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22 Apr 2024 at 01:44
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Bibliography on: Ecological Informatics


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RJR: Recommended Bibliography 22 Apr 2024 at 01:44 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 the National Science Foundation's Datanet , DataONE and Data Conservancy projects.

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

Citations The Papers (from PubMed®)


RevDate: 2024-04-16

Jonathan J, Barakabitze AA, Fast CD, et al (2024)

Machine Learning for Prediction of Tuberculosis Detection: Case Study of Trained African Giant Pouched Rats.

Online journal of public health informatics, 16:e50771 pii:v16i1e50771.

BACKGROUND: Technological advancement has led to the growth and rapid increase of tuberculosis (TB) medical data generated from different health care areas, including diagnosis. Prioritizing better adoption and acceptance of innovative diagnostic technology to reduce the spread of TB significantly benefits developing countries. Trained TB-detection rats are used in Tanzania and Ethiopia for operational research to complement other TB diagnostic tools. This technology has increased new TB case detection owing to its speed, cost-effectiveness, and sensitivity.

OBJECTIVE: During the TB detection process, rats produce vast amounts of data, providing an opportunity to identify interesting patterns that influence TB detection performance. This study aimed to develop models that predict if the rat will hit (indicate the presence of TB within) the sample or not using machine learning (ML) techniques. The goal was to improve the diagnostic accuracy and performance of TB detection involving rats.

METHODS: APOPO (Anti-Persoonsmijnen Ontmijnende Product Ontwikkeling) Center in Morogoro provided data for this study from 2012 to 2019, and 366,441 observations were used to build predictive models using ML techniques, including decision tree, random forest, naïve Bayes, support vector machine, and k-nearest neighbor, by incorporating a variety of variables, such as the diagnostic results from partner health clinics using methods endorsed by the World Health Organization (WHO).

RESULTS: The support vector machine technique yielded the highest accuracy of 83.39% for prediction compared to other ML techniques used. Furthermore, this study found that the inclusion of variables related to whether the sample contained TB or not increased the performance accuracy of the predictive model.

CONCLUSIONS: The inclusion of variables related to the diagnostic results of TB samples may improve the detection performance of the trained rats. The study results may be of importance to TB-detection rat trainers and TB decision-makers as the results may prompt them to take action to maintain the usefulness of the technology and increase the TB detection performance of trained rats.

RevDate: 2024-04-18
CmpDate: 2024-04-17

Liu X, Chen J, Tang BH, et al (2024)

Eco-environmental changes due to human activities in the Erhai Lake Basin from 1990 to 2020.

Scientific reports, 14(1):8646.

Human activities have increased with urbanisation in the Erhai Lake Basin, considerably impacting its eco-environmental quality (EEQ). This study aims to reveal the evolution and driving forces of the EEQ using water benefit-based ecological index (WBEI) in response to human activities and policy variations in the Erhai Lake Basin from 1990 to 2020. Results show that (1) the EEQ exhibited a pattern of initial degradation, subsequent improvement, further degradation and a rebound from 1990 to 2020, and the areas with poor and fair EEQ levels mainly concentrated around the Erhai Lake Basin with a high level of urbanisation and relatively flat terrain; (2) the EEQ levels were not optimistic in 1990, 1995 and 2015, and areas with poor and fair EEQ levels accounted for 43.41%, 47.01% and 40.05% of the total area, respectively; and (3) an overall improvement in the EEQ was observed in 1995-2000, 2000-2005, 2005-2009 and 2015-2020, and the improvement was most significant in 1995-2000, covering an area of 823.95 km[2] and accounting for 31.79% of the total area. Results also confirmed that the EEQ changes in the Erhai Lake Basin were primarily influenced by human activities and policy variations. Moreover, these results can provide a scientific basis for the formulation and planning of sustainable development policy in the Erhai Lake Basin.

RevDate: 2024-04-18
CmpDate: 2024-04-18

Hou Z, Qiang W, Wang X, et al (2024)

"Cell Disk" DNA Storage System Capable of Random Reading and Rewriting.

Advanced science (Weinheim, Baden-Wurttemberg, Germany), 11(15):e2305921.

DNA has emerged as an appealing material for information storage due to its great storage density and durability. Random reading and rewriting are essential tasks for practical large-scale data storage. However, they are currently difficult to implement simultaneously in a single DNA-based storage system, strongly limiting their practicability. Here, a "Cell Disk" storage system is presented, achieving high-density in vivo DNA data storage that enables both random reading and rewriting. In this system, each yeast cell is used as a chamber to store information, similar to a "disk block" but with the ability to self-replicate. Specifically, each genome of yeast cell has a customized CRISPR/Cas9-based "lock-and-key" module inserted, which allows selective retrieval, erasure, or rewriting of the targeted cell "block" from a pool of cells ("disk"). Additionally, a codec algorithm with lossless compression ability is developed to improve the information density of each cell "block". As a proof of concept, target-specific reading and rewriting of the compressed data from a mimic cell "disk" comprising up to 10[5] "blocks" are demonstrated and achieve high specificity and reliability. The "Cell Disk" system described here concurrently supports random reading and rewriting, and it should have great scalability for practical data storage use.

RevDate: 2024-04-15

Turtle L, Elliot S, Drake TM, et al (2024)

Changes in hospital mortality in patients with cancer during the COVID-19 pandemic (ISARIC-CCP-UK): a prospective, multicentre cohort study.

The Lancet. Oncology pii:S1470-2045(24)00107-4 [Epub ahead of print].

BACKGROUND: Patients with cancer are at greater risk of dying from COVID-19 than many other patient groups. However, how this risk evolved during the pandemic remains unclear. We aimed to determine, on the basis of the UK national pandemic protocol, how factors influencing hospital mortality from COVID-19 could differentially affect patients undergoing cancer treatment. We also examined changes in hospital mortality and escalation of care in patients on cancer treatment during the first 2 years of the COVID-19 pandemic in the UK.

METHODS: We conducted a prospective cohort study of patients aged older than 19 years and admitted to 306 health-care facilities in the UK with confirmed SARS-CoV-2 infection, who were enrolled in the International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) WHO Clinical Characterisation Protocol (CCP) across the UK from April 23, 2020, to Feb 28, 2022; this analysis included all patients in the complete dataset when the study closed. The primary outcome was 30-day in-hospital mortality, comparing patients on cancer treatment and those without cancer. The study was approved by the South Central-Oxford C Research Ethics Committee in England (Ref: 13/SC/0149) and the Scotland A Research Ethics Committee (Ref 20/SS/0028), and is registered on the ISRCTN Registry (ISRCTN66726260).

FINDINGS: 177 871 eligible adult patients either with no history of cancer (n=171 303) or on cancer treatment (n=6568) were enrolled; 93 205 (52·4%) were male, 84 418 (47·5%) were female, and in 248 (13·9%) sex or gender details were not specified or data were missing. Patients were followed up for a median of 13 (IQR 6-21) days. Of the 6568 patients receiving cancer treatment, 2080 (31·7%) died at 30 days, compared with 30 901 (18·0%) of 171 303 patients without cancer. Patients aged younger than 50 years on cancer treatment had the highest age-adjusted relative risk (hazard ratio [HR] 5·2 [95% CI 4·0-6·6], p<0·0001; vs 50-69 years 2·4 [2·2-2·6], p<0·0001; 70-79 years 1·8 [1·6-2·0], p<0·0001; and >80 years 1·5 [1·3-1·6], p<0·0001) but a lower absolute risk (51 [6·7%] of 763 patients <50 years died compared with 459 [30·2%] of 1522 patients aged >80 years). In-hospital mortality decreased for all patients during the pandemic but was higher for patients on cancer treatment than for those without cancer throughout the study period.

INTERPRETATION: People with cancer have a higher risk of mortality from COVID-19 than those without cancer. Patients younger than 50 years with cancer treatment have the highest relative risk of death. Continued action is needed to mitigate the poor outcomes in patients with cancer, such as through optimising vaccination, long-acting passive immunisation, and early access to therapeutics. These findings underscore the importance of the ISARIC-WHO pandemic preparedness initiative.

FUNDING: National Institute for Health Research and the Medical Research Council.

RevDate: 2024-04-17
CmpDate: 2024-04-17

Enjavinejad SM, Zahedifar M, Moosavi AA, et al (2024)

Integrated application of multiple indicators and geographic information system-based approaches for comprehensive assessment of environmental impacts of toxic metals-contaminated agricultural soils and vegetables.

The Science of the total environment, 926:171747.

Conventional monitoring and mapping approaches are laborious, expensive, and time-consuming because they need a large number of data and consequently extensive sampling and experimental operations. Therefore, due to the growing concern about the potential of contamination of soils and agricultural products with heavy metals (HMs), a field experiment was conducted on 77 farm lands in an area of 2300 ha in the southeast of Shiraz (Iran) to investigate the source of metal contamination in the soils and vegetables and to model spatial distribution of HMs (iron, Fe; manganese, Mn; copper, Cu; zinc, Zn; cadmium, Cd; nickel, Ni, and lead, Pb) over the region using geographic information system (GIS) and geostatistical (Ordinary Kriging, OK) approaches and compare the results with deterministic approaches (Inverse Distance Weighting, IDW with different weighting power). Furthermore, some ecological and health risks indices including Pollution index (PI), Nemerow integrated pollution index (NIPI), pollution load index (PLI), degree of contamination (Cdeg), modified contamination degree (mCd), PIaverage and PIvector for soil quality, multi-element contamination (MEC), the probability of toxicity (MERMQ), the potential ecological index (RI), total hazard index (THI) and total carcinogenic risk index (TCR) based on ingestion, inhalation, and dermal exposure pathways for adults and children respectively for analyzing the noncarcinogenic and carcinogenic risks were calculated. Experimental semivariogram of the mentioned HMs were calculated and theoretical models (i.e., exponential, spherical, Gaussian, and linear models) were fitted in order to model their spatial structures and to investigate the most representative models. Moreover, principal component analysis (PCA) and cluster analysis (CA) were used to identify sources of HMs in the soils. Results showed that IDW method was more efficient than the OK approach to estimate the properties and HMs contents in the soils and plants. The estimated daily intake of metals (DIM) values of Pb and Ni exceeded their safe limits. In addition, Cd was the main element responsible for ecological risk. The PIave and PIvector indices showed that soil quality in the study area is not suitable. According to mCd values, the soils classified as ultra-high contaminated for Cu and Cd, extremely high for Zn and Pb, very high, high, and very low degree of contamination for Ni, Mn, and Fe, respectively. 36, 60, and 4 % of the sampling sites had high, medium, and low risk levels with 49, 21, and 9 % probability of toxicity, respectively. The maximum health risk index (HRI) value of 20.42 with extremely high risk for children was obtained for Ni and the HI for adults and children were 0.22 and 1.55, respectively. The THI values of Pb and Cd were the highest compared to the other HMs studied, revealing a possible non-cancer risk in children associated with exposure to these metals. The routes of exposure with the greatest influence on the THI and TCR indices were in the order of ingestion > inhalation > dermal. Therefore, ingestion, as the main route of exposure, is the route of greatest contribution to health risks. PCA analysis revealed that Fe, Mn, Cu, and Ni may originate from natural sources, while Fe was appeared to be controlled by fertilizer, and Cu primarily coming from pesticide, while Cd and Pb were mainly associated with the anthropogenic contamination, atmospheric depositions, and terrific in the urban soils. While, Zn mainly originated from fertilization. Findings are vital for developing remediation approaches for controlling the contaminants distribution as well as for monitoring and mapping the quality and health of soil resources.

RevDate: 2024-04-16

Short S, Green Etxabe A, Robinson A, et al (2023)

The genome sequence of the red compost earthworm, Lumbricus rubellus (Hoffmeister, 1843).

Wellcome open research, 8:354.

We present a genome assembly from an individual Lumbricus rubellus (the red compost earthworm; Annelida; Clitellata; Haplotaxida; Lumbricidae). The genome sequence is 787.5 megabases in span. Most of the assembly is scaffolded into 18 chromosomal pseudomolecules. The mitochondrial genome has also been assembled and is 15.81 kilobases in length. Gene annotation of this assembly on Ensembl identified 33,426 protein coding genes.

RevDate: 2024-04-16

Liu J, He C, Si Y, et al (2024)

Toward Better and Healthier Air Quality: Global PM2.5 and O3 Pollution Status and Risk Assessment Based on the New WHO Air Quality Guidelines for 2021.

Global challenges (Hoboken, NJ), 8(4):2300258.

To reduce the high burden of disease caused by air pollution, the World Health Organization (WHO) released new Air Quality Guidelines (AQG) on September 22, 2021. In this study, the daily fine particulate matter (PM2.5) and surface ozone (O3) data of 618 cities around the world is collected from 2019 to 2022. Based on the new AQG, the number of attainment days for daily average concentrations of PM2.5 (≤ 15 µg m[-3]) and O3 (≤ 100 µg m[-3]) is approximately 10% and 90%, respectively. China and India exhibit a decreasing trend in the number of highly polluted days (> 75 µg m[-3]) for PM. Every year over 68% and 27% of cities in the world are exposed to harmful PM2.5 (> 35 µg m[-3]) and O3 (> 100 µg m[-3]) pollution, respectively. Combined with the United Nations Sustainable Development Goals (SDGs), it is found that more than 35% of the world's cities face PM2.5-O3 compound pollution. Furthermore, the exposure risks in these cities (China, India, etc.) are mainly categorized as "High Risk", "Risk", and "Stabilization". In contrast, economically developed cities are mainly categorized as "High Safety", "Safety", and "Deep Stabilization." These findings indicate that global implementation of the WHO's new AQG will minimize the inequitable exposure risk from air pollution.

RevDate: 2024-04-16
CmpDate: 2024-04-16

Kibet CK, Entfellner JD, Jjingo D, et al (2024)

Designing and delivering bioinformatics project-based learning in East Africa.

BMC bioinformatics, 25(1):150.

BACKGROUND: The Eastern Africa Network for Bioinformatics Training (EANBiT) has matured through continuous evaluation, feedback, and codesign. We highlight how the program has evolved to meet challenges and achieve its goals and how experiential learning through mini projects enhances the acquisition of skills and collaboration. We continued to learn and grow through honest feedback and evaluation of the program, trainers, and modules, enabling us to provide robust training even during the Coronavirus disease 2019 (COVID-19) pandemic, when we had to redesign the program due to restricted travel and in person group meetings.

RESULTS: In response to the pandemic, we developed a program to maintain "residential" training experiences and benefits remotely. We had to answer the following questions: What must change to still achieve the RT goals? What optimal platforms should be used? How would we manage connectivity and data challenges? How could we avoid online fatigue? Going virtual presented an opportunity to reflect on the essence and uniqueness of the program and its ability to meet the objective of strengthening bioinformatics skills among the cohorts of students using different delivery approaches. It allowed an increase in the number of participants. Evaluating each program component is critical for improvement, primarily when feedback feeds into the program's continuous amendment. Initially, the participants noted that there were too many modules, insufficient time, and a lack of hands-on training as a result of too much focus on theory. In the subsequent iterations, we reduced the number of modules from 27 to five, created a harmonized repository for the materials on GitHub, and introduced project-based learning through the mini projects.

CONCLUSION: We demonstrate that implementing a program design through detailed monitoring and evaluation leads to success, especially when participants who are the best fit for the program are selected on an appropriate level of skills, motivation, and commitment.

RevDate: 2024-04-16
CmpDate: 2024-04-16

Barrett C, Chiphwanya J, Mkwanda S, et al (2024)

The national distribution of lymphatic filariasis cases in Malawi using patient mapping and geostatistical modelling.

PLoS neglected tropical diseases, 18(3):e0012056.

BACKGROUND: In 2020 the World Health Organization (WHO) declared that Malawi had successfully eliminated lymphatic filariasis (LF) as a public health problem. Understanding clinical case distributions at a national and sub-national level is important, so essential care packages can be provided to individuals living with LF symptoms. This study aimed to develop a national database and map of LF clinical cases across Malawi using geostatistical modelling approaches, programme-identified clinical cases, antigenaemia prevalence and climate information.

METHODOLOGY: LF clinical cases identified through programme house-to-house surveys across 90 sub-district administrative boundaries (Traditional Authority (TA)) and antigenaemia prevalence from 57 sampled villages in Malawi were used in a two-step geostatistical modelling process to predict LF clinical cases across all TAs of the country. First, we modelled antigenaemia prevalence in relation to climate covariates to predict nationwide antigenaemia prevalence. Second, we modelled clinical cases for unmapped TAs based on our antigenaemia prevalence spatial estimates.

PRINCIPLE FINDINGS: The models estimated 20,938 (95% CrI 18,091 to 24,071) clinical cases in unmapped TAs (70.3%) in addition to the 8,856 (29.7%), programme-identified cases in mapped TAs. In total, the overall national number of LF clinical cases was estimated to be 29,794 (95% CrI 26,957 to 32,927). The antigenaemia prevalence and clinical case mapping and modelling found the highest burden of disease in Chikwawa and Nsanje districts in the Southern Region and Karonga district in the Northern Region of the country.

CONCLUSIONS: The models presented in this study have facilitated the development of the first national LF clinical case database and map in Malawi, the first endemic country in sub-Saharan Africa. It highlights the value of using existing LF antigenaemia prevalence and clinical case data together with modelling approaches to produce estimates that may be used for the WHO dossier requirements, to help target limited resources and implement long-term health strategies.

RevDate: 2024-04-13

Breeyear JH, Mautz BS, Keaton JM, et al (2024)

A new test for trait mean and variance detects unreported loci for blood-pressure variation.

American journal of human genetics pii:S0002-9297(24)00087-9 [Epub ahead of print].

Variability in quantitative traits has clinical, ecological, and evolutionary significance. Most genetic variants identified for complex quantitative traits have only a detectable effect on the mean of trait. We have developed the mean-variance test (MVtest) to simultaneously model the mean and log-variance of a quantitative trait as functions of genotypes and covariates by using estimating equations. The advantages of MVtest include the facts that it can detect effect modification, that multiple testing can follow conventional thresholds, that it is robust to non-normal outcomes, and that association statistics can be meta-analyzed. In simulations, we show control of type I error of MVtest over several alternatives. We identified 51 and 37 previously unreported associations for effects on blood-pressure variance and mean, respectively, in the UK Biobank. Transcriptome-wide association studies revealed 633 significant unique gene associations with blood-pressure mean variance. MVtest is broadly applicable to studies of complex quantitative traits and provides an important opportunity to detect novel loci.

RevDate: 2024-04-15
CmpDate: 2024-04-15

Kredics L, Büchner R, Balázs D, et al (2024)

Recent advances in the use of Trichoderma-containing multicomponent microbial inoculants for pathogen control and plant growth promotion.

World journal of microbiology & biotechnology, 40(5):162.

Chemical pesticides and fertilizers are used in agricultural production worldwide to prevent damage from plant pathogenic microorganisms, insects, and nematodes, to minimize crop losses and to preserve crop quality. However, the use of chemical pesticides and fertilizers can severely pollute soil, water, and air, posing risks to the environment and human health. Consequently, developing new, alternative, environment-friendly microbial soil treatment interventions for plant protection and crop yield increase has become indispensable. Members of the filamentous fungal genus Trichoderma (Ascomycota, Sordariomycetes, Hypocreales) have long been known as efficient antagonists of plant pathogenic microorganisms based on various beneficial traits and abilities of these fungi. This minireview aims to discuss the advances in the field of Trichoderma-containing multicomponent microbiological inoculants based on recent experimental updates. Trichoderma strains can be combined with each other, with other fungi and/or with beneficial bacteria. The development and field performance of such inoculants will be addressed, focusing on the complementarity, synergy, and compatibility of their microbial components.

RevDate: 2024-04-15
CmpDate: 2024-04-15

Wan JSH, Bonser SP, Pang CK, et al (2024)

Adaptive responses to living in stressful habitats: Do invasive and native plant populations use different strategies?.

Ecology letters, 27(4):e14419.

Plants inhabit stressful environments characterized by a variety of stressors, including mine sites, mountains, deserts, and high latitudes. Populations from stressful and reference (non-stressful) sites often have performance differences. However, while invasive and native species may respond differently to stressful environments, there is limited understanding of the patterns in reaction norms of populations from these sites. Here, we use phylogenetically controlled meta-analysis to assess the performance of populations under stress and non-stress conditions. We ask whether stress populations of natives and invasives differ in the magnitude of lowered performance under non-stress conditions and if they vary in the degree of performance advantage under stress. We also assessed whether these distinctions differ with stress intensity. Our findings revealed that natives not only have greater adaptive advantages but also more performance reductions than invasives. Populations from very stressful sites had more efficient adaptations, and performance costs increased with stress intensity in natives only. Overall, the results support the notion that adaptation is frequently costless. Reproductive output was most closely associated with adaptive costs and benefits. Our study characterized the adaptive strategies used by invasive and native plants under stressful conditions, thereby providing important insights into the limitations of adaptation to extreme sites.

RevDate: 2024-04-15
CmpDate: 2024-04-15

Jeong S, YJ Choi (2024)

Association between Socioecological Status, Nutrient Intake, and Cancer Screening Behaviors in Adults Aged 40 and Over: Insights from the Eighth Korea National Health and Nutrition Examination Survey (KNHANES, 2019).

Nutrients, 16(7):.

Cancer screening is pivotal for early detection and improved survival rates. While socio-ecological factors are known to influence screening uptake, the role of lifestyle, dietary habits, and general health in shaping these decisions remains underexplored. Utilizing the 2019 Korea National Health and Nutrition Examination Survey (KNHANES), this study examined the myriad of factors impacting cancer screening utilization. Data from 274,872 adults aged 40 years or older were scrutinized, highlighting demographics, income, lifestyle behaviors, health-related variables, nutrient intake, and dietary quality. A combination of descriptive statistics and logistic regression helped us ascertain influential determinants. Higher educational attainment and income quartiles were positively correlated with cancer screening rates. Regular walkers, those engaged in moderate physical activity, and individuals with a previous cancer diagnosis were more likely to get screened. High-risk drinkers and smokers were less inclined towards screening. Dietary habits also influenced screening decisions. Notably, participants with healthier eating behaviors, indicated by factors such as regular breakfasts and fewer meals out, were more likely to undergo screening. Additionally, nutrient intake analysis revealed that those who had undergone screening consumed greater quantities of most nutrients, bar a few exceptions. For individuals aged 50-64, nutritional assessment indicators highlighted a higher mean adequacy ratio (MAR) and index of nutritional quality (INQ) value among those who participated in screening, suggesting better nutritional quality. This study elucidates the complex socio-ecological and nutritional landscape influencing cancer screening decisions. The results underscore the importance of a holistic approach, emphasizing lifestyle, dietary habits, and socio-economic considerations. It provides a roadmap for policymakers to craft more inclusive screening programs, ensuring equal access and promoting early detection.

RevDate: 2024-04-15
CmpDate: 2024-04-15

Roder T, Pimentel G, Fuchsmann P, et al (2024)

Scoary2: rapid association of phenotypic multi-omics data with microbial pan-genomes.

Genome biology, 25(1):93.

Unraveling bacterial gene function drives progress in various areas, such as food production, pharmacology, and ecology. While omics technologies capture high-dimensional phenotypic data, linking them to genomic data is challenging, leaving 40-60% of bacterial genes undescribed. To address this bottleneck, we introduce Scoary2, an ultra-fast microbial genome-wide association studies (mGWAS) software. With its data exploration app and improved performance, Scoary2 is the first tool to enable the study of large phenotypic datasets using mGWAS. As proof of concept, we explore the metabolome of yogurts, each produced with a different Propionibacterium reichii strain and discover two genes affecting carnitine metabolism.

RevDate: 2024-04-13

Jankovic M, Knezevic T, Tomic A, et al (2024)

Human Cytomegalovirus Oncoprotection across Diverse Populations, Tumor Histologies, and Age Groups: The Relevance for Prospective Vaccinal Therapy.

International journal of molecular sciences, 25(7): pii:ijms25073741.

The oncogenicity of the human cytomegalovirus (CMV) is currently being widely debated. Most recently, mounting clinical evidence suggests an anti-cancer effect via CMV-induced T cell-mediated tumor destruction. However, the data were mostly obtained from single-center studies and in vitro experiments. Broad geographic coverage is required to offer a global perspective. Our study examined the correlation between country-specific CMV seroprevalence (across 73 countries) and the age-standardized incidence rate (of 34 invasive tumors). The populations studied were stratified according to decadal age periods as the immunologic effects of CMV seropositivity may depend upon age at initial infection. The International Agency for Research on Cancer of the World Health Organization (IARC WHO) database was used. The multivariate linear regression analysis revealed a worldwide inverse correlation between CMV seroprevalence and the incidences of 62.8% tumors. Notably, this inverse link persists for all cancers combined (Spearman's ρ = -0.732, p < 0.001; β = -0.482, p < 0.001, adjusted R[2] = 0.737). An antithetical and significant correlation was also observed in particular age groups for the vast majority of tumors. Our results corroborate the conclusions of previous studies and indicate that this oncopreventive phenomenon holds true on a global scale. It applies to a wide spectrum of cancer histologies, additionally supporting the idea of a common underlying mechanism-CMV-stimulated T cell tumor targeting. Although these results further advance the notion of CMV-based therapies, in-depth investigation of host-virus interactions is still warranted.

RevDate: 2024-04-13

Sulaiman N, Salehi F, Prakofjewa J, et al (2024)

Cultural vs. State Borders: Plant Foraging by Hawraman and Mukriyan Kurds in Western Iran.

Plants (Basel, Switzerland), 13(7): pii:plants13071048.

Plant foraging is a millennia-old activity still practiced by many people in the Middle East, particularly in the Fertile Crescent region, where several socioeconomic, ecological, and cultural factors shape this practice. This study seeks to understand the drivers of plant foraging in this complex region characterized by highly diverse linguistic, religious, and cultural groups. Our study aims to document the wild plants used by Kurds in Western Iran, identify similarities and differences among Hawraman and Mukriyan Kurdish groups in Iran, and compare our findings with a previous study on the Hawramani in Iraq. Forty-three semi-structured in-depth interviews were conducted in Kurdish villages of Western Iran. The results revealed the use of 44 wild food plant taxa, their preparation, and culinary uses. Among the reported taxa, 28 plant taxa were used by Mukriyani, and 33 by Hawramani. The study revealed a significant difference between the Hawraman and Mukriyan regions in Iran, whereas there is a high similarity between Hawramani Kurds in Iran and Iraq. We found that the invisible cultural border carries more weight than political divisions, and this calls for a paradigm shift in how we perceive and map the distribution of ethnobotanical knowledge.

RevDate: 2024-04-12

Kazlou A, Bornukova K, Wickham A, et al (2024)

Effects of stress on pain in females using a mobile health app in the Russia-Ukraine conflict.

Npj mental health research, 3(1):2.

The chronic and acute effects of stress can have divergent effects on health; long-term effects are associated with detrimental physical and mental health sequelae, while acute effects may be advantageous in the short-term. Stress-induced analgesia, the attenuation of pain perception due to stress, is a well-known phenomenon that has yet to be systematically investigated under ecological conditions. Using Flo, a women's health and wellbeing app and menstrual cycle tracker, with a world-wide monthly active usership of more than 57 million, women in Ukraine were monitored for their reporting of stress, pain and affective symptoms before, and immediately after, the onset of the Russian-Ukrainian conflict. To avoid potential selection (attrition) or collider bias, we rely on a sample of 87,315 users who were actively logging multiple symptoms before and after the start of the war. We found an inverse relationship between stress and pain, whereby higher reports of stress predicted lower rates of pain. Stress did not influence any other physiological symptoms with a similar magnitude, nor did any other symptom have a similar effect on pain. This relationship generally decreased in magnitude in countries neighbouring and surrounding Ukraine, with Ukraine serving as the epicentre. These findings help characterise the relationship between stress and health in a real-world setting.

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

Nurkassimova M, Omarova N, Zinicovscaia I, et al (2024)

Mosses as bioindicators of air pollution with potentially toxic elements in the Burabay State National Natural Park, Kazakhstan.

Environmental monitoring and assessment, 196(5):442.

The Burabay State National Natural Park is a national park of the great natural and historical values located in the north of Kazakhstan, which has been exposed in recent years to significant anthropogenic impact. The moss biomonitoring was performed in the Borovoye resort community, an important tourist destination in the national park, to identify the level of air pollution. Mosses collected at 29 locations were subjected to neutron activation analysis to determine 36 elements and additionally to ICP-OES to detect the level of Cu and Pb. Factor analysis was applied to check if there are any associations between identified elements and to link them with possible emission sources. According to contamination factor and pollution load indices the investigated area belongs to three classes of pollution: unpolluted, suspected and moderate. Potential ecological risk index calculated for selected elements revealed harmless risk to human health. The level of element obtained in Burabay State National Natural Park was compared with the data available for other national parks.

RevDate: 2024-04-10

Wei X, Tsai MS, Liang L, et al (2024)

Vaginal microbiomes show ethnic evolutionary dynamics and positive selection of Lactobacillus adhesins driven by a long-term niche-specific process.

Cell reports, 43(4):114078 pii:S2211-1247(24)00406-6 [Epub ahead of print].

The vaginal microbiome's composition varies among ethnicities. However, the evolutionary landscape of the vaginal microbiome in the multi-ethnic context remains understudied. We perform a systematic evolutionary analysis of 351 vaginal microbiome samples from 35 multi-ethnic pregnant women, in addition to two validation cohorts, totaling 462 samples from 90 women. Microbiome alpha diversity and community state dynamics show strong ethnic signatures. Lactobacillaceae have a higher ratio of non-synonymous to synonymous polymorphism and lower nucleotide diversity than non-Lactobacillaceae in all ethnicities, with a large repertoire of positively selected genes, including the mucin-binding and cell wall anchor genes. These evolutionary dynamics are driven by the long-term evolutionary process unique to the human vaginal niche. Finally, we propose an evolutionary model reflecting the environmental niches of microbes. Our study reveals the extensive ethnic signatures in vaginal microbial ecology and evolution, highlighting the importance of studying the host-microbiome ecosystem from an evolutionary perspective.

RevDate: 2024-04-10

Schwartz LC, González VL, Strong EE, et al (2024)

Transgressive gene expression and expression plasticity under thermal stress in a stable hybrid zone.

Molecular ecology [Epub ahead of print].

Interspecific hybridization can lead to myriad outcomes, including transgressive phenotypes in which the hybrids are more fit than either parent species. Such hybrids may display important traits in the context of climate change, able to respond to novel environmental conditions not previously experienced by the parent populations. While this has been evaluated in an agricultural context, the role of transgressive hybrids under changing conditions in the wild remains largely unexplored; this is especially true regarding transgressive gene expression. Using the blue mussel species complex (genus Mytilus) as a model system, we investigated the effects of hybridization on temperature induced gene expression plasticity by comparing expression profiles in parental species and their hybrids following a 2-week thermal challenge. Hybrid expression plasticity was most often like one parent or the other (50%). However, a large fraction of genes (26%) showed transgressive expression plasticity (i.e. the change in gene expression was either greater or lesser than that of both parent species), while only 2% were intermediately plastic in hybrids. Despite their close phylogenetic relationship, there was limited overlap in the differentially expressed genes responding to temperature, indicating interspecific differences in the responses to high temperature in which responses from hybrids are distinct from both parent species. We also identified differentially expressed long non-coding RNAs (lncRNAs), which we suggest may contribute to species-specific differences in thermal tolerance. Our findings provide important insight into the impact of hybridization on gene expression under warming. We propose transgressive hybrids may play an important role in population persistence under future warming conditions.

RevDate: 2024-04-09

Brodie JF, Mohd-Azlan J, Chen C, et al (2024)

Author Correction: Landscape-scale benefits of protected areas for tropical biodiversity.

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

Guevara Beltran D, Shiota MN, A Aktipis (2024)

Empathic concern motivates willingness to help in the absence of interdependence.

Emotion (Washington, D.C.), 24(3):628-647.

Previous research suggests that empathic concern selectively promotes motivation to help those with whom we typically have interdependent relationships, such as friends or siblings, rather than strangers or acquaintances. In a sample of U.S. participants (collected between 2018 and 2020), our studies not only confirmed the finding that empathic concern is directed somewhat more strongly toward interdependent relationship partners, but also showed cross-sectionally (Studies 1a-1b), and when manipulating target distress experimentally (Study 2), that empathic concern predicts higher willingness to help only when people perceive low interdependence in their relationship with the target. In Study 3, we manipulated perceived interdependence with an acquaintance via shared fate, and found that empathic concern only predicted helping motivation when we reduced shared fate, but not when we increased shared fate. These results suggest that when people perceive high interdependence in their relationships, shared fate is the driving force behind their desire to help, whereas when people perceive low interdependence with someone in need, empathic concern motivates them to help. A relationship-building perspective on empathic concern provides avenues for testing additional moderators, including those related to target-specific characteristics and culture and ecology. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

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

Liew F, Efstathiou C, Fontanella S, et al (2024)

Large-scale phenotyping of patients with long COVID post-hospitalization reveals mechanistic subtypes of disease.

Nature immunology, 25(4):607-621.

One in ten severe acute respiratory syndrome coronavirus 2 infections result in prolonged symptoms termed long coronavirus disease (COVID), yet disease phenotypes and mechanisms are poorly understood[1]. Here we profiled 368 plasma proteins in 657 participants ≥3 months following hospitalization. Of these, 426 had at least one long COVID symptom and 233 had fully recovered. Elevated markers of myeloid inflammation and complement activation were associated with long COVID. IL-1R2, MATN2 and COLEC12 were associated with cardiorespiratory symptoms, fatigue and anxiety/depression; MATN2, CSF3 and C1QA were elevated in gastrointestinal symptoms and C1QA was elevated in cognitive impairment. Additional markers of alterations in nerve tissue repair (SPON-1 and NFASC) were elevated in those with cognitive impairment and SCG3, suggestive of brain-gut axis disturbance, was elevated in gastrointestinal symptoms. Severe acute respiratory syndrome coronavirus 2-specific immunoglobulin G (IgG) was persistently elevated in some individuals with long COVID, but virus was not detected in sputum. Analysis of inflammatory markers in nasal fluids showed no association with symptoms. Our study aimed to understand inflammatory processes that underlie long COVID and was not designed for biomarker discovery. Our findings suggest that specific inflammatory pathways related to tissue damage are implicated in subtypes of long COVID, which might be targeted in future therapeutic trials.

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

Baril T, Galbraith J, A Hayward (2024)

Earl Grey: A Fully Automated User-Friendly Transposable Element Annotation and Analysis Pipeline.

Molecular biology and evolution, 41(4):.

Transposable elements (TEs) are major components of eukaryotic genomes and are implicated in a range of evolutionary processes. Yet, TE annotation and characterization remain challenging, particularly for nonspecialists, since existing pipelines are typically complicated to install, run, and extract data from. Current methods of automated TE annotation are also subject to issues that reduce overall quality, particularly (i) fragmented and overlapping TE annotations, leading to erroneous estimates of TE count and coverage, and (ii) repeat models represented by short sections of total TE length, with poor capture of 5' and 3' ends. To address these issues, we present Earl Grey, a fully automated TE annotation pipeline designed for user-friendly curation and annotation of TEs in eukaryotic genome assemblies. Using nine simulated genomes and an annotation of Drosophila melanogaster, we show that Earl Grey outperforms current widely used TE annotation methodologies in ameliorating the issues mentioned above while scoring highly in benchmarking for TE annotation and classification and being robust across genomic contexts. Earl Grey provides a comprehensive and fully automated TE annotation toolkit that provides researchers with paper-ready summary figures and outputs in standard formats compatible with other bioinformatics tools. Earl Grey has a modular format, with great scope for the inclusion of additional modules focused on further quality control and tailored analyses in future releases.

RevDate: 2024-04-09

Badiyal A, Mahajan R, Rana RS, et al (2024)

Synergizing biotechnology and natural farming: pioneering agricultural sustainability through innovative interventions.

Frontiers in plant science, 15:1280846.

The world has undergone a remarkable transformation from the era of famines to an age of global food production that caters to an exponentially growing population. This transformation has been made possible by significant agricultural revolutions, marked by the intensification of agriculture through the infusion of mechanical, industrial, and economic inputs. However, this rapid advancement in agriculture has also brought about the proliferation of agricultural inputs such as pesticides, fertilizers, and irrigation, which have given rise to long-term environmental crises. Over the past two decades, we have witnessed a concerning plateau in crop production, the loss of arable land, and dramatic shifts in climatic conditions. These challenges have underscored the urgent need to protect our global commons, particularly the environment, through a participatory approach that involves countries worldwide, regardless of their developmental status. To achieve the goal of sustainability in agriculture, it is imperative to adopt multidisciplinary approaches that integrate fields such as biology, engineering, chemistry, economics, and community development. One noteworthy initiative in this regard is Zero Budget Natural Farming, which highlights the significance of leveraging the synergistic effects of both plant and animal products to enhance crop establishment, build soil fertility, and promote the proliferation of beneficial microorganisms. The ultimate aim is to create self-sustainable agro-ecosystems. This review advocates for the incorporation of biotechnological tools in natural farming to expedite the dynamism of such systems in an eco-friendly manner. By harnessing the power of biotechnology, we can increase the productivity of agro-ecology and generate abundant supplies of food, feed, fiber, and nutraceuticals to meet the needs of our ever-expanding global population.

RevDate: 2024-04-06

Loos D, Filho APDC, Dutilh BE, et al (2024)

A global survey of host, aquatic, and soil microbiomes reveals shared abundance and genomic features between bacterial and fungal generalists.

Cell reports, 43(4):114046 pii:S2211-1247(24)00374-7 [Epub ahead of print].

Environmental change, coupled with alteration in human lifestyles, is profoundly impacting the microbial communities critical to the health of the Earth and its inhabitants. To identify bacteria and fungi that are resistant and susceptible to habitat change, we analyze thousands of genera detected in 1,580 host, soil, and aquatic samples. This large-scale analysis identifies 48 bacterial and 4 fungal genera that are abundant across the three biomes, demonstrating fitness in diverse environmental conditions. Samples containing these generalists have significantly higher alpha diversity. These generalists play a significant role in shaping cross-kingdom community structure, boasting larger genomes with more secondary metabolism and antimicrobial resistance genes. Conversely, 30 bacterial and 19 fungal genera are only found in a single habitat, suggesting a limited ability to adapt to different and changing environments. These findings contribute to our understanding of microbial niche breadth and its consequences for global biodiversity loss.

RevDate: 2024-04-08
CmpDate: 2024-04-08

Chen Z, Ain NU, Zhao Q, et al (2024)

From tradition to innovation: conventional and deep learning frameworks in genome annotation.

Briefings in bioinformatics, 25(3):.

Following the milestone success of the Human Genome Project, the 'Encyclopedia of DNA Elements (ENCODE)' initiative was launched in 2003 to unearth information about the numerous functional elements within the genome. This endeavor coincided with the emergence of numerous novel technologies, accompanied by the provision of vast amounts of whole-genome sequences, high-throughput data such as ChIP-Seq and RNA-Seq. Extracting biologically meaningful information from this massive dataset has become a critical aspect of many recent studies, particularly in annotating and predicting the functions of unknown genes. The core idea behind genome annotation is to identify genes and various functional elements within the genome sequence and infer their biological functions. Traditional wet-lab experimental methods still rely on extensive efforts for functional verification. However, early bioinformatics algorithms and software primarily employed shallow learning techniques; thus, the ability to characterize data and features learning was limited. With the widespread adoption of RNA-Seq technology, scientists from the biological community began to harness the potential of machine learning and deep learning approaches for gene structure prediction and functional annotation. In this context, we reviewed both conventional methods and contemporary deep learning frameworks, and highlighted novel perspectives on the challenges arising during annotation underscoring the dynamic nature of this evolving scientific landscape.

RevDate: 2024-04-05

Zhang T, Peng W, Xiao H, et al (2024)

Population genomics highlights structural variations in local adaptation to saline coastal environments in woolly grape.

Journal of integrative plant biology [Epub ahead of print].

Structural variations (SVs) are a feature of plant genomes that has been largely unexplored despite their significant impact on plant phenotypic traits and local adaptation to abiotic and biotic stress. In this study, we employed woolly grape (Vitis retordii), a species native to the tropical and subtropical regions of East Asia with both coastal and inland habitats, as a valuable model for examining the impact of SVs on local adaptation. We assembled a haplotype-resolved chromosomal reference genome for woolly grape, and conducted population genetic analyses based on whole-genome sequencing (WGS) data from coastal and inland populations. The demographic analyses revealed recent bottlenecks in all populations and asymmetric gene flow from the inland to the coastal population. In total, 1,035 genes associated with plant adaptive regulation for salt stress, radiation, and environmental adaptation were detected underlying local selection by SVs and SNPs in the coastal population, of which 37.29% and 65.26% were detected by SVs and SNPs, respectively. Candidate genes such as FSD2, RGA1, and AAP8 associated with salt tolerance were found to be highly differentiated and selected during the process of local adaptation to coastal habitats in SV regions. Our study highlights the importance of SVs in local adaptation; candidate genes related to salt stress and climatic adaptation to tropical and subtropical environments are important genomic resources for future breeding programs of grapevine and its rootstocks.

RevDate: 2024-04-01

Stiller J, Feng S, Chowdhury AA, et al (2024)

Complexity of avian evolution revealed by family-level genomes.

Nature pii:10.1038/s41586-024-07323-1 [Epub ahead of print].

Despite tremendous efforts in the past decades, relationships among main avian lineages remain heavily debated without a clear resolution. Discrepancies have been attributed to diversity of species sampled, phylogenetic method, and the choice of genomic regions [1-3]. Here, we address these issues by analyzing genomes of 363 bird species [4] (218 taxonomic families, 92% of total). Using intergenic regions and coalescent methods, we present a well-supported tree but also a remarkable degree of discordance. The tree confirms that Neoaves experienced rapid radiation at or near the Cretaceous-Paleogene (K-Pg) boundary. Sufficient loci rather than extensive taxon sampling were more effective in resolving difficult nodes. Remaining recalcitrant nodes involve species that challenge modeling due to extreme GC content, variable substitution rates, incomplete lineage sorting, or complex evolutionary events such as ancient hybridization. Assessment of the impacts of different genomic partitions showed high heterogeneity across the genome. We discovered sharp increases in effective population size, substitution rates, and relative brain size following the K-Pg extinction event, supporting the hypothesis that emerging ecological opportunities catalyzed the diversification of modern birds. The resulting phylogenetic estimate offers novel insights into the rapid radiation of modern birds and provides a taxon-rich backbone tree for future comparative studies.

RevDate: 2024-04-03

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

The genome sequence of the Brown Oak Tortrix, Archips crataeganus (Hübner, 1796).

Wellcome open research, 9:9.

We present a genome assembly from an individual female Archips crataeganus (the Brown Oak Tortrix; Arthropoda; Insecta; Lepidoptera; Tortricidae). The genome sequence is 626.9 megabases in span. Most of the assembly is scaffolded into 31 chromosomal pseudomolecules, including the Z and W sex chromosomes. The mitochondrial genome has also been assembled and is 16.64 kilobases in length. Gene annotation of this assembly on Ensembl identified 19,596 protein coding genes.

RevDate: 2024-04-08
CmpDate: 2024-04-08

Chen X, Zhu Y, Zheng W, et al (2024)

Elucidating doxycycline biotransformation mechanism by Chryseobacterium sp. WX1: Multi-omics insights.

Journal of hazardous materials, 469:133975.

Doxycycline (DOX) represents a second-generation tetracycline antibiotic that persists as a challenging-to-degrade contaminant in environmental compartments. Despite its ubiquity, scant literature exists on bacteria proficient in DOX degradation. This study marked a substantial advancement in this field by isolating Chryseobacterium sp. WX1 from an activated sludge enrichment culture, showcasing its unprecedented ability to completely degrade 50 mg/L of DOX within 44 h. Throughout the degradation process, seven biotransformation products were identified, revealing a complex pathway that began with the hydroxylation of DOX, followed by a series of transformations. Employing an integrated multi-omics approach alongside in vitro heterologous expression assays, our study distinctly identified the tetX gene as a critical facilitator of DOX hydroxylation. Proteomic analyses further pinpointed the enzymes postulated to mediate the downstream modifications of DOX hydroxylation derivatives. The elucidated degradation pathway encompassed several key biological processes, such as the microbial transmembrane transport of DOX and its intermediates, the orchestration of enzyme synthesis for transformation, energy metabolism, and other gene-regulated biological directives. This study provides the first insight into the adaptive biotransformation strategies of Chryseobacterium under DOX-induced stress, highlighting the potential applications of this strain to augment DOX removal in wastewater treatment systems containing high concentrations of DOX.

RevDate: 2024-03-30

Li W, Feng Q, Li Z, et al (2024)

Inhibition of iron oxidation in Acidithiobacillus ferrooxidans by low-molecular-weight organic acids: Evaluation of performance and elucidation of mechanisms.

The Science of the total environment pii:S0048-9697(24)02062-X [Epub ahead of print].

The catalytic role of Acidithiobacillus ferrooxidans (A. ferrooxidans) in iron biooxidation is pivotal in the formation of Acid Mine Drainage (AMD), which poses a significant threat to the environment. To control AMD generation, treatments with low-molecular-weight organic acids are being studied, yet their exact acid-inhibiting mechanisms are unclear. In this study, AMD materials, organic acids, and molecular methods were employed to gain a deeper understanding of the inhibitory effects of low-molecular-weight organic acids on the biooxidation of iron by A. ferrooxidans. The inhibition experiment of A. ferrooxidans on the oxidation of Fe[2+] showed that to attain a 90 % inhibition efficacy within 72 h, the minimum concentrations required for formic acid, acetic acid, propionic acid, and lactic acid are 0.5, 6, 4, and 10 mmol/L, respectively. Bacterial imaging illustrated the detrimental effects of these organic acids on the cell envelope structure. This includes severe damage to the outer membrane, particularly from formic and acetic acids, which also caused cell wall damage. Coupled with alterations in the types and quantities of protein, carbohydrate, and nucleic acid content in extracellular polymeric substances (EPS), indicate the mechanisms underlying these inhibitory treatments. Transcriptomic analysis revealed interference of these organic acids with crucial metabolic pathways, particularly those related to energy metabolism. These findings establish a comprehensive theoretical basis for understanding the inhibition of A. ferrooxidans' biooxidation by low-molecular-weight organic acids, offering a novel opportunity to effectively mitigate the generation of AMD at its source.

RevDate: 2024-03-30

Sfriso AA, Juhmani AS, Tomio Y, et al (2024)

Microplastic accumulation and ecological impacts on benthic invertebrates: Insights from a microcosm experiment.

Marine pollution bulletin, 202:116231 pii:S0025-326X(24)00208-X [Epub ahead of print].

Microplastic (MP) pollution poses a global concern, especially for benthic invertebrates. This one-month study investigated the accumulation of small MP polymers (polypropylene and polyester resin, 3-500 μm, 250 μg L[-1]) in benthic invertebrates and on one alga species. Results revealed species-specific preferences for MP size and type, driven by ingestion, adhesion, or avoidance behaviours. Polyester resin accumulated in Mytilus galloprovincialis, Chamelea gallina, Hexaplex trunculus, and Paranemonia cinerea, while polypropylene accumulated on Ulva rigida. Over time, MP accumulation decreased in count but not size, averaging 6.2 ± 5.0 particles per individual after a month. MP were mainly found inside of the organisms, especially in the gut, gills, and gonads and externally adherent MP ranged from 11 to 35 % of the total. Biochemical energy assessments after two weeks of MP exposure indicated energy gains for water column species but energy loss for sediment-associated species, highlighting the susceptibility of infaunal benthic communities to MP contamination.

RevDate: 2024-04-02

McConnell RJ, Kamysh O, O'Kane PL, et al (2024)

Radiation Dose Does Not Affect the Predictive Value of Thyroid Biopsy for Diagnosing Papillary Thyroid Cancer in a Belarusian Cohort Exposed to Chernobyl Fallout.

Acta cytologica, 68(1):34-44.

INTRODUCTION: The Chernobyl nuclear accident exposed residents of contaminated territories to substantial quantities of radioiodines and was followed by an increase in thyroid cancer, primarily papillary thyroid cancer (PTC), among exposed children and adolescents. Although thyroid biopsy is an essential component of screening programs following accidental exposure to radioiodines, it is unknown whether the predictive value of biopsy is affected by different levels of environmental exposure.

METHODS: A cohort of 11,732 Belarusians aged ≤18 years at the time of the Chernobyl accident with individual thyroid radiation dose estimates was screened at least once 11-22 years later. Paired cytologic conclusions and histopathologic diagnoses were possible for 258 thyroid nodules from 238 cohort members. Cytologic conclusions were divided into five reporting categories, with all follicular lesion aspirates combined into a single indeterminate category. Standard performance indicators, risk of malignancy (ROM), and odds ratios for a correct cytologic conclusion were calculated, both overall and according to quintile of thyroid radiation dose.

RESULTS: The arithmetic mean thyroid dose estimate for the study group was 1.73 Gy (range: 0.00-23.64 Gy). The final histopathologic diagnosis was cancer for 136 of 258 biopsies (52.7%; 135 papillary and 1 follicular). The overall ROM was 96.7% for cytologies definite for PTC, 83.7% for suspicious for PTC, 33.0% for indeterminate, 8.1% for benign, and 31.0% for non-diagnostic. The ROM showed little change according to level of radiation exposure. Overall, there was no association between thyroid radiation dose and the odds ratio for a correct cytologic conclusion (p = 0.24). When analyzed according to dose quintile, the odds ratio for a correct conclusion increased two-fold at 0.10-0.29 Gy compared to a dose of 0.00-0.09 Gy and decreased at doses of 0.3-24 Gy (p value for linear trend = 0.99).

CONCLUSIONS: At radiation doses received by a cohort of young Belarusians exposed to radioiodines by the Chernobyl accident, the predictive value of thyroid biopsy for diagnosing PTC was not significantly affected by level of radiation exposure.

RevDate: 2024-04-01
CmpDate: 2024-04-01

Han B, Tian D, Li X, et al (2024)

Multiomics Analyses Provide New Insight into Genetic Variation of Reproductive Adaptability in Tibetan Sheep.

Molecular biology and evolution, 41(3):.

Domestication and artificial selection during production-oriented breeding have greatly shaped the level of genomic variability in sheep. However, the genetic variation associated with increased reproduction remains elusive. Here, two groups of samples from consecutively monotocous and polytocous sheep were collected for genome-wide association, transcriptomic, proteomic, and metabolomic analyses to explore the genetic variation in fecundity in Tibetan sheep. Genome-wide association study revealed strong associations between BMPR1B (p.Q249R) and litter size, as well as between PAPPA and lambing interval; these findings were validated in 1,130 individuals. Furthermore, we constructed the first single-cell atlas of Tibetan sheep ovary tissues and identified a specific mural granulosa cell subtype with PAPPA-specific expression and differential expression of BMPR1B between the two groups. Bulk RNA-seq indicated that BMPR1B and PAPPA expressions were similar between the two groups of sheep. 3D protein structure prediction and coimmunoprecipitation analysis indicated that mutation and mutually exclusive exons of BMPR1B are the main mechanisms for prolific Tibetan sheep. We propose that PAPPA is a key gene for stimulating ovarian follicular growth and development, and steroidogenesis. Our work reveals the genetic variation in reproductive performance in Tibetan sheep, providing insights and valuable genetic resources for the discovery of genes and regulatory mechanisms that improve reproductive success.

RevDate: 2024-04-01
CmpDate: 2024-04-01

Milić D, Rat M, Bokić B, et al (2024)

Exploring the effects of habitat management on grassland biodiversity: A case study from northern Serbia.

PloS one, 19(3):e0301391.

Grasslands represent a biodiversity hotspot in the European agricultural landscape, their restoration is necessary and offers a great opportunity to mitigate or halt harmful processes. These measures require a comprehensive knowledge of historical landscape changes, but also adequate management strategies. The required data was gathered from the sand grasslands of northern Serbia, as this habitat is of high conservation priority. This area also has a long history of different habitat management approaches (grazing and mowing versus unmanaged), which has been documented over of the last two decades. This dataset enabled us to quantify the effects of different measures across multiple taxa (plants, insect pollinators, and birds). We linked the gathered data on plants, pollinators, and birds with habitat management measures. Our results show that, at the taxon level, the adopted management strategies were beneficial for species richness, abundance, and composition, as the highest diversity of plant, insect pollinator, and bird species was found in managed areas. Thus, an innovative modelling approach was adopted in this work to identify and explain the effects of management practices on changes in habitat communities. The findings yielded can be used in the decision making as well as development of new management programmes. We thus posit that, when restoring and establishing particular communities, priority needs to be given to species with a broad ecological response. We recommend using the decision tree as a suitable machine learning model for this purpose.

RevDate: 2024-03-30
CmpDate: 2024-03-29

Giordano D, Bonora S, D'Orsi I, et al (2024)

Structural and Functional Characterization of Lipoxygenases from Diatoms by Bioinformatics and Modelling Studies.

Biomolecules, 14(3):.

Lipoxygenases make several biological functions in cells, based on the products of the catalyzed reactions. In diatoms, microalgae ubiquitous in aquatic ecosystems, lipoxygenases have been noted for the oxygenation of fatty acids with the production of oxylipins, which are involved in many physiological and pathological processes in marine organisms. The interest in diatoms' lipoxygenases and oxylipins has increased due to their possible biotechnological applications, ranging from ecology to medicine. We investigated using bioinformatics and molecular docking tools the lipoxygenases of diatoms and the possible interaction with substrates. A large-scale analysis of sequence resources allowed us to retrieve 45 sequences of lipoxygenases from diatoms. We compared and analyzed the sequences by multiple alignments and phylogenetic trees, suggesting the possible clustering in phylogenetic groups. Then, we modelled the 3D structure of representative enzymes from the different groups and investigated in detail the structural and functional properties by docking simulations with possible substrates. The results allowed us to propose a classification of the lipoxygenases from diatoms based on their sequence features, which may be reflected in specific structural differences and possible substrate specificity.

RevDate: 2024-04-01
CmpDate: 2024-04-01

Grones C, Eekhout T, Shi D, et al (2024)

Best practices for the execution, analysis, and data storage of plant single-cell/nucleus transcriptomics.

The Plant cell, 36(4):812-828.

Single-cell and single-nucleus RNA-sequencing technologies capture the expression of plant genes at an unprecedented resolution. Therefore, these technologies are gaining traction in plant molecular and developmental biology for elucidating the transcriptional changes across cell types in a specific tissue or organ, upon treatments, in response to biotic and abiotic stresses, or between genotypes. Despite the rapidly accelerating use of these technologies, collective and standardized experimental and analytical procedures to support the acquisition of high-quality data sets are still missing. In this commentary, we discuss common challenges associated with the use of single-cell transcriptomics in plants and propose general guidelines to improve reproducibility, quality, comparability, and interpretation and to make the data readily available to the community in this fast-developing field of research.

RevDate: 2024-03-30

Santric-Milicevic M, Pavlekic K, Bukumiric Z, et al (2024)

Nurses' Perception of Tension, Stress, and Pressure before and during the COVID-19 Pandemic: A Multicenter Serbian Study.

Healthcare (Basel, Switzerland), 12(6):.

The mental health of healthcare workers, especially the nursing staff in intensive care units, is crucial for the optimal functioning of healthcare systems during medical emergencies. This study implements a cross-sectional design to investigate the associations between nurses' personal characteristics, workplace challenges, and job satisfaction with the increased perception of tension, stress, and pressure at the workplace (TSPW) before and during the COVID-19 pandemic. In 2021, we surveyed 4210 nurses from 19 intensive healthcare facilities in the capital of Serbia, Belgrade, and, at that time, collected data about their perceived TSPW before and during the COVID-19 pandemic. Our study identified six predictors of the increase in TSPW, as perceived by nurses: their work in COVID-19 infectious zones (OR = 1.446), exhaustion due to work under protective equipment (OR = 1.413), uncertainty and fear of infection (OR = 1.481), a high degree of superiors' appreciation and respect (OR = 1.147), a high degree of patients' attitudes (OR = 1.111), and a low degree of work autonomy (OR = 0.889). The study's findings suggest that a solution to this issue is necessary to ensure that nurses are safe and able to alleviate the physical and mental strain that comes with prolonged use of protective equipment. Nurses on the frontline of the pandemic require better health protection, better conditions, and respect for their role. Strategies to promote mental health would help reduce nurses' stress and increase job satisfaction.

RevDate: 2024-03-28

Feutz E, Biswas PK, Ndeketa L, et al (2024)

Data Management in Multicountry Consortium Studies: The Enterics For Global Health (EFGH) Shigella Surveillance Study Example.

Open forum infectious diseases, 11(Suppl 1):S48-S57.

BACKGROUND: Rigorous data management systems and planning are essential to successful research projects, especially for large, multicountry consortium studies involving partnerships across multiple institutions. Here we describe the development and implementation of data management systems and procedures for the Enterics For Global Health (EFGH) Shigella surveillance study-a 7-country diarrhea surveillance study that will conduct facility-based surveillance concurrent with population-based enumeration and a health care utilization survey to estimate the incidence of Shigella--associated diarrhea in children 6 to 35 months old.

METHODS: The goals of EFGH data management are to utilize the knowledge and experience of consortium members to collect high-quality data and ensure equity in access and decision-making. During the planning phase before study initiation, a working group of representatives from each EFGH country site, the coordination team, and other partners met regularly to develop the data management systems for the study.

RESULTS: This resulted in the Data Management Plan, which included selecting REDCap and SurveyCTO as the primary database systems. Consequently, we laid out procedures for data processing and storage, study monitoring and reporting, data quality control and assurance activities, and data access. The data management system and associated real-time visualizations allow for rapid data cleaning activities and progress monitoring and will enable quicker time to analysis.

CONCLUSIONS: Experiences from this study will contribute toward enriching the sparse landscape of data management methods publications and serve as a case study for future studies seeking to collect and manage data consistently and rigorously while maintaining equitable access to and control of data.

RevDate: 2024-03-29
CmpDate: 2024-03-28

Corponi F, Li BM, Anmella G, et al (2024)

Automated mood disorder symptoms monitoring from multivariate time-series sensory data: getting the full picture beyond a single number.

Translational psychiatry, 14(1):161.

Mood disorders (MDs) are among the leading causes of disease burden worldwide. Limited specialized care availability remains a major bottleneck thus hindering pre-emptive interventions. MDs manifest with changes in mood, sleep, and motor activity, observable in ecological physiological recordings thanks to recent advances in wearable technology. Therefore, near-continuous and passive collection of physiological data from wearables in daily life, analyzable with machine learning (ML), could mitigate this problem, bringing MDs monitoring outside the clinician's office. Previous works predict a single label, either the disease state or a psychometric scale total score. However, clinical practice suggests that the same label may underlie different symptom profiles, requiring specific treatments. Here we bridge this gap by proposing a new task: inferring all items in HDRS and YMRS, the two most widely used standardized scales for assessing MDs symptoms, using physiological data from wearables. To that end, we develop a deep learning pipeline to score the symptoms of a large cohort of MD patients and show that agreement between predictions and assessments by an expert clinician is clinically significant (quadratic Cohen's κ and macro-average F1 score both of 0.609). While doing so, we investigate several solutions to the ML challenges associated with this task, including multi-task learning, class imbalance, ordinal target variables, and subject-invariant representations. Lastly, we illustrate the importance of testing on out-of-distribution samples.

RevDate: 2024-03-26

Yuan Q, Yao LF, Tang JW, et al (2024)

Rapid discrimination and ratio quantification of mixed antibiotics in aqueous solution through integrative analysis of SERS spectra via CNN combined with NN-EN model.

Journal of advanced research pii:S2090-1232(24)00116-4 [Epub ahead of print].

INTRODUCTION: Abusing antibiotic residues in the natural environment has become a severe public health and ecological environmental problem. The side effects of its biochemical and physiological consequences are severe. To avoid antibiotic contamination in water, implementing universal and rapid antibiotic residue detection technology is critical to maintaining antibiotic safety in aquatic environments. Surface-enhanced Raman spectroscopy (SERS) provides a powerful tool for identifying small molecular components with high sensitivity and selectivity. However, it remains a challenge to identify pure antibiotics from SERS spectra due to coexisting components in the mixture.

OBJECTIVES: In this study, an intelligent analysis model for the SERS spectrum based on a deep learning algorithm was proposed for rapid identification of the antibiotic components in the mixture and quantitative determination of the ratios of these components.

METHODS: We established a water environment system containing three antibiotic residues of ciprofloxacin, doxycycline, and levofloxacin. To facilitate qualitative and quantitative analysis of the SERS spectra antibiotic mixture datasets, we developed a computational framework integrating a convolutional neural network (CNN) and a non-negative elastic network (NN-EN) method.

RESULTS: The experimental results demonstrate that the CNN model has a recognition accuracy of 98.68%, and the interpretation analysis of Shapley Additive exPlanations (SHAP) shows that our model can specifically focus on the characteristic peak distribution. In contrast, the NN-EN model can accurately quantify each component's ratio in the mixture.

CONCLUSION: Integrating the SERS technique assisted by the CNN combined with the NN-EN model exhibits great potential for rapid identification and high-precision quantification of antibiotic residues in aquatic environments.

RevDate: 2024-03-27
CmpDate: 2024-03-27

Del Bianco T, Haartsen R, Mason L, et al (2024)

The importance of decomposing periodic and aperiodic EEG signals for assessment of brain function in a global context.

Developmental psychobiology, 66(4):e22484.

Measures of early neuro-cognitive development that are suitable for use in low-resource settings are needed to enable studies of the effects of early adversity on the developing brain in a global context. These measures should have high acquisition rates and good face and construct validity. Here, we investigated the feasibility of a naturalistic electroencephalography (EEG) paradigm in a low-resource context during childhood. Additionally, we examined the sensitivity of periodic and aperiodic EEG metrics to social and non-social stimuli. We recorded simultaneous 20-channel EEG and eye-tracking in 72 children aged 4-12 years (45 females) while they watched videos of women singing nursery rhymes and moving toys, selected to represent familiar childhood experiences. These measures were part of a feasibility study that assessed the feasibility and acceptability of a follow-up data collection of the South African Safe Passage Study, which tracks environmental adversity and brain and cognitive development from before birth up until childhood. We examined whether data quantity and quality varied with child characteristics and the sensitivity of varying EEG metrics (canonical band power in the theta and alpha band and periodic and aperiodic features of the power spectra). We found that children who completed the EEG and eye-tracking assessment were, in general, representative of the full cohort. Data quantity was higher in children with greater visual attention to the stimuli. Out of the tested EEG metrics, periodic measures in the theta frequency range were most sensitive to condition differences, compared to alpha range measures and canonical and aperiodic EEG measures. Our results show that measuring EEG during ecologically valid social and non-social stimuli is feasible in low-resource settings, is feasible for most children, and produces robust indices of social brain function. This work provides preliminary support for testing longitudinal links between social brain function, environmental factors, and emerging behaviors.

RevDate: 2024-03-26
CmpDate: 2024-03-26

Ouyang YY, Su ZW, Li CH, et al (2024)

Forest fire risk zoning based on fuzzy logic and analytical network process.

Ying yong sheng tai xue bao = The journal of applied ecology, 35(2):354-362.

Forest fires have a significant impact on human life, property safety, and ecological environment. Deve-loping high-quality forest fire risk maps is beneficial for preventing forest fires, guiding resource allocation for firefighting, assisting in fire suppression efforts, and supporting decision-making. With a multi-criteria decision analysis (MCDA) method based on geographic information systems (GIS) and literature review, we assessed the main factors influencing the occurrences of forest fires in Youxi County, Fujian Province. We analyzed the importance of each fire risk factor using the analytic network process (ANP) and assigned weights, and evaluated the sub-standard weights using fuzzy logic assessment. Using ArcGIS aggregation functions, we generated a forest fire risk map and validated it with satellite fire points. The results showed that the areas classified as level 4 or higher fire risk accounted for a considerable proportion in Youxi County, and that the central and northern regions were at higher risk. The overall fire risk situation in the county was severe. The fuzzy ANP model demonstrated a high accuracy of 85.8%. The introduction of this novel MCDA method could effectively improve the accuracy of forest fire risk mapping at a small scale, providing a basis for early fire warning and the planning and allocation of firefighting resources.

RevDate: 2024-03-26
CmpDate: 2024-03-25

Wu J, Lv Y, Hao P, et al (2024)

Immunological profile of lactylation-related genes in Crohn's disease: a comprehensive analysis based on bulk and single-cell RNA sequencing data.

Journal of translational medicine, 22(1):300.

BACKGROUND: Crohn's disease (CD) is a disease characterized by intestinal immune dysfunction, often accompanied by metabolic abnormalities. Disturbances in lactate metabolism have been found in the intestine of patients with CD, but studies on the role of lactate and related Lactylation in the pathogenesis of CD are still unknown.

METHODS: We identified the core genes associated with Lactylation by downloading and merging three CD-related datasets (GSE16879, GSE75214, and GSE112366) from the GEO database, and analyzed the functions associated with the hub genes and the correlation between their expression levels and immune infiltration through comprehensive analysis. We explored the Lactylation levels of different immune cells using single-cell data and further analyzed the differences in Lactylation levels between inflammatory and non-inflammatory sites.

RESULTS: We identified six Lactylation-related hub genes that are highly associated with CD. Further analysis revealed that these six hub genes were highly correlated with the level of immune cell infiltration. To further clarify the effect of Lactylation on immune cells, we analyzed single-cell sequencing data of immune cells from inflammatory and non-inflammatory sites in CD patients and found that there were significant differences in the levels of Lactylation between different types of immune cells, and that the levels of Lactylation were significantly higher in immune cells from inflammatory sites.

CONCLUSIONS: These results suggest that Lactylation-related genes and their functions are closely associated with changes in inflammatory cells in CD patients.

RevDate: 2024-03-27
CmpDate: 2024-03-27

Liu Y, You S, Ding L, et al (2024)

Hepatotoxic effects of chronic exposure to environmentally relevant concentrations of Di-(2-ethylhexyl) phthalate (DEHP) on crucian carp: Insights from multi-omics analyses.

The Science of the total environment, 923:171447.

Di-(2-ethylhexyl) phthalate (DEHP) is an extensively used phthalate esters (PAEs) that raise growing ecotoxicological concerns due to detrimental effects on living organisms and ecosystems. This study performed hepatotoxic investigations on crucian carp under chronic low-dosage (CLD) exposure to DEHP at environmentally relevant concentrations (20-500 μg/L). The results demonstrated that the CLD exposure induced irreversible damage to the liver tissue. Multi-omics (transcriptomics and metabolomics) analyses revealed the predominant toxicological mechanisms underlying DEHP-induced hepatotoxicity by inhibiting energy production pathways and the up-regulation of the purine metabolism. Disruption of metabolic pathways led to excessive reactive oxygen species (ROS) production and subsequent oxidative stress. The adverse metabolic effects were exacerbated by an interplay between oxidative stress and endoplasmic reticulum stress. This study not only provides new mechanistic insights into the ecotoxicological effects of DEHP under chronic low-dosage exposure, but also suggests a potential strategy for further ecological risk assessment of PAEs.

RevDate: 2024-03-25
CmpDate: 2024-03-25

Alari A, Ranzani O, Olmos S, et al (2024)

Short-term exposure to air pollution and hospital admission after COVID-19 in Catalonia: the COVAIR-CAT study.

International journal of epidemiology, 53(2):.

BACKGROUND: A growing body of evidence has reported positive associations between long-term exposure to air pollution and poor COVID-19 outcomes. Inconsistent findings have been reported for short-term air pollution, mostly from ecological study designs. Using individual-level data, we studied the association between short-term variation in air pollutants [nitrogen dioxide (NO2), particulate matter with a diameter of <2.5 µm (PM2.5) and a diameter of <10 µm (PM10) and ozone (O3)] and hospital admission among individuals diagnosed with COVID-19.

METHODS: The COVAIR-CAT (Air pollution in relation to COVID-19 morbidity and mortality: a large population-based cohort study in Catalonia, Spain) cohort is a large population-based cohort in Catalonia, Spain including 240 902 individuals diagnosed with COVID-19 in the primary care system from 1 March until 31 December 2020. Our outcome was hospitalization within 30 days of COVID-19 diagnosis. We used individual residential address to assign daily air-pollution exposure, estimated using machine-learning methods for spatiotemporal prediction. For each pandemic wave, we fitted Cox proportional-hazards models accounting for non-linear-distributed lagged exposure over the previous 7 days.

RESULTS: Results differed considerably by pandemic wave. During the second wave, an interquartile-range increase in cumulative weekly exposure to air pollution (lag0_7) was associated with a 12% increase (95% CI: 4% to 20%) in COVID-19 hospitalizations for NO2, 8% (95% CI: 1% to 16%) for PM2.5 and 9% (95% CI: 3% to 15%) for PM10. We observed consistent positive associations for same-day (lag0) exposure, whereas lag-specific associations beyond lag0 were generally not statistically significant.

CONCLUSIONS: Our study suggests positive associations between NO2, PM2.5 and PM10 and hospitalization risk among individuals diagnosed with COVID-19 during the second wave. Cumulative hazard ratios were largely driven by exposure on the same day as hospitalization.

RevDate: 2024-03-25
CmpDate: 2024-03-25

Chanda MM, Purse BV, Hemadri D, et al (2024)

Spatial and temporal analysis of haemorrhagic septicaemia outbreaks in India over three decades (1987-2016).

Scientific reports, 14(1):6773.

Haemorrhagic septicaemia (HS) is an economically important disease affecting cattle and buffaloes and the livelihoods of small-holder farmers that depend upon them. The disease is caused by Gram-negative bacterium, Pasteurella multocida, and is considered to be endemic in many states of India with more than 25,000 outbreaks in the past three decades. Currently, there is no national policy for control of HS in India. In this study, we analysed thirty year (1987-2016) monthly data on HS outbreaks using different statistical and mathematical methods to identify spatial variability and temporal patterns (seasonality, periodicity). There was zonal variation in the trend and seasonality of HS outbreaks. Overall, South zone reported maximum proportion of the outbreaks (70.2%), followed by East zone (7.2%), Central zone (6.4%), North zone (5.6%), West zone (5.5%) and North-East zone (4.9%). Annual state level analysis indicated that the reporting of HS outbreaks started at different years independently and there was no apparent transmission between the states. The results of the current study are useful for the policy makers to design national control programme on HS in India and implement state specific strategies. Further, our study and strategies could aid in implementation of similar approaches in HS endemic tropical countries around the world.

RevDate: 2024-03-21

Morel B, Williams TA, Stamatakis A, et al (2024)

AleRax: a tool for gene and species tree co-estimation and reconciliation under a probabilistic model of gene duplication, transfer, and loss.

Bioinformatics (Oxford, England) pii:7633408 [Epub ahead of print].

MOTIVATION: Genomes are a rich source of information on the pattern and process of evolution across biological scales. How best to make use of that information is an active area of research in phylogenetics. Ideally, phylogenetic methods should not only model substitutions along gene trees, which explain differences between homologous gene sequences, but also the processes that generate the gene trees themselves along a shared species tree. To conduct accurate inferences, one needs to account for uncertainty at both levels, that is, in gene trees estimated from inherently short sequences and in their diverse evolutionary histories along a shared species tree.

RESULTS: We present AleRax, a software that can infer reconciled gene trees together with a shared species tree using a simple, yet powerful, probabilistic model of gene duplication, transfer, and loss. A key feature of AleRax is its ability to account for uncertainty in the gene tree and its reconciliation by using an efficient approximation to calculate the joint phylogenetic-reconciliation likelihood and sample reconciled gene trees accordingly. Simulations and analyses of empirical data show that AleRax is one order of magnitude faster than competing gene tree inference tools while attaining the same accuracy. It is consistently more robust than species tree inference methods such as SpeciesRax and ASTRAL-Pro 2 under gene tree uncertainty. Finally, AleRax can process multiple gene families in parallel thereby allowing users to compare competing phylogenetic hypotheses and estimate model parameters, such as DTL probabilities for genome-scale datasets with hundreds of taxa.

GNU GPL at https://github.com/BenoitMorel/AleRax and data are made available at https://cme.h-its.org/exelixis/material/alerax_data.tar.gz.

SUPPLEMENTARY INFORMATION: Supplementary material is available at Bioinformatics online.

RevDate: 2024-03-26
CmpDate: 2024-03-26

Chandel AS (2024)

Geo-spatial technology based on a multi-criteria evaluation technique used to find potential landfill sites in the town of Bule Hora in southern Ethiopia.

Journal of the Air & Waste Management Association (1995), 74(4):207-239.

Solid waste has surfaced as an eminent and critical concern of environmental and social significance on a global scale, and Ethiopia, a developing country with limited income, has also encountered unfavorable outcomes due to substandard waste management practices. When pinpointing a fitting landfill location in the town of Bule Hora, various ecological, economic, and societal aspects must be considered; these may result in discord and exacerbate a multifaceted and lengthy process. Hence, this research aims to identify prospective landfill sites within the town and utilize geospatial methods, such as Multi-Criteria Evaluation and Analytic Hierarchy Process, to accomplish its objectives. The utilization of geospatial technology and multi-criteria evaluation provides an efficient manner to simultaneously address all bottlenecks involved in the selection of an appropriate landfill location. Geospatial technology evaluates and manages environmental constraints, whereas multi-criteria assessment categorizes choices based on their desirability. Furthermore, by employing a restriction map adhering to established standards, seven landfill sites have successfully been identified within the town. The Land Suitability Index assesses site suitability based on ecological factors, while the Total Hauling Distance evaluates sites within an economic framework. AHP determines weightings through 25.4 pairwise comparisons, resulting in a consistency ratio of 1.95%. The cartographic analysis is conducted using ESRI ArcGIS version 10.8 software. The findings of this study reveal that 98.69% of the area under study is subject to restrictions. The study recommends the implementation of geospatial methods for identifying suitable landfill sites, which would aid in the decision-making process and prevent hasty decisions from triggering environmental degradation. Proper waste disposal would augment the quality of life for residents by diminishing health hazards. The study endeavors to serve as a reference for other developing countries in selecting appropriate landfill sites.Implications: The town of Bule Hora also faces the problem of waste disposal; there is no scientifically selected suitable landfill. Residents of the town of Bule Hora practice waste disposal in open fields, near settlements, water bodies, roads, agricultural land, and other places. The main sources of solid waste in the town are homes, shops, hotels, restaurants, open markets, hospitals, educational institutions, private clinics, etc. Water pollution can potentially lead to the spread of waterborne diseases. According to reports from the Bule Horas Health Department, many people are affected by water-related diseases every year. These open landfill systems with no regard for settlement, topography, geology, surface, or groundwater conditions are the consequences of these unsuitable habitats and health problems. To reduce these problems, this study plays an important role in determining the suitability of landfills for the town and proposing alternative measures that can minimize negative environmental impacts from waste. This study aims to apply geospatial-based technology to a multi-criteria assessment technique to select perfectly suitable landfill sites that are environmentally friendly, economically cost-effective, and socially responsible; examine the town's current waste management system; calculate the selected parameter weights for feature ranking; and delineate solid waste landfills.

RevDate: 2024-03-22
CmpDate: 2024-03-15

Delavaux CS, Crowther TW, Bever JD, et al (2024)

Mutualisms weaken the latitudinal diversity gradient among oceanic islands.

Nature, 627(8003):335-339.

The latitudinal diversity gradient (LDG) dominates global patterns of diversity[1,2], but the factors that underlie the LDG remain elusive. Here we use a unique global dataset[3] to show that vascular plants on oceanic islands exhibit a weakened LDG and explore potential mechanisms for this effect. Our results show that traditional physical drivers of island biogeography[4]-namely area and isolation-contribute to the difference between island and mainland diversity at a given latitude (that is, the island species deficit), as smaller and more distant islands experience reduced colonization. However, plant species with mutualists are underrepresented on islands, and we find that this plant mutualism filter explains more variation in the island species deficit than abiotic factors. In particular, plant species that require animal pollinators or microbial mutualists such as arbuscular mycorrhizal fungi contribute disproportionately to the island species deficit near the Equator, with contributions decreasing with distance from the Equator. Plant mutualist filters on species richness are particularly strong at low absolute latitudes where mainland richness is highest, weakening the LDG of oceanic islands. These results provide empirical evidence that mutualisms, habitat heterogeneity and dispersal are key to the maintenance of high tropical plant diversity and mediate the biogeographic patterns of plant diversity on Earth.

RevDate: 2024-03-21

Scalabrin E, Radaelli M, Capodaglio G, et al (2024)

Hemp cultivation opportunities for marginal lands development.

PloS one, 19(3):e0299981 pii:PONE-D-23-37006.

Agricultural diversification and high-quality products deriving from sustainable crops such as hemp can represent a solution to revitalize marginal areas and reverse land abandonment. This study aimed at comparing four different hemp cultivars (Carmagnola Selezionata, "CS"; Futura 75, "FUT"; Felina 32, "FEL"; Secuieni Jubileu, "JUB") to provide information to select the best suited cultivar for cultivation in mountain marginal areas and for specific end-use applications. Hemp cultivars were cultivated in a single experimental field to compare their ecological and agronomic behavior (duration of life cycle phases, plant size and biomass allocation, and plant resource-use strategies). Through metabolomic analysis of both vegetative and reproductive parts of the plants we tested the presence of substances of nutraceutical interest and traced seed nutritional profile. The four cultivars had different ecological and agronomic behavior, and nutritional profile. We found several compounds with potential pharmaceutical and nutraceutical values in all parts of the plant (leaves, inflorescences, and stems). JUB resulted the most suitable for seed production while CS showed the highest content of bioactive compounds in flowers and leaves. FUT, showed the best suitability for multi-purpose cultivation, while FEL seemed to be not appropriate for the cultivation in mountain area. The multi-disciplinary approach we adopted was effective in distinguish across hemp cultivars and provided information to farmers for the selection of the best hemp cultivar to select. Hemp had a high potential for cultivation in marginal lands, demonstrating to be an economic resource due to its multi-purpose use and to the possibility to generate high-added values products. Our results could serve as a stimulus for the reintroduction of this culture in the study area and in other similar environments.

RevDate: 2024-03-22
CmpDate: 2024-03-22

Berner LT, Orndahl KM, Rose M, et al (2024)

The Arctic Plant Aboveground Biomass Synthesis Dataset.

Scientific data, 11(1):305.

Plant biomass is a fundamental ecosystem attribute that is sensitive to rapid climatic changes occurring in the Arctic. Nevertheless, measuring plant biomass in the Arctic is logistically challenging and resource intensive. Lack of accessible field data hinders efforts to understand the amount, composition, distribution, and changes in plant biomass in these northern ecosystems. Here, we present The Arctic plant aboveground biomass synthesis dataset, which includes field measurements of lichen, bryophyte, herb, shrub, and/or tree aboveground biomass (g m[-2]) on 2,327 sample plots from 636 field sites in seven countries. We created the synthesis dataset by assembling and harmonizing 32 individual datasets. Aboveground biomass was primarily quantified by harvesting sample plots during mid- to late-summer, though tree and often tall shrub biomass were quantified using surveys and allometric models. Each biomass measurement is associated with metadata including sample date, location, method, data source, and other information. This unique dataset can be leveraged to monitor, map, and model plant biomass across the rapidly warming Arctic.

RevDate: 2024-03-22
CmpDate: 2024-03-22

Mueller HM, Franzisky BL, Messerer M, et al (2024)

Integrative multi-omics analyses of date palm (Phoenix dactylifera) roots and leaves reveal how the halophyte land plant copes with sea water.

The plant genome, 17(1):e20372.

Date palm (Phoenix dactylifera L.) is able to grow and complete its life cycle while being rooted in highly saline soils. Which of the many well-known salt-tolerance strategies are combined to fine-tune this remarkable resilience is unknown. The precise location, whether in the shoot or the root, where these strategies are employed remains uncertain, leaving us unaware of how the various known salt-tolerance mechanisms are integrated to fine-tune this remarkable resilience. To address this shortcoming, we exposed date palm to a salt stress dose equivalent to seawater for up to 4 weeks and applied integrative multi-omics analyses followed by targeted metabolomics, hormone, and ion analyses. Integration of proteomic into transcriptomic data allowed a view beyond simple correlation, revealing a remarkably high degree of convergence between gene expression and protein abundance. This sheds a clear light on the acclimatization mechanisms employed, which depend on reprogramming of protein biosynthesis. For growth in highly saline habitats, date palm effectively combines various salt-tolerance mechanisms found in both halophytes and glycophytes: "avoidance" by efficient sodium and chloride exclusion at the roots, and "acclimation" by osmotic adjustment, reactive oxygen species scavenging in leaves, and remodeling of the ribosome-associated proteome in salt-exposed root cells. Combined efficiently as in P. dactylifera L., these sets of mechanisms seem to explain the palm's excellent salt stress tolerance.

RevDate: 2024-03-22
CmpDate: 2024-03-22

Kudapa H, Ghatak A, Barmukh R, et al (2024)

Integrated multi-omics analysis reveals drought stress response mechanism in chickpea (Cicer arietinum L.).

The plant genome, 17(1):e20337.

Drought is one of the major constraints limiting chickpea productivity. To unravel complex mechanisms regulating drought response in chickpea, we generated transcriptomics, proteomics, and metabolomics datasets from root tissues of four contrasting drought-responsive chickpea genotypes: ICC 4958, JG 11, and JG 11+ (drought-tolerant), and ICC 1882 (drought-sensitive) under control and drought stress conditions. Integration of transcriptomics and proteomics data identified enriched hub proteins encoding isoflavone 4'-O-methyltransferase, UDP-d-glucose/UDP-d-galactose 4-epimerase, and delta-1-pyrroline-5-carboxylate synthetase. These proteins highlighted the involvement of pathways such as antibiotic biosynthesis, galactose metabolism, and isoflavonoid biosynthesis in activating drought stress response mechanisms. Subsequently, the integration of metabolomics data identified six metabolites (fructose, galactose, glucose, myoinositol, galactinol, and raffinose) that showed a significant correlation with galactose metabolism. Integration of root-omics data also revealed some key candidate genes underlying the drought-responsive "QTL-hotspot" region. These results provided key insights into complex molecular mechanisms underlying drought stress response in chickpea.

RevDate: 2024-03-21
CmpDate: 2024-03-21

Stefanovic M, Takano K, Wittekind CE, et al (2024)

Dynamic symptom associations in posttraumatic stress disorder: a network approach.

European journal of psychotraumatology, 15(1):2317675.

Background and objective: The current study aimed to investigate the within-day symptom dynamics in PTSD patients, specifically focusing on symptoms that most predict changes in other symptoms. The study included a baseline diagnostic assessment, followed by an assessment using the experience sampling method (ESM) via a smartphone.Method: Participants answered questions related to their PTSD symptoms four times per day for 15 consecutive days (compliance rate 75%). The clinical sample consisted of 48 treatment-seeking individuals: 44 with PTSD as a primary diagnosis, and four patients with subsyndromal PTSD, all of whom had not yet begun trauma-focused treatment. The ESM assessment included the 20 items from the PTSD Checklist for DSM-5, five items from the International Trauma Questionnaire (ITQ) assessing disturbances in relationships and functional impairment, and two items from the Clinician-Administered PTSD Scale for DSM-5 assessing symptoms of depersonalization and derealization.Results: Temporal networks (prospective associations between symptoms) showed that changes in hypervigilance predicted changes in the greatest number of symptoms at the next time point. Furthermore, hypervigilance showed temporal connections with at least one additional symptom from each of the DSM-5 PTSD symptom clusters.Conclusions: Results show that the contemporaneous network (representing the relationship between given symptoms within the same assessment occasion) and the temporal network (representing prospective associations between symptoms) differ and that it is important to estimate both. Some findings from earlier research are replicated, but heterogeneity across studies remains. Future studies should include potential moderators.

RevDate: 2024-03-21

Clifton-Brown J, Hastings A, von Cossel M, et al (2023)

Perennial biomass cropping and use: Shaping the policy ecosystem in European countries.

Global change biology. Bioenergy, 15(5):538-558.

Demand for sustainably produced biomass is expected to increase with the need to provide renewable commodities, improve resource security and reduce greenhouse gas emissions in line with COP26 commitments. Studies have demonstrated additional environmental benefits of using perennial biomass crops (PBCs), when produced appropriately, as a feedstock for the growing bioeconomy, including utilisation for bioenergy (with or without carbon capture and storage). PBCs can potentially contribute to Common Agricultural Policy (CAP) (2023-27) objectives provided they are carefully integrated into farming systems and landscapes. Despite significant research and development (R&D) investment over decades in herbaceous and coppiced woody PBCs, deployment has largely stagnated due to social, economic and policy uncertainties. This paper identifies the challenges in creating policies that are acceptable to all actors. Development will need to be informed by measurement, reporting and verification (MRV) of greenhouse gas emissions reductions and other environmental, economic and social metrics. It discusses interlinked issues that must be considered in the expansion of PBC production: (i) available land; (ii) yield potential; (iii) integration into farming systems; (iv) R&D requirements; (v) utilisation options; and (vi) market systems and the socio-economic environment. It makes policy recommendations that would enable greater PBC deployment: (1) incentivise farmers and land managers through specific policy measures, including carbon pricing, to allocate their less productive and less profitable land for uses which deliver demonstrable greenhouse gas reductions; (2) enable greenhouse gas mitigation markets to develop and offer secure contracts for commercial developers of verifiable low-carbon bioenergy and bioproducts; (3) support innovation in biomass utilisation value chains; and (4) continue long-term, strategic R&D and education for positive environmental, economic and social sustainability impacts.

RevDate: 2024-03-17

Ketterer T, Sieke E, Min J, et al (2024)

Contraception Initiation in the Emergency Department: Adolescent Perspectives.

The Journal of adolescent health : official publication of the Society for Adolescent Medicine pii:S1054-139X(24)00112-5 [Epub ahead of print].

PURPOSE: The purpose of this study was to identify factors affecting contraceptive intention and behavior among adolescent females in the pediatric Emergency Department.

METHODS: We conducted a qualitative interview study nested within a larger prospective cohort study examining adolescent contraceptive counseling for females ages 15-18 years at-risk of unintended pregnancy presenting to the pediatric Emergency Department. Interviews were conducted in a subset of participants. The ecologically expanded Theory of Planned Behavior, expert opinion, and literature review informed the interview guide. Interviews were recorded, transcribed, coded and monitored for thematic saturation.

RESULTS: Twenty-eight interviews were analyzed. Mean age was 17.1 years. Themes were mapped to ecologically expanded Theory of Planned Behavior constructs. Within health system influences, prior contraceptive experiences and patient-clinician interactions were described. Within community influences, contraceptive education, knowledge and misinformation, teen pregnancy norms, and social media impacts were described. Within attitudes influences, side-effect and safety concerns, contraceptive motivations and teen pregnancy beliefs were described. Within subjective norm influences, peer and family impacts were described. Within perceived behavioral control, Emergency Department (ED) counseling intervention impacts were described.

DISCUSSION: We identified factors affecting contraceptive initiation/behavior among an ED adolescent population that otherwise may not have received contraceptive education in similar detail as provided by study clinicians. Adolescents' prior contraceptive and clinician interactions, limited access to contraceptive education, knowledge and misinformation, and side-effect and safety concerns affected initiation. Peer/family sharing and social media were leading contraceptive information sources. Future studies should incorporate insights into adolescent ED intervention design to make optimal use of resources while maximizing potential benefit.

RevDate: 2024-03-19
CmpDate: 2024-03-18

Arslan D, Akdağ B, Yaşar Ç, et al (2024)

An extensive database on the traits and occurrences of amphibian species in Turkey.

Scientific data, 11(1):292.

Amphibians are the most endangered taxa among vertebrates, and they face many threats during their complex life cycles. The species' life history traits and occurrence database help understand species responses against ecological factors. Consequently, the species-level-trait database has gained more prominence in recent years as a useful tool for understanding the dimensions of communities, assembly processes of communities, and conserving biodiversity at the ecosystem level against environmental changes. However, in Turkey, there are deficiencies in the knowledge of the ecological traits of amphibians compared to other vertebrate taxa, as most studies have focused on their distribution or taxonomic status. Consequently, there is a need to create such a database for future research on all known extant amphibians in Turkey. We compiled a species-level data set of species traits and occurrences for all amphibians in Turkey using 436 literature sources. We completed 36 trait categories with 5611 occurrence data for 37 amphibian species in Turkey. This study provides an open, useful, and comprehensive database for macroecological and conservation studies on amphibians in Turkey.

RevDate: 2024-03-18
CmpDate: 2024-03-18

Guo Y, Li X, Li Q, et al (2024)

Environmental impact assessment of acidic coal gangue leaching solution on groundwater: a coal gangue pile in Shanxi, China.

Environmental geochemistry and health, 46(4):120.

With the continual advancement of coal resource development, the comprehensive utilization of coal gangue as a by-product encounters certain constraints. A substantial amount of untreated coal gangue is openly stored, particularly acidic gangue exposed to rainfall. The leaching effect of acidic solutions, containing heavy metal ions and other pollutants, results in environmental challenges such as local soil or groundwater pollution, presenting a significant concern in the current ecological landscape of mining areas. Investigating the migration patterns of pollutants in the soil-groundwater system and elucidating the characteristics of polluted solute migration are imperative. To understand the migration dynamics of pollutants and unveil the features of solute migration, this study focuses on a coal gangue dump in a mining area in Shanxi. Utilizing indoor leaching experiments and soil column migration experiments, a two-dimensional soil-groundwater model is established using the finite element method of COMSOL. This model quantitatively delineates the migration patterns of key pollutant components leached from coal gangue into the groundwater. The findings reveal that sulfate ions can migrate and infiltrate groundwater within a mere 7 years in the vadose zone of aeration. Moreover, the average concentration of iron ions in groundwater can reach approximately 58.3 mg/L. Convection, hydrodynamic dispersion, and adsorption emerge as the primary factors influencing pollution transport. Understanding the leaching patterns and environmental impacts of major pollutants in acidic coal gangue is crucial for predicting soil-groundwater pollution and implementing effective protective measures.

RevDate: 2024-03-20
CmpDate: 2024-03-20

Ulanova A, C Mansfeldt (2024)

EcoGenoRisk: Developing a computational ecological risk assessment tool for synthetic biology.

Environmental pollution (Barking, Essex : 1987), 346:123647.

The expanding field of synthetic biology (synbio) supports new opportunities in the design of targeted bioproducts or modified microorganisms. However, this rapid development of synbio products raises concerns surrounding the potential risks of modified microorganisms contaminating unintended environments. These potential invasion risks require new bioinformatic tools to inform the design phase. EcoGenoRisk is a newly constructed computational risk assessment tool for invasiveness that aims to predict where synbio microorganisms may establish a population by screening for habitats of genetically similar microorganisms. The first module of the tool identifies genetically similar microorganisms and potential ecological relationships such as competition, mutualism, and inhibition. In total, 520 archaeal and 32,828 bacterial complete assembly genomes were analyzed to test the specificity and accuracy of the tool as well as to characterize the enzymatic profiles of different taxonomic lineages. Additionally, ecological relationships were analyzed to determine which would result in the greatest potential overlap between shared functional profiles. Notably, competition displayed the significantly highest overlap of shared functions between compared genomes. Overall, EcoGenoRisk is a flexible software pipeline that assists environmental risk assessors to query large databases of known microorganisms and prioritize follow-up bench scale studies.

RevDate: 2024-03-15
CmpDate: 2024-03-15

Yang R, Feng J, Tang J, et al (2024)

Risk assessment and classification prediction for water environment treatment PPP projects.

Water science and technology : a journal of the International Association on Water Pollution Research, 89(5):1264-1281.

Water treatment public-private partnership (PPP) projects are pivotal for sustainable water management but are often challenged by complex risk factors. Efficient risk management in these projects is crucial, yet traditional methodologies often fall short of addressing the dynamic and intricate nature of these risks. Addressing this gap, this comprehensive study introduces an advanced risk classification prediction model tailored for water treatment PPP projects, aimed at enhancing risk management capabilities. The proposed model encompasses an intricate evaluation of crucial risk areas: the natural and ecological environments, socio-economic factors, and engineering entities. It delves into the complex relationships between these risk elements and the overall risk profile of projects. Grounded in a sophisticated ensemble learning framework employing stacking, our model is further refined through a weighted voting mechanism, significantly elevating its predictive accuracy. Rigorous validation using data from the Jiujiang City water environment system project Phase I confirms the model's superiority over standard machine learning models. The development of this model marks a significant stride in risk classification for water treatment PPP projects, offering a powerful tool for enhancing risk management practices. Beyond accurately predicting project risks, this model also aids in developing effective government risk management strategies.

RevDate: 2024-03-19
CmpDate: 2024-02-29

Xu W, Pan Z, Wu Y, et al (2024)

A database on the abundance of environmental antibiotic resistance genes.

Scientific data, 11(1):250.

Antimicrobial resistance (AMR) poses a severe threat to global health. The wide distribution of environmental antibiotic resistance genes (ARGs), which can be transferred between microbiota, especially clinical pathogens and human commensals, contributed significantly to AMR. However, few databases on the spatiotemporal distribution, abundance, and health risk of ARGs from multiple environments have been developed, especially on the absolute level. In this study, we compiled the ARG occurrence data generated by a high-throughput quantitative PCR platform from 1,403 samples in 653 sampling sites across 18 provinces in China. The database possessed 291,870 records from five types of habitats on the abundance of 290 ARGs, as well as 8,057 records on the abundance of 30 mobile genetic elements (MGEs) from 2013 to 2020. These ARGs conferred resistance to major common types of antibiotics (a total of 15 types) and represented five major resistance mechanisms, as well as four risk ranks. The database can provide information for studies on the dynamics of ARGs and is useful for the health risk assessment of AMR.

RevDate: 2024-03-18
CmpDate: 2024-03-18

Thenmozhi M, Sujatha M, Kavitha M, et al (2024)

Assessment of cyclone risk and case study of Gaja cyclone using GIS techniques and machine learning algorithms in coastal zone of Tamil Nadu, India.

Environmental research, 246:118089.

Cyclones can cause devastating impacts, including strong winds, heavy rainfall, storm surges, and flooding. The aftermath includes infrastructure damage, loss of life, displacement of communities, and ecological disruptions. Timely response and recovery efforts are crucial to minimize the socio-economic and environmental consequences of cyclones. To accelerate the time-consuming risk assessment process, particularly in geographically diverse regions, a blend of multi-criteria decision-making and machine learning models was utilized. This novel approach swiftly assessed cyclone risk and the impact of the Gaja cyclone in Nagapattinam, India. The method involved assigning weights to distinct criteria, unveiling notable vulnerability aspects like elevation, slope, proximity to the coast, distance from cyclone tracts, Lu/Lc, population density, proximity to cyclone shelters, household density, accessibility to healthcare facilities, NDVI, and levels of awareness. Daddavari, Ettugudi, Kodikarai, Vedharanyam, Velankanni, and Thirupoondi face high/extreme cyclone risk. Nagore, Nagapattinam, Pillai, Enangudi, and Sannanllur have low/no threat. To further enhance the precision of the study, machine learning algorithms like SVM, SAM, and MLC were deployed. These models were instrumental in generating pre- and post-cyclone land use maps. The influence of Gaja cyclones effects shows decreasing of agriculture land from 34% to 30%, aquaculture increase 1%, barren land decrease from 8% to 6%, Built-up land decrease from 15% to 13%, land with scrub and salt pan also decrease from 21% to 17% and 10%-8%. Mostly effect of Gaja cyclone is dramatic increase of water body from 8% to 21%. Conducting cyclone risk zone analysis and pre/post-cyclone Land Use Land Cover (LULC) detection in Nagapattinam offers valuable insights for disaster preparedness, infrastructure planning, and climate resilience. This study can enhance understanding of vulnerability and aid in formulating strategies to mitigate cyclone impacts, ensuring sustainable development in the region.

RevDate: 2024-03-18
CmpDate: 2024-03-18

Chaves T, Azevedo Á, IM Caldas (2024)

Cheiloscopy in sex estimation: a systematic review.

Forensic science, medicine, and pathology, 20(1):280-292.

This study aimed to conduct a systematic review to gather evidence to clarify if cheiloscopy can be used in sex estimation and identify the reasons behind the lack of consensus in the scientific community. The systematic review was performed following the PRISMA guidelines. A bibliographic survey was conducted in PubMed, Scopus, and Web of Science databases, restricted to articles published between 2010 and 2020. Studies were selected according to eligibility criteria, and then the study data were collected. The risk of bias in each study was assessed and applied as additional inclusion or exclusion criteria. The results of the articles eligible for analysis were synthesized using a descriptive approach. In the 41 included studies, several methodological flaws and variations between studies that contribute to the discrepancy in results were identified. The data gathered allowed us to conclude that there is no strong scientific evidence to support the use of cheiloscopy in sex estimation, as there is no specific pattern for each sex, which reduces the criminalistic interest of cheiloscopy in estimating this parameter.

RevDate: 2024-03-14

Furuya S, Zheng F, Lu Q, et al (2024)

Separating Scarring Effect and Selection of Early-Life Exposures With Genetic Data.

Demography pii:386301 [Epub ahead of print].

Causal life course research examining consequences of early-life exposures has largely relied on associations between early-life environments and later-life outcomes using exogenous environmental shocks. Nonetheless, even with (quasi-)randomized early-life exposures, these associations may reflect not only causation ("scarring") but also selection (i.e., which members are included in data assessing later life). Investigating this selection and its impacts on estimated effects of early-life conditions has, however, often been ignored because of a lack of pre-exposure data. This study proposes an approach for assessing and correcting selection, separately from scarring, using genetic measurements. Because genetic measurements are determined at the time of conception, any associations with early-life exposures should be interpreted as selection. Using data from the UK Biobank, we find that in utero exposure to a higher area-level infant mortality rate is associated with genetic predispositions correlated with better educational attainment and health. These findings point to the direction and magnitude of selection from this exposure. Corrections for this selection in examinations of effects of exposure on later educational attainment suggest underestimates of 26-74%; effects on other life course outcomes also vary across selection correction methods.

RevDate: 2024-03-13

Kekalih A, Adi NP, DS Soemarko (2024)

Preparation and Challenges in Developing a Big Data Analysis Framework in Occupational Medicine in Indonesia.

Journal of UOEH, 46(1):113-118.

This mini review explores the transformative potential of big data analysis and artificial intelligence (AI) in reforming occupational medicine in Indonesia. Emphasizing the preconditions, case studies, and benefits, it underscores the role of big data in enhancing worker well-being. The review highlights the importance of informative health big data, especially in high-risk industries, with examples of case studies of AI implementation in occupational medicine during the COVID-19 pandemic and other relevant scenarios. While acknowledging the challenges of AI implementation, the essay identifies the role of academic and professional organizations as pioneers in big data utilization. Six potential benefits that are identified, including improved patient care and efficient resource allocation, demonstrate the transformative impact of big data analysis. The proposed pathway of preparation underscores the need for awareness, skill enhancement, and collaboration, addressing challenges in data management and stakeholder engagement. The conclusion emphasizes continuous assessment, feasibility studies, and commitment as essential steps in advancing occupational medicine through big data analysis.

RevDate: 2024-03-14

Kearsley E, Verbeeck H, Stoffelen P, et al (2024)

Historical tree phenology data reveal the seasonal rhythms of the Congo Basin rainforest.

Plant-environment interactions (Hoboken, N.J.), 5(2):e10136.

Tropical forest phenology directly affects regional carbon cycles, but the relation between species-specific and whole-canopy phenology remains largely uncharacterized. We present a unique analysis of historical tropical tree phenology collected in the central Congo Basin, before large-scale impacts of human-induced climate change. Ground-based long-term (1937-1956) phenological observations of 140 tropical tree species are recovered, species-specific phenological patterns analyzed and related to historical meteorological records, and scaled to characterize stand-level canopy dynamics. High phenological variability within and across species and in climate-phenology relationships is observed. The onset of leaf phenophases in deciduous species was triggered by drought and light availability for a subset of species and showed a species-specific decoupling in time along a bi-modal seasonality. The majority of the species remain evergreen, although central African forests experience relatively low rainfall. Annually a maximum of 1.5% of the canopy is in leaf senescence or leaf turnover, with overall phenological variability dominated by a few deciduous species, while substantial variability is attributed to asynchronous events of large and/or abundant trees. Our results underscore the importance of accounting for constituent signals in canopy-wide scaling and the interpretation of remotely sensed phenology signals.

RevDate: 2024-03-14
CmpDate: 2024-03-14

Omega RL, Ishigaki Y, Permana S, et al (2024)

Low-Cost Sensor Deployment on a Public Minibus in Fukushima Prefecture.

Sensors (Basel, Switzerland), 24(5):.

This study analyzed radiation dose data to observe the annual decline in ambient radiation doses and assess the factors contributing to fluctuations in reconstructed areas of the Fukushima prefecture. Utilizing a novel mobile monitoring system installed on a community minibus, the study employed a cost-effective sensor, namely, Pocket Geiger which was integrated with a microcontroller and telecommunication system for data transfer, access, visualization, and accumulation. The study area included the region between Okuma and Tomioka towns. The ambient dose rate recorded along the minibus route was depicted on a map, averaged within a 1 × 1 km mesh created with the Quantum Geographic Information System. To ensure accuracy, the shielding factor of the minibus material is determined to adjust the dose readings. A significant decrease (p < 0.001) in the radiation dose ranges from 2022 to 2023 was observed. The land use classification by the Advanced Land Observation Satellite revealed an ecological half-life ranging from 2.41 years to 1 year, suggesting a rapid radiation decay across all land types. This underscores the close connection between radiation attenuation and environmental factors, as well as decontamination efforts across diverse land categories.

RevDate: 2024-03-14
CmpDate: 2024-03-14

Li Z, Fan H, Yang L, et al (2024)

Multi-Omics Analysis of the Effects of Soil Amendment on Rapeseed (Brassica napus L.) Photosynthesis under Drip Irrigation with Brackish Water.

International journal of molecular sciences, 25(5):.

Drip irrigation with brackish water increases the risk of soil salinization while alleviating water shortage in arid areas. In order to alleviate soil salinity stress on crops, polymer soil amendments are increasingly used. But the regulation mechanism of a polymer soil amendment composed of polyacrylamide polyvinyl alcohol, and manganese sulfate (PPM) on rapeseed photosynthesis under drip irrigation with different types of brackish water is still unclear. In this field study, PPM was applied to study the responses of the rapeseed (Brassica napus L.) phenotype, photosynthetic physiology, transcriptomics, and metabolomics at the peak flowering stage under drip irrigation with water containing 6 g·L[-1] NaCl (S) and Na2CO3 (A). The results showed that the inhibitory effect of the A treatment on rapeseed photosynthesis was greater than that of the S treatment, which was reflected in the higher Na[+] content (73.30%) and lower photosynthetic-fluorescence parameters (6.30-61.54%) and antioxidant enzyme activity (53.13-77.10%) of the A-treated plants. The application of PPM increased the biomass (63.03-75.91%), photosynthetic parameters (10.55-34.06%), chlorophyll fluorescence parameters (33.83-62.52%), leaf pigment content (10.30-187.73%), and antioxidant enzyme activity (28.37-198.57%) under S and A treatments. However, the difference is that under the S treatment, PPM regulated the sulfur metabolism, carbon fixation and carbon metabolism pathways in rapeseed leaves. And it also regulated the photosynthesis-, oxidative phosphorylation-, and TCA cycle-related metabolic pathways in rapeseed leaves under A treatment. This study will provide new insights for the application of polymer materials to tackle the salinity stress on crops caused by drip irrigation with brackish water, and solve the difficulty in brackish water utilization.

RevDate: 2024-03-14
CmpDate: 2024-03-14

Viera A, Ondrusek A, Tengatenga C, et al (2024)

A Qualitative Exploration of Attitudes Toward Global Positioning System Tracking and Ecological Momentary Assessment Among Individuals in Substance Use Treatment.

Substance use & addiction journal, 45(2):260-267.

BACKGROUND: The use of tracking technology in substance use research can uncover the role of contextual factors, such as social networks and environmental cues, in triggering cravings and precipitating return to use. Few studies have explored the opinions of individuals in substance use treatment related to tracking technology.

METHODS: We conducted 30 semi-structured interviews with individuals in substance use treatment facilities in Connecticut and Georgia. Interviews were not limited to individuals with any specific substance use disorder. Interviewers described a hypothetical study involving ecological momentary assessment and global positioning system tracking to examine place-based predictors of substance use. Participants were invited to share reactions to this description. We used thematic analysis to identify themes in participant perceptions of this hypothetical research study.

RESULTS: Most participants shared positive opinions about study participation and expressed little to no concern about the tracking components. Participant concerns focused on the security of their information and the potential burden of responding to study questions. Participants largely understood the importance of study participation for promoting greater understanding of substance use and identified potential therapeutic effects of study participation on their own recovery.

CONCLUSIONS: Individuals in substance use treatment expressed little concern with research studies or interventions incorporating mobile-tracking elements. Future studies should explore the responsible use of tracking elements in recovery support interventions.

RevDate: 2024-03-13

Kozicki M, Sąsiadek-Andrzejczak E, Wach R, et al (2024)

Flexible Cotton Fabric-Based Ionizing Radiation Dosimeter for 2D Dose Distribution Measurements over a Wide Dose Range at High Dose Rates.

International journal of molecular sciences, 25(5): pii:ijms25052916.

This work presents an ecological, flexible 2D radiochromic dosimeter for measuring ionizing radiation in the kilogray dose range. Cotton woven fabric made of cellulose was volume-modified with nitrotetrazolium blue chloride as a radiation-sensitive compound. Its features include a color change during exposure from yellowish to purple-brown and flexibility that allows it to adapt to various shapes. It was found that (i) the dose response is up to ~80 kGy, (ii) it is independent of the dose rate for 1.1-73.1 kGy/min, (iii) it can be measured in 2D using a flatbed scanner, (iv) the acquired images can be filtered using a mean filter, which improves its dose resolution, (v) the dose resolution is -0.07 to -0.4 kGy for ~0.6 to ~75.7 kGy for filtered images, and (vi) two linear dose subranges can be distinguished: ~0.6 to ~7.6 kGy and ~9.9 to ~62.0 kGy. The dosimeter combined with flatbed scanner reading and data processing using dedicated software packages constitutes a comprehensive system for measuring dose distributions for objects with complex shapes.

RevDate: 2024-03-12

Bhosle A, Bae S, Zhang Y, et al (2024)

Integrated annotation prioritizes metabolites with bioactivity in inflammatory bowel disease.

Molecular systems biology [Epub ahead of print].

Microbial biochemistry is central to the pathophysiology of inflammatory bowel diseases (IBD). Improved knowledge of microbial metabolites and their immunomodulatory roles is thus necessary for diagnosis and management. Here, we systematically analyzed the chemical, ecological, and epidemiological properties of ~82k metabolic features in 546 Integrative Human Microbiome Project (iHMP/HMP2) metabolomes, using a newly developed methodology for bioactive compound prioritization from microbial communities. This suggested >1000 metabolic features as potentially bioactive in IBD and associated ~43% of prevalent, unannotated features with at least one well-characterized metabolite, thereby providing initial information for further characterization of a significant portion of the fecal metabolome. Prioritized features included known IBD-linked chemical families such as bile acids and short-chain fatty acids, and less-explored bilirubin, polyamine, and vitamin derivatives, and other microbial products. One of these, nicotinamide riboside, reduced colitis scores in DSS-treated mice. The method, MACARRoN, is generalizable with the potential to improve microbial community characterization and provide therapeutic candidates.

RevDate: 2024-03-11

Rivero-Marcos M, Lasa B, Neves T, et al (2024)

Plant ammonium sensitivity is associated with the external pH adaptation, repertoire of nitrogen transporters, and nitrogen requirement.

Journal of experimental botany pii:7625386 [Epub ahead of print].

Modern crops exhibit diverse sensitivities to ammonium as the primary nitrogen source, influenced by environmental factors such as external pH and nutrient availability. Despite its significance, there is currently no systematic classification of plant species based on their ammonium sensitivity. This study conducts a meta-analysis of 50 plant species and presents a new classification method based on the comparison of fresh biomass obtained under ammonium and nitrate nutrition. The classification uses the natural logarithm of biomass ratio as the size effect indicator of ammonium sensitivity. This numerical parameter is associated with critical factors for nitrogen demand and form preference, such as Ellenberg indicators and the repertoire of nitrogen transporters for ammonium and nitrate uptake. Finally, a comparative analysis of the developmental and metabolic responses, including hormonal balance, is conducted in two species with divergent ammonium sensitivity values in the classification. Results indicate that nitrate has a key counteracting role of ammonium toxicity in species with a higher abundance of genes encoding NRT2-type proteins and fewer of the AMT2-type proteins. Additionally, the study confirms the reliability of the phytohormone balance and methylglyoxal content as indicators for anticipating ammonium toxicity.

RevDate: 2024-03-12
CmpDate: 2024-03-11

Zhang L, Li H, Shi M, et al (2024)

FishSNP: a high quality cross-species SNP database of fishes.

Scientific data, 11(1):286.

The progress of aquaculture heavily depends on the efficient utilization of diverse genetic resources to enhance production efficiency and maximize profitability. Single nucleotide polymorphisms (SNPs) have been widely used in the study of aquaculture genomics, genetics, and breeding research since they are the most prevalent molecular markers on the genome. Currently, a large number of SNP markers from cultured fish species are scattered in individual studies, making querying complicated and data reuse problematic. We compiled relevant SNP data from literature and public databases to create a fish SNP database, FishSNP (http://bioinfo.ihb.ac.cn/fishsnp), and also used a unified analysis pipeline to process raw data that the author of the literature did not perform SNP calling on to obtain SNPs with high reliability. This database presently contains 45,690,243 (45 million) nonredundant SNP data for 13 fish species, with 30,288,958 (30 million) of those being high-quality SNPs. The main function of FishSNP is to search, browse, annotate and download SNPs, which provide researchers various and comprehensive associated information.

RevDate: 2024-03-13
CmpDate: 2024-03-13

Akar AU, Sisman S, Ulku H, et al (2024)

Evaluating lake water quality with a GIS-based MCDA integrated approach: a case in Konya/Karapınar.

Environmental science and pollution research international, 31(13):19478-19499.

Considering water quality is an essential requirement in terms of environmental planning and management. To protect and manage water resources effectively, it is necessary to develop an analytical decision-support system. In this study, a systematic approach was suggested to evaluate the lake water quality. The methodology includes the prediction of the values in different locations of the lakes from experimental data through inverse distance weighting (IDW) method, creation of maps by using Geographic Information System (GIS) integrated with analytic hierarchy process (AHP) from multi-criteria decision analysis (MCDA), reclassification into five class, combining the time-related spatial data into a single map to predict the whole lake water quality from the data of sampling points, and finally overlapping the final maps with topography/geology and land use. The proposed approach was verified and presented as case study for Meke and Acigol Lakes in Konya/Turkey which were affected by human and natural factors although they have ecological, hydromorphological, and socio-economic importance. In the proposed approach, categorizing water quality parameters as "hardness and minerals," "substrates and nutrients," "solids content," "metals," and "oil-grease" groups was helpful for AHP with the determined group weights of 0.484, 0.310, 0.029, and 0.046, respectively. Assigning weights within each group and then assigning weights between groups resulted in creating accurate final map. The proposed approach is flexible and applicable to any lake water quality data; even with a limited number of data, the whole lake water quality maps could be created for assessment.

RevDate: 2024-03-13
CmpDate: 2024-02-14

Brehm AM, JL Orrock (2023)

Extensive behavioral data contained within existing ecological datasets.

Trends in ecology & evolution, 38(12):1129-1133.

Long-term ecological datasets contain vast behavioral data, enabling the quantification of among-individual behavioral variation at unprecedented spatiotemporal scales. We detail how behaviors can be extracted and describe how such data can be used to test new hypotheses, inform population and community ecology, and address pressing conservation needs.

RevDate: 2024-03-08
CmpDate: 2024-03-08

Souza IM, Araújo EM, AMD Silva Filho (2024)

Incomplete recording of race/colour in health information systems in Brazil: time trend, 2009-2018.

Ciencia & saude coletiva, 29(3):e05092023.

This ecological study of time trends and multiple groups evaluated incompleteness in the race/colour field of Brazilian health information system records and the related time trend, 2009-2018, for the diseases and disorders most prevalent in the black population. The Romero and Cunha (2006) classification was applied in order to examine incompleteness using secondary data from Brazil's National Notifiable Diseases System, Hospital Information System and Mortality Information System, by administrative regions of Brazil, while percentage underreporting and time trend were calculated using simple linear regression models with Prais-Winsten correction (p-value<0.05). All records scored poorly except those for mortality from external causes (excellent), tuberculosis (good) and infant mortality (fair). An overall downward trend was observed in percentage incompleteness. Analysis by region found highest mean incompleteness in the North (30.5%), Northeast (33.3%) and Midwest (33.0%) regions. The Southeast and Northeast regions showed the strongest downward trends. The findings intended to increase visibility on the implications of the race/color field for health equity.

RevDate: 2024-03-11
CmpDate: 2024-03-08

Tao F, Houlton BZ, Frey SD, et al (2024)

Reply to: Model uncertainty obscures major driver of soil carbon.

Nature, 627(8002):E4-E6.

RevDate: 2024-03-06

van der Feltz-Cornelis C, Turk F, Sweetman J, et al (2024)

Prevalence of mental health conditions and brain fog in people with long COVID: A systematic review and meta-analysis.

General hospital psychiatry, 88:10-22 pii:S0163-8343(24)00039-2 [Epub ahead of print].

OBJECTIVE: Long COVID can include impaired cognition ('brain fog'; a term encompassing multiple symptoms) and mental health conditions. We performed a systematic review and meta-analysis to estimate their prevalence and to explore relevant factors associated with the incidence of impaired cognition and mental health conditions.

METHODS: Searches were conducted in Medline and PsycINFO to cover the start of the pandemic until August 2023. Included studies reported prevalence of mental health conditions and brain fog in adults with long COVID after clinically-diagnosed or PCR-confirmed SARS-CoV-2 infection.

FINDINGS: 17 studies were included, reporting 41,249 long COVID patients. Across all timepoints (3-24 months), the combined prevalence of mental health conditions and brain fog was 20·4% (95% CI 11·1%-34·4%), being lower among those previously hospitalised than in community-managed patients(19·5 vs 29·7% respectively; p = 0·047). The odds of mental health conditions and brain fog increased over time and when validated instruments were used. Odds of brain fog significantly decreased with increasing vaccination rates (p = ·000).

CONCLUSIONS: Given the increasing prevalence of mental health conditions and brain fog over time, preventive interventions and treatments are needed. Research is needed to explore underlying mechanisms that could inform further research in development of effective treatments. The reduced risk of brain fog associated with vaccination emphasizes the need for ongoing vaccination programs.

RevDate: 2024-03-11
CmpDate: 2024-03-11

Gonyo SB, Burkart H, S Regan (2024)

Leveraging big data for outdoor recreation management: A case study from the York river in Virginia.

Journal of environmental management, 354:120482.

Outdoor recreation is important for improving quality of life, well-being, and local economies, but quantifying its value without direct monetary transactions can be challenging. This study explores combining non-market valuation techniques with emerging big data sources to estimate the value of recreation for the York River and surrounding parks in Virginia. By applying the travel cost method to anonymous human mobility data, we gain deeper insights into the significance of recreational experiences for visitors and the local economy. Results of a zero-inflated Negative Binomial model show a mean consumer surplus value of $26.91 per trip, totaling $15.5 million across nearly 600,000 trips observed in 2022. Further, weekends, holidays, and the summer and fall months are found to be peak visitation times, whereas those with young children and who are Hispanic or over 64 years old are less likely to visit. These findings shed light on various factors influencing visitation patterns and recreation values, including temporal effects and socio-demographics, revealing disparities that warrant targeted efforts for inclusivity and accessibility. Policymakers can use these insights to make informed and sustainable choices in outdoor recreation management, fostering the preservation of natural resources for the benefit of both visitors and the environment.

RevDate: 2024-03-08
CmpDate: 2024-03-07

Kudamba A, Kasolo JN, Bbosa GS, et al (2024)

Review of Herbal Medicinal Plants Used in the Management of Cancers in the East Africa Region from 2019 to 2023.

Integrative cancer therapies, 23:15347354241235583.

BACKGROUND: In the East African region, herbal plants are essential in the treatment and control of cancer. Given the diverse ecological and cultural makeup of the regional states, it is likely that different ethnic groups will use the same or different plants for the same or different diseases. However, since 2019, this has not been compiled into a single study.

PURPOSE: The study aimed to compile and record the medicinal plants utilized in East Africa from April 2019 to June 2023 to treat various cancer types.

MATERIALS AND METHODS: The study examined 13 original studies that included ethnobotanical research conducted in East Africa. They were retrieved from several internet databases, including Google Scholar, Scopus, PubMed/Medline, Science Direct, and Research for Life. The study retrieved databases on plant families and species, plant parts used, preparation methods and routes of administration, and the country where the ethnobotanical field surveys were conducted. Graphs were produced using the GraphPad Prism 8.125 program (GraphPad Software, Inc., San Diego, CA). Tables and figures were used to present the data, which had been condensed into percentages and frequencies.

RESULTS: A total of 105 different plant species from 45 different plant families were identified, including Asteraceae (14), Euphorbiaceae (12), Musaceae (8), and Apocynaceae (7). Uganda registered the highest proportion (46% of the medicinal plants used). The most commonly mentioned medicinal plant species in cancer management was Prunus africana. Herbs (32%), trees and shrubs (28%), and leaves (45%) constituted the majority of herbal remedies. Most herbal remedies were prepared by boiling (decoction) and taken orally (57%).

CONCLUSION: East Africa is home to a wide variety of medicinal plant species that local populations and herbalists, or TMP, frequently use in the treatment of various types of cancer. The most frequently used families are Asteraceae and Euphorbiaceae, with the majority of species being found in Uganda. The most frequently utilized plant species is Prunus africana. Studies on the effectiveness of Prunus africana against other malignancies besides prostate cancer are required.

RevDate: 2024-03-07
CmpDate: 2024-03-07

Liu Y, Li L, Feng J, et al (2024)

Modulation of chronic obstructive pulmonary disease progression by antioxidant metabolites from Pediococcus pentosaceus: enhancing gut probiotics abundance and the tryptophan-melatonin pathway.

Gut microbes, 16(1):2320283.

Chronic obstructive pulmonary disease (COPD), a condition primarily linked to oxidative stress, poses significant health burdens worldwide. Recent evidence has shed light on the association between the dysbiosis of gut microbiota and COPD, and their metabolites have emerged as potential modulators of disease progression through the intricate gut-lung axis. Here, we demonstrate the efficacy of oral administration of the probiotic Pediococcus pentosaceus SMM914 (SMM914) in delaying the progression of COPD by attenuating pulmonary oxidative stress. Specially, SMM914 induces a notable shift in the gut microbiota toward a community structure characterized by an augmented abundance of probiotics producing short-chain fatty acids and antioxidant metabolisms. Concurrently, SMM914 synthesizes L-tryptophanamide, 5-hydroxy-L-tryptophan, and 3-sulfino-L-alanine, thereby enhancing the tryptophan-melatonin pathway and elevating 6-hydroxymelatonin and hypotaurine in the lung environment. This modulation amplifies the secretion of endogenous anti-inflammatory factors, diminishes macrophage polarization toward the M1 phenotype, and ultimately mitigates the oxidative stress in mice with COPD. The demonstrated efficacy of the probiotic intervention, specifically with SMM914, not only highlights the modulation of intestine microbiota but also emphasizes the consequential impact on the intricate interplay between the gastrointestinal system and respiratory health.

RevDate: 2024-03-07
CmpDate: 2024-03-07

Ge X, Peng L, Deng Z, et al (2024)

Chromosome-scale genome assemblies of Himalopsyche anomala and Eubasilissa splendida (Insecta: Trichoptera).

Scientific data, 11(1):267.

Trichoptera is one of the most evolutionarily successful aquatic insect lineages and is highly valued value in adaptive evolution research. This study presents the chromosome-level genome assemblies of Himalopsyche anomala and Eubasilissa splendida achieved using PacBio, Illumina, and Hi-C sequencing. For H. anomala and E. splendida, assembly sizes were 663.43 and 859.28 Mb, with scaffold N50 lengths of 28.44 and 31.17 Mb, respectively. In H. anomala and E. splendida, we anchored 24 and 29 pseudochromosomes, and identified 11,469 and 10,554 protein-coding genes, respectively. The high-quality genomes of H. anomala and E. splendida provide critical genomic resources for understanding the evolution and ecology of Trichoptera and performing comparative genomics analyses.

RevDate: 2024-03-07
CmpDate: 2024-03-07

Zhou H, Zhang X, Liu H, et al (2024)

Chromosome-level genome assembly of Platycarya strobilacea.

Scientific data, 11(1):269.

Platycarya strobilacea belongs to the walnut family (Juglandaceae), is commonly known as species endemic to East Asia, and is an ecologically important, wind pollinated, woody deciduous tree. To facilitate this ancient tree for the ecological value and conservation of this ancient tree, we report a new high-quality genome assembly of P. strobilacea. The genome size was 677.30 Mb, with a scaffold N50 size of 45,791,698 bp, and 98.43% of the assembly was anchored to 15 chromosomes. We annotated 32,246 protein-coding genes in the genome, of which 96.30% were functionally annotated in six databases. This new high-quality assembly of P. strobilacea provide valuable resource for the phylogenetic and evolutionary analysis of the walnut family and angiosperm.

RevDate: 2024-03-07
CmpDate: 2024-02-09

Del Campo J, Carlos-Oliveira M, Čepička I, et al (2024)

The protist cultural renaissance.

Trends in microbiology, 32(2):128-131.

Protists are key players in the biosphere. Here, we provide a perspective on integrating protist culturing with omics approaches, imaging, and high-throughput single-cell manipulation strategies, concluding with actions required for a successful return of the golden age of protist culturing.

RevDate: 2024-03-05

Zhang Z, Xu H, G Zhu (2024)

Incorporating high-frequency information into edge convolution for link prediction in complex networks.

Scientific reports, 14(1):5437.

Link prediction in complex networks aims to mine hidden or to-be-generated links between network nodes, which plays a significant role in fields such as the cold start of recommendation systems, knowledge graph completion and biomedical experiments. The existing link prediction models based on graph neural networks, such as graph convolution neural networks, often only learn the low-frequency information reflecting the common characteristics of nodes while ignoring the high-frequency information reflecting the differences between nodes when learning node representation, which makes the corresponding link prediction models show over smoothness and poor performance. Focusing on links in complex networks, this paper proposes an edge convolutional graph neural network EdgeConvHiF that fuses high-frequency node information to achieve the representation learning of links so that link prediction can be realized by implementing the classification of links. EdgeConvHiF can also be employed as a baseline, and extensive experiments on real-world benchmarks validate that EdgeConvHiF not only has high stability but also has more advantages than the existing representative baselines.

RevDate: 2024-03-05

Tamosiunaite M, Tetzlaff C, F Wörgötter (2024)

Unsupervised learning of perceptual feature combinations.

PLoS computational biology, 20(3):e1011926 pii:PCOMPBIOL-D-23-01087 [Epub ahead of print].

In many situations it is behaviorally relevant for an animal to respond to co-occurrences of perceptual, possibly polymodal features, while these features alone may have no importance. Thus, it is crucial for animals to learn such feature combinations in spite of the fact that they may occur with variable intensity and occurrence frequency. Here, we present a novel unsupervised learning mechanism that is largely independent of these contingencies and allows neurons in a network to achieve specificity for different feature combinations. This is achieved by a novel correlation-based (Hebbian) learning rule, which allows for linear weight growth and which is combined with a mechanism for gradually reducing the learning rate as soon as the neuron's response becomes feature combination specific. In a set of control experiments, we show that other existing advanced learning rules cannot satisfactorily form ordered multi-feature representations. In addition, we show that networks, which use this type of learning always stabilize and converge to subsets of neurons with different feature-combination specificity. Neurons with this property may, thus, serve as an initial stage for the processing of ecologically relevant real world situations for an animal.

RevDate: 2024-03-06
CmpDate: 2024-03-06

Wu LF, Zhu WG, Yu EP, et al (2024)

Draft genome of Brasenia schreberi, a worldwide distributed and endangered aquatic plant.

BMC genomic data, 25(1):24.

OBJECTIVES: Brasenia is a monotypic genus in the family of Cabombaceae. The only species, B. schreberi, is a macrophyte distributed worldwide. Because it requires good water quality, it is endangered in China and other countries due to the deterioration of aquatic habitats. The young leaves and stems of B. schreberi are covered by thick mucilage, which has high medical value. As an allelopathic aquatic plant, it can also be used in the management of aquatic weeds. Here, we present its assembled and annotated genome to help shed light on medial and allelopathic substrates and facilitate their conservation.

DATA DESCRIPTION: Genomic DNA and RNA extracted from B. schreberi leaf tissues were used for whole genome and RNA sequencing using a Nanopore and/or MGI sequencer. The assembly was 1,055,148,839 bp in length, with 92 contigs and an N50 of 22,379,495 bp. The repetitive elements in the assembly were 555,442,205 bp. A completeness assessment of the assembly with BUSCO and compleasm indicated 88.4 and 90.9% completeness in the Eudicots database and 95.4 and 96.6% completeness in the Embryphyta database. Gene annotation revealed 67,747 genes that coded for 73,344 proteins.

RevDate: 2024-03-04

Qian J, Qian L, Pu N, et al (2024)

An Intelligent Early Warning System for Harmful Algal Blooms: Harnessing the Power of Big Data and Deep Learning.

Environmental science & technology [Epub ahead of print].

Harmful algal blooms (HABs) pose a significant ecological threat and economic detriment to freshwater environments. In order to develop an intelligent early warning system for HABs, big data and deep learning models were harnessed in this study. Data collection was achieved utilizing the vertical aquatic monitoring system (VAMS). Subsequently, the analysis and stratification of the vertical aquatic layer were conducted employing the "DeepDPM-Spectral Clustering" method. This approach drastically reduced the number of predictive models and enhanced the adaptability of the system. The Bloomformer-2 model was developed to conduct both single-step and multistep predictions of Chl-a, integrating the " Alert Level Framework" issued by the World Health Organization to accomplish early warning for HABs. The case study conducted in Taihu Lake revealed that during the winter of 2018, the water column could be partitioned into four clusters (Groups W1-W4), while in the summer of 2019, the water column could be partitioned into five clusters (Groups S1-S5). Moreover, in a subsequent predictive task, Bloomformer-2 exhibited superiority in performance across all clusters for both the winter of 2018 and the summer of 2019 (MAE: 0.175-0.394, MSE: 0.042-0.305, and MAPE: 0.228-2.279 for single-step prediction; MAE: 0.184-0.505, MSE: 0.101-0.378, and MAPE: 0.243-4.011 for multistep prediction). The prediction for the 3 days indicated that Group W1 was in a Level I alert state at all times. Conversely, Group S1 was mainly under an Level I alert, with seven specific time points escalating to a Level II alert. Furthermore, the end-to-end architecture of this system, coupled with the automation of its various processes, minimized human intervention, endowing it with intelligent characteristics. This research highlights the transformative potential of integrating big data and artificial intelligence in environmental management and emphasizes the importance of model interpretability in machine learning applications.

RevDate: 2024-03-06
CmpDate: 2024-03-06

Han K, Li J, Yang D, et al (2024)

Detecting horizontal gene transfer with metagenomics co-barcoding sequencing.

Microbiology spectrum, 12(3):e0360223.

Horizontal gene transfer (HGT) is the process through which genetic information is transferred between different genomes and that played a crucial role in bacterial evolution. HGT can enable bacteria to rapidly acquire antibiotic resistance and bacteria that have acquired resistance is spreading within the microbiome. Conventional methods of characterizing HGT patterns include short-read metagenomic sequencing (short-reads mNGS), long-read sequencing, and single-cell sequencing. These approaches present several limitations, such as short-read fragments, high amounts of input DNA, and sequencing costs, respectively. Here, we attempt to circumvent present limitations to detect HGT by developing a metagenomics co-barcode sequencing workflow (MECOS) and applying it to the human and mouse gut microbiomes. In addition to that, we have over 10-fold increased contig length compared to short-reads mNGS; we also obtained exceeding 30 million paired reads with co-barcode information. Applying the novel bioinformatic pipeline, we integrated this co-barcoding information and the context information from long reads, and observed over 50-fold HGT events after we corrected the potential wrong HGT events. Specifically, we detected approximately 3,000 HGT blocks in individual samples, encompassing ~6,000 genes and ~100 taxonomic groups, including loci conferring tetracycline resistance through ribosomal protection. MECOS provides a valuable tool for investigating HGT and advance our understanding on the evolution of natural microbial communities within hosts.IMPORTANCEIn this study, to better identify horizontal gene transfer (HGT) in individual samples, we introduce a new co-barcoding sequencing system called metagenomics co-barcoding sequencing (MECOS), which has three significant improvements: (i) long DNA fragment extraction, (ii) a special transposome insertion, (iii) hybridization of DNA to barcode beads, and (4) an integrated bioinformatic pipeline. Using our approach, we have over 10-fold increased contig length compared to short-reads mNGS, and observed over 50-fold HGT events after we corrected the potential wrong HGT events. Our results indicate the presence of approximately 3,000 HGT blocks, involving roughly 6,000 genes and 100 taxonomic groups in individual samples. Notably, these HGT events are predominantly enriched in genes that confer tetracycline resistance via ribosomal protection. MECOS is a useful tool for investigating HGT and the evolution of natural microbial communities within hosts, thereby advancing our understanding of microbial ecology and evolution.

RevDate: 2024-03-05
CmpDate: 2024-03-05

Specker F, Paz A, Crowther TW, et al (2024)

Treemendous: an R package for integrating taxonomic information across backbones.

PeerJ, 12:e16896.

Standardizing and translating species names from different databases is key to the successful integration of data sources in biodiversity research. There are numerous taxonomic name-resolution applications that implement increasingly powerful name-cleaning and matching approaches, allowing the user to resolve species relative to multiple backbones simultaneously. Yet there remains no principled approach for combining information across these underlying taxonomic backbones, complicating efforts to combine and merge species lists with inconsistent and conflicting taxonomic information. Here, we present Treemendous, an open-source software package for the R programming environment that integrates taxonomic relationships across four publicly available backbones to improve the name resolution of tree species. By mapping relationships across the backbones, this package can be used to resolve datasets with conflicting and inconsistent taxonomic origins, while ensuring the resulting species are accepted and consistent with a single reference backbone. The user can chain together different functionalities ranging from simple matching to a single backbone, to graph-based iterative matching using synonym-accepted relations across all backbones in the database. In addition, the package allows users to 'translate' one tree species list into another, streamlining the assimilation of new data into preexisting datasets or models. The package provides a flexible workflow depending on the use case, and can either be used as a stand-alone name-resolution package or in conjunction with existing packages as a final step in the name-resolution pipeline. The Treemendous package is fast and easy to use, allowing users to quickly merge different data sources by standardizing their species names according to the regularly updated database. By combining taxonomic information across multiple backbones, the package increases matching rates and minimizes data loss, allowing for more efficient translation of tree species datasets to aid research into forest biodiversity and tree ecology.

RevDate: 2024-03-05

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

The genome sequence of the Diamond-back Marble, Eudemis profundana (Denis & Schiffermüller, 1775).

Wellcome open research, 8:184.

We present a genome assembly from an individual male Eudemis profundana (the Diamond-back Marble; Arthropoda; Insecta; Lepidoptera; Tortricidae). The genome sequence is 691.3 megabases in span. Most of the assembly is scaffolded into 28 chromosomal pseudomolecules, including the Z sex chromosome. The mitochondrial genome has also been assembled and is 16.5 kilobases in length.

RevDate: 2024-03-05
CmpDate: 2024-03-05

Thiébaut A, Altenhoff AM, Campli G, et al (2023)

DrosOMA: the Drosophila Orthologous Matrix browser.

F1000Research, 12:936.

BACKGROUND: Comparative genomic analyses to delineate gene evolutionary histories inform the understanding of organismal biology by characterising gene and gene family origins, trajectories, and dynamics, as well as enabling the tracing of speciation, duplication, and loss events, and facilitating the transfer of gene functional information across species. Genomic data are available for an increasing number of species from the genus Drosophila, however, a dedicated resource exploiting these data to provide the research community with browsable results from genus-wide orthology delineation has been lacking.

METHODS: Using the OMA Orthologous Matrix orthology inference approach and browser deployment framework, we catalogued orthologues across a selected set of Drosophila species with high-quality annotated genomes. We developed and deployed a dedicated instance of the OMA browser to facilitate intuitive exploration, visualisation, and downloading of the genus-wide orthology delineation results.

RESULTS: DrosOMA - the Drosophila Orthologous Matrix browser, accessible from https://drosoma.dcsr.unil.ch/ - presents the results of orthology delineation for 36 drosophilids from across the genus and four outgroup dipterans. It enables querying and browsing of the orthology data through a feature-rich web interface, with gene-view, orthologous group-view, and genome-view pages, including comprehensive gene name and identifier cross-references together with available functional annotations and protein domain architectures, as well as tools to visualise local and global synteny conservation.

CONCLUSIONS: The DrosOMA browser demonstrates the deployability of the OMA browser framework for building user-friendly orthology databases with dense sampling of a selected taxonomic group. It provides the Drosophila research community with a tailored resource of browsable results from genus-wide orthology delineation.

RevDate: 2024-03-04

Boyes D, Lees DC, Hammond J, et al (2023)

The genome sequence of the Ashy Button, Acleris sparsana (Denis & Schiffermüller, 1775).

Wellcome open research, 8:241.

We present a genome assembly from an individual male Acleris sparsana (the Ashy Button; Arthropoda; Insecta; Lepidoptera; Tortricidae). The genome sequence is 589.5 megabases in span. Most of the assembly is scaffolded into 30 chromosomal pseudomolecules, including the Z sex chromosome. The mitochondrial genome has also been assembled and is 16.4 kilobases in length. Gene annotation of this assembly on Ensembl identified 22,123 protein coding genes.

RevDate: 2024-03-04

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

The genome sequence of the Minor Shoulder-knot, Brachylomia viminalis (Fabricius, 1777).

Wellcome open research, 8:245.

We present a genome assembly from an individual male Brachylomia viminalis (the Minor Shoulder-knot; Arthropoda; Insecta; Lepidoptera; Noctuidae). The genome sequence is 782.2 megabases in span. Most of the assembly is scaffolded into 31 chromosomal pseudomolecules, including the Z sex chromosome. The mitochondrial genome has also been assembled and is 16.15 kilobases in length. Gene annotation of this assembly on Ensembl identified 20,191 protein coding genes.

RevDate: 2024-03-04

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

The genome sequence of the Orange Footman, Eilema sororcula (Hufnagel, 1766).

Wellcome open research, 8:282.

We present a genome assembly from an individual male Eilema sororcula (the Orange Footman; Arthropoda; Insecta; Lepidoptera; Erebidae). The genome sequence is 729.4 megabases in span. Most of the assembly is scaffolded into 30 chromosomal pseudomolecules, including the Z sex chromosome. The mitochondrial genome has also been assembled and is 15.46 kilobases in length. Gene annotation of this assembly on Ensembl identified 21,093 protein coding genes.

RevDate: 2024-03-04

Mallinson DC, Elwert F, DB Ehrenthal (2024)

Spillover effects of gestational age on sibling's literacy.

Early child development and care, 194(2):244-259.

Adverse health events within families can harm children's development, including their early literacy. Using data from a longitudinal Wisconsin birth cohort, we estimated the spillover effect of younger siblings' gestational ages on older siblings' kindergarten-level literacy. We sampled 20,014 sibling pairs born during 2007-2010 who took Phonological Awareness Literacy Screening-Kindergarten tests during 2012-2016. Exposures were gestational age (completed weeks), preterm birth (gestational age <37 weeks), and very preterm birth (gestational age <32 weeks). We used gain-score regression-a fixed effects strategy-to estimate spillover effect. A one-week increase in younger siblings' gestational age improved the older siblings' test score by 0.011 SD (95% confidence interval: 0.001, 0.021 SD). The estimated spillover effect was larger among siblings whose mothers reported having a high school diploma/equivalent only (0.024 SD; 95% CI: 0.004, 0.044 SD). The finding underscores the networked effects of one individual's early-life health shocks on their family members.

RevDate: 2024-03-03

Freitas IBF, Duarte-Neto PJ, Sorigotto LR, et al (2024)

Effects of pasture intensification and sugarcane cultivation on non-target species: A realistic evaluation in pesticide-contaminated mesocosms.

The Science of the total environment pii:S0048-9697(24)01566-3 [Epub ahead of print].

Conventional soil management in agricultural areas may expose non-target organisms living nearby to several types of contaminants. In this study, the effects of soil management in extensive pasture (EP), intensive pasture (IP), and sugarcane crops (C) were evaluated in a realistic-field-scale study. Thirteen aquatic mesocosms embedded in EP, IP, and C treatments were monitored over 392 days. The recommended management for each of the areas was simulated, such as tillage, fertilizer, pesticides (i.e. 2,4-D, fipronil) and vinasse application, and cattle pasture. To access the potential toxic effects that the different steps of soil management in these areas may cause, the cladoceran Ceriophania silvestrii was used as aquatic bioindicator, the dicot Eruca sativa as phytotoxicity bioindicator in water, and the dipteran Chironomus sancticaroli as sediment bioindicator. Generalized linear mixed models were used to identify differences between the treatments. Low concentrations of 2,4-D (<97 μg L[-1]) and fipronil (<0.21 μg L[-1]) in water were able to alter fecundity, female survival, and the intrinsic rate of population increase of C. silvestrii in IP and C treatments. Similarly, the dicot E. sativa had germination, shoot and root growth affected mainly by 2,4-D concentrations in the water. For C. sancticarolli, larval development was affected by the presence of fipronil (<402.6 ng g[-1]). The acidic pH (below 5) reduced the fecundity and female survival of C. silvestrii and affected the germination and growth of E. sativa. Fecundity and female survival of C. silvestrii decrease in the presence of phosphorus-containing elements. The outcomes of this study may improve our understanding of the consequences of exposure of freshwater biota to complex stressors in an environment that is rapidly and constantly changing.

RevDate: 2024-03-04
CmpDate: 2024-03-04

Rillig MC, Mansour I, Hempel S, et al (2024)

How widespread use of generative AI for images and video can affect the environment and the science of ecology.

Ecology letters, 27(3):e14397.

Generative artificial intelligence (AI) models will have broad impacts on society including the scientific enterprise; ecology and environmental science will be no exception. Here, we discuss the potential opportunities and risks of advanced generative AI for visual material (images and video) for the science of ecology and the environment itself. There are clearly opportunities for positive impacts, related to improved communication, for example; we also see possibilities for ecological research to benefit from generative AI (e.g., image gap filling, biodiversity surveys, and improved citizen science). However, there are also risks, threatening to undermine the credibility of our science, mostly related to actions of bad actors, for example in terms of spreading fake information or committing fraud. Risks need to be mitigated at the level of government regulatory measures, but we also highlight what can be done right now, including discussing issues with the next generation of ecologists and transforming towards radically open science workflows.


RJR Experience and Expertise


Robbins holds BS, MS, and PhD degrees in the life sciences. He served as a tenured faculty member in the Zoology and Biological Science departments at Michigan State University. He is currently exploring the intersection between genomics, microbial ecology, and biodiversity — an area that promises to transform our understanding of the biosphere.


Robbins has extensive experience in college-level education: At MSU he taught introductory biology, genetics, and population genetics. At JHU, he was an instructor for a special course on biological database design. At FHCRC, he team-taught a graduate-level course on the history of genetics. At Bellevue College he taught medical informatics.


Robbins has been involved in science administration at both the federal and the institutional levels. At NSF he was a program officer for database activities in the life sciences, at DOE he was a program officer for information infrastructure in the human genome project. At the Fred Hutchinson Cancer Research Center, he served as a vice president for fifteen years.


Robbins has been involved with information technology since writing his first Fortran program as a college student. At NSF he was the first program officer for database activities in the life sciences. At JHU he held an appointment in the CS department and served as director of the informatics core for the Genome Data Base. At the FHCRC he was VP for Information Technology.


While still at Michigan State, Robbins started his first publishing venture, founding a small company that addressed the short-run publishing needs of instructors in very large undergraduate classes. For more than 20 years, Robbins has been operating The Electronic Scholarly Publishing Project, a web site dedicated to the digital publishing of critical works in science, especially classical genetics.


Robbins is well-known for his speaking abilities and is often called upon to provide keynote or plenary addresses at international meetings. For example, in July, 2012, he gave a well-received keynote address at the Global Biodiversity Informatics Congress, sponsored by GBIF and held in Copenhagen. The slides from that talk can be seen HERE.


Robbins is a skilled meeting facilitator. He prefers a participatory approach, with part of the meeting involving dynamic breakout groups, created by the participants in real time: (1) individuals propose breakout groups; (2) everyone signs up for one (or more) groups; (3) the groups with the most interested parties then meet, with reports from each group presented and discussed in a subsequent plenary session.


Robbins has been engaged with photography and design since the 1960s, when he worked for a professional photography laboratory. He now prefers digital photography and tools for their precision and reproducibility. He designed his first web site more than 20 years ago and he personally designed and implemented this web site. He engages in graphic design as a hobby.

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This book introduces readers to ecological informatics as an emerging discipline that takes into account the data-intensive nature of ecology, the valuable information to be found in ecological data, and the need to communicate results and inform decisions, including those related to research, conservation and resource management. At its core, ecological informatics combines developments in information technology and ecological theory with applications that facilitate ecological research and the dissemination of results to scientists and the public. Its conceptual framework links ecological entities (genomes, organisms, populations, communities, ecosystems, landscapes) with data management, analysis and synthesis, and communicates new findings to inform decisions by following the course of a loop. In comparison to the 2nd edition published in 2006, the 3rd edition of Ecological Informatics reflects the significant advances in data management, analysis and synthesis that have been made over the past 10 years, including new remote and in situ sensing techniques, the emergence of ecological and environmental observatories, novel evolutionary computations for knowledge discovery and forecasting, and new approaches to communicating results and informing decisions.

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Collection of publications by R J Robbins

Reprints and preprints of publications, slide presentations, instructional materials, and data compilations written or prepared by Robert Robbins. Most papers deal with computational biology, genome informatics, using information technology to support biomedical research, and related matters.

Research Gate page for R J Robbins

ResearchGate is a social networking site for scientists and researchers to share papers, ask and answer questions, and find collaborators. According to a study by Nature and an article in Times Higher Education , it is the largest academic social network in terms of active users.

Curriculum Vitae for R J Robbins

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Curriculum Vitae for R J Robbins

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