
CmpDate: 2025-01-31

Marques PH, Rodrigues TCV, Santos EH, et al (2025)

Design of a multi-epitope vaccine (vme-VAC/MST-1) against cholera and vibriosis based on reverse vaccinology and immunoinformatics approaches.

Journal of biomolecular structure & dynamics, 43(4):1788-1803.

Vibriosis and cholera are serious diseases distributed worldwide and caused by six marine bacteria of the Vibrio genus. Thousands of deaths occur each year due to these illnesses, necessitating the development of new preventive measures. Presently, the existing cholera vaccine demonstrates an effectiveness of approximately 60%. Here we describe a new multi-epitope vaccine, 'vme-VAC/MST-1' based on vaccine targets identified by reverse vaccinology and epitopes predicted by immunoinformatics, two currently effective tools for predicting new vaccines for bacterial pathogens. The vaccine was designed to combat vibriosis and cholera by incorporating epitopes predicted for CTL, HTL, and B cells. These epitopes were identified from six vaccine targets revealed through subtractive genomics, combined with reverse vaccinology, and were further filtered using immunoinformatics approaches based on their predicted immunogenicity. To construct the vaccine, 28 epitopes (24 CTL/B and 4 HTL/B) were linked to the sequence of the cholera toxin B subunit adjuvant. In silico analyses indicate that the resulting immunogen is stable, soluble, non-toxic, and non-allergenic. Furthermore, it exhibits no homology to the host and demonstrates a strong capacity to elicit innate, B-cell, and T-cell immune responses. Our analysis suggests that it is likely to elicit immune reactions mediated through the TLR5 pathway, as evidenced by the molecular docking of the vaccine with the receptor, which revealed high affinity and a favorable reaction. Thus, vme-VAC/MST-1 is predicted to be a safe and effective solution against pathogenic Vibrio spp. However, further experimental analyses are required to measure the vaccine's effects In vivo.Communicated by Ramaswamy H. Sarma.

RevDate: 2025-01-29
CmpDate: 2025-01-29

Chen L, Xu Z, He Y, et al (2025)

Multiomics Analysis Reveals Key Targeted Metabolic Pathways Underlying the Hormesis and Detrimental Effects of Enrofloxacin on Rice Plants.

Journal of agricultural and food chemistry, 73(4):2678-2695.

Fluoroquinolone antibiotic enrofloxacin (ENR) is frequently detected in agricultural environments. The hormesis and detrimental effects of ENR on crops have been extensively observed. However, the molecular mechanisms underlying these crops' responses to ENR remain limited. Here, integrated physiological, transcriptomic, and metabolomic analysis revealed the key metabolic pathway responses underlying the ENR-induced effects on rice. The results showed that ENR mainly affected three metabolic pathways: 'biosynthesis of amino acids', "tryptophan metabolism", and 'phenylpropanoid/flavonoid biosynthesis'. A low level of ENR treatment promoted root elongation and enhanced the antioxidant capacity by increasing the phytohormone gibberellin A3 and the flavonol quercetin-3-O-neohesperidoside, respectively. However, the high dose of ENR significantly stimulated ROS production, inhibited photosynthesis, and ultimately impaired plant growth. In response to high ENR toxicity, plants accumulated more quercetin derivatives as antioxidants and produced defense-related substances, such as N-hydroxytryptamine, indole-3-acetonitrile, and jasmonic acid, to combat biotic stress. In conclusion, this study provides new insights into the molecular mechanism accounting for the ecological effects of antibiotic pollution in farmland.

RevDate: 2025-01-28
CmpDate: 2025-01-28

Sahandi Far M, Fischer JM, Senge S, et al (2025)

Cross-Platform Ecological Momentary Assessment App (JTrack-EMA+): Development and Usability Study.

Journal of medical Internet research, 27:e51689 pii:v27i1e51689.

BACKGROUND: Traditional in-clinic methods of collecting self-reported information are costly, time-consuming, subjective, and often limited in the quality and quantity of observation. However, smartphone-based ecological momentary assessments (EMAs) provide complementary information to in-clinic visits by collecting real-time, frequent, and longitudinal data that are ecologically valid. While these methods are promising, they are often prone to various technical obstacles. However, despite the potential of smartphone-based EMAs, they face technical obstacles that impact adaptability, availability, and interoperability across devices and operating systems. Deficiencies in these areas can contribute to selection bias by excluding participants with unsupported devices or limited digital literacy, increase development and maintenance costs, and extend deployment timelines. Moreover, these limitations not only impede the configurability of existing solutions but also hinder their adoption for addressing diverse clinical challenges.

OBJECTIVE: The primary aim of this research was to develop a cross-platform EMA app that ensures a uniform user experience and core features across various operating systems. Emphasis was placed on maximizing the integration and adaptability to various study designs, all while maintaining strict adherence to security and privacy protocols. JTrack-EMA+ was designed and implemented per the FAIR (findable, accessible, interpretable, and reusable) principles in both its architecture and data management layers, thereby reducing the burden of integration for clinicians and researchers.

METHODS: JTrack-EMA+ was built using the Flutter framework, enabling it to run seamlessly across different platforms. This platform comprises two main components. JDash (Research Centre Jülich, Institute of Neuroscience and Medicine, Brain and Behaviour [INM-7]) is an online management tool created using Python (Python Software Foundation) with the Django (Django Software Foundation) framework. This online dashboard offers comprehensive study management tools, including assessment design, user administration, data quality control, and a reminder casting center. The JTrack-EMA+ app supports a wide range of question types, allowing flexibility in assessment design. It also has configurable assessment logic and the ability to include supplementary materials for a richer user experience. It strongly commits to security and privacy and complies with the General Data Protection Regulations to safeguard user data and ensure confidentiality.

RESULTS: We investigated our platform in a pilot study with 480 days of follow-up to assess participants' compliance. The 6-month average compliance was 49.3%, significantly declining (P=.004) from 66.7% in the first month to 42% in the sixth month.

CONCLUSIONS: The JTrack-EMA+ platform prioritizes platform-independent architecture, providing an easy entry point for clinical researchers to deploy EMA in their respective clinical studies. Remote and home-based assessments of EMA using this platform can provide valuable insights into patients' daily lives, particularly in a population with limited mobility or inconsistent access to health care services.

RevDate: 2025-01-28
CmpDate: 2025-01-28

Ahmad S, Peng X, Ashraf A, et al (2025)

Building resilient urban drainage systems by integrated flood risk index for evidence-based planning.

Journal of environmental management, 374:124130.

Urban flooding poses a significant risk to cities worldwide, exacerbated by increasing urbanization and climate change. Effective flood risk management requires comprehensive assessments considering the complex interaction of social, economic, and environmental factors. This study developed an innovative Urban Flood Risk Index (FRI) to quantify and assess flood risk at the sub-catchment level, providing a tool for evidence-based planning and resilient infrastructure development. This study integrates Geographic Information System (GIS), Storm Water Management Model (SWMM), Analytic Hierarchy Process (AHP), and the Pressure-State-Response (PSR) framework. The FRI incorporates seven pressure and state indicators and three response indicators weighted by expert judgment. The FRI was calculated by combining the weighted sub-indices, classifying flood risk into five levels. Results showed that 51% of the study area experienced high pressure, with 26% facing very-high pressure. The state index indicated that 55% of the area falls under a moderate state, while 21% exhibits a high state. Importantly, the response index highlighted the effectiveness of Low Impact Development (LID) practices, with 20% of the area showing high to very-high response levels. The integrated FRI demonstrated an overall moderate flood risk level for maximum sub-catchments, emphasizing the positive impact of LID practices in mitigating flood risk despite existing pressures and system limitations. This evidence-based assessment provides a valuable tool for sub-catchment level flood risk assessment. It empowers decision-makers to prioritize investments, target interventions, and develop adaptive strategies to enhance urban resilience in a changing climate.

RevDate: 2025-01-28
CmpDate: 2025-01-28

Jia W, Chan JC, Wong TY, et al (2025)

Diabetes in China: epidemiology, pathophysiology and multi-omics.

Nature metabolism, 7(1):16-34.

Although diabetes is now a global epidemic, China has the highest number of affected people, presenting profound public health and socioeconomic challenges. In China, rapid ecological and lifestyle shifts have dramatically altered diabetes epidemiology and risk factors. In this Review, we summarize the epidemiological trends and the impact of traditional and emerging risk factors on Chinese diabetes prevalence. We also explore recent genetic, metagenomic and metabolomic studies of diabetes in Chinese, highlighting their role in pathogenesis and clinical management. Although heterogeneity across these multidimensional areas poses major analytic challenges in classifying patterns or features, they have also provided an opportunity to increase the accuracy and specificity of diagnosis for personalized treatment and prevention. National strategies and ongoing research are essential for improving diabetes detection, prevention and control, and for personalizing care to alleviate societal impacts and maintain quality of life.

RevDate: 2025-01-28
CmpDate: 2025-01-28

Huang Y, Wang T, Li Y, et al (2025)

In Vitro-to-In Vivo Extrapolation on Lung Toxicity Induced by Metal Oxide Nanoparticles via Data-Mining.

Environmental science & technology, 59(3):1673-1682.

While in silico analyses are commonly employed for chemical risk assessments, predicting chronic lung toxicity induced by engineered nanoparticles (ENMs) in vivo still faces many challenges due to complex interactions at multiple nanobio interfaces. In this study, we developed a rigorous method to compile published evidence on the in vivo lung toxicity of metal oxide nanoparticles (MeONPs) and revealed previously overlooked in vitro-to-in vivo extrapolation (IVIVE) relationships. A comprehensive multidimensional data set containing 1102 in vivo data points, 75 pulmonary toxicological biomarkers, and 20 features (covering in vitro effects, physicochemical properties, and exposure conditions) was constructed. An IVIVE approach that related effects at the cellular level to in vivo lung toxicity in rodent model was established with prediction accuracy reaching 89 and 80% in training and test sets. Experimental validation was conducted by testing chronic lung fibrosis of 8 new MeONPs in 32 independent mice, with prediction accuracy reaching 88%. The IVIVE model indicated that the proinflammatory cytokine IL-1β in THP-1 cells could serve as an in vitro marker to predict lung toxicity. The IVIVE model showed great promise for minimizing unnecessary animal tests and understanding toxicological mechanisms.

RevDate: 2025-01-27

Lazaro A, Tiago I, Mendes J, et al (2025)

Sleeve Gastrectomy and Gastric Bypass Impact in Patient's Metabolic, Gut Microbiome, and Immuno-inflammatory Profiles-A Comparative Study.

Obesity surgery [Epub ahead of print].

BACKGROUND: Bariatric surgery is the most long-term effective treatment option for severe obesity. The role of gut microbiome (GM) in either the development of obesity or in response to obesity management strategies has been a matter of debate. This study aims to compare the impact of two of the most popular procedures, sleeve gastrectomy (SG) and Roux-en-Y gastric bypass (GB), on metabolic syndrome parameters and gut bacterial microbiome and in systemic immuno-inflammatory response.

METHODS: A prospective observational study enrolled 24 patients with severe obesity, 14 underwent SG and 10 GB. Evaluations before (0 M) and 6 months (6 M) after surgical procedures included clinical and biochemical parameters, expression of 17 immuno-inflammatory genes in peripheral blood leukocytes, and assessment of gut microbiome profile using 16 s rRNA next-generation sequencing approach. Statistical significance was set to a p value < 0.05 with an FDR < 0.1.

RESULTS: A significant and similar decrease in weight-associated parameters and for most metabolic markers was achieved with both surgeries. Considering the gut microbiome in the whole study population, there was an increase in alpha diversity at family-level taxa. Beta diversity between SG and GB at 6 M showed near significant differences (p = 0.042) at genus levels. Analysis of the relative abundance of individual taxonomic groups highlighted differences between pre- and post-surgical treatment and between both approaches, namely, a higher representation of family Enterobacteriaceae and genera Veillonella and Enterobacteriaceae_unclassified after GB. Increased expression of immune-inflammatory genes was observed mainly for SG patients.

CONCLUSIONS: We conclude that SG and GB have similar clinical and metabolic outcomes but different impacts in the gut bacterial microbiome. Results also suggest reactivation of immune response after bariatric surgery.

RevDate: 2025-01-27
CmpDate: 2025-01-27

Koizumi T, Suzuki K, Mizuki I, et al (2025)

A quantitative prediction method utilizing whole omics data for biosensing.

Scientific reports, 15(1):1928.

Omics data provide a plethora of quantifiable information that can potentially be used to identify biomarkers targeting the physiological processes and ecological phenomena of organisms. However, omics data have not been fully utilized because current prediction methods in biomarker construction are susceptible to data multidimensionality and noise. We developed OmicSense, a quantitative prediction method that uses a mixture of Gaussian distributions as the probability distribution, yielding the most likely objective variable predicted for each biomarker. Our benchmark test using a transcriptome dataset revealed that OmicSense achieves accurate and robust prediction against background noise without overfitting. Weighted gene co-expression network analysis revealed that OmicSense preferentially utilized hub nodes of the network, indicating the interpretability of the method. Application of OmicSense to single-cell transcriptome, metabolome, and microbiome datasets confirmed high prediction performance (r > 0.8), suggesting applicability to diverse scientific fields. Given the recent rapidly expanding availability of omics data, the developed prediction tool OmicSense, can accelerate the use of omics data as a "biosensor" based on an assemblage of potential biomarkers.

RevDate: 2025-01-27

Terauds A, Lee JR, Wauchope HS, et al (2025)

The biodiversity of ice-free Antarctica database.

Ecology, 106(1):e70000.

Antarctica is one of Earth's most untouched, inhospitable, and poorly known regions. Although knowledge of its biodiversity has increased over recent decades, a diverse, wide-ranging, and spatially explicit compilation of the biodiversity that inhabits Antarctica's permanently ice-free areas is unavailable. This absence hinders both Antarctic biodiversity research and the integration of Antarctica in global biodiversity-related studies. Fundamental and applied research on biodiversity patterns, ecological structure and function, and options for conservation are reliant on spatially resolved, taxonomically consistent observations. Such information is especially important for modern, data-driven biodiversity science, in both Antarctica and globally, and forms the backbone of biodiversity informatics, reflected, for example, in the Darwin Core Standard used by the Global Biodiversity Information Facility. Biodiversity data are also essential to fulfill the conservation requirements for Antarctica, as set out in the Protocol on Environmental Protection to the Antarctic Treaty and inform the design of systematic surveys to address biodiversity and ecological knowledge gaps, for both specific taxa and ecosystems. Such surveys are key requirements for understanding and mitigating the impacts of environmental change on the region's biodiversity. Here, we address these requirements through the public release of The Biodiversity of Ice-free Antarctica Database. In 2008, we extracted a subset of biodiversity records only from terrestrial ice-free areas from the Scientific Committee on Antarctic Research (SCAR) Antarctic Biodiversity Database. We have subsequently added thousands of records from a range of sources: checking, and where necessary (and possible), correcting the spatial location, clarifying, cross-referencing, and harmonizing taxonomy with globally recognized sources, and documenting the original source of records. The Biodiversity of Ice-free Antarctica Database spans the early 1800s to 2019 (with most records collected after 1950) and represents the most comprehensive consolidation of Antarctic ice-free biodiversity occurrence data yet compiled into a single database. The Biodiversity of Ice-free Antarctica Database contains 35,654 records of 1890 species in over 800 genera across six kingdoms and spans all Antarctic Conservation Biogeographic Regions. These data are released under a CC BY Attribution License (http://creativecommons.org/licenses/by/4.0/).

RevDate: 2025-01-27
CmpDate: 2025-01-27

Ridgway J, J Wesner (2025)

A global dataset of freshwater fish trophic interactions.

Scientific data, 12(1):160.

Freshwater management and research frequently rely on trophic data to manage freshwater fishes, yet it is difficult to perform a simple search of dietary information for any one species. FishBase represents the largest effort to organize freshwater dietary data into a singular, navigable dataset. Nonetheless, FishBase excludes a large portion of the ecological literature because it was developed before the creation of most modern scientific search engines. Our project, TroPhish, builds upon FishBase by digitizing over 100 years of data from the fish predation literature. Data from 1,106 published papers, theses, dissertations, and government reports were filtered, scanned in through third-party software (Able2Extract), reorganized, and consolidated with FishBase to form a unified dataset. This dataset contains 54,750 observations of data on 4,571 unique dietary samples, representing 9% (982) of all freshwater fish species and 43% (111) of all freshwater fish families. Fish species and family representation varied by continent, ranging from 3-32% and 34-75%, respectively. Users are encouraged to submit errors or additional data through GitHub's fork and pull model.

RevDate: 2025-01-27
CmpDate: 2025-01-27

Yeom JW, Kim H, Pack SP, et al (2025)

Exploring the Psychological and Physiological Insights Through Digital Phenotyping by Analyzing the Discrepancies Between Subjective Insomnia Severity and Activity-Based Objective Sleep Measures: Observational Cohort Study.

JMIR mental health, 12:e67478 pii:v12i1e67478.

BACKGROUND: Insomnia is a prevalent sleep disorder affecting millions worldwide, with significant impacts on daily functioning and quality of life. While traditionally assessed through subjective measures such as the Insomnia Severity Index (ISI), the advent of wearable technology has enabled continuous, objective sleep monitoring in natural environments. However, the relationship between subjective insomnia severity and objective sleep parameters remains unclear.

OBJECTIVE: This study aims to (1) explore the relationship between subjective insomnia severity, as measured by ISI scores, and activity-based objective sleep parameters obtained through wearable devices; (2) determine whether subjective perceptions of insomnia align with objective measures of sleep; and (3) identify key psychological and physiological factors contributing to the severity of subjective insomnia complaints.

METHODS: A total of 250 participants, including both individuals with and without insomnia aged 19-70 years, were recruited from March 2023 to November 2023. Participants were grouped based on ISI scores: no insomnia, mild, moderate, and severe insomnia. Data collection involved subjective assessments through self-reported questionnaires and objective measurements using wearable devices (Fitbit Inspire 3) that monitored sleep parameters, physical activity, and heart rate. The participants also used a smartphone app for ecological momentary assessment, recording daily alcohol consumption, caffeine intake, exercise, and stress. Statistical analyses were used to compare groups on subjective and objective measures.

RESULTS: Results indicated no significant differences in general sleep structure (eg, total sleep time, rapid eye movement sleep time, and light sleep time) among the insomnia groups (mild, moderate, and severe) as classified by ISI scores (all P>.05). Interestingly, the no insomnia group had longer total awake times and lower sleep quality compared with the insomnia groups. Among the insomnia groups, no significant differences were observed regarding sleep structure (all P>.05), suggesting similar sleep patterns regardless of subjective insomnia severity. There were significant differences among the insomnia groups in stress levels, dysfunctional beliefs about sleep, and symptoms of restless leg syndrome (all P≤.001), with higher severity associated with higher scores in these factors. Contrary to expectations, no significant differences were observed in caffeine intake (P=.42) and alcohol consumption (P=.07) between the groups.

CONCLUSIONS: The findings demonstrate a discrepancy between subjective perceptions of insomnia severity and activity-based objective sleep parameters, suggesting that factors beyond sleep duration and quality may contribute to subjective sleep complaints. Psychological factors, such as stress, dysfunctional sleep beliefs, and symptoms of restless legs syndrome, appear to play significant roles in the perception of insomnia severity. These results highlight the importance of considering both subjective and objective assessments in the evaluation and treatment of insomnia and suggest potential avenues for personalized treatment strategies that address both psychological and physiological aspects of sleep disturbances.

TRIAL REGISTRATION: Clinical Research Information Service KCT0009175; https://cris.nih.go.kr/cris/search/detailSearch.do?seq=26133.

RevDate: 2025-01-27

Grikscheit K, Berger A, Rabenau H, et al (2025)

Occurrence and clinical correlates of SARS-CoV-2 viremia in two German patient cohorts.

Emerging microbes & infections [Epub ahead of print].

Viremia defined as detectable SARS-CoV-2 RNA in the blood is a potential marker of disease severity and prognosis in COVID-19 patients. Here, we determined the frequency of viremia in serum of two independent COVID-19 patient cohorts within the German National Pandemic Cohort Network (German: Nationales Pandemie Kohorten Netzwerk, NAPKON) with diagnostic RT-PCR against SARS-CoV-2. A cross-sectional cohort with 1,122 COVID-19 patients (German: Sektorenuebergreifende Platform, SUEP) and 299 patients recruited in a high-resolution platform with patients at high risk to develop severe courses (German: Hochaufloesende Plattform, HAP) were tested for viremia. Our study also involved a comprehensive analysis and association of serological, diagnostic and clinical parameters of the NAPKON medical dataset. Prevalence of viremia at the recruitment visit was 12,8% (SUEP) and 13% (HAP) respectively. Serological analysis revealed that viremic patients had lower levels of SARS-CoV-2 specific antibodies as well as lower neutralizing antibodies compared to aviremic patients. Viremia was associated with severity (<0.0001 SUEP; 0.002 HAP) and mortality of COVID-19 (both cohorts <0.0001) compared to aviremic patients. While rare, viremia was also detected in patients with mild disease (0.7%). In patients of the SUEP cohort with acute kidney disease (p = 0.0099) and hematooncological conditions (p = 0.0091), viremia was detected more frequently. Compared to the aviremic group, treatment with immunomodulating drugs as well as elevated levels of inflammatory markers in the blood was more frequent in the viremic group. In conclusion, our analysis revealed that detectable viremia correlates with hyperinflammatory conditions and higher risk for severe COVID-19 disease.

RevDate: 2025-01-27

Couch J, Arnaout R, R Arnaout (2024)

Beyond Size and Class Balance: Alpha as a New Dataset Quality Metric for Deep Learning.

ArXiv.

In deep learning, achieving high performance on image classification tasks requires diverse training sets. However, the current best practice-maximizing dataset size and class balance-does not guarantee dataset diversity. We hypothesized that, for a given model architecture, model performance can be improved by maximizing diversity more directly. To test this hypothesis, we introduce a comprehensive framework of diversity measures from ecology that generalizes familiar quantities like Shannon entropy by accounting for similarities among images. (Size and class balance emerge as special cases.) Analyzing thousands of subsets from seven medical datasets showed that the best correlates of performance were not size or class balance but A -"big alpha"-a set of generalized entropy measures interpreted as the effective number of image-class pairs in the dataset, after accounting for image similarities. One of these, A 0 , explained 67% of the variance in balanced accuracy, vs. 54% for class balance and just 39% for size. The best pair of measures was size-plus- A 1 (79%), which outperformed size-plus-class-balance (74%). Subsets with the largest A 0 performed up to 16% better than those with the largest size (median improvement, 8%). We propose maximizing A as a way to improve deep learning performance in medical imaging.

RevDate: 2025-01-27
CmpDate: 2025-01-27

Gudelj Rakić J, Maksimović M, Vlajinac H, et al (2023)

TRENDS IN OVERWEIGHT AND OBESITY AMONG SERBIAN ADULT POPULATION 2000-2013.

Acta clinica Croatica, 62(4):605-614.

The aim of the study was to determine changes in body mass index (BMI) and in the prevalence of overweight and obesity in Serbian adult population. Data for this study were obtained from three National Health Interview Surveys, carried out as cross-sectional, nationally representative surveys in 2000, 2006 and 2013. The values of p for trends of sociodemographic and health related behavioral characteristics, of BMI distribution, and of overweight and obesity prevalence were determined by univariate and multivariate linear and logistic regression analyses, with year of survey as a continuous variable. The mean values of BMI and standard deviations in surveys were 26.09±3.92, 26.28±4.02 and 26.87±4.33 in men, and 25.91±5.25, 25.77±5.22 and 26.35±5.58 in women, respectively (trend p<0.001 both). The prevalence of obesity was 14.3%, 16.5% and 21.4% in men, and 20.0%, 19.7% and 23.3% in women, respectively (trend p<0.001 both). The prevalence of overweight did not change significantly during the observed period. In conclusion, the prevalence of obesity showed an increasing trend in both men and women, demanding targeted public health interventions.

RevDate: 2025-01-26
CmpDate: 2025-01-26

Alekseeva AO, Zolotovskaia MA, Sorokin MI, et al (2024)

The First Multiomics Association Study of Trace Element and Mineral Concentration and RNA Sequencing Profiles in Human Cancers.

Biochemistry. Biokhimiia, 89(12):2274-2286.

Integration of various types of omics data is an important trend in contemporary molecular oncology. In this regard, high-throughput analysis of trace and essential elements in cancer biosamples is an emerging field that has not yet been sufficiently addressed. For the first time, we simultaneously obtained gene expression profiles (RNA sequencing) and essential and trace element profiles (inductively coupled plasma mass spectrometry) for a set of human cancer samples. The biosamples were formalin-fixed, paraffin-embedded primary tumor tissue blocks: 67 for colorectal cancer patients and 18 for other solid cancer types (16 types). Mass spectrometry profiles were obtained for 45 chemical elements: Ag, Al, As, Au, B, Ba, Be, Bi, Ca, Cd, Co, Cr, Cu, Fe, Ga, Ge, Hg, I, K, La, Li, Mg, Mn, Mo, Na, Ni, P, Pb, Pd, Pt, Rb, Sb, Sc, Se, Si, Sn, Sr, Te, Ti, Tl, Zn, U, V, W, and Zr. The expression levels were profiled for 36,596 known human genes, and the activation levels were assessed for 10,520 human intracellular molecular pathways. For the concentrations of essential elements Ca, Cu, Fe, K, Mg, Na, P, and Zn we detected statistically significant correlations on both gene expression and pathway activation levels for both colorectal cancer samples and at the pan-cancer level. In total, 222/137, 122/220, 1/0, 239/186, 71/44, 1/0, 354/294, 69/82 gene/pathway biomarkers were detected for Ca, Cu, Fe, K, Mg, Na, P, and Zn, respectively. We believe that this first-in-class database provided here will be valuable for multiomics cancer research.

RevDate: 2025-01-25
CmpDate: 2025-01-25

Dewmini H, Meedeniya D, C Perera (2025)

Elephant Sound Classification Using Deep Learning Optimization.

Sensors (Basel, Switzerland), 25(2): pii:s25020352.

Elephant sound identification is crucial in wildlife conservation and ecological research. The identification of elephant vocalizations provides insights into the behavior, social dynamics, and emotional expressions, leading to elephant conservation. This study addresses elephant sound classification utilizing raw audio processing. Our focus lies on exploring lightweight models suitable for deployment on resource-costrained edge devices, including MobileNet, YAMNET, and RawNet, alongside introducing a novel model termed ElephantCallerNet. Notably, our investigation reveals that the proposed ElephantCallerNet achieves an impressive accuracy of 89% in classifying raw audio directly without converting it to spectrograms. Leveraging Bayesian optimization techniques, we fine-tuned crucial parameters such as learning rate, dropout, and kernel size, thereby enhancing the model's performance. Moreover, we scrutinized the efficacy of spectrogram-based training, a prevalent approach in animal sound classification. Through comparative analysis, the raw audio processing outperforms spectrogram-based methods. In contrast to other models in the literature that primarily focus on a single caller type or binary classification that identifies whether a sound is an elephant voice or not, our solution is designed to classify three distinct caller-types namely roar, rumble, and trumpet.

RevDate: 2025-01-24

Gulakhmadov A, Chen X, Gulahmadov N, et al (2025)

Modeling of historical and future changes in temperature and precipitation in the Panj River Basin in Central Asia under the CMIP5 RCP and CMIP6 SSP scenarios.

Scientific reports, 15(1):3037.

This study examines the complexities of climate modeling, specifically in the Panj River Basin (PRB) in Central Asia, to evaluate the transition from CMIP5 to CMIP6 models. The research aimed to identify differences in historical simulations and future predictions of rainfall and temperature, examining the accuracy of eight General Circulation Models (GCMs) used in both CMIP5 (RCP4.5 and 8.5) and CMIP6 (SSP2-4.5 and 5-8.5). The evaluation metrics demonstrated that the GCMs have a high level of accuracy in reproducing maximum temperature (Tmax) with a correlation coefficient of 0.96. The models also performed well in replicating minimum temperature (Tmin) with a correlation coefficient of 0.94. This suggests that the models have improved modeling capabilities in both CMIPs. The performance of Max Plank Institute (MPI) across all variables in CMIP6 models was exceptional. Within the CMIP5 domain, Geophysical Fluid Dynamics (GFDL) demonstrated outstanding skill in reproducing maximum temperature (Tmax) and precipitation (KGE 0.58 and 0.34, respectively), while (Institute for Numerical Mathematics) INMCM excelled in replicating minimum temperature (Tmin) (KGE 0.28). The uncertainty analysis revealed a significant improvement in the CMIP6 precipitation bias bands, resulting in a more precise depiction of diverse climate zones compared to CMIP5. Both CMIPs consistently tended to underestimate Tmax in the Csa zone and overestimate it in the Bwk zone throughout all months. Nevertheless, the CMIP6 models demonstrated a significant decrease in uncertainty, especially in ensemble simulations, suggesting improvements in forecasting PRB climate dynamics. The projections revealed a complex story, as the CMIP6 models predict a relatively small increase in temperature and a simultaneous drop in precipitation. This indicates a trend towards more uniform temperature patterns across different areas. Nevertheless, the precipitation forecasts exhibited increased variability, highlighting the intricate interaction of climate dynamics in the PRB area under the impact of global warming scenarios. Hydrological components in global climate models can be further improved and developed with the theoretical reference provided by this study.

RevDate: 2025-01-24
CmpDate: 2025-01-24

Zhou J, Johnson VC, Shi J, et al (2025)

Multi-scenario land use change simulation and spatial-temporal evolution of carbon storage in the Yangtze River Delta region based on the PLUS-InVEST model.

PloS one, 20(1):e0316255 pii:PONE-D-24-36597.

Influenced by urban expansion, population growth, and various socio-economic activities, land use in the Yangtze River Delta (YRD) area has undergone prominent changes. Modifications in land use have resulted in adjustments to ecological structures, leading to subsequent fluctuations in carbon storage. This study focuses on YRD region and analyzes the characteristics of land use changes in the area using land use data from 2000 to 2020, with a 10-year interval. Utilizing InVEST Model's Carbon Storage module in combination with PLUS model (patch-generating land use simulation), we simulated and projected future land use patterns and carbon storage across YRD region under five scenarios including natural development (ND), urban development (UD), ecological protection (EP), cropland protection (CP), and balanced development (BD). Upon comparing carbon storage levels predicted for 2030 under the five scenarios with those in 2020, carbon stocks decrease in the initial four scenarios and then increase in the fifth scenario. In the initial four declining scenarios, CP scenario had the least reduction in carbon storage, followed by EP scenario. The implementation of policies aimed at safeguarding cropland and preserving ecological integrity can efficaciously curtail the expansion of developed land into woodland and cropland, enhance the structure of land use, and mitigate the loss of carbon storage.

RevDate: 2025-01-24
CmpDate: 2025-01-24

Katchali M, Richard E, Tonnang HEZ, et al (2025)

Mathematical and computational modeling for organic and insect frass fertilizer production: A systematic review.

PloS one, 20(1):e0292418 pii:PONE-D-23-28302.

Organic fertilizers have been identified as a sustainable agricultural practice that can enhance productivity and reduce environmental impact. Recently, the European Union defined and accepted insect frass as an innovative and emerging organic fertilizer. In the wider domain of organic fertilizers, mathematical and computational models have been developed to optimize their production and application conditions. However, with the advancement in policies and regulations, modelling has shifted towards efficiencies in the deployment of these technologies. Therefore, this paper reviews and critically analyzes the recent developments in the mathematical and computation modeling that have promoted various organic fertilizer products including insect frass. We reviewed a total of 35 studies and discussed the methodologies, benefits, and challenges associated with the use of these models. The results show that mathematical and computational modeling can improve the efficiency and effectiveness of organic fertilizer production, leading to improved agricultural productivity and reduced environmental impact. Mathematical models such as simulation, regression, dynamics, and kinetics have been applied while computational data driven machine learning models such as random forest, support vector machines, gradient boosting, and artificial neural networks have also been applied as well. These models have been used in quantifying nutrients concentration/release, effects of nutrients in agro-production, and fertilizer treatment. This paper also discusses prospects for the use of these models, including the development of more comprehensive and accurate models and integration with emerging technologies such as Internet of Things.

RevDate: 2025-01-24

Pierrat ZA, Magney TS, Richardson WP, et al (2025)

Proximal remote sensing: an essential tool for bridging the gap between high-resolution ecosystem monitoring and global ecology.

The New phytologist [Epub ahead of print].

A new proliferation of optical instruments that can be attached to towers over or within ecosystems, or 'proximal' remote sensing, enables a comprehensive characterization of terrestrial ecosystem structure, function, and fluxes of energy, water, and carbon. Proximal remote sensing can bridge the gap between individual plants, site-level eddy-covariance fluxes, and airborne and spaceborne remote sensing by providing continuous data at a high-spatiotemporal resolution. Here, we review recent advances in proximal remote sensing for improving our mechanistic understanding of plant and ecosystem processes, model development, and validation of current and upcoming satellite missions. We provide current best practices for data availability and metadata for proximal remote sensing: spectral reflectance, solar-induced fluorescence, thermal infrared radiation, microwave backscatter, and LiDAR. Our paper outlines the steps necessary for making these data streams more widespread, accessible, interoperable, and information-rich, enabling us to address key ecological questions unanswerable from space-based observations alone and, ultimately, to demonstrate the feasibility of these technologies to address critical questions in local and global ecology.

RevDate: 2025-01-22
CmpDate: 2025-01-22

Gioiosa S, Gasparini S, Presutti C, et al (2025)

Integrated gene expression and alternative splicing analysis in human and mouse models of Rett syndrome.

Scientific reports, 15(1):2778.

Mutations of the MECP2 gene lead to Rett syndrome (RTT), a rare developmental disease causing severe intellectual and physical disability. How the loss or defective function of MeCP2 mediates RTT is still poorly understood. MeCP2 is a global gene expression regulator, acting at transcriptional and post-transcriptional levels. Little attention has been given so far to the contribution of alternative splicing (AS) dysregulation to RTT pathophysiology. To perform a comparative analysis of publicly available RNA sequencing (RNA-seq) studies and generate novel data resources for AS, we explored 100 human datasets and 130 mouse datasets from Mecp2-mutant models, processing data for gene expression and alternative splicing. Our comparative analysis across studies indicates common species-specific differentially expressed genes (DEGs) and differentially alternatively spliced (DAS) genes. Human and mouse dysregulated genes are involved in two main functional categories: cell-extracellular matrix adhesion regulation and synaptic functions, the first category more significantly enriched in human datasets. Our extensive bioinformatics study indicates, for the first time, a significant dysregulation of AS in human RTT datasets, suggesting the crucial contribution of altered RNA processing to the pathophysiology of RTT.

RevDate: 2025-01-22
CmpDate: 2025-01-22

Cardoso ADRO, Ferreira ACG, MF Rabahi (2025)

Asthma-related deaths in Brazil: data from an ecological study.

Jornal brasileiro de pneumologia : publicacao oficial da Sociedade Brasileira de Pneumologia e Tisilogia, 50(6):e20240296 pii:S1806-37132024000600608.

OBJECTIVE: The aim of this study was to present epidemiological data on hospitalizations and deaths related to asthma in Brazil over the past 11 years.

METHODS: An ecological study was conducted on asthma-related hospitalizations and mortality in Brazil from 2013 to 2023, using data extracted from the Department of Informatics of the Brazilian Unified Health System and the Mortality Information System.

RESULTS: Asthma-related deaths showed an increasing trend during the analyzed period. A surge in deaths was observed in 2022 compared to 2014 (difference between means = 56.08 ± 19.7; 95% CI = 15.2-96.9). The mean number of deaths was higher among females, with their rate remaining stable, while the rate for males increased. Individuals aged >60 years accounted for approximately 65% of all asthma-related deaths from 2013 to 2023, with a strong direct correlation observed between age and the number of deaths, regardless of sex. During the same period, the total number of asthma-related hospitalizations in Brazil showed a declining trend, decreasing from 134,322 in 2013 to 87,707 in 2023.

CONCLUSION: Over the past 11 years, asthma-related deaths have increased in Brazil, with the majority occurring among females. Older individuals accounted for most asthma-related deaths, and a positive correlation was observed between age and the number of deaths.

RevDate: 2025-01-22

Yan B, Nam Y, Li L, et al (2024)

Recent advances in deep learning and language models for studying the microbiome.

Frontiers in genetics, 15:1494474.

Recent advancements in deep learning, particularly large language models (LLMs), made a significant impact on how researchers study microbiome and metagenomics data. Microbial protein and genomic sequences, like natural languages, form a language of life, enabling the adoption of LLMs to extract useful insights from complex microbial ecologies. In this paper, we review applications of deep learning and language models in analyzing microbiome and metagenomics data. We focus on problem formulations, necessary datasets, and the integration of language modeling techniques. We provide an extensive overview of protein/genomic language modeling and their contributions to microbiome studies. We also discuss applications such as novel viromics language modeling, biosynthetic gene cluster prediction, and knowledge integration for metagenomics studies.

RevDate: 2025-01-22
CmpDate: 2025-01-22

Guan J, Ji Y, Peng C, et al (2024)

GOPhage: protein function annotation for bacteriophages by integrating the genomic context.

Briefings in bioinformatics, 26(1):.

Bacteriophages are viruses that target bacteria, playing a crucial role in microbial ecology. Phage proteins are important in understanding phage biology, such as virus infection, replication, and evolution. Although a large number of new phages have been identified via metagenomic sequencing, many of them have limited protein function annotation. Accurate function annotation of phage proteins presents several challenges, including their inherent diversity and the scarcity of annotated ones. Existing tools have yet to fully leverage the unique properties of phages in annotating protein functions. In this work, we propose a new protein function annotation tool for phages by leveraging the modular genomic structure of phage genomes. By employing embeddings from the latest protein foundation models and Transformer to capture contextual information between proteins in phage genomes, GOPhage surpasses state-of-the-art methods in annotating diverged proteins and proteins with uncommon functions by 6.78% and 13.05% improvement, respectively. GOPhage can annotate proteins lacking homology search results, which is critical for characterizing the rapidly accumulating phage genomes. We demonstrate the utility of GOPhage by identifying 688 potential holins in phages, which exhibit high structural conservation with known holins. The results show the potential of GOPhage to extend our understanding of newly discovered phages.

RevDate: 2025-01-21
CmpDate: 2025-01-21

Paris JR, King RA, Ferrer Obiol J, et al (2025)

The Genomic Signature and Transcriptional Response of Metal Tolerance in Brown Trout Inhabiting Metal-Polluted Rivers.

Molecular ecology, 34(1):e17591.

Industrial pollution is a major driver of ecosystem degradation, but it can also act as a driver of contemporary evolution. As a result of intense mining activity during the Industrial Revolution, several rivers across the southwest of England are polluted with high concentrations of metals. Despite the documented negative impacts of ongoing metal pollution, brown trout (Salmo trutta L.) survive and thrive in many of these metal-impacted rivers. We used population genomics, transcriptomics, and metal burdens to investigate the genomic and transcriptomic signatures of potential metal tolerance. RADseq analysis of six populations (originating from three metal-impacted and three control rivers) revealed strong genetic substructuring between impacted and control populations. We identified selection signatures at 122 loci, including genes related to metal homeostasis and oxidative stress. Trout sampled from metal-impacted rivers exhibited significantly higher tissue concentrations of cadmium, copper, nickel and zinc, which remained elevated after 11 days in metal-free water. After depuration, we used RNAseq to quantify gene expression differences between metal-impacted and control trout, identifying 2042 differentially expressed genes (DEGs) in the gill, and 311 DEGs in the liver. Transcriptomic signatures in the gill were enriched for genes involved in ion transport processes, metal homeostasis, oxidative stress, hypoxia, and response to xenobiotics. Our findings reveal shared genomic and transcriptomic pathways involved in detoxification, oxidative stress responses and ion regulation. Overall, our results demonstrate the diverse effects of metal pollution in shaping both neutral and adaptive genetic variation, whilst also highlighting the potential role of constitutive gene expression in promoting metal tolerance.

RevDate: 2025-01-20
CmpDate: 2025-01-21

Akar SE, Nwachukwu W, Adewuyi OS, et al (2025)

Epidemiology of Yellow Fever in Nigeria: Analysis of Climatic, Ecological, Socio-Demographic, and Clinical Factors Associated with Viral Positivity Among Suspected Cases Using National Surveillance Data, 2017-2023.

Journal of epidemiology and global health, 15(1):2.

BACKGROUND: Since its resurgence in 2017, Yellow fever (YF) outbreaks have continued to occur in Nigeria despite routine immunization and the implementation of several reactive mass vaccinations. Nigeria, Africa's most populous endemic country, is considered a high-priority country for implementing the End Yellow fever Epidemics strategy.

METHODS: This retrospective analysis described the epidemiological profile, trends, and factors associated with Yellow fever viral positivity in Nigeria. We conducted a multivariable binary logistic regression analysis to identify factors associated with YF viral positivity.

RESULTS: Of 16,777 suspected cases, 8532(50.9%) had laboratory confirmation with an overall positivity rate of 6.9%(585). Predictors of YFV positivity were the Jos Plateau, Derived/Guinea Savanah, and the Freshwater/Lowland rainforest compared to the Sahel/Sudan Savannah; dry season compared to rainy season; the hot dry or humid compared to the temperate, dry cool/humid climatic zone; 2019, 2020, 2021, 2022, and 2023 epidemic years compared to compared to 2017; first, third, and fourth quarters compared to the second; male sex compared to female; age group > = 15 years compared to < 15 years; working in outdoor compared to indoor settings; having traveled within the last two weeks; being of unknown vaccination status compared to being vaccinated; and vomiting.

CONCLUSION: Ecological, climatic, and socio-demographic characteristics are drivers of YF outbreaks in Nigeria, and public health interventions need to target these factors to halt local epidemics and reduce the risk of international spread. Inadequate vaccination coverage alone may not account for the recurrent outbreaks of YF in Nigeria.

RevDate: 2025-01-20
CmpDate: 2025-01-20

Liu F, Zhao Z, Y Liu (2024)

PHPGAT: predicting phage hosts based on multimodal heterogeneous knowledge graph with graph attention network.

Briefings in bioinformatics, 26(1):.

Antibiotic resistance poses a significant threat to global health, making the development of alternative strategies to combat bacterial pathogens increasingly urgent. One such promising approach is the strategic use of bacteriophages (or phages) to specifically target and eradicate antibiotic-resistant bacteria. Phages, being among the most prevalent life forms on Earth, play a critical role in maintaining ecological balance by regulating bacterial communities and driving genetic diversity. Accurate prediction of phage hosts is essential for successfully applying phage therapy. However, existing prediction models may not fully encapsulate the complex dynamics of phage-host interactions in diverse microbial environments, indicating a need for improved accuracy through more sophisticated modeling techniques. In response to this challenge, this study introduces a novel phage-host prediction model, PHPGAT, which leverages a multimodal heterogeneous knowledge graph with the advanced GATv2 (Graph Attention Network v2) framework. The model first constructs a multimodal heterogeneous knowledge graph by integrating phage-phage, host-host, and phage-host interactions to capture the intricate connections between biological entities. GATv2 is then employed to extract deep node features and learn dynamic interdependencies, generating context-aware embeddings. Finally, an inner product decoder is designed to compute the likelihood of interaction between a phage and host pair based on the embedding vectors produced by GATv2. Evaluation results using two datasets demonstrate that PHPGAT achieves precise phage host predictions and outperforms other models. PHPGAT is available at https://github.com/ZhaoZMer/PHPGAT.

RevDate: 2025-01-20
CmpDate: 2025-01-20

Shimels T, Kantelhardt EJ, Assefa M, et al (2025)

Spatiotemporal dynamics and prevention strategies of cervical cancer incidence in Addis Ababa, Ethiopia: an ecological study.

BMJ open, 15(1):e089521 pii:bmjopen-2024-089521.

OBJECTIVE: This study analysed the spatial and temporal patterns of cervical cancer incidence in Addis Ababa from 2012 to 2021.

DESIGN: An ecological study was conducted from 1 September to 30 November 2023 to examine the spatiotemporal trends of cervical cancer incidence.

SETTING: The research was conducted in Addis Ababa, the capital city of Ethiopia.

PARTICIPANTS: Included were all patients with clinically and/or histopathologically confirmed diagnoses of cervical cancer.

DATA ANALYSIS: The study employed advanced analytical tools including R programming, Quantum Geographic Information System V.3.36.0, GeoDa V.1.2.2 and System for Automated Geoscientific Analyses GIS V.9.3.2. Techniques such as Bayesian empirical testing with a block weighting matrix for hotspot identification, Global Moran's I for spatial autocorrelation, nearest neighbour imputation and universal Kriging interpolation were used to manage data gaps. Joinpoint trend analysis and direct age-standardised incidence rate (ASIR) using the Segi's World standard population was applied to compare trends across subcities. A statistical significance threshold was set at p<0.05.

RESULTS: Between 2012 and 2021, a total of 2435 new cervical cancer cases were recorded in the Addis Ababa City Population-based Cancer Registry, with significant spatial clustering observed in Nifas Silk Lafto, Bole, Kirkos as well as parts of Gulele and Yeka sub cities (z score>1.96) in 2018. The citywide age-standardised incidence rate varied from 19 to 26 cases per 100 000 women-years during 2013 and 2016, respectively. Subcity trends varied significantly, with increases and decreases noted in Akaki Kality and Kolfe Keraniyo over different periods while Bole subcity showed modest increase at 4.2% APC (95% CI: 0.6% to 7.9%; p=0.026).

CONCLUSION: The study highlights substantial fluctuations in ASIR and significant geographic disparities in cervical cancer throughout Addis Ababa. To address these challenges, the implementation of school-based human papillomavirus vaccination programmes, alongside targeted interventions, active campaigns and sustained surveillance, is critical. These strategies are essential to effectively reduce the cervical cancer burden and improve health outcomes in the community.

RevDate: 2025-01-20
CmpDate: 2025-01-20

Ištoňová M, Dorko E, Knap V, et al (2024)

Assessment of depressive disorders and states of anxiety in patients following cerebrovascular accidents in connection with health care provision.

Central European journal of public health, 32(Supplement):18-24.

OBJECTIVE: Anxiety and depression in patients following cerebrovascular accidents are among frequently occurring complications of the medical condition. The consequences affect personal, family, professional, and social life. They cause severe functional and cognitive impairments, limit the ability to perform normal daily activities, which can result in complete disability. The aim of the study was to monitor the occurrence of anxiety and depression in patients following cerebrovascular accidents hospitalized in neurological departments in the region of eastern Slovakia.

METHODS: A total of 101 patients following cerebrovascular accidents, aged from 48-86 years, were included in the descriptive study. Demographic and clinical data were obtained from patients and from medical records. We determined the occurrence of anxiety disorders, depression and emotional distress in patients following cerebrovascular accidents using a standardized Hospital Anxiety and Depression Scale (HADS) questionnaire.

RESULTS: Data analysis confirms a high incidence of anxiety in the HADS-A subscale (9.23 ± 4.13) and depression in the HADS-D subscale (9.09 ± 4.43) during the hospitalization phase of the disease. It demonstrates the pathological occurrence of anxiety states in 37%, depression in 36%, emotional distress in 36%, and a serious degree of combination of pathological values of the anxiety subscale and the depression subscale in 27% of patients. The existence of a strong positive correlation between anxiety and depression indicators was confirmed.

CONCLUSION: The results confirm a high prevalence of anxiety and depression in the acute phase of the disease. The findings indicate that patients recovering from cerebrovascular accidents not only face physical difficulties and loss of independence but also struggle with anxiety and depression, which can negatively impact and slow their recovery. Given the high frequency of these psychological conditions, further research is needed to enhance the quality and effectiveness of care provided to patients with cerebrovascular accidents.

RevDate: 2025-01-20

Iobbi V, Parisi V, Giacomini M, et al (2025)

Sesterterpenoids: sources, structural diversity, biological activity, and data management.

Natural product reports [Epub ahead of print].

Reviewing the literature published up to October 2024.Sesterterpenoids are one of the most chemically diverse and biologically promising subgroup of terpenoids, the largest family of secondary metabolites. The present review article summarizes more than seven decades of studies on isolation and characterization of more than 1600 structurally novel sesterterpenoids, supplemented by biological, pharmacological, ecological, and geographic distribution data. All the information have been implemented in eight tables available on the web and a relational database https://sesterterpenoids.unige.net/. The interface has two sections, one open to the public for reading only and the other, protected by an authentication mechanism, for timely updating of published results.

RevDate: 2025-01-20

Gartler S, Scheer J, Meyer A, et al (2025)

A transdisciplinary, comparative analysis reveals key risks from Arctic permafrost thaw.

Communications earth & environment, 6(1):21.

Permafrost thaw poses diverse risks to Arctic environments and livelihoods. Understanding the effects of permafrost thaw is vital for informed policymaking and adaptation efforts. Here, we present the consolidated findings of a risk analysis spanning four study regions: Longyearbyen (Svalbard, Norway), the Avannaata municipality (Greenland), the Beaufort Sea region and the Mackenzie River Delta (Canada) and the Bulunskiy District of the Sakha Republic (Russia). Local stakeholders' and scientists' perceptions shaped our understanding of the risks as dynamic, socionatural phenomena involving physical processes, key hazards, and societal consequences. Through an inter- and transdisciplinary risk analysis based on multidirectional knowledge exchanges and thematic network analysis, we identified five key hazards of permafrost thaw. These include infrastructure failure, disruption of mobility and supplies, decreased water quality, challenges for food security, and exposure to diseases and contaminants. The study's novelty resides in the comparative approach spanning different disciplines, environmental and societal contexts, and the transdisciplinary synthesis considering various risk perceptions.

RevDate: 2025-01-18

Akhoon BA, Qiao Q, Stewart A, et al (2025)

Pangenomic analysis of the bacterial cellulose-producing genera Komagataeibacter and Novacetimonas.

International journal of biological macromolecules pii:S0141-8130(25)00529-X [Epub ahead of print].

Bacterial cellulose (BC) holds significant commercial potential due to its unique structural and chemical properties, making it suitable for applications in electronics, medicine, and pharmaceuticals. However, large-scale BC production remains limited by challenges in bacterial performance. In this study, we compared 79 microbial genomes from three genera-Komagataeibacter, Novacetimonas, and Gluconacetobacter-to investigate their pangenomes, genetic diversity, and evolutionary relationships. Through comparative genomic and phylogenetic analyses, we identified distinct genome compositions and evolutionary patterns that differ from previous reports. The role of horizontal gene transfer (HGT) in shaping the genetic diversity and adaptability of these bacteria was also explored. Key determinants in BC production, such as variations in the bacterial cellulose biosynthesis (bcs) operon, carbohydrate uptake genes, and carbohydrate-active enzymes, were examined. Additionally, several biosynthetic gene clusters (BGCs), including Linocin M18 and sactipeptides, which encode for antimicrobial peptides known as bacteriocins, were identified. These findings reveal new aspects of the genetic diversity in cellulose-producing bacteria and present a comprehensive genomic toolkit that will support future efforts to optimize BC production and improve microbial performance for commercial applications.

RevDate: 2025-01-20

Blum J, Brüll M, Hengstler JG, et al (2025)

The long way from raw data to NAM-based information: Overview on data layers and processing steps.

ALTEX, 42(1):167-180.

Toxicological test methods generate raw data and provide instructions on how to use these to determine a final outcome such as a classification of test compounds as hits or non-hits. The data processing pipeline provided in the test method description is often highly complex. Usually, multiple layers of data, ranging from a machine-generated output to the final hit definition, are considered. Transition between each of these layers often requires several data processing steps. As changes in any of these processing steps can impact the final output of new approach methods (NAMs), the processing pipeline is an essential part of a NAM description and should be included in reporting templates such as the ToxTemp. The same raw data, processed in different ways, may result in different final outcomes that may affect the readiness status and regulatory acceptance of the NAM, as an altered output can affect robustness, performance, and relevance. Data management, pro­cessing, and interpretation are therefore important elements of a comprehensive NAM definition. We aim to give an overview of the most important data levels to be considered during the devel­opment and application of a NAM. In addition, we illustrate data processing and evaluation steps between these data levels. As NAMs are increasingly standard components of the spectrum of toxi­cological test methods used for risk assessment, awareness of the significance of data processing steps in NAMs is crucial for building trust, ensuring acceptance, and fostering the reproducibility of NAM outcomes.

RevDate: 2025-01-20
CmpDate: 2025-01-20

Naderian M, Norland K, Schaid DJ, et al (2025)

Development and Evaluation of a Comprehensive Prediction Model for Incident Coronary Heart Disease Using Genetic, Social, and Lifestyle-Psychological Factors: A Prospective Analysis of the UK Biobank.

Annals of internal medicine, 178(1):1-10.

BACKGROUND: Clinical risk calculators for coronary heart disease (CHD) do not include genetic, social, and lifestyle-psychological risk factors.

OBJECTIVE: To improve CHD risk prediction by developing and evaluating a prediction model that incorporated a polygenic risk score (PRS) and a polysocial score (PSS), the latter including social determinants of health and lifestyle-psychological factors.

DESIGN: Cohort study.

SETTING: United Kingdom.

PARTICIPANTS: UK Biobank participants recruited between 2006 and 2010.

MEASUREMENTS: Incident CHD (myocardial infarction and/or coronary revascularization); 10-year clinical risk based on pooled cohort equations (PCE), Predicting Risk of cardiovascular disease EVENTs (PREVENT), and QRISK3; PRS (Polygenic Score Catalog identification: PGS000018) for CHD (PRSCHD); and PSSCHD from 100 related covariates. Machine-learning and time-to-event analyses and model performance indices.

RESULTS: In 388 224 participants (age, 55.5 [SD, 8.1] years; 42.5% men; 94.9% White), the hazard ratio for 1 SD increase in PSSCHD for incident CHD was 1.43 (95% CI, 1.38 to 1.49; P < 0.001) and for 1 SD increase in PRSCHD was 1.59 (CI, 1.53 to 1.66, P < 0.001). Non-White persons had higher PSSCHD than White persons. The effects of PSSCHD and PRSCHD on CHD were independent and additive. At a 10-year CHD risk threshold of 7.5%, adding PSSCHD and PRSCHD to PCE reclassified 12% of participants, with 1.86 times higher CHD risk in the up- versus down-reclassified persons and showed superior performance compared with PCE as reflected by improved net benefit while maintaining good calibration relative to the clinical risk calculators. Similar results were seen when incorporating PSSCHD and PRSCHD into PREVENT and QRISK3.

LIMITATION: A predominantly White cohort; possible healthy participant effect and ecological fallacy.

CONCLUSION: A PSSCHD was associated with incident CHD and its joint modeling with PRSCHD improved the performance of clinical risk calculators.

PRIMARY FUNDING SOURCE: National Human Genome Research Institute.

RevDate: 2025-01-20

Boyes D, Eljounaidi K, University of Oxford and Wytham Woods Genome Acquisition Lab, et al (2023)

The genome sequence of the Beautiful Golden Y, Autographa pulchrina (Haworth, 1809).

Wellcome open research, 8:375.

We present a genome assembly from an individual female Autographa pulchrina (the Beautiful Golden Y; Arthropoda; Insecta; Lepidoptera; Noctuidae). The genome sequence is 426.2 megabases in span. Most of the assembly is scaffolded into 32 chromosomal pseudomolecules, including the Z and W sex chromosomes. The mitochondrial genome has also been assembled and is 15.25 kilobases in length. Gene annotation of this assembly on Ensembl identified 12,916 protein coding genes.

RevDate: 2025-01-17
CmpDate: 2025-01-17

Burthe SJ, Kumbar B, Schäfer SM, et al (2025)

First evidence of transovarial transmission of Kyasanur Forest disease virus in Haemaphysalis and Rhipicephalus ticks in the wild.

Parasites & vectors, 18(1):14.

BACKGROUND: Kyasanur forest disease virus (KFDV) is a tick-borne flavivirus causing debilitating and potentially fatal disease in people in the Western Ghats region of India. The transmission cycle is complex, involving multiple vector and host species, but there are significant gaps in ecological knowledge. Empirical data on pathogen-vector-host interactions and incrimination have not been updated since the last century, despite significant local changes in land use and the expansion of KFD to new areas. Mathematical models predict that transovarial transmission, whereby adult female ticks pass KFDV infections to their offspring, plays an important role in the persistence of KFD, but this has not been shown in the wild. Here we set out to establish whether transovarial transmission of KFDV was occurring under natural field conditions by assessing whether host-seeking larvae were positive for KFDV.

METHODS: Ticks were sampled by dragging and flagging across a broad range of habitats within the agro-forest matrix at 49 sites in two districts: Shivamogga, Karnataka and Wayanad, Kerala (September 2018-March 2019), and larvae were tested for KFDV by PCR.

RESULTS: In total, larval ticks from 7 of the 49 sites sampled tested positive for KFDV, indicating that transovarial transmission is occurring. Of the 13 KFDV-positive larval samples, 3 came from around houses and gardens, 5 from crops (3 from harvested rice paddy and 2 from areca plantation), 1 from teak plantation and 4 (2 from 1 transect) from forests. Five different tick species were found to have KFDV-positive larvae: Haemaphysalis spinigera, H. bispinosa, Rhipicephalus annulatus, R. microplus and an unidentifiable species of Haemaphysalis (no close match in GenBank).

CONCLUSIONS: Our empirical confirmation of transovarial transmission has important implications for understanding and predicting KFD dynamics, suggesting that ticks may act as a reservoir for KFDV. Moreover, small mammals and cattle may play crucial roles in transmission if small mammals are the main hosts for larvae infected via transovarial transmission, and cattle support large numbers of infected female adult ticks. This first report of transovarial transmission of KFDV, and within a hitherto undescribed range of vectors and habitats, will help disease managers improve KFD surveillance and mitigation strategies, ultimately leading to communities becoming more resilient to the risk of this tick-transmitted disease.

RevDate: 2025-01-17
CmpDate: 2025-01-17

Canzler S, Schubert K, Rolle-Kampczyk UE, et al (2025)

Evaluating the performance of multi-omics integration: a thyroid toxicity case study.

Archives of toxicology, 99(1):309-332.

Multi-omics data integration has been repeatedly discussed as the way forward to more comprehensively cover the molecular responses of cells or organisms to chemical exposure in systems toxicology and regulatory risk assessment. In Canzler et al. (Arch Toxicol 94(2):371-388. https://doi.org/10.1007/s00204-020-02656-y), we reviewed the state of the art in applying multi-omics approaches in toxicological research and chemical risk assessment. We developed best practices for the experimental design of multi-omics studies, omics data acquisition, and subsequent omics data integration. We found that multi-omics data sets for toxicological research questions were generally rare, with no data sets comprising more than two omics layers adhering to these best practices. Due to these limitations, we could not fully assess the benefits of different data integration approaches or quantitatively evaluate the contribution of various omics layers for toxicological research questions. Here, we report on a multi-omics study on thyroid toxicity that we conducted in compliance with these best practices. We induced direct and indirect thyroid toxicity through Propylthiouracil (PTU) and Phenytoin, respectively, in a 28-day plus 14-day recovery oral rat toxicity study. We collected clinical and histopathological data and six omics layers, including the long and short transcriptome, proteome, phosphoproteome, and metabolome from plasma, thyroid, and liver. We demonstrate that the multi-omics approach is superior to single-omics in detecting responses at the regulatory pathway level. We also show how combining omics data with clinical and histopathological parameters facilitates the interpretation of the data. Furthermore, we illustrate how multi-omics integration can hint at the involvement of non-coding RNAs in post-transcriptional regulation. Also, we show that multi-omics facilitates grouping, and we assess how much information individual and combinations of omics layers contribute to this approach.

RevDate: 2025-01-17

Boyes D, University of Oxford and Wytham Woods Genome Acquisition Lab, Darwin Tree of Life Barcoding collective, et al (2024)

The genome sequence of the Poplar Grey moth, Subacronicta megacephala (Denis & Schiffermüller, 1775).

Wellcome open research, 9:696.

We present a genome assembly from an individual male Subacronicta megacephala (Poplar Grey moth; Arthropoda; Insecta; Lepidoptera; Noctuidae). The genome sequence has a total length of 424.20 megabases. Most of the assembly (99.02%) is scaffolded into 31 chromosomal pseudomolecules, including the Z sex chromosome. The mitochondrial genome has also been assembled and is 15.35 kilobases in length. Gene annotation of this assembly on Ensembl identified 18,189 protein-coding genes.

RevDate: 2025-01-17

Proença Neto MA, MPA De Sousa (2025)

Pytaxon: A Python software for resolving and correcting taxonomic names in biodiversity data.

Biodiversity data journal, 13:e138257 pii:138257.

BACKGROUND: The standardisation and correction of taxonomic names in large biodiversity databases remain persistent challenges for researchers, as errors in species names can compromise ecological analyses, land-use planning and conservation efforts, particularly when inaccurate data are shared on global biodiversity portals.

NEW INFORMATION: We present pytaxon, a Python software designed to resolve and correct taxonomic names in biodiversity data by leveraging the Global Names Verifier (GNV) API and employing fuzzy matching techniques to suggest corrections for discrepancies and nomenclatural inconsistencies. The pytaxon offers both a Command Line Interface (CLI) and a Graphical User Interface (GUI), ensuring accessibility to users with different levels of computing expertise. Tests on spreadsheets derived from datasets published in the Global Biodiversity Information Facility (GBIF) demonstrated its effectiveness in identifying and resolving taxonomic errors. By mitigating the propagation of inaccuracies from researchers' datasets to global biodiversity databases, pytaxon supports more reliable conservation decisions and robust scientific investigations. Its contributions enhance data integrity and promote informed biodiversity management in a rapidly evolving global environment.

RevDate: 2025-01-17
CmpDate: 2025-01-17

Zhang D, Cai Y, Sun Y, et al (2025)

A Real-World Disproportionality Analysis of Histamine H2-Receptors Antagonists (Famotidine): A Pharmacovigilance Study Based on Spontaneous Reports in the FDA Adverse Event Reporting System.

Drug development research, 86(1):e70045.

Famotidine is an H2 receptor antagonist and is currently used on a large scale in gastroenterology. However, Famotidine may also cause severe toxicity to organ systems, including the blood system, digestive system, and urinary system. The objective of this study was to scientifically and systematically investigate the adverse events (AEs) of Famotidine in the real world through the FDA Adverse Event Reporting System (FAERS) database. A disproportionality analysis was used to quantify the signals of AEs associated with Famotidine in FAERS data from the first quarter of 2004 to the first quarter of 2023. The clinical features, onset time, oral and intravenous administration and severe consequences of Famotidine induced AEs were further analyzed. Among the four tests, we found several AEs that were not mentioned in the drug label. For example, abdominal pain upper, abdominal discomfort, dyspepsia, liver disorder, gastrooesophageal reflux disease, and rhabdomyolysis. These AEs are consistent with the drug instructions. Interestingly, we found several unreported AEs, such as: cerebral infarction, hypocalcaemia, hallucination, visual, hypomagnesaemia, hypoparathyroidism, diabetes insipidus, vulvovaginal candidiasis, retro-orbital neoplasm, neuroblastoma recurrent, and malignant cranial nerve neoplasm. Most of our findings are consistent with clinical observations and drug labels, and we also found possible new and unexpected AEs signals, which suggest the need for prospective clinical studies to confirm these results and explain their relationships. Our findings provide valuable evidence for further safety studies.

RevDate: 2025-01-17
CmpDate: 2025-01-17

Tian Y, Yang L, Ding S, et al (2025)

BioTRY: A Comprehensive Knowledge Base for Titer, Rate, and Yield of Biosynthesis.

ACS synthetic biology, 14(1):285-289.

Synthetic biology is rapidly evolving into a data-intensive science that increasingly relies on massive data sets; one of its applications is the evaluation of the economic viability of fermentation processes. However, the key economic indicators, namely titer, rate, and yield (TRY), which respectively reflect the downstream processing, reactor size, and raw material costs, are not well captured in bioinformatics databases. In this paper, we present BioTRY, an intuitive and user-friendly tool that contains >5,000 biochemicals and >3,800 strains, along with over 52,000 corresponding TRY entries with original references. It is freely available at http://www.synbiohealth.cn/biotry. To our knowledge, BioTRY is the first available database on biosynthesis TRY data from original research. We anticipate that BioTRY will become a useful tool that aids researchers and decision-makers in understanding the current development state of biosynthesis and allows them to foresee potential prospects and applications for biosynthesis.

RevDate: 2025-01-17
CmpDate: 2025-01-17

Nevers Y, Warwick Vesztrocy A, Rossier V, et al (2025)

Quality assessment of gene repertoire annotations with OMArk.

Nature biotechnology, 43(1):124-133.

In the era of biodiversity genomics, it is crucial to ensure that annotations of protein-coding gene repertoires are accurate. State-of-the-art tools to assess genome annotations measure the completeness of a gene repertoire but are blind to other errors, such as gene overprediction or contamination. We introduce OMArk, a software package that relies on fast, alignment-free sequence comparisons between a query proteome and precomputed gene families across the tree of life. OMArk assesses not only the completeness but also the consistency of the gene repertoire as a whole relative to closely related species and reports likely contamination events. Analysis of 1,805 UniProt Eukaryotic Reference Proteomes with OMArk demonstrated strong evidence of contamination in 73 proteomes and identified error propagation in avian gene annotation resulting from the use of a fragmented zebra finch proteome as a reference. This study illustrates the importance of comparing and prioritizing proteomes based on their quality measures.

RevDate: 2025-01-15
CmpDate: 2025-01-15

Gómez-Gras D, Linares C, Viladrich N, et al (2025)

The Octocoral Trait Database: a global database of trait information for octocoral species.

Scientific data, 12(1):82.

Trait-based approaches are revolutionizing our understanding of high-diversity ecosystems by providing insights into the principles underlying key ecological processes, such as community assembly, species distribution, resilience, and the relationship between biodiversity and ecosystem functioning. In 2016, the Coral Trait Database advanced coral reef science by centralizing trait information for stony corals (i.e., Subphylum Anthozoa, Class Hexacorallia, Order Scleractinia). However, the absence of trait data for soft corals, gorgonians, and sea pens (i.e., Class Octocorallia) limits our understanding of ecosystems where these organisms are significant members and play pivotal roles. To address this gap, we introduce the Octocoral Trait Database, a global, open-source database of curated trait data for octocorals. This database houses species- and individual-level data, complemented by contextual information that provides a relevant framework for analyses. The inaugural dataset, OctocoralTraits v2.2, contains over 97,500 global trait observations across 98 traits and over 3,500 species. The database aims to evolve into a steadily growing, community-led resource that advances future marine science, with a particular emphasis on coral reef research.

RevDate: 2025-01-15

Knight ME, Farkas K, Wade M, et al (2025)

Wastewater-based analysis of antimicrobial resistance at UK airports: Evaluating the potential opportunities and challenges.

Environment international, 195:109260 pii:S0160-4120(25)00011-X [Epub ahead of print].

With 40 million annual passenger flights, airports are key hubs for microbial communities from diverse geographic origins to converge, mix, and distribute. Wastewater derived from airports and aircraft represent both a potential route for the global dispersion of antimicrobial resistant (AMR) organisms and an under-utilised resource for strengthening global AMR surveillance. This study investigates the abundance and diversity of antimicrobial resistance genes (ARGs) in wastewater samples collected from airport terminals (n = 132), aircraft (n = 25), and a connected wastewater treatment plant (n = 11) at three international airports in the UK (London Heathrow, Edinburgh and Bristol). A total of 76 ARGs were quantified using high throughput qPCR (HT-qPCR) while a subset of samples (n = 30) was further analysed by metagenomic sequencing. Our findings reveal that aircraft wastewater resistomes were compositionally distinct from those observed at airport terminals, despite their similar diversity. Notably, flights originating from Asia and Africa carried a higher number of unique ARGs compared to those from Europe and North America. However, clustering of the ARG profile displayed no overall association with geography. Edinburgh terminal and pumping station wastewater had compositionally comparable resistomes to that of the connected urban wastewater treatment plant, though further research is needed to determine the relative contributions of the local population and international travellers. This study provides the first comprehensive investigation of AMR in wastewater from both aircraft and terminals across multiple international airports. Our results highlight aircraft wastewater as a potential route for cross-border AMR transmission and a valuable tool for global AMR surveillance. However, the findings also underscore the limitations and need for standardised approaches for AMR monitoring in airport environments, to effectively mitigate the global spread of AMR and enhance public health surveillance strategies.

RevDate: 2025-01-15
CmpDate: 2025-01-15

Gu S, Shao Z, Qu Z, et al (2025)

Siderophore synthetase-receptor gene coevolution reveals habitat- and pathogen-specific bacterial iron interaction networks.

Science advances, 11(3):eadq5038.

Bacterial social interactions play crucial roles in various ecological, medical, and biotechnological contexts. However, predicting these interactions from genome sequences is notoriously difficult. Here, we developed bioinformatic tools to predict whether secreted iron-scavenging siderophores stimulate or inhibit the growth of community members. Siderophores are chemically diverse and can be stimulatory or inhibitory depending on whether bacteria have or lack corresponding uptake receptors. We focused on 1928 representative Pseudomonas genomes and developed an experimentally validated coevolution algorithm to match encoded siderophore synthetases to corresponding receptor groups. We derived community-level iron interaction networks to show that siderophore-mediated interactions differ across habitats and lifestyles. Specifically, dense networks of siderophore sharing and competition were observed among environmental and nonpathogenic species, while small, fragmented networks occurred among human-associated and pathogenic species. Together, our sequence-to-ecology approach empowers the analyses of social interactions among thousands of bacterial strains and offers opportunities for targeted intervention to microbial communities.

RevDate: 2025-01-14
CmpDate: 2025-01-14

Amino K, Hirakawa T, Yago M, et al (2025)

Dorsoventral comparison of intraspecific variation in the butterfly wing pattern using a convolutional neural network.

Biology letters, 21(1):20240446.

Butterfly wing patterns exhibit notable differences between the dorsal and ventral surfaces, and morphological analyses of them have provided insights into the ecological and behavioural characteristics of wing patterns. Conventional methods for dorsoventral comparisons are constrained by the need for homologous patches or shared features between two surfaces, limiting their applicability across species. We used a convolutional neural network (CNN)-based analysis, which can compare images of the two surfaces without focusing on homologous patches or features, to detect dorsoventral bias in two types of intraspecific variation: sexual dimorphism and mimetic polymorphism. Using specimen images of 29 species, we first showed that the level of sexual dimorphism calculated by CNN-based analysis corresponded well with traditional assessments of sexual dissimilarity, demonstrating the validity of the method. Dorsal biases were widely detected in sexual dimorphism, suggesting that the conventional hypothesis of dorsally biased sexual selection can be supported in a broader range of species. In contrast, mimetic polymorphism showed no such bias, indicating the importance of both surfaces in mimicry. Our study demonstrates the potential versatility of CNN in comparing wing patterns between the two surfaces, while elucidating the relationship between dorsoventrally different selections and dorsoventral biases in intraspecific variations.

RevDate: 2025-01-14
CmpDate: 2025-01-14

Smith SD, Geraghty EM, Rivas AL, et al (2024)

Multidimensional perspectives of geo-epidemiology: from interdisciplinary learning and research to cost-benefit oriented decision-making.

Frontiers in public health, 12:1492426.

Research typically promotes two types of outcomes (inventions and discoveries), which induce a virtuous cycle: something suspected or desired (not previously demonstrated) may become known or feasible once a new tool or procedure is invented and, later, the use of this invention may discover new knowledge. Research also promotes the opposite sequence-from new knowledge to new inventions. This bidirectional process is observed in geo-referenced epidemiology-a field that relates to but may also differ from spatial epidemiology. Geo-epidemiology encompasses several theories and technologies that promote inter/transdisciplinary knowledge integration, education, and research in population health. Based on visual examples derived from geo-referenced studies on epidemics and epizootics, this report demonstrates that this field may extract more (geographically related) information than simple spatial analyses, which then supports more effective and/or less costly interventions. Actual (not simulated) bio-geo-temporal interactions (never captured before the emergence of technologies that analyze geo-referenced data, such as geographical information systems) can now address research questions that relate to several fields, such as Network Theory. Thus, a new opportunity arises before us, which exceeds research: it also demands knowledge integration across disciplines as well as novel educational programs which, to be biomedically and socially justified, should demonstrate cost-effectiveness. Grounded on many bio-temporal-georeferenced examples, this report reviews the literature that supports this hypothesis: novel educational programs that focus on geo-referenced epidemic data may help generate cost-effective policies that prevent or control disease dissemination.

RevDate: 2025-01-14
CmpDate: 2025-01-14

Shen A, Ye J, Zhao H, et al (2024)

Risk factors and prediction model of breast cancer-related lymphoedema in a Chinese cancer centre: a prospective cohort study protocol.

BMJ open, 14(12):e089769 pii:bmjopen-2024-089769.

INTRODUCTION: Lymphoedema is a distressing and long-term complication for breast cancer survivors. However, the reported incidence of lymphoedema varies, and its risk factors remain underexplored. Currently, a well-established risk prediction model is still lacking. This study aims to describe the rationale, objectives, protocol and baseline characteristics of a prospective cohort study focused on examining the incidence and risk factors of breast cancer-related lymphoedema (BCRL), as well as developing a risk prediction model.

METHODS AND ANALYSIS: This study is an ongoing single-centre prospective observational cohort study recruiting 1967 patients with breast cancer scheduled for surgery treatment in northern China between 15 February 2022 and 21 June 2023. Assessments will be conducted presurgery and at 1, 3, 6, 12, 18, 24, 30 and 36 months postsurgery. Bilateral limb circumferences will be measured by patients at home or by researchers at the outpatient clinics during follow-up visits. The diagnosis of lymphoedema is based on a relative limb volume increase of ≥10% from the preoperative assessment. Self-reported symptoms will be assessed to assist in diagnosis. Potential risk factors are classified into innate personal traits, behavioural lifestyle, interpersonal networks, socioeconomic status and macroenvironmental factors, based on health ecology model. Data collection, storage and management were conducted using the online 'H6WORLD' data management platform. Survival analysis using the Kaplan-Meier estimate will determine the incidence of BCRL. Risk factors of BCRL will be analysed using log-rank test and COX-LASSO regression. Traditional COX regression analysis and seven common survival analysis machine learning algorithms (COX, CARST, RSF, GBSM, XGBS, SSVM and SANN) will be employed for model construction and validation.

ETHICS AND DISSEMINATION: The study protocol was approved by the Biomedical Ethics Committee of Peking University (IRB00001052-21124) and the Research Ethics Committee of Tianjin Medical University Cancer Institute and Hospital (bc2023013). The results of this study will be published in peer-reviewed journals and will be presented at several research conferences.

TRIAL REGISTRATION NUMBER: ChiCTR2200057083.

RevDate: 2025-01-14
CmpDate: 2025-01-14

Paulukonis EA, ST Purucker (2025)

Spatiotemporally derived agricultural field delineations for species effects assessments and environmental decision support.

The Science of the total environment, 958:177967.

Rural landscapes are strongly defined by the spatial distribution of agricultural fields. GIS layers that capture this information have much utility in many decision support contexts, particularly with regards to the intersection of agricultural pesticide use and endangered species habitat. The United States Department of Agriculture's Cropland Data Layer (CDL) is a georeferenced, annual resource that often serves a crucial role in pesticide risk-related decision support applications. However, CDL agriculture timeseries data are not mapped to explicit field boundaries, contributing to increased uncertainty regarding differentiated crop type spatial homogeneity and geographic extent, inherently adding complexity to multi-temporal crop monitoring and analyses efforts. We describe the development and testing of an approach for field delineation based on timeseries information from the 2008-2021 CDL at spatial scales relevant for endangered species risk assessment. We validate and test the approach against quantitative crop information and contextualize the outputs as part of a case study reconstructing past agricultural pesticide exposures to non-target species to demonstrate the utility of the method for ecological risk assessment decision support. The approach resulted in delineated field unit boundaries that effectively incorporated the unmodified CDL crop type generalized spatial distribution patterns; derived metrics closely corresponded with reported crop metrics for landscapes with proportionally significant agriculture use. When modified to reflect areas of mixed/small crop acreages, the method can provide a useful framework for large-scale field delineation of the CDL, which can complement ongoing environmental risk assessment and conservation efforts in agricultural landscapes.

RevDate: 2025-01-14
CmpDate: 2025-01-14

Daru BH (2025)

A global database of butterfly species native distributions.

Ecology, 106(1):e4462.

Butterflies represent a diverse group of insects, playing key ecosystem roles such as pollination and their larval form engage in herbivory. Despite their importance, comprehensive global distribution data for butterfly species are lacking. This lack of comprehensive global data has hindered many large-scale questions in ecology, evolutionary biology, and conservation at the regional and global scales. Here, I use an integrative workflow that combines occurrence records, alpha hull polygons, species' dispersal capacity, and natural habitat and environmental variables within a framework of species distribution models to generate species-level native distributions for butterflies at a global scale in the contemporary period. The database releases native range maps for 10,372 extant species of butterflies at a spatial grain resolution of 5 arcmin (~10 km). This database has the potential to allow unprecedented large-scale analyses in ecology, biogeography, and conservation of butterflies. The maps are available in the WGS84 coordinate reference system (EPSG:4326 code) and stored as vector polygons in the GEOPACKAGE format for maximum compression, allowing easy data manipulation using a standard computer. I additionally provide each species' spatial raster. All maps and R scripts are open access and available for download in Dryad and Zenodo, respectively, and are guided by FAIR (Findable, Accessible, Interoperable, and Reusable) data principles. By making these data available to the scientific community, I aim to advance the sharing of biological data to stimulate more comprehensive research in ecology, biogeography, and conservation of butterflies.

RevDate: 2025-01-13

Daruka L, Czikkely MS, Szili P, et al (2025)

ESKAPE pathogens rapidly develop resistance against antibiotics in development in vitro.

Nature microbiology [Epub ahead of print].

Despite ongoing antibiotic development, evolution of resistance may render candidate antibiotics ineffective. Here we studied in vitro emergence of resistance to 13 antibiotics introduced after 2017 or currently in development, compared with in-use antibiotics. Laboratory evolution showed that clinically relevant resistance arises within 60 days of antibiotic exposure in Escherichia coli, Klebsiella pneumoniae, Acinetobacter baumannii and Pseudomonas aeruginosa, priority Gram-negative ESKAPE pathogens. Resistance mutations are already present in natural populations of pathogens, indicating that resistance in nature can emerge through selection of pre-existing bacterial variants. Functional metagenomics showed that mobile resistance genes to antibiotic candidates are prevalent in clinical bacterial isolates, soil and human gut microbiomes. Overall, antibiotic candidates show similar susceptibility to resistance development as antibiotics currently in use, and the corresponding resistance mechanisms overlap. However, certain combinations of antibiotics and bacterial strains were less prone to developing resistance, revealing potential narrow-spectrum antibacterial therapies that could remain effective. Finally, we develop criteria to guide efforts in developing effective antibiotic candidates.

RevDate: 2025-01-13

Palma-Martínez MJ, Posadas-García YS, López-Ángeles BE, et al (2024)

The multi-scale complexity of human genetic variation beyond continental groups.

bioRxiv : the preprint server for biology.

Traditional clustering and visualization approaches in human genetics often operate under frameworks that assume inherent, discrete groupings[1,2]. These methods can inadvertently simplify multifaceted relationships, functioning to entrench the idea of typological groups[3]. We introduce a network-based pipeline and visualization tool grounded in relational thinking[4], which constructs networks from a variety of genetic similarity metrics. We identify communities at multiple resolutions, departing from typological models of analysis and interpretation that categorize individuals into a (predefined) number of sets. We applied our pipeline to a dataset merged from the 1000 Genomes and Human Genome Diversity Project[5], revealing the limitations of traditional groupings and capturing the complexities introduced by demographic events and evolutionary processes. This method embraces the context-specificity of genetic similarities that are salient depending on the question, markers of interest, and study individuals. Different numbers of communities are revealed depending on the resolution chosen and metric used, underscoring a fluid spectrum of genetic relationships and challenging the notion of universal categorization. We provide a web application (https://sohail-lab.shinyapps.io/GG-NC/) for interactive visualization and engagement with these intricate genetic landscapes.

RevDate: 2025-01-12

Fridman M, Krasko O, I Veyalkin (2025)

The incidence trends of papillary thyroid carcinoma in Belarus during the post-Chernobyl epoch.

Cancer epidemiology, 95:102745 pii:S1877-7821(25)00004-9 [Epub ahead of print].

BACKGROUND: The increase of papillary thyroid cancer (PTC) rate among children who were exposed to post-Chernobyl 131-I release was reported only four years after the accident, first in Belarus where the heaviest fallout happened. The evolution of the occurrence of thyroid carcinoma based on the age-period-cohort analysis and the effects of age, period, and birth cohort on time trends aimed to reveal if post-Chernobyl follicular cells irradiation still has been impacting on incidence rate of papillary thyroid carcinoma nowadays.

METHODS: The Belarusian Cancer Registry was used to identify patients with PTC diagnosed during the years 1980-2019. The incidence trends were analysed using Join-point regression software.

RESULTS: The highest peak of age-specific incidence curve was shown during the years 1980-2001 in the age group of 15-19 years old that was associated also with short-latency cases of post-Chernobyl PTC. This is the same age group that demonstrated significant growth of the incidence rate during the years 2006-2019, largely because of the increasing number of non-exposed patients with PTC (p < 0.001). Influence of post-Chernobyl exposure also can be seen in the young adults age-groups of patients (for 20-24 years old during the years 1980-2003 and 2013-2019, p < 0.001; for 25-29 years old during the years 1980-1999 and 1999-2011, p < 0.001).

CONCLUSION: After the Chernobyl accident, epidemiological waves that reflect the age shift of the group of children exposed to 131-I have consistently emerged. Currently, the incidence rate continues to increase only in the cohort of patients aged 20-44 years.

RevDate: 2025-01-11

Li J, Lu Y, Chen X, et al (2025)

Seasonal variation of microbial community and diversity in the Taiwan Strait sediments.

Environmental research pii:S0013-9351(25)00060-X [Epub ahead of print].

Human activities and ocean currents in the Taiwan Strait exhibit significant seasonal variation, yet the response of marine microbes to ocean changes under anthropogenic and climatic stress remains unclear. Using 16S rRNA gene amplicon sequencing, we investigated the spatiotemporal dynamics and functional variations of microbial communities in sediment samples. Our findings revealed distinct seasonal patterns in microbial diversity and composition. Proteobacteria, Desulfobacterota, and Crenarchaeota dominated at the phylum level, while Candidatus Nitrosopumilus, Woeseia, and Subgroup 10 were prevalent at the genus level. Iron concentrations, heavy metals and C/N ratio were primary factors influencing microbial communities during specific seasons, whereas sulfur content, temperature fluctuations, and heavy metals shaped the entire microbial structure and diversity. Core microbial groups, including Desulfobulbus, Subgroup 10, Unidentified Latescibacterota, and Sumerlaea, played essential roles in regulating community structure and functional transitions. Marker species, such as Aliidiomarina sanyensis, Spirulina platensis, Croceimarina litoralis and Sulfuriflexus mobilis, acted as seasonal indicators. Bacteria exhibited survival strategy akin to higher organisms, encompassing process of synthesis, growth, dormancy, and disease resistance throughout the seasonal cycle. Core microbial groups and marker species in specific seasons can serve as indicators for monitoring and assessing the health of the Taiwan Strait ecosystem.

RevDate: 2025-01-10
CmpDate: 2025-01-10

Mohammad L, Bandyopadhyay J, Mondal I, et al (2025)

Assessing cropping system dynamics over three decades: remote sensing and GIS insights in Murshidabad-Jiaganj Block.

Environmental monitoring and assessment, 197(2):164.

Agriculture is a significant contributor to the country's economic development. We used multiple Landsat images from 1990 to 2021 in the Murshidabad-Jiaganj Block to assess changes in the agricultural system and their underlying causes. The Rabi season saw a 10.99% growth in agrarian regions from 1990 to 2000 and an 8.86% increase in 2010, yet it declined by 28.12% in 2021. During the summer, the cultivated lands diminished by 26.63%, 19.43%, and 19.64%, while in the Kharif season, they declined by 21.78%, 15.68%, and 11.99% from 1990 in the years 2000, 2010, and 2021, respectively. The agricultural area had 36.82%, 34.16%, and 19.01% increases between 1990 and 2021, respectively. Regarding direction, farmland acreage decreased in all zones except the SSE, which had a 0.95% increase. Mono-, double-, and triple-cropping systems have decreased in area, while multi-cropping systems have experienced increases of 43.51%, 4.50%, and 18.49% in 1990-2021, respectively. The multi-cropping system has a good correlation with all agroclimatic factors. The reduction of irrigated lands post-2009 significantly affected the agriculture system. The fall in agricultural employment in recent decades is attributable to migration seeking higher-paying occupations. The advancement of accurate remote sensing-based modeling is crucial for mitigating food security risks, particularly those posed by climate change, and informing policy decisions.

RevDate: 2025-01-10
CmpDate: 2025-01-10

Sasia I, Bueno G, I Etxano (2025)

Amalur EIS: a system for calculating the environmental impacts of industrial sites from E-PRTR records.

Environmental monitoring and assessment, 197(2):163.

This article presents Amalur EIS (https://www.amalur-eis.eus/), an Environmental Information System that estimates environmental impacts using data sourced from the European Pollutant Release and Transfer Register database (E-PRTR). The system uses data on the releases into land, air and water of 31,556 European industrial facilities for the period 2007-2021. Amalur EIS calculates environmental impacts of industrial releases using 31 life cycle impact assessment methods (LCIA) and covering 78 of the 91 pollutants regulated by the PRTR Protocol. The system has been constructed using a two-layer software infrastructure: (i) a data layer supported by a relational database built in Postgres and (ii) a presentation layer built in Tableau, so it provides user-friendly access to the information. For an illustrative analysis of the tool, the EF 3.0 LCIA method recommended by the European Commission was used, including normalisation and weighting steps for a better comparison. The analysis concludes that the climate change impact category contributes the most (68.6%) to the total impacts, while the largest contributor from an economic activity perspective is the energy sector (59.5%). Geographically, both elements coincide in the German regions of Düsseldorf, Köln and Brandenburg, resulting in the concentration of the largest impacts at the European regional level. In fact, Germany is the country with the highest impact (20.3% of total). Beyond this analysis, Amalur EIS is poised to be a valuable tool for tracking the transition towards sustainability, particularly in Europe.

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ESP Quick Facts

ESP Origins

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

ESP Support

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

ESP Rationale

Although the methods of molecular biology can seem almost magical to the uninitiated, the original techniques of classical genetics are readily appreciated by one and all: cross individuals that differ in some inherited trait, collect all of the progeny, score their attributes, and propose mechanisms to explain the patterns of inheritance observed.

ESP Goal

In reading the early works of classical genetics, one is drawn, almost inexorably, into ever more complex models, until molecular explanations begin to seem both necessary and natural. At that point, the tools for understanding genome research are at hand. Assisting readers reach this point was the original goal of The Electronic Scholarly Publishing Project.

ESP Usage

Usage of the site grew rapidly and has remained high. Faculty began to use the site for their assigned readings. Other on-line publishers, ranging from The New York Times to Nature referenced ESP materials in their own publications. Nobel laureates (e.g., Joshua Lederberg) regularly used the site and even wrote to suggest changes and improvements.

ESP Content

When the site began, no journals were making their early content available in digital format. As a result, ESP was obliged to digitize classic literature before it could be made available. For many important papers — such as Mendel's original paper or the first genetic map — ESP had to produce entirely new typeset versions of the works, if they were to be available in a high-quality format.

ESP Help

Early support from the DOE component of the Human Genome Project was critically important for getting the ESP project on a firm foundation. Since that funding ended (nearly 20 years ago), the project has been operated as a purely volunteer effort. Anyone wishing to assist in these efforts should send an email to Robbins.

ESP Plans

With the development of methods for adding typeset side notes to PDF files, the ESP project now plans to add annotated versions of some classical papers to its holdings. We also plan to add new reference and pedagogical material. We have already started providing regularly updated, comprehensive bibliographies to the ESP.ORG site.

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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

Electronic Scholarly Publishing
961 Red Tail Lane
Bellingham, WA 98226

E-mail: RJR8222 @ gmail.com

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.

Digital Books

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.

Biographies

Biographical information about many key scientists (e.g., Walter Sutton).

Selected Bibliographies

Bibliographies on several topics of potential interest to the ESP community are automatically maintained and generated on the ESP site.

ESP Picks from Around the Web (updated 28 JUL 2024 )