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Bibliography on: Ecological Informatics

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ESP: PubMed Auto Bibliography 18 May 2024 at 01:47 Created: 

Ecological Informatics

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

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

Citations The Papers (from PubMed®)

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RevDate: 2024-05-17
CmpDate: 2024-05-17

Oszoli I, I Zachar (2024)

Group-selection via aggregative propagule-formation enables cooperative multicellularity in an individual based, spatial model.

PLoS computational biology, 20(5):e1012107 pii:PCOMPBIOL-D-23-01729.

The emergence of multicellularity is one of the major transitions in evolution that happened multiple times independently. During aggregative multicellularity, genetically potentially unrelated lineages cooperate to form transient multicellular groups. Unlike clonal multicellularity, aggregative multicellular organisms do not rely on kin selection instead other mechanisms maintain cooperation against cheater phenotypes that benefit from cooperators but do not contribute to groups. Spatiality with limited diffusion can facilitate group selection, as interactions among individuals are restricted to local neighbourhoods only. Selection for larger size (e.g. avoiding predation) may facilitate the emergence of aggregation, though it is unknown, whether and how much role such selection played during the evolution of aggregative multicellularity. We have investigated the effect of spatiality and the necessity of predation on the stability of aggregative multicellularity via individual-based modelling on the ecological timescale. We have examined whether aggregation facilitates the survival of cooperators in a temporally heterogeneous environment against cheaters, where only a subset of the population is allowed to periodically colonize a new, resource-rich habitat. Cooperators constitutively produce adhesive molecules to promote aggregation and propagule-formation while cheaters spare this expense to grow faster but cannot aggregate on their own, hence depending on cooperators for long-term survival. We have compared different population-level reproduction modes with and without individual selection (predation) to evaluate the different hypotheses. In a temporally homogeneous environment without propagule-based colonization, cheaters always win. Predation can benefit cooperators, but it is not enough to maintain the necessary cooperator amount in successive dispersals, either randomly or by fragmentation. Aggregation-based propagation however can ensure the adequate ratio of cooperators-to-cheaters in the propagule and is sufficient to do so even without predation. Spatiality combined with temporal heterogeneity helps cooperators via group selection, thus facilitating aggregative multicellularity. External stress selecting for larger size (e.g. predation) may facilitate aggregation, however, according to our results, it is neither necessary nor sufficient for aggregative multicellularity to be maintained when there is effective group-selection.

RevDate: 2024-05-17
CmpDate: 2024-05-17

Crauwels C, Heidig SL, Díaz A, et al (2024)

Large-scale structure-informed multiple sequence alignment of proteins with SIMSApiper.

Bioinformatics (Oxford, England), 40(5):.

SUMMARY: SIMSApiper is a Nextflow pipeline that creates reliable, structure-informed MSAs of thousands of protein sequences faster than standard structure-based alignment methods. Structural information can be provided by the user or collected by the pipeline from online resources. Parallelization with sequence identity-based subsets can be activated to significantly speed up the alignment process. Finally, the number of gaps in the final alignment can be reduced by leveraging the position of conserved secondary structure elements.

The pipeline is implemented using Nextflow, Python3, and Bash. It is publicly available on github.com/Bio2Byte/simsapiper.

RevDate: 2024-05-16

Schaupp CM, Byrne G, Chan M, et al (2024)

An automated computational data pipeline to rapidly acquire, score, and rank toxicological data for ecological hazard assessment.

Integrated environmental assessment and management [Epub ahead of print].

Biological Evaluations support Endangered Species Act (ESA) consultation with the US Fish and Wildlife Service and National Marine Fisheries Service by federal action agencies, such as the USEPA, regarding impacts of federal activities on threatened or endangered species. However, they are often time-consuming and challenging to conduct. The identification of pollutant benchmarks or guidance to protect taxa for states and tribes when USEPA has not yet developed criteria recommendations is also of importance to ensure a streamlined approach to Clean Water Act program implementation. Due to substantial workloads, tight regulatory timelines, and the often-protracted length of ESA consultations, there is a need to streamline the development of biological evaluation toxicity assessments for determining the impact of chemical pollutants on ESA-listed species. Moreover, there is limited availability of species-specific toxicity data for many contaminants, further complicating the consultation process. New approach methodologies are being increasingly used in toxicology and chemical safety assessment to rapidly and cost-effectively provide data that can fill gaps in hazard and/or exposure characterization. Here, we present the development of an automated computational pipeline-RASRTox (Rapidly Acquire, Score, and Rank Toxicological data)-to rapidly extract and categorize ecological toxicity benchmark values from curated data sources (ECOTOX, ToxCast) and well-established quantitative structure-activity relationships (TEST, ECOSAR). As a proof of concept, points-of-departure (PODs) generated in RASRTox for 13 chemicals were compared against benchmark values derived using traditional methods-toxicity reference values (TRVs) and water quality criteria (WQC). The RASRTox PODs were generally within an order of magnitude of corresponding TRVs, though less concordant compared with WQC. The greatest utility of RASRTox, however, lies in its ability to quickly and systematically identify critical studies that may serve as a basis for screening value derivation by toxicologists as part of an ecological hazard assessment. As such, the strategy described in this case study can potentially be adapted for other risk assessment contexts and stakeholder needs. Integr Environ Assess Manag 2024;00:1-15. © 2024 Society of Environmental Toxicology & Chemistry (SETAC). This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

RevDate: 2024-05-15

Acheampong DA, Jenjaroenpun P, Wongsurawat T, et al (2024)

CAIM: Coverage-based Analysis for Identification of Microbiome.

bioRxiv : the preprint server for biology.

Accurate taxonomic profiling of microbial taxa in a metagenomic sample is vital to gain insights into microbial ecology. Recent advancements in sequencing technologies have contributed tremendously toward understanding these microbes at species resolution through a whole shotgun metagenomic (WMS) approach. In this study, we developed a new bioinformatics tool, CAIM, for accurate taxonomic classification and quantification within both long- and short-read metagenomic samples using an alignment-based method. CAIM depends on two different containment techniques to identify species in metagenomic samples using their genome coverage information to filter out false positives rather than the traditional approach of relative abundance. In addition, we propose a nucleotide-count based abundance estimation, which yield lesser root mean square error than the traditional read-count approach. We evaluated the performance of CAIM on 28 metagenomic mock communities and 2 synthetic datasets by comparing it with other top-performing tools. CAIM maintained a consitently good performance across datasets in identifying microbial taxa and in estimating relative abundances than other tools. CAIM was then applied to a real dataset sequenced on both Nanopore (with and without amplification) and Illumina sequencing platforms and found high similality of taxonomic profiles between the sequencing platforms. Lastly, CAIM was applied to fecal shotgun metagenomic datasets of 232 colorectal cancer patients and 229 controls obtained from 4 different countries and primary 44 liver cancer patients and 76 controls. The predictive performance of models using the genome-coverage cutoff was better than those using the relative-abundance cutoffs in discriminating colorectal cancer and primary liver cancer patients from healthy controls with a highly confident species markers.

RevDate: 2024-05-15
CmpDate: 2024-05-15

Swain A, Woodhouse A, Fagan WF, et al (2024)

Biogeographic response of marine plankton to Cenozoic environmental changes.

Nature, 629(8012):616-623.

In palaeontological studies, groups with consistent ecological and morphological traits across a clade's history (functional groups)[1] afford different perspectives on biodiversity dynamics than do species and genera[2,3], which are evolutionarily ephemeral. Here we analyse Triton, a global dataset of Cenozoic macroperforate planktonic foraminiferal occurrences[4], to contextualize changes in latitudinal equitability gradients[1], functional diversity, palaeolatitudinal specialization and community equitability. We identify: global morphological communities becoming less specialized preceding the richness increase after the Cretaceous-Palaeogene extinction; ecological specialization during the Early Eocene Climatic Optimum, suggesting inhibitive equatorial temperatures during the peak of the Cenozoic hothouse; increased specialization due to circulation changes across the Eocene-Oligocene transition, preceding the loss of morphological diversity; changes in morphological specialization and richness about 19 million years ago, coeval with pelagic shark extinctions[5]; delayed onset of changing functional group richness and specialization between hemispheres during the mid-Miocene plankton diversification. The detailed nature of the Triton dataset permits a unique spatiotemporal view of Cenozoic pelagic macroevolution, in which global biogeographic responses of functional communities and richness are decoupled during Cenozoic climate events. The global response of functional groups to similar abiotic selection pressures may depend on the background climatic state (greenhouse or icehouse) to which a group is adapted.

RevDate: 2024-05-14
CmpDate: 2024-05-14

Tian C, Li J, Wu Y, et al (2024)

An integrative database and its application for plant synthetic biology research.

Plant communications, 5(5):100827.

Plant synthetic biology research requires diverse bioparts that facilitate the redesign and construction of new-to-nature biological devices or systems in plants. Limited by few well-characterized bioparts for plant chassis, the development of plant synthetic biology lags behind that of its microbial counterpart. Here, we constructed a web-based Plant Synthetic BioDatabase (PSBD), which currently categorizes 1677 catalytic bioparts and 384 regulatory elements and provides information on 309 species and 850 chemicals. Online bioinformatics tools including local BLAST, chem similarity, phylogenetic analysis, and visual strength are provided to assist with the rational design of genetic circuits for manipulation of gene expression in planta. We demonstrated the utility of the PSBD by functionally characterizing taxadiene synthase 2 and its quantitative regulation in tobacco leaves. More powerful synthetic devices were then assembled to amplify the transcriptional signals, enabling enhanced expression of flavivirus non-structure 1 proteins in plants. The PSBD is expected to be an integrative and user-centered platform that provides a one-stop service for diverse applications in plant synthetic biology research.

RevDate: 2024-05-14

Klatt S, Otte FW, Beavan A, et al (2024)

How did you perform? Investigating football players' perception of self-regulated passing performances under auditory noise environments.

Frontiers in psychology, 15:1390487.

INTRODUCTION: This paper deals with the question on how sport performances may be influenced by internal, emotional processes, which stem from outside feedback.

METHODS: In terms of methods, players' subjective performance ratings for four experimental auditory cue conditions were examined; these included both 'positive' and 'negative' stadium noise, 'no (auditory) conditions,' and a control/'baseline' condition. This resulted in a qualitative-analytic data set that was obtained succeeding each auditory cue condition using a unique football training machine (i.e., known as 'Footbonaut'). Without having received any coaching/performance feedback, players were asked to rate and individually comment on their perceived performance ratings for each experimental auditory condition.

RESULTS: Findings indicate stronger and more significant correlations between auditory conditions and subjective ratings compared to the non-auditory condition and its subjective rating. Furthermore, data provides initial insight into players' emotional experiences during each of the practice conditions.

DISCUSSION: These noteworthy findings on players' abilities to accurately judge their performances based on selfmonitoring and intrinsic feedback are discussed from an Ecological Dynamics perspective, linked to a Nonlinear Pedagogy for coaching. Here, representative and affective learning designs for skill learning and performance preparation are presented. Finally, a hypothetical catalyst effect of auditory stadium noise on subjective performance rating is proposed.

RevDate: 2024-05-14
CmpDate: 2024-05-14

Sõukand R (2024)

Dark local knowledge: the yet-to-be scientifically discovered and locally acknowledged aspects of local knowledge systems.

Journal of ethnobiology and ethnomedicine, 20(1):50.

This essay brings forward the idea that there is more than meets the eye in local knowledge systems than what science can show us now. To comprehend this, we need to make a conceptual jump and look for the "dark matter" (the notion borrowed from astronomy that refers to a hypothetical form of matter that does not interact with light or electromagnetic fields) that can potentially sustain local knowledge. Considering that it is a complex of knowledge, practices, and beliefs contained in TEK, knowledge in LEK does not correspond to the notion of knowledge in science. Therefore, in order to map LEK-science interactions, we will refer to the concept of peoples' knowledge of LEK as acknowledgement and the scientific recognition and awareness of information, facts, and principles as knowledge. Applying this to a Johari Window, we can observe four categories of LEK in a known-unknown/acknowledged-unacknowledged matrix. We can refer to unknown and unacknowledged as dark local knowledge. Indeed, local knowledge systems contain many aspects that modern science cannot yet explain, as a major part of its components are not even considered in scholarly research. Dark local knowledge can potentially provide us with the invaluable touch of experience of countless generations, opening different ways of seeing reality.

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

Lee KS, Landry Z, Athar A, et al (2024)

MicrobioRaman: an open-access web repository for microbiological Raman spectroscopy data.

Nature microbiology, 9(5):1152-1156.

RevDate: 2024-05-10

Yu H, Yin D, Yang B, et al (2024)

Challenges for sustainable development goal of land degradation neutrality in drylands: Evidence from China's Northern Slope of the Tianshian Mountains, China.

The Science of the total environment pii:S0048-9697(24)03241-8 [Epub ahead of print].

The SDG 15.3.1 target of Land Degradation Neutrality (LDN) only has 15 years from conception (in 2015) to realization (in 2030). Therefore, investigating the effectiveness and challenges of LDN has become a priority, especially in drylands, where fragile ecosystems intersect with multiple disturbances. In this study, solutions are proposed and validated based on the challenges of LDN. We chose the Northern Slope of the Tianshan Mountains as a case study and set baselines in 2005 and 2010. The region and degree of land change (including degraded, stable, and improved) were depicted at the pixel scale (100 × 100 m), and LDN realization was assessed at the regional scale (including administrative districts and 5000 × 5000 m grids). The results showed a significant disparity between the two baselines. The number of areas that realized the LDN target was rare, regardless of the scale of the administrative districts or grids. Chord plots, Spearman's correlation, and curve estimation were employed to reveal the relationship between LDN and seven natural or socioeconomic factors. We found that substantial degradation was closely related to the expansion of unused, urban, and mining land and reduction in water, glaciers, and forests. Further evidence suggests that agricultural development both positively and negatively affects LDN, whereas urbanization and mining activities are undesirable for LDN. Notably, the adverse effects of glacier melting require additional attention. Therefore, we consider the easy-to-achieve and hard-to-achieve baselines as the mandatory and desirable targets of LDN, respectively, and focus further efforts in three aspects: preventing agricultural exploitation from occupying ecological resources, defining reasonable zones for urbanization and mining, and reducing greenhouse gas emissions to mitigate warming. Overall, this study is expected to be a beneficial addition to existing LDN theoretical systems and serve as a case validation of the challenges of LDN in drylands.

RevDate: 2024-05-09
CmpDate: 2024-05-09

Bhandari N, Bald L, Wraase L, et al (2024)

Multispectral analysis-ready satellite data for three East African mountain ecosystems.

Scientific data, 11(1):473.

The East African mountain ecosystems are facing increasing threats due to global change, putting their unique socio-ecological systems at risk. To monitor and understand these changes, researchers and stakeholders require accessible analysis-ready remote sensing data. Although satellite data is available for many applications, it often lacks accurate geometric orientation and has extensive cloud cover. This can generate misleading results and make it unreliable for time-series analysis. Therefore, it needs comprehensive processing before usage, which encompasses multi-step operations, requiring large computational and storage capacities, as well as expert knowledge. Here, we provide high-quality, atmospherically corrected, and cloud-free analysis-ready Sentinel-2 imagery for the Bale Mountains (Ethiopia), Mounts Kilimanjaro and Meru (Tanzania) ecosystems in East Africa. Our dataset ranges from 2017 to 2021 and is provided as monthly and annual aggregated products together with 24 spectral indices. Our dataset enables researchers and stakeholders to conduct immediate and impactful analyses. These applications can include vegetation mapping, wildlife habitat assessment, land cover change detection, ecosystem monitoring, and climate change research.

RevDate: 2024-05-09

Freedman AH, TB Sackton (2024)

Rethinking eco-evo studies of gene expression for non-model organisms in the genomic era.

Molecular ecology [Epub ahead of print].

Recent advances in genomic technology, including the rapid development of long-read sequencing technology and single-cell RNA-sequencing methods, are poised to significantly expand the kinds of studies that are feasible in ecological genomics. In this perspective, we review these new technologies and discuss their potential impact on gene expression studies in non-model organisms. Although traditional RNA-sequencing methods have been an extraordinarily powerful tool to apply functional genomics in an ecological context, bulk RNA-seq approaches often rely on de novo transcriptome assembly, and cannot capture expression changes in rare cell populations or distinguish shifts in cell type abundance. Advancements in genome assembly technology, particularly long-read sequencing, and improvements in the scalability of single-cell RNA-sequencing (scRNA-seq) offer unprecedented resolution in understanding cellular heterogeneity and gene regulation. We discuss the potential of these technologies to enable disentangling differential gene regulation from cell type composition differences and uncovering subtle expression patterns masked by bulk RNA-seq. The integration of these approaches provides a more nuanced understanding of the ecological and evolutionary dynamics of gene expression, paving the way for refined models and deeper insights into the generation of biodiversity.

RevDate: 2024-05-10

Ross KE, Bastian FB, Buys M, et al (2024)

Perspectives on tracking data reuse across biodata resources.

Bioinformatics advances, 4(1):vbae057.

MOTIVATION: Data reuse is a common and vital practice in molecular biology and enables the knowledge gathered over recent decades to drive discovery and innovation in the life sciences. Much of this knowledge has been collated into molecular biology databases, such as UniProtKB, and these resources derive enormous value from sharing data among themselves. However, quantifying and documenting this kind of data reuse remains a challenge.

RESULTS: The article reports on a one-day virtual workshop hosted by the UniProt Consortium in March 2023, attended by representatives from biodata resources, experts in data management, and NIH program managers. Workshop discussions focused on strategies for tracking data reuse, best practices for reusing data, and the challenges associated with data reuse and tracking. Surveys and discussions showed that data reuse is widespread, but critical information for reproducibility is sometimes lacking. Challenges include costs of tracking data reuse, tensions between tracking data and open sharing, restrictive licenses, and difficulties in tracking commercial data use. Recommendations that emerged from the discussion include: development of standardized formats for documenting data reuse, education about the obstacles posed by restrictive licenses, and continued recognition by funding agencies that data management is a critical activity that requires dedicated resources.

Summaries of survey results are available at: https://docs.google.com/forms/d/1j-VU2ifEKb9C-sW6l3ATB79dgHdRk5v_lESv2hawnso/viewanalytics (survey of data providers) and https://docs.google.com/forms/d/18WbJFutUd7qiZoEzbOytFYXSfWFT61hVce0vjvIwIjk/viewanalytics (survey of users).

RevDate: 2024-05-08

Leroux A, Crainiceanu C, Zeger S, et al (2024)

Statistical modeling of acute and chronic pain patient-reported outcomes obtained from ecological momentary assessment.

Pain pii:00006396-990000000-00594 [Epub ahead of print].

Ecological momentary assessment (EMA) allows for the collection of participant-reported outcomes (PROs), including pain, in the normal environment at high resolution and with reduced recall bias. Ecological momentary assessment is an important component in studies of pain, providing detailed information about the frequency, intensity, and degree of interference of individuals' pain. However, there is no universally agreed on standard for summarizing pain measures from repeated PRO assessment using EMA into a single, clinically meaningful measure of pain. Here, we quantify the accuracy of summaries (eg, mean and median) of pain outcomes obtained from EMA and the effect of thresholding these summaries to obtain binary clinical end points of chronic pain status (yes/no). Data applications and simulations indicate that binarizing empirical estimators (eg, sample mean, random intercept linear mixed model) can perform well. However, linear mixed-effect modeling estimators that account for the nonlinear relationship between average and variability of pain scores perform better for quantifying the true average pain and reduce estimation error by up to 50%, with larger improvements for individuals with more variable pain scores. We also show that binarizing pain scores (eg, <3 and ≥3) can lead to a substantial loss of statistical power (40%-50%). Thus, when examining pain outcomes using EMA, the use of linear mixed models using the entire scale (0-10) is superior to splitting the outcomes into 2 groups (<3 and ≥3) providing greater statistical power and sensitivity.

RevDate: 2024-05-08

Zhou Q, Song Y, Zhang Y, et al (2024)

Land use transition and its effect on ecosystem service value with introducing "three wastes" factor in the industrial county, China.

Environmental science and pollution research international [Epub ahead of print].

Land use transition and its impact on ecosystem service value (ESV) are the foundation for optimizing the layout of territorial space and ecological civilization construction. With the acceleration of industrialization and urbanization, the area of construction land expands in China. To accurately estimate the ESV in industrial counties, the impact of construction land on the ecological environment should be fully considered. This paper took Gangcheng District, Jinan City, a steel base in the Shandong Province of China as an example, then the value coefficients of "three wastes" factors (waste gas, wastewater, and waste) were introduced, and an improved calculation method of ESV was put forward for industrial counties in combination with remote sensing and land use data. Finally, the land use transition and its ESV effect in typical industrial counties were analyzed using geo-informatic Tupu and grid method. The results showed that the most important land use transitions were from grassland and forestland to cultivated land, from cultivated land and forestland to construction land in 1990-2010, and from cultivated land transformed to forestland in 2010-2021. The types of land use transition were mainly repetitive and continuous. The ESV first decreased and then increased, with a slight overall decline for more than 30 years, showing a spatial distribution characteristic of "low in the south-central and high around." Land use transition had the impact on ESV with the negative contribution rate of 68.28% in 1990-2000 and 73.16% in 2000-2010, mainly caused by the transition from forestland and grassland to cultivated land and construction land, and the positive contribution rate of 81.72% in 2010-2021, mainly caused by the transition from cultivated land to forestland. Compared with the ESV calculation method without introducing the "three wastes" factor and Xie Gaodi's method, the improved method in this paper considered the inevitable impact of construction land on ESV in industrial counties and made the ESV calculated more accurate according to the regional nature. This paper cannot only enrich the theories and technical methods of land use transition and its effects, and provide a case reference for similar industrial counties, but also provide data and decision-making support for the spatial layout and ecological protection in the study area.

RevDate: 2024-05-10

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

The genome sequence of the Ruddy Flat-body, Agonopterix subpropinquella (Stainton, 1849).

Wellcome open research, 8:487.

We present a genome assembly from an individual male Agonopterix subpropinquella (the Ruddy Flat-body; Arthropoda; Insecta; Lepidoptera; Depressariidae). The genome sequence is 667.9 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. Gene annotation of this assembly on Ensembl identified 18,796 protein coding genes.

RevDate: 2024-05-10
CmpDate: 2024-05-08

Zhang L, Zhang Y, Liu Y, et al (2024)

Multi-omics analysis revealed that the protein kinase MoKin1 affected the cellular response to endoplasmic reticulum stress in the rice blast fungus, Magnaporthe oryzae.

BMC genomics, 25(1):449.

BACKGROUND: Previous studies have shown that protein kinase MoKin1 played an important role in the growth, conidiation, germination and pathogenicity in rice blast fungus, Magnaporthe oryzae. ΔMokin1 mutant showed significant phenotypic defects and significantly reduced pathogenicity. However, the internal mechanism of how MoKin1 affected the development of physiology and biochemistry remained unclear in M. oryzae.

RESULT: This study adopted a multi-omics approach to comprehensively analyze MoKin1 function, and the results showed that MoKin1 affected the cellular response to endoplasmic reticulum stress (ER stress). Proteomic analysis revealed that the downregulated proteins in ΔMokin1 mutant were enriched mainly in the response to ER stress triggered by the unfolded protein. Loss of MoKin1 prevented the ER stress signal from reaching the nucleus. Therefore, the phosphorylation of various proteins regulating the transcription of ER stress-related genes and mRNA translation was significantly downregulated. The insensitivity to ER stress led to metabolic disorders, resulting in a significant shortage of carbohydrates and a low energy supply, which also resulted in severe phenotypic defects in ΔMokin1 mutant. Analysis of MoKin1-interacting proteins indicated that MoKin1 really took participate in the response to ER stress.

CONCLUSION: Our results showed the important role of protein kinase MoKin1 in regulating cellular response to ER stress, providing a new research direction to reveal the mechanism of MoKin1 affecting pathogenic formation, and to provide theoretical support for the new biological target sites searching and bio-pesticides developing.

RevDate: 2024-05-09
CmpDate: 2024-05-07

Tsutsui K, Tanaka R, Takeda K, et al (2024)

Collaborative hunting in artificial agents with deep reinforcement learning.

eLife, 13:.

Collaborative hunting, in which predators play different and complementary roles to capture prey, has been traditionally believed to be an advanced hunting strategy requiring large brains that involve high-level cognition. However, recent findings that collaborative hunting has also been documented in smaller-brained vertebrates have placed this previous belief under strain. Here, using computational multi-agent simulations based on deep reinforcement learning, we demonstrate that decisions underlying collaborative hunts do not necessarily rely on sophisticated cognitive processes. We found that apparently elaborate coordination can be achieved through a relatively simple decision process of mapping between states and actions related to distance-dependent internal representations formed by prior experience. Furthermore, we confirmed that this decision rule of predators is robust against unknown prey controlled by humans. Our computational ecological results emphasize that collaborative hunting can emerge in various intra- and inter-specific interactions in nature, and provide insights into the evolution of sociality.

RevDate: 2024-05-08
CmpDate: 2024-05-06

Xu N, Zeng P, Guo Y, et al (2024)

The spatiotemporal evolution of rural landscape patterns in Chinese metropolises under rapid urbanization.

PloS one, 19(5):e0301754.

Understanding the evolution of rural landscapes in metropolises during rapid urbanization is crucial for formulating policies to protect the rural ecological environment. In this study, remote sensing and geographical information system data, as well as applied landscape index analysis, are used to examine the spatiotemporal evolution of rural landscape patterns in the Beijing-Tianjin region of China, which has experienced rapid urbanization. The relationships between land use/land cover changes and changes in rural landscape patterns are explored. The results revealed significant spatial differences in the rural landscapes in the Beijing-Tianjin region; farmland and forestland were the main types of landscapes, creating a "mountain-field-sea" natural landscape pattern. The conversion of rural landscapes in the Beijing-Tianjin region involved mainly the conversion of farmland to urban areas, with few exchanges between other landscape types. The urban areas in the Beijing-Tianjin region increased by 3% per decade; farmland decreased at the same rate. Additionally, the rural landscape patterns in the Beijing-Tianjin region were dominated by fragmentation, dispersion, and heterogeneity and moved from complex to regular. Water bodies displayed the most fragmented natural landscape; their number of patches increased by 36%, though their network characteristics were maintained. Forestland was the most concentrated natural landscape. In this study, theoretical support and a scientific reference for the optimization of rural landscape patterns and the improvement in rural living environments in rapidly urbanizing areas are provided.

RevDate: 2024-05-08

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

The genome sequence of the Early Thorn, Selenia dentaria (Fabricius, 1775).

Wellcome open research, 8:485.

We present a genome assembly from an individual male Selenia dentaria (the Early Thorn; Arthropoda; Insecta; Lepidoptera; Geometridae). The genome sequence is 1,030.8 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 15.41 kilobases in length. Gene annotation of this assembly on Ensembl identified 21,390 protein coding genes.

RevDate: 2024-05-08
CmpDate: 2024-05-05

Meier R, Hartop E, Pylatiuk C, et al (2024)

Towards holistic insect monitoring: species discovery, description, identification and traits for all insects.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 379(1904):20230120.

Holistic insect monitoring needs scalable techniques to overcome taxon biases, determine species abundances, and gather functional traits for all species. This requires that we address taxonomic impediments and the paucity of data on abundance, biomass and functional traits. We here outline how these data deficiencies could be addressed at scale. The workflow starts with large-scale barcoding (megabarcoding) of all specimens from mass samples obtained at biomonitoring sites. The barcodes are then used to group the specimens into molecular operational taxonomic units that are subsequently tested/validated as species with a second data source (e.g. morphology). New species are described using barcodes, images and short diagnoses, and abundance data are collected for both new and described species. The specimen images used for species discovery then become the raw material for training artificial intelligence identification algorithms and collecting trait data such as body size, biomass and feeding modes. Additional trait data can be obtained from vouchers by using genomic tools developed by molecular ecologists. Applying this pipeline to a few samples per site will lead to greatly improved insect monitoring regardless of whether the species composition of a sample is determined with images, metabarcoding or megabarcoding. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

RevDate: 2024-05-08

Song X, Li C, Qiu Z, et al (2024)

Ecotoxicological effects of polyethylene microplastics and lead (Pb) on the biomass, activity, and community diversity of soil microbes.

Environmental research, 252(Pt 3):119012 pii:S0013-9351(24)00916-2 [Epub ahead of print].

Microplastics and heavy metals are ubiquitous and persistent contaminants that are widely distributed worldwide, yet little is known about the effects of their interaction on soil ecosystems. A soil incubation experiment was conducted to investigate the individual and combined effects of polyethylene microplastics (PE-MPs) and lead (Pb) on soil enzymatic activities, microbial biomass, respiration rate, and community diversity. The results indicate that the presence of PE-MPs notably reduced soil pH and elevated soil Pb bioavailability, potentially exacerbated the combined toxicity on the biogeochemical cycles of soil nutrients, microbial biomass carbon and nitrogen, and the activities of soil urease, sucrase, and alkaline phosphatase. Soil CO2 emissions increased by 7.9% with PE-MPs alone, decreased by 46.3% with single Pb, and reduced by 69.4% with PE-MPs and Pb co-exposure, compared to uncontaminated soils. Specifically, the presence of PE-MPs and Pb, individually and in combination, facilitated the soil metabolic quotient, leading to reduced microbial metabolic efficiency. Moreover, the addition of Pb and PE-MPs modified the composition of the microbial community, leading to the enrichment of specific taxa. Tax4Fun analysis showed the effects of Pb, PE-MPs and their combination on the biogeochemical processes and ecological functions of microbes were mainly by altering amino acid metabolism, carbohydrate metabolism, membrane transport, and signal transduction. These findings offer valuable insights into the ecotoxicological effects of combined PE-MPs and Pb on soil microbial dynamics, reveals key assembly mechanisms and environmental drivers, and highlights the potential threat of MPs and heavy metals to the multifunctionality of soil ecosystems.

RevDate: 2024-05-10

Li JY, Yao S, Mo Z, et al (2024)

Submerged plant-biochar composite system exhibits effective control over residual organic pollutants in the benthic organisms of aquaculture ponds.

Environmental pollution (Barking, Essex : 1987), 351:124078 pii:S0269-7491(24)00792-9 [Epub ahead of print].

As of now, submerged plants and biochar have demonstrated significant benefits in aquaculture pond sediment remediation. However, there is limited research on the synergistic effects of biochar and submerged plants in mitigating hydrophobic organic contaminant (HOC) accumulation in aquaculture benthic organisms and in controlling the nutrient (nitrogen and phosphorus) levels in aquaculture water. This study assesses a submerged plant-biochar system's efficacy in removing HOCs from simulated freshwater aquaculture ponds. Vallisneria natans was planted in sediment with varying levels of wheat straw biochar, while Corbicula fluminea served as the targeted benthic organism. The bioaccumulation experiment identified the optimal biochar ratio for the Vallisneria natans-biochar system in controlling HOCs in aquaculture products. Analyses included final accumulation concentrations in benthic organisms, changes in freely-dissolved concentrations in aquaculture sediment, and a mass balance calculation to explore key factors in their removal from the system. Results indicated that the Vallisneria natans-1.5% biochar composite system achieved optimal control of HOCs in sediment and aquaculture products. Biochar addition to the sediment in the composite system demonstrated a "promotion with low addition, inhibition with high addition" effect on Vallisneria natans growth. Notably, the addition of 1.5% biochar (VN1.5 group) significantly promoted the growth of Vallisneria natans leaves and roots. Comparing the final pollutant proportions in different environmental media, concentrations in water (0.20%-1.8%), clam accumulation (0.032%-0.11%), and plant absorption (0.10%-0.44%) constituted a minimal portion of the overall pollutant load in the system. The majority of pollutants (24%-65%) were degraded in the aquaculture environment, with microbial degradation likely playing a predominant role. Bacterial phyla, particularly Proteobacteria and Firmicutes, were identified as potential direct contributors to pollutant degradation in the Vallisneria natans-biochar system.

RevDate: 2024-05-02

Xiao Y, Luan H, Lu S, et al (2024)

Correction: Toxic effects of atmospheric deposition in mining areas on wheat seedlings.

Environmental geochemistry and health, 46(6):199 pii:10.1007/s10653-024-01986-5.

RevDate: 2024-05-02

Falk S, Poole O, University of Oxford and Wytham Woods Genome Acquisition Lab, et al (2024)

The genome sequence of a conopid fly, Myopa testacea (Linnaeus, 1767).

Wellcome open research, 9:99.

We present a genome assembly from an individual male Myopa testacea (conopid fly; Arthropoda; Insecta; Diptera; Conopidae). The genome sequence is 243.3 megabases in span. Most of the assembly is scaffolded into 5 chromosomal pseudomolecules, including the X and Y sex chromosomes. The mitochondrial genome has also been assembled and is 17.61 kilobases in length. Gene annotation of this assembly on Ensembl identified 25,472 protein coding genes.

RevDate: 2024-05-03

Hu YL, Liu Y, Fu W, et al (2024)

Efficiency and mechanism of enhanced norfloxacin removal using amorphous TiO2-modified biochar.

Environmental pollution (Barking, Essex : 1987), 351:124027 pii:S0269-7491(24)00741-3 [Epub ahead of print].

Inadequate treatment of antibiotic-contaminated wastewater, including compounds such as norfloxacin (NOR), poses a substantial treat to both ecological safety and human well-being. An innovative approach was devised to address NOR pollution using amorphous TiO2 modified biochar (A-TiO2/BC) prepared via sol-gel impregnation. The resultant had a commendably specific surface area of 131.8 m[2]/g[-1], which was 1.91 times more than the original surface area of unmodified BC. A-TiO2/BC also exhibited abundant hydroxyl and oxygen-containing functional groups, thereby provided adequately active sites for NOR adsorption. R[2] values obtained from NOR isotherm adsorption models descended in order of Freundlich < Temkin < Sips < Langmuir, which indicated that the NOR removal by A-TiO2/BC mainly complied with monolayer adsorption accompanied by heterogeneous surface adsorption. Under weakly acidic conditions, NOR adsorption benefits from the synergistic physicochemical interactions of A-TiO2 and BC. Notably, A-TiO2/BC demonstrated an impressive NOR adsorption capacity of up to 78.14 mg g[-1], with a dosage of 20 mg L[-1] at 25 °C under pH 6. Such A-TiO2 modified biochar thus presents a promising alternative for NOR removal.

RevDate: 2024-04-30

Ghani MI, Yi B, Rehmani MS, et al (2024)

Potential of melatonin and Trichoderma harzianum inoculation in ameliorating salt toxicity in watermelon: Insights into antioxidant system, leaf ultrastructure, and gene regulation.

Plant physiology and biochemistry : PPB, 211:108639 pii:S0981-9428(24)00307-3 [Epub ahead of print].

Melatonin (MT) is an extensively studied biomolecule with dual functions, serving as an antioxidant and a signaling molecule. Trichoderma Harzianum (TH) is widely recognized for its effectiveness as a biocontrol agent against many plant pathogens. However, the interplay between seed priming and MT (150 μm) in response to NaCl (100 mM) and its interaction with TH have rarely been investigated. This study aimed to evaluate the potential of MT and TH, alone and in combination, to mitigate salt stress (SS) in watermelon plants. The findings of this study revealed a significant decline in the morphological, physiological, and biochemical indices of watermelon seedlings exposed to SS. However, MT and TH treatments reduced the negative impact of salt stress. The combined application of MT and TH exerted a remarkable positive effect by increasing the growth, photosynthetic and gas exchange parameters, chlorophyll fluorescence indices, and ion balance (decreasing Na[+] and enhancing K[+]). MT and TH effectively alleviated oxidative injury by inhibiting hydrogen peroxide formation in saline and non-saline environments, as established by reduced lipid peroxidation and electrolyte leakage. Moreover, oxidative injury induced by SS on the cells was significantly mitigated by regulation of the antioxidant system, AsA-GSH-related enzymes, the glyoxalase system, augmentation of osmolytes, and activation of several genes involved in the defense system. Additionally, the reduction in oxidative damage was examined by chloroplast integrity via transmission electron microscopy (TEM). Overall, the results of this study provide a promising contribution of MT and TH in safeguarding the watermelon crop from oxidative damage induced by salt stress.

RevDate: 2024-05-10

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

The genome sequence of the Tipped Oak Case-bearer, Coleophora flavipennella (Duponchel 1843).

Wellcome open research, 9:3.

We present a genome assembly from an individual female Coleophora flavipennella (the Tipped Oak Case-bearer; Arthropoda; Insecta; Lepidoptera; Coleophoridae). The genome sequence is 989.3 megabases in span. Most of the assembly is scaffolded into 57 chromosomal pseudomolecules, including the W and Z sex chromosomes. The mitochondrial genome has also been assembled and is 15.77 kilobases in length.

RevDate: 2024-05-02
CmpDate: 2024-04-29

Yang P, Huang G, Li Y, et al (2024)

Identification of PANoptosis-related biomarkers and analysis of prognostic values in head and neck squamous cell carcinoma.

Scientific reports, 14(1):9824.

PANoptosis plays a crucial role in cancer initiation and progression. However, the roles of PANoptosis-related genes (PARGs) in the prognosis and immune landscape of head and neck squamous cell carcinoma (HNSCC) remain unclear. Integrated bioinformatics analyses based on the data of HNSCC patients in the TCGA database were conducted. We extracted 48 PARGs expression profile and then conducted differentially expressed analysis, following building a Cox model to predict the survival of HNSCC patients. Subsequently, the relationships between the risk score, immune landscape, chemo-, and immune-therapy responses were analyzed, respectively. Moreover, we investigated the prognostic value, and further predicted the pathways influenced by PARGs. Finally, we identified the biological function of crucial PARGs. A total of 18 differentially expressed PARGs were identified in HNSCC, and a Cox model including CASP8, FADD, NLRP1, TNF, and ZBP1 was constructed, which showed that the risk score was associated with the prognosis as well as immune infiltration of HNSCC patients, and the risk score could be regarded as an independent biomarker. Additionally, patients with high-risk score might be an indicator of lymph node metastasis and advanced clinical stage. High-risk scores also contributed to the chemotherapy resistance and immune escape of HNSCC patients. In addition, FADD and ZBP1 played a crucial role in various cancer-related pathways, such as the MAPK, WNT, and MTOR signaling pathways. On the other hand, we suggested that FADD facilitated the progression and 5-fluorouracil (5-FU) resistance of HNSCC cells. A signature based on PANoptosis showed great predictive power for lymph node metastasis and advanced stage, suggesting that the risk score might be an independent prognostic biomarker for HNSCC. Meanwhile, FADD, identified as a prognostic biomarker, may represent an effective therapeutic target for HNSCC.

RevDate: 2024-05-02
CmpDate: 2024-04-29

Poquérusse J, Brown CL, Gaillard C, et al (2024)

Assessing contemporary Arctic habitat availability for a woolly mammoth proxy.

Scientific reports, 14(1):9804.

Interest continues to grow in Arctic megafaunal ecological engineering, but, since the mass extinction of megafauna ~ 12-15 ka, key physiographic variables and available forage continue to change. Here we sought to assess the extent to which contemporary Arctic ecosystems are conducive to the rewilding of megaherbivores, using a woolly mammoth (M. primigenius) proxy as a model species. We first perform a literature review on woolly mammoth dietary habits. We then leverage Oak Ridge National Laboratories Distributive Active Archive Center Global Aboveground and Belowground Biomass Carbon Density Maps to generate aboveground biomass carbon density estimates in plant functional types consumed by the woolly mammoth at 300 m resolution on Alaska's North Slope. We supplement these analyses with a NASA Arctic Boreal Vulnerability Experiment dataset to downgrade overall biomass estimates to digestible levels. We further downgrade available forage by using a conversion factor representing the relationship between total biomass and net primary productivity (NPP) for arctic vegetation types. Integrating these estimates with the forage needs of woolly mammoths, we conservatively estimate Alaska's North Slope could support densities of 0.0-0.38 woolly mammoth km[-2] (mean 0.13) across a variety of habitats. These results may inform innovative rewilding strategies.

RevDate: 2024-05-02
CmpDate: 2024-04-29

Bai Y, Song K, Gao M, et al (2024)

Using multi-omics to explore the effect of Bacillus velezensis SAAS-63 on resisting nutrient stress in lettuce.

Applied microbiology and biotechnology, 108(1):313.

To avoid the unreasonable use of chemical fertilizer, an environmentally friendly means of improving soil fertility is required. This study explored the role of the plant growth-promoting rhizosphere bacteria (PGPR) strain Bacillus velezensis SAAS-63 in improving nutrient stress in lettuce. Compared with no inoculation, B. velezensis SAAS-63 inoculants exhibited significantly increased fresh weight, root length, and shoot height under nutrient deficiency, as well as improved antioxidant activities and proline contents. The exogenous addition of B. velezensis SAAS-63 also significantly increased the accumulation of macroelements and micronutrients in lettuce. To elucidate the resistance mechanisms induced by B. velezensis SAAS-63 under nutrient stress, high-throughput sequencing and multi-omics analysis were performed. Inoculation with B. velezensis SAAS-63 altered the microbial community of the rhizosphere and increased the relative abundances of Streptomyces, Actinoallomurus, Verrucomicrobia, and Chloroflexi. It is worth noting that the inoculant SAAS-63 can affect plant rhizosphere metabolism. The inoculant changed the metabolic flow of phenylpropanoid metabolic pathway under nutrient deficiency and promoted phenylalanine to participate more in the synthesis of lignin precursors and coumarin substances by inhibiting the synthesis of flavone and isoflavone, thus improving plant resistance. This study showed that the addition of inoculant SAAS-63 could help plants recruit microorganisms to decompose and utilize trehalose and re-established the carbon metabolism of the plant rhizosphere. Additionally, microbes were found to be closely related to the accumulation of metabolites based on correlation analysis. The results indicated that the addition of PGPRs has an important role in regulating soil rhizosphere microbes and metabolism, providing valuable information for understanding how PGPRs affect complex biological processes and enhance plant adaptation to nutrient deficiency. KEY POINTS: • Inoculation with SAAS-63 significantly promoted plant growth under nutrient-deficient conditions • Inoculation with SAAS-63 affected rhizosphere microbial diversity and community structure • Inoculation with SAAS-63 affected plant rhizosphere metabolism and induced plants to synthesize substances that resist stress.

RevDate: 2024-04-30

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

The genome sequence of the Crescent Bell, Epinotia bilunana (Haworth, 1811).

Wellcome open research, 8:163.

We present a genome assembly from an individual male Epinotia bilunana (the Crescent Bell; Arthropoda; Insecta; Lepidoptera; Tortricidae). The genome sequence is 659.0 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 15.4 kilobases in length.

RevDate: 2024-04-29

Bakacsy L, Kardos LV, Szepesi Á, et al (2024)

Investigation of the Allelopathic Effect of Two Invasive Plant Species in Rhizotron System.

Life (Basel, Switzerland), 14(4):.

A key question in plant invasion biology is why invasive plants are more competitive in their introduced habitat than in their native habitat. Studies show that invasive species exhibit allelopathy, influencing other plants by releasing chemicals. Research on allelopathy uses in vitro tests, investigating effects on seed germination and seedling development. Although soil plays a role in modifying allelopathic effects, observations with soil are rare and almost nothing is known about the root development of test plants developing in soil and the effects of allelopathic compounds on root architecture. Our study evaluates the allelopathic effects of false indigo-bush (Amorpha fruticosa L.) and common milkweed (Asclepias syriaca L.) on oilseed rape growth as a model plant. The rhizotron system was used to study the effect of morphology and root architecture. Leaf-soil mixtures at 0.5%, 1%, and 5% concentrations were used. Shoot and root development was strongly inhibited at 5%. But there was no difference between the allelopathy of the two species, and the application of lower concentrations did not show any effect, demonstrating that soil has a significant modifying effect on their allelopathy. Our results highlight that the development of roots growing in the soil is also worth investigating in connection with allelopathy, which can strengthen the ecological importance of allelochemicals during successful invasions.

RevDate: 2024-04-26

Atağ G, Kaptan D, Yüncü E, et al (2024)

Population genomic history of the endangered Anatolian and Cyprian mouflons in relation to worldwide wild, feral and domestic sheep lineages.

Genome biology and evolution pii:7658889 [Epub ahead of print].

Once widespread in their homelands, the Anatolian mouflon (Ovis gmelini anatolica) and the Cyprian mouflon (Ovis gmelini ophion) were driven to near extinction during the 20th century and are currently listed as endangered populations by the IUCN. While the exact origins of these lineages remain unclear, they have been suggested to be close relatives of domestic sheep or remnants of proto-domestic sheep. Here, we study whole genome sequences of n = 5 Anatolian mouflons and n = 10 Cyprian mouflons in terms of population history and diversity, comparing them to eight other extant sheep lineages. We find reciprocal genetic affinity between Anatolian and Cyprian mouflons and domestic sheep, higher than all other studied wild sheep genomes, including the Iranian mouflon (Ovis gmelini). Studying diversity indices, we detect a considerable load of short runs of homozygosity (ROH) blocks (<2 Mb) in both Anatolian and Cyprian mouflons, reflecting small effective population size (Ne). Meanwhile, Ne as well as mutation load estimates are lower in Cyprian compared to Anatolian mouflons, suggesting the purging of recessive deleterious variants in Cyprian sheep under a small long-term Ne, possibly attributable to founder effects, island isolation, introgression from domestic lineages, or differences in their bottleneck dynamics. Expanding our analyses to worldwide wild and feral Ovis genomes, we observe varying viability metrics among different lineages, and a limited consistency between viability metrics and IUCN conservation status. Factors such as recent inbreeding, introgression, and unique population dynamics may have contributed to the observed disparities.

RevDate: 2024-04-26
CmpDate: 2024-04-26

Muthye V, DV Lavrov (2024)

Characterization of the Mitochondrial Proteome in the Ctenophore Mnemiopsis leidyi Using MitoPredictor.

Methods in molecular biology (Clifton, N.J.), 2757:239-257.

Mitochondrial proteomes have been experimentally characterized for only a handful of animal species. However, the increasing availability of genomic and transcriptomic data allows one to infer mitochondrial proteins using computational tools. MitoPredictor is a novel random forest classifier, which utilizes orthology search, mitochondrial targeting signal (MTS) identification, and protein domain content to infer mitochondrial proteins in animals. MitoPredictor's output also includes an easy-to-use R Shiny applet for the visualization and analysis of the results. In this article, we provide a guide for predicting and analyzing the mitochondrial proteome of the ctenophore Mnemiopsis leidyi using MitoPredictor.

RevDate: 2024-04-29

Li Q, Yao S, Wen H, et al (2024)

Improving Lead Phytoremediation Using Endophytic Bacteria Isolated from the Pioneer Plant Ageratina adenophora (Spreng.) from a Mining Area.

Toxics, 12(4):.

This study aimed to isolate and characterise endophytic bacteria from the pioneer plant Ageratina adenophora in a mining area. Seven strains of metal-resistant endophytic bacteria that belong to five genera were isolated from the roots of A. adenophora. These strains exhibited various plant growth-promoting (PGP) capabilities. Sphingomonas sp. ZYG-4, which exhibited the ability to secrete indoleacetic acid (IAA; 53.2 ± 8.3 mg·L[-1]), solubilize insoluble inorganic phosphates (Phosphate solubilization; 11.2 ± 2.9 mg·L[-1]), and regulate root ethylene levels (1-aminocyclopropane-1-carboxylic acid deaminase activity; 2.87 ± 0.19 µM α-KB·mg[-1]·h[-1]), had the highest PGP potential. Therefore, Sphingomonas sp. ZYG-4 was used in a pot experiment to study its effect on the biomass and Pb uptake of both host (Ageratina adenophora) and non-host (Dysphania ambrosioides) plants. Compared to the uninoculated control, Sphingomonas sp. ZYG-4 inoculation increased the biomass of shoots and roots by 59.4% and 144.4% for A. adenophora and by 56.2% and 57.1% for D. ambrosioides, respectively. In addition, Sphingomonas sp. ZYG-4 inoculation enhanced Pb accumulation in the shoot and root by 268.9% and 1187.3% for A. adenophora, and by 163.1% and 343.8% for D. ambrosioides, respectively, compared to plants without bacterial inoculation. Our research indicates that endophytic bacteria are promising candidates for enhancing plant growth and facilitating microbe-assisted phytoremediation in heavy metal-contaminated soil.

RevDate: 2024-04-29

Li S, Yang J, Zheng K, et al (2024)

Effective Activation of Peroxymonosulfate by Oxygen Vacancy Induced Musa Basjoo Biochar to Degrade Sulfamethoxazole: Efficiency and Mechanism.

Toxics, 12(4):.

Biochar materials have garnered attention as potential catalysts for peroxymonosulfate (PMS) activation due to their cost-effectiveness, notable specific surface area, and advantageous structural properties. In this study, a suite of plantain-derived biochar (MBB-400, MBB-600, and MBB-800), possessing a well-defined pore structure and a substantial number of uniformly distributed active sites (oxygen vacancy, OVs), was synthesized through a facile calcination process at varying temperatures (400, 600, and 800 °C). These materials were designed for the activation of PMS in the degradation of sulfamethoxazole (SMX). Experimental investigations revealed that OVs not only functioned as enriched sites for pollutants, enhancing the opportunities for free radicals ([•]OH/SO4[•-]) and surface-bound radicals (SBRs) to attack pollutants, but also served as channels for intramolecular charge transfer leaps. This role contributed to a reduction in interfacial charge transfer resistance, expediting electron transfer rates with PMS, thereby accelerating the decomposition of pollutants. Capitalizing on these merits, the MBB-800/PMS system displayed a 61-fold enhancement in the conversion rate for SMX degradation compared to inactivated MBB/PMS system. Furthermore, the MBB-800 exhibited less cytotoxicity towards rat pheochromocytoma (PC12) cells. Hence, the straightforward calcination synthesis of MBB-800 emerges as a promising biochar catalyst with vast potential for sustainable and efficient wastewater treatment and environmental remediation.

RevDate: 2024-04-27
CmpDate: 2024-04-26

Omar KM, Kitundu GL, Jimoh AO, et al (2024)

Investigating antimicrobial resistance genes in Kenya, Uganda and Tanzania cattle using metagenomics.

PeerJ, 12:e17181.

Antimicrobial resistance (AMR) is a growing problem in African cattle production systems, posing a threat to human and animal health and the associated economic value chain. However, there is a poor understanding of the resistomes in small-holder cattle breeds in East African countries. This study aims to examine the distribution of antimicrobial resistance genes (ARGs) in Kenya, Tanzania, and Uganda cattle using a metagenomics approach. We used the SqueezeMeta-Abricate (assembly-based) pipeline to detect ARGs and benchmarked this approach using the Centifuge-AMRplusplus (read-based) pipeline to evaluate its efficiency. Our findings reveal a significant number of ARGs of critical medical and economic importance in all three countries, including resistance to drugs of last resort such as carbapenems, suggesting the presence of highly virulent and antibiotic-resistant bacterial pathogens (ESKAPE) circulating in East Africa. Shared ARGs such as aph(6)-id (aminoglycoside phosphotransferase), tet (tetracycline resistance gene), sul2 (sulfonamide resistance gene) and cfxA_gen (betalactamase gene) were detected. Assembly-based methods revealed fewer ARGs compared to read-based methods, indicating the sensitivity and specificity of read-based methods in resistome characterization. Our findings call for further surveillance to estimate the intensity of the antibiotic resistance problem and wider resistome classification. Effective management of livestock and antibiotic consumption is crucial in minimizing antimicrobial resistance and maximizing productivity, making these findings relevant to stakeholders, agriculturists, and veterinarians in East Africa and Africa at large.

RevDate: 2024-04-25

Lu XY, Wu HP, Ma H, et al (2024)

Deep Learning-Assisted Spectrum-Structure Correlation: State-of-the-Art and Perspectives.

Analytical chemistry [Epub ahead of print].

Spectrum-structure correlation is playing an increasingly crucial role in spectral analysis and has undergone significant development in recent decades. With the advancement of spectrometers, the high-throughput detection triggers the explosive growth of spectral data, and the research extension from small molecules to biomolecules accompanies massive chemical space. Facing the evolving landscape of spectrum-structure correlation, conventional chemometrics becomes ill-equipped, and deep learning assisted chemometrics rapidly emerges as a flourishing approach with superior ability of extracting latent features and making precise predictions. In this review, the molecular and spectral representations and fundamental knowledge of deep learning are first introduced. We then summarize the development of how deep learning assist to establish the correlation between spectrum and molecular structure in the recent 5 years, by empowering spectral prediction (i.e., forward structure-spectrum correlation) and further enabling library matching and de novo molecular generation (i.e., inverse spectrum-structure correlation). Finally, we highlight the most important open issues persisted with corresponding potential solutions. With the fast development of deep learning, it is expected to see ultimate solution of establishing spectrum-structure correlation soon, which would trigger substantial development of various disciplines.

RevDate: 2024-04-24

Andrianova MA, Seplyarskiy VB, Terradas M, et al (2024)

Discovery of recessive effect of human polymerase δ proofreading deficiency through mutational analysis of POLD1-mutated normal and cancer cells.

European journal of human genetics : EJHG [Epub ahead of print].

Constitutional heterozygous pathogenic variants in the exonuclease domain of POLE and POLD1, which affect the proofreading activity of the corresponding polymerases, cause a cancer predisposition syndrome characterized by increased risk of gastrointestinal polyposis, colorectal cancer, endometrial cancer and other tumor types. The generally accepted explanation for the connection between the disruption of the proofreading activity of polymerases epsilon and delta and cancer development is through an increase in the somatic mutation rate. Here we studied an extended family with multiple members heterozygous for the pathogenic POLD1 variant c.1421T>C p.(Leu474Pro), which segregates with the polyposis and cancer phenotypes. Through the analysis of mutational patterns of patient-derived fibroblasts colonies and de novo mutations obtained by parent-offspring comparisons, we concluded that heterozygous POLD1 L474P just subtly increases the somatic and germline mutation burden. In contrast, tumors developed in individuals with a heterozygous mutation in the exonuclease domain of POLD1, including L474P, have an extremely high mutation rate (>100 mut/Mb) associated with signature SBS10d. We solved this contradiction through the observation that tumorigenesis involves somatic inactivation of the wildtype POLD1 allele. These results imply that exonuclease deficiency of polymerase delta has a recessive effect on mutation rate.

RevDate: 2024-04-24
CmpDate: 2024-04-24

Jiménez-Madrigal JP, Till BJ, A Gatica-Arias (2024)

Genetic Diversity Assessment in Plants from Reduced Representation Sequencing Data.

Methods in molecular biology (Clifton, N.J.), 2787:107-122.

Genetic diversity refers to the variety of genetic traits within a population or a species. It is an essential aspect of both plant ecology and plant breeding because it contributes to the adaptability, survival, and resilience of populations in changing environments. This chapter outlines a pipeline for estimating genetic diversity statistics from reduced representation or whole genome sequencing data. The pipeline involves obtaining DNA sequence reads, mapping the corresponding reads to a reference genome, calling variants from the alignments, and generating an unbiased estimation of nucleotide diversity and divergence between populations. The pipeline is suitable for single-end Illumina reads and can be adjusted for paired-end reads. The resulting pipeline provides a comprehensive approach for aligning and analyzing sequencing data to estimate genetic diversity.

RevDate: 2024-04-26
CmpDate: 2024-04-24

Wu SH, Ko JC, Lin RS, et al (2023)

Evaluating community-wide temporal sampling in passive acoustic monitoring: A comprehensive study of avian vocal patterns in subtropical montane forests.

F1000Research, 12:1299.

BACKGROUND: From passive acoustic monitoring (PAM) recordings, the vocal activity rate (VAR), vocalizations per unit of time, can be calculated and is essential for assessing bird population abundance. However, VAR is subject to influences from a range of factors, including species and environmental conditions. Identifying the optimal sampling design to obtain representative acoustic data for VAR estimation is crucial for research objectives. PAM commonly uses temporal sampling strategies to decrease the volume of recordings and the resources needed for audio data management. Yet, the comprehensive impact of this sampling approach on VAR estimation remains insufficiently explored.

METHODS: In this study, we used vocalizations extracted from recordings of 12 bird species, taken at 14 PAM stations situated in subtropical montane forests over a four-month period, to assess the impact of temporal sampling on VAR across three distinct scales: short-term periodic, diel, and hourly. For short-term periodic sampling analysis, we employed hierarchical clustering analysis (HCA) and the coefficient of variation (CV). Generalized additive models (GAMs) were utilized for diel sampling analysis, and we determined the average difference in VAR values per minute for the hourly sampling analysis.

RESULTS: We identified significant day and species-specific VAR fluctuations. The survey season was divided into five segments; the earliest two showed high variability and are best avoided for surveys. Data from days with heavy rain and strong winds showed reduced VAR values and should be excluded from analysis. Continuous recordings spanning at least seven days, extending to 14 days is optimal for minimizing sampling variance. Morning chorus recordings effectively capture the majority of bird vocalizations, and hourly sampling with frequent, shorter intervals aligns closely with continuous recording outcomes.

CONCLUSIONS: While our findings are context-specific, they highlight the significance of strategic sampling in avian monitoring, optimizing resource utilization and enhancing the breadth of monitoring efforts.

RevDate: 2024-04-27
CmpDate: 2024-04-24

Spake L, Hassan A, Schaffnit SB, et al (2024)

A practical guide to cross-cultural and multi-sited data collection in the biological and behavioural sciences.

Proceedings. Biological sciences, 291(2021):20231422.

Researchers in the biological and behavioural sciences are increasingly conducting collaborative, multi-sited projects to address how phenomena vary across ecologies. These types of projects, however, pose additional workflow challenges beyond those typically encountered in single-sited projects. Through specific attention to cross-cultural research projects, we highlight four key aspects of multi-sited projects that must be considered during the design phase to ensure success: (1) project and team management; (2) protocol and instrument development; (3) data management and documentation; and (4) equitable and collaborative practices. Our recommendations are supported by examples from our experiences collaborating on the Evolutionary Demography of Religion project, a mixed-methods project collecting data across five countries in collaboration with research partners in each host country. To existing discourse, we contribute new recommendations around team and project management, introduce practical recommendations for exploring the validity of instruments through qualitative techniques during piloting, highlight the importance of good documentation at all steps of the project, and demonstrate how data management workflows can be strengthened through open science practices. While this project was rooted in cross-cultural human behavioural ecology and evolutionary anthropology, lessons learned from this project are applicable to multi-sited research across the biological and behavioural sciences.

RevDate: 2024-05-01
CmpDate: 2024-04-29

Niimura Y, Biswa BB, Kishida T, et al (2024)

Synchronized Expansion and Contraction of Olfactory, Vomeronasal, and Taste Receptor Gene Families in Hystricomorph Rodents.

Molecular biology and evolution, 41(4):.

Chemical senses, including olfaction, pheromones, and taste, are crucial for the survival of most animals. There has long been a debate about whether different types of senses might influence each other. For instance, primates with a strong sense of vision are thought to have weakened olfactory abilities, although the oversimplified trade-off theory is now being questioned. It is uncertain whether such interactions between different chemical senses occur during evolution. To address this question, we examined four receptor gene families related to olfaction, pheromones, and taste: olfactory receptor (OR), vomeronasal receptor type 1 and type 2 (V1R and V2R), and bitter taste receptor (T2R) genes in Hystricomorpha, which is morphologically and ecologically the most diverse group of rodents. We also sequenced and assembled the genome of the grasscutter, Thryonomys swinderianus. By examining 16 available genome assemblies alongside the grasscutter genome, we identified orthologous gene groups among hystricomorph rodents for these gene families to separate the gene gain and loss events in each phylogenetic branch of the Hystricomorpha evolutionary tree. Our analysis revealed that the expansion or contraction of the four gene families occurred synchronously, indicating that when one chemical sense develops or deteriorates, the others follow suit. The results also showed that V1R/V2R genes underwent the fastest evolution, followed by OR genes, and T2R genes were the most evolutionarily stable. This variation likely reflects the difference in ligands of V1R/V2Rs, ORs, and T2Rs: species-specific pheromones, environment-based scents, and toxic substances common to many animals, respectively.

RevDate: 2024-05-04
CmpDate: 2024-05-02

Lauber C, Zhang X, Vaas J, et al (2024)

Deep mining of the Sequence Read Archive reveals major genetic innovations in coronaviruses and other nidoviruses of aquatic vertebrates.

PLoS pathogens, 20(4):e1012163.

Virus discovery by genomics and metagenomics empowered studies of viromes, facilitated characterization of pathogen epidemiology, and redefined our understanding of the natural genetic diversity of viruses with profound functional and structural implications. Here we employed a data-driven virus discovery approach that directly queries unprocessed sequencing data in a highly parallelized way and involves a targeted viral genome assembly strategy in a wide range of sequence similarity. By screening more than 269,000 datasets of numerous authors from the Sequence Read Archive and using two metrics that quantitatively assess assembly quality, we discovered 40 nidoviruses from six virus families whose members infect vertebrate hosts. They form 13 and 32 putative viral subfamilies and genera, respectively, and include 11 coronaviruses with bisegmented genomes from fishes and amphibians, a giant 36.1 kilobase coronavirus genome with a duplicated spike glycoprotein (S) gene, 11 tobaniviruses and 17 additional corona-, arteri-, cremega-, nanhypo- and nangoshaviruses. Genome segmentation emerged in a single evolutionary event in the monophyletic lineage encompassing the subfamily Pitovirinae. We recovered the bisegmented genome sequences of two coronaviruses from RNA samples of 69 infected fishes and validated the presence of poly(A) tails at both segments using 3'RACE PCR and subsequent Sanger sequencing. We report a genetic linkage between accessory and structural proteins whose phylogenetic relationships and evolutionary distances are incongruent with the phylogeny of replicase proteins. We rationalize these observations in a model of inter-family S recombination involving at least five ancestral corona- and tobaniviruses of aquatic hosts. In support of this model, we describe an individual fish co-infected with members from the families Coronaviridae and Tobaniviridae. Our results expand the scale of the known extraordinary evolutionary plasticity in nidoviral genome architecture and call for revisiting fundamentals of genome expression, virus particle biology, host range and ecology of vertebrate nidoviruses.

RevDate: 2024-04-23
CmpDate: 2024-04-23

Hu JY, Liu LY, Dai QL, et al (2024)

Evaluation of ecotourism suitability based on AHP-GIS: Taking Xiaoxiangling area of the Giant Panda National Park and the surrounding communities as an example.

Ying yong sheng tai xue bao = The journal of applied ecology, 35(3):780-788.

The primary goal of national parks is to protect ecological environment, but also with the functions of scientific research, education, and recreation. Aiming for the realization of universal sharing, we used the analytic hierarchy process (AHP) to construct an ecotourism suitability evaluation system by selecting four factors, including landscape resources, ecological environment carrying capacity, recreation utilization capacity and social condition, taking Xiaoxiangling area of Giant Panda National Park and the surrounding communities as an example. We evaluated the ecotourism suitability based on GIS, and conducted a questionnaire survey of tourists, to propose suggestions on the functional zoning in terms of ecotourism suitability and subjective choice preferences of tourists. The results showed that the ecotourism suitability of the evaluation area could be classified into five levels. The most suitable areas were located nearby the natural landscape resources and far away from the core conservation area, and the least suitable areas distributed at the edge of the core conservation area. According to the results of suitability analysis, the evaluation area was divided into suitable development area, moderate development area, and restricted development area. Combined with the tourist preferences, we divided the recreational activities in the evaluation area into seven activities, namely, ecotourism, eco-camping, science education, leisure vacation, agricultural and animal husbandry culture experience, eco-education, and mountain adventure. These findings could help provide suitable services for different tourists and offer reference for the ecotourism developmental planning of the Xiaoxiangling area of the Giant Panda National Park.

RevDate: 2024-04-23

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

The genome sequence of the Scalloped Oak, Crocallis elinguaria (Linneas, 1758).

Wellcome open research, 8:426.

We present a genome assembly from an individual female Crocallis elinguaria (the Scalloped Oak; Arthropoda; Insecta; Lepidoptera; Geometridae). The genome sequence is 430.4 megabases in span. Most of the assembly is scaffolded into 17 chromosomal pseudomolecules, including the Z and W sex chromosomes. The mitochondrial genome has also been assembled and is 16.86 kilobases in length. Gene annotation of this assembly on Ensembl identified 17,741 protein coding genes.

RevDate: 2024-05-10
CmpDate: 2024-04-23

Chen J, Lin JJ, Wang W, et al (2024)

EV-COMM: A database of interspecies and intercellular interactions mediated by extracellular vesicles.

Journal of extracellular vesicles, 13(4):e12442.

Intra- and inter-organismal interactions play a crucial role in the maintenance and function of individuals, as well as communities. Extracellular vesicles (EVs) have been identified as effective mediators for the communication both within and between species. They can carry and transport molecular cargoes to transmit biological messages. Several databases (ExoBCD, ExoCarta, EVpedia, EV-TRACK, Vesiclepedia) complied the cargoes information including DNA, RNA, protein, lipid and metabolite associated with EVs. Databases that refer to the complete records on both donor and recipient information are warranted to facilitate the understanding of the interaction across cells and species. In this study, we developed a database that compiled the records equipped with a structured process of EV-mediated interaction. The sources of donor and recipient were classified by cell type, tissues/organs and species, thus providing an extended knowledge of cell-cell, species-species interaction. The isolation and identification methods were presented for assessing the quality of EVs. Information on functional cargoes was included, where microRNA was linked to a prediction server to broaden its potential effects. Physiological and pathological context was marked to show the environment where EVs functioned. At present, a total of 1481 data records in our database, including 971 cell-cell interactions belonging to more than 40 different tissues/organs, and 510 cross-species records. The database provides a web interface to browse, search, visualize and download the interaction records. Users can search for interactions by selecting the context of interest or specific cells/species types, as well as functional cargoes. To the best of our knowledge, the database is the first comprehensive database focusing on interactions between donor and recipient cells or species mediated by EVs, serving as a convenient tool to explore and validate interactions. The Database, shorten as EV-COMM (EV mediated communication) is freely available at http://sdc.iue.ac.cn/evs/list/ and will be continuously updated.

RevDate: 2024-04-23
CmpDate: 2024-04-22

Xiao W, Chen YL, Du LY, et al (2024)

Bacterial interactome disturbance in chronic obstructive pulmonary disease clinical stability and exacerbations.

Respiratory research, 25(1):173.

RATIONALE: Our understanding of airway dysbiosis in chronic obstructive pulmonary disease (COPD) remains incomplete, which may be improved by unraveling the complexity in microbial interactome.

OBJECTIVES: To characterize reproducible features of airway bacterial interactome in COPD at clinical stability and during exacerbation, and evaluate their associations with disease phenotypes.

METHODS: We performed weighted ensemble-based co-occurrence network analysis of 1742 sputum microbiomes from published and new microbiome datasets, comprising two case-control studies of stable COPD versus healthy control, two studies of COPD stability versus exacerbation, and one study with exacerbation-recovery time series data.

RESULTS: Patients with COPD had reproducibly lower degree of negative bacterial interactions, i.e. total number of negative interactions as a proportion of total interactions, in their airway microbiome compared with healthy controls. Evaluation of the Haemophilus interactome showed that the antagonistic interaction networks of this established pathogen rather than its abundance consistently changed in COPD. Interactome dynamic analysis revealed reproducibly reduced antagonistic interactions but not diversity loss during COPD exacerbation, which recovered after treatment. In phenotypic analysis, unsupervised network clustering showed that loss of antagonistic interactions was associated with worse clinical symptoms (dyspnea), poorer lung function, exaggerated neutrophilic inflammation, and higher exacerbation risk. Furthermore, the frequent exacerbators (≥ 2 exacerbations per year) had significantly reduced antagonistic bacterial interactions while exhibiting subtle compositional changes in their airway microbiota.

CONCLUSIONS: Bacterial interactome disturbance characterized by reduced antagonistic interactions, rather than change in pathogen abundance or diversity, is a reproducible feature of airway dysbiosis in COPD clinical stability and exacerbations, which suggests that we may target interactome rather than pathogen alone for disease treatment.

RevDate: 2024-05-04
CmpDate: 2024-05-01

Maes SL, Dietrich J, Midolo G, et al (2024)

Environmental drivers of increased ecosystem respiration in a warming tundra.

Nature, 629(8010):105-113.

Arctic and alpine tundra ecosystems are large reservoirs of organic carbon[1,2]. Climate warming may stimulate ecosystem respiration and release carbon into the atmosphere[3,4]. The magnitude and persistency of this stimulation and the environmental mechanisms that drive its variation remain uncertain[5-7]. This hampers the accuracy of global land carbon-climate feedback projections[7,8]. Here we synthesize 136 datasets from 56 open-top chamber in situ warming experiments located at 28 arctic and alpine tundra sites which have been running for less than 1 year up to 25 years. We show that a mean rise of 1.4 °C [confidence interval (CI) 0.9-2.0 °C] in air and 0.4 °C [CI 0.2-0.7 °C] in soil temperature results in an increase in growing season ecosystem respiration by 30% [CI 22-38%] (n = 136). Our findings indicate that the stimulation of ecosystem respiration was due to increases in both plant-related and microbial respiration (n = 9) and continued for at least 25 years (n = 136). The magnitude of the warming effects on respiration was driven by variation in warming-induced changes in local soil conditions, that is, changes in total nitrogen concentration and pH and by context-dependent spatial variation in these conditions, in particular total nitrogen concentration and the carbon:nitrogen ratio. Tundra sites with stronger nitrogen limitations and sites in which warming had stimulated plant and microbial nutrient turnover seemed particularly sensitive in their respiration response to warming. The results highlight the importance of local soil conditions and warming-induced changes therein for future climatic impacts on respiration.

RevDate: 2024-04-17

Dai WT, Zhang H, Wu X, et al (2024)

[Pollution Characteristics and Source Analysis of Soil Heavy Metal in Coal Mine Area near the Yellow River in Shandong].

Huan jing ke xue= Huanjing kexue, 45(5):2952-2961.

To explore the pollution characteristics and source of soil heavy metal in a coal mine area near the Yellow River in Shandong, the geo-accumulation index method and improved Nemerow pollution index method were used to evaluate the pollution characteristics of soil heavy metal. The absolute principal component-multiple linear regression model (APCS-MLR) was used to quantitatively analyze the source of soil heavy metal, and the spatial distribution of Hg and Cd were analyzed using the Kriging spatial difference method in ArcGIS. The result accuracy of the APCS-MLR model was further verified. The results showed that:The measured contents of soil heavy metal Cu, Zn, Pb, Cr, Cd, Ni, As, and Hg all exceeded the normal site, among which, Hg and Cd exceeded the background values of soil elements in Shandong. The coefficient of variation (CV) of Hg was higher than 0.500, indicating significant spatial heterogeneity. Moreover, the correlation between Hg and other heavy metals was generally low, and the possibility of the same pollution source was small. The results of the geo-accumulation index and improved Nemerow pollution index showed that the overall soil heavy metal pollution was at a moderate level, among which the Hg pollution level was the highest, and its maximum value was at a slanted-heavy pollution level; Cu, Cd, and As in soil caused local pollution, which were at a slanted-light pollution level. Soil heavy metal pollution was closely related to mining activities, rehabilitation, and engineering construction in the coal mine area. The two major pollution sources of soil heavy metal in the research area were the compound source of the parent material and industrial and mining transportation sources (known source 1) and the compound source of atmospheric sedimentation and coal production (known source 2), the contribution rates of which were 76.705% and 16.171%, respectively. The results of the APCS-MLR model were shown to be reliable by analyzing the content distribution of Hg and Cd using the Kriging space difference mode. This research can provide scientific basis for the precise control and improvement of soil heavy metal pollution, ensuring the safety of food and agricultural products and improving the quality of the ecological environment in the coal mine area in the Shandong section of the Yellow River Basin.

RevDate: 2024-04-25
CmpDate: 2024-04-18

Ridley RS, Conrad RE, Lindner BG, et al (2024)

Potential routes of plastics biotransformation involving novel plastizymes revealed by global multi-omic analysis of plastic associated microbes.

Scientific reports, 14(1):8798.

Despite increasing efforts across various disciplines, the fate, transport, and impact of synthetic plastics on the environment and public health remain poorly understood. To better elucidate the microbial ecology of plastic waste and its potential for biotransformation, we conducted a large-scale analysis of all publicly available meta-omic studies investigating plastics (n = 27) in the environment. Notably, we observed low prevalence of known plastic degraders throughout most environments, except for substantial enrichment in riverine systems. This indicates rivers may be a highly promising environment for discovery of novel plastic bioremediation products. Ocean samples associated with degrading plastics showed clear differentiation from non-degrading polymers, showing enrichment of novel putative biodegrading taxa in the degraded samples. Regarding plastisphere pathogenicity, we observed significant enrichment of antimicrobial resistance genes on plastics but not of virulence factors. Additionally, we report a co-occurrence network analysis of 10 + million proteins associated with the plastisphere. This analysis revealed a localized sub-region enriched with known and putative plastizymes-these may be useful for deeper investigation of nature's ability to biodegrade man-made plastics. Finally, the combined data from our meta-analysis was used to construct a publicly available database, the Plastics Meta-omic Database (PMDB)-accessible at plasticmdb.org. These data should aid in the integrated exploration of the microbial plastisphere and facilitate research efforts investigating the fate and bioremediation potential of environmental plastic waste.

RevDate: 2024-04-25
CmpDate: 2024-04-18

Hammoud R, Tognin S, Smythe M, et al (2024)

Smartphone-based ecological momentary assessment reveals an incremental association between natural diversity and mental wellbeing.

Scientific reports, 14(1):7051.

Using smartphone-based ecological momentary assessment, this study investigated an association between natural diversity on mental wellbeing. A sample of 1,998 participants completed 41,448 assessments between April 2018 and September 2023. Environments which included a larger range of natural features, such as trees, plants and birdlife (high natural diversity) were associated with greater mental wellbeing than environments including a smaller range of natural features (low natural diversity). There was evidence of a mediating effect of natural diversity on the association between natural environments and mental wellbeing. These results highlight the importance of policies and practices that support richness of biodiversity for public mental health.

RevDate: 2024-05-03

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.

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: 2024-04-25
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: 2024-05-02
CmpDate: 2024-05-02

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, 25(5):636-648.

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: 2024-04-16

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: 2024-04-25

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: 2024-04-25
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: 2024-05-03
CmpDate: 2024-05-03

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, 111(5):954-965.

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: 2024-04-28
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: 2024-04-25
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: 2024-04-25
CmpDate: 2024-04-15

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):.

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: 2024-04-25

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):.

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: 2024-04-16

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: 2024-04-25
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: 2024-04-12
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: 2024-04-27
CmpDate: 2024-04-26

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.

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: 2024-04-23
CmpDate: 2024-04-23

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, 33(9):e17333.

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: 2024-04-25

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

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

Nature, 628(8009):E5.

RevDate: 2024-04-26
CmpDate: 2024-04-25

Mujica MI, Silva-Flores P, Bueno CG, et al (2024)

Integrating perspectives in developing mycorrhizal trait databases: a call for inclusive and collaborative continental efforts.

The New phytologist, 242(4):1436-1440.

Global assessments of mycorrhizal symbiosis present large sampling gaps in rich biodiversity regions. Filling these gaps is necessary to build large-scale, unbiased mycorrhizal databases to obtain reliable analyses and prevent misleading generalizations. Underrepresented regions in mycorrhizal research are mainly in Africa, Asia, and South America. Despite the high biodiversity and endemism in these regions, many groups of organisms remain understudied, especially mycorrhizal fungi. In this Viewpoint, we emphasize the importance of inclusive and collaborative continental efforts in integrating perspectives for comprehensive trait database development and propose a conceptual framework that can help build large mycorrhizal databases in underrepresented regions. Based on the four Vs of big data (volume, variety, veracity, and velocity), we identify the main challenges of constructing a large mycorrhizal dataset and propose solutions for each challenge. We share our collaborative methodology, which involves employing open calls and working groups to engage all mycorrhizal researchers in the region to build a South American Mycorrhizal Database. By fostering interdisciplinary collaborations and embracing a continental-scale approach, we can create robust mycorrhizal trait databases that provide valuable insights into the evolution, ecology, and functioning of mycorrhizal associations, reducing the geographical biases that are so common in large-scale ecological studies.

RevDate: 2024-04-25
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: 2024-04-09

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: 2024-04-27
CmpDate: 2024-04-26

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.

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: 2024-04-11
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: 2024-05-09
CmpDate: 2024-04-23

Augustijn HE, Roseboom AM, Medema MH, et al (2024)

Harnessing regulatory networks in Actinobacteria for natural product discovery.

Journal of industrial microbiology & biotechnology, 51:.

UNLABELLED: Microbes typically live in complex habitats where they need to rapidly adapt to continuously changing growth conditions. To do so, they produce an astonishing array of natural products with diverse structures and functions. Actinobacteria stand out for their prolific production of bioactive molecules, including antibiotics, anticancer agents, antifungals, and immunosuppressants. Attention has been directed especially towards the identification of the compounds they produce and the mining of the large diversity of biosynthetic gene clusters (BGCs) in their genomes. However, the current return on investment in random screening for bioactive compounds is low, while it is hard to predict which of the millions of BGCs should be prioritized. Moreover, many of the BGCs for yet undiscovered natural products are silent or cryptic under laboratory growth conditions. To identify ways to prioritize and activate these BGCs, knowledge regarding the way their expression is controlled is crucial. Intricate regulatory networks control global gene expression in Actinobacteria, governed by a staggering number of up to 1000 transcription factors per strain. This review highlights recent advances in experimental and computational methods for characterizing and predicting transcription factor binding sites and their applications to guide natural product discovery. We propose that regulation-guided genome mining approaches will open new avenues toward eliciting the expression of BGCs, as well as prioritizing subsets of BGCs for expression using synthetic biology approaches.

ONE-SENTENCE SUMMARY: This review provides insights into advances in experimental and computational methods aimed at predicting transcription factor binding sites and their applications to guide natural product discovery.

RevDate: 2024-05-04

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

Complexity of avian evolution revealed by family-level genomes.

Nature [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 analysing the 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 marked degree of discordance. The tree confirms that Neoaves experienced rapid radiation at or near the Cretaceous-Palaeogene boundary. Sufficient loci rather than extensive taxon sampling were more effective in resolving difficult nodes. Remaining recalcitrant nodes involve species that are a challenge to model due to either extreme DNA composition, variable substitution rates, incomplete lineage sorting or complex evolutionary events such as ancient hybridization. Assessment of the effects 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 Cretaceous-Palaeogene extinction event, supporting the hypothesis that emerging ecological opportunities catalysed the diversification of modern birds. The resulting phylogenetic estimate offers fresh insights into the rapid radiation of modern birds and provides a taxon-rich backbone tree for future comparative studies.

RevDate: 2024-04-17

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: 2024-04-25
CmpDate: 2024-04-24

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, 927:171919.

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 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 experiments 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: 2024-05-07
CmpDate: 2024-05-07

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.

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: 2024-05-02
CmpDate: 2024-05-02

Martin NG, Defres S, Willis L, et al (2024)

Paediatric meningitis in the conjugate vaccine era and a novel clinical decision model to predict bacterial aetiology.

The Journal of infection, 88(5):106145.

OBJECTIVES: The aims of this study were to assess aetiology and clinical characteristics in childhood meningitis, and develop clinical decision rules to distinguish bacterial meningitis from other similar clinical syndromes.

METHODS: Children aged <16 years hospitalised with suspected meningitis/encephalitis were included, and prospectively recruited at 31 UK hospitals. Meningitis was defined as identification of bacteria/viruses from cerebrospinal fluid (CSF) and/or a raised CSF white blood cell count. New clinical decision rules were developed to distinguish bacterial from viral meningitis and those of alternative aetiology.

RESULTS: The cohort included 3002 children (median age 2·4 months); 1101/3002 (36·7%) had meningitis, including 180 bacterial, 423 viral and 280 with no pathogen identified. Enterovirus was the most common pathogen in those aged <6 months and 10-16 years, with Neisseria meningitidis and/or Streptococcus pneumoniae commonest at age 6 months to 9 years. The Bacterial Meningitis Score had a negative predictive value of 95·3%. We developed two clinical decision rules, that could be used either before (sensitivity 82%, specificity 71%) or after lumbar puncture (sensitivity 84%, specificity 93%), to determine risk of bacterial meningitis.

CONCLUSIONS: Bacterial meningitis comprised 6% of children with suspected meningitis/encephalitis. Our clinical decision rules provide potential novel approaches to assist with identifying children with bacterial meningitis.

FUNDING: This study was funded by the Meningitis Research Foundation, Pfizer and the NIHR Programme Grants for Applied Research.

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: 2024-03-30

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: 2024-05-01
CmpDate: 2024-04-25

Johnson TF, Beckerman AP, Childs DZ, et al (2024)

Revealing uncertainty in the status of biodiversity change.

Nature, 628(8009):788-794.

Biodiversity faces unprecedented threats from rapid global change[1]. Signals of biodiversity change come from time-series abundance datasets for thousands of species over large geographic and temporal scales. Analyses of these biodiversity datasets have pointed to varied trends in abundance, including increases and decreases. However, these analyses have not fully accounted for spatial, temporal and phylogenetic structures in the data. Here, using a new statistical framework, we show across ten high-profile biodiversity datasets[2-11] that increases and decreases under existing approaches vanish once spatial, temporal and phylogenetic structures are accounted for. This is a consequence of existing approaches severely underestimating trend uncertainty and sometimes misestimating the trend direction. Under our revised average abundance trends that appropriately recognize uncertainty, we failed to observe a single increasing or decreasing trend at 95% credible intervals in our ten datasets. This emphasizes how little is known about biodiversity change across vast spatial and taxonomic scales. Despite this uncertainty at vast scales, we reveal improved local-scale prediction accuracy by accounting for spatial, temporal and phylogenetic structures. Improved prediction offers hope of estimating biodiversity change at policy-relevant scales, guiding adaptive conservation responses.

RevDate: 2024-05-03

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: 2024-03-29

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: 2024-04-17
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: 2024-03-27
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: 2024-04-25
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: 2024-04-02
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: 2024-03-25
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: 2024-04-05
CmpDate: 2024-04-05

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), 40(4):.

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 duplication, transfer, and loss 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.

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

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

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Papers in Classical Genetics

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

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

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