bluuebunny/crossref_metadata_2025_split huggingface dataset:
Discovery of SARS-CoV-2 papain-like protease inhibitors through a combination of high-throughput screening and FlipGFP-based reporter assay
Authors: Xia Zilei , Sacco Michael Dominic , Ma Chunlong , Townsend Julia Alma , Kitamura Naoya , Hu Yanmei , Ba Mandy , Szeto Tommy , Zhang Xiujun , Meng Xiangzhi , Zhang Fushun , Xiang Yan , Marty Michael Thomas , Chen Yu , Wang Jun 
Published: March 2021

AbstractThe papain-like protease (PLpro) of SARS-CoV-2 is a validated antiviral drug target. PLprois involved in the cleavage of viral polyproteins and antagonizing host innate immune response through its deubiquitinating and deISG15ylating activities, rendering it a high profile antiviral drug target. Through a FRET-based high-throughput screening, several hits were identified as PLproinhibitors with IC50values at the single-digit micromolar range. Subsequent lead optimization led to potent inhibitors with IC50values ranging from 0.56 to 0.90 µM. To help prioritize lead compounds for the cellular antiviral assay against SARS-CoV-2, we developed the cell-based FlipGFP assay that is suitable for quantifying the intracellular enzymatic inhibition potency of PLproinhibitors in the BSL-2 setting. Two compounds selected from the FlipGFP-PLproassay, Jun9-53-2 and Jun9-72-2, inhibited SARS-CoV-2 replication in Caco-2 hACE2 cells with EC50values of 8.89 and 8.32 µM, respectively, which were 3-fold more potent than GRL0617 (EC50= 25.1 µM). The X-ray crystal structures of PLproin complex with GRL0617 showed that binding of GRL0617 to SARS-CoV-2 induced a conformational change in the BL2 loop to the more closed conformation. Overall, the PLproinhibitors identified in this study represent promising starting points for further development as SARS-CoV-2 antivirals, and FlipGFP-PLproassay might be a suitable surrogate for screening PLproinhibitors in the BSL-2 setting.
Antibiotic Resistance inBacillus-based Biopesticide Products
Authors: Kaze Mo , Brooks Lauren , Sistrom Mark 
Published: March 2021

AbstractThe crisis of antibiotic resistant bacterial infections is one of the most pressing public health issues. Common agricultural practices have been implicated in the generation of antibiotic resistant bacteria. Biopesticides, live bacteria used for pest control, are non-pathogenic and considered safe for consumption. Application of bacteria-based pesticides to crops in high concentrations raises the possibility of unintentional contributions to the movement and generation of antibiotic resistance genes in the environment. However, the presence of clinically relevant antibiotic resistance genes and their resistance phenotypes are currently unknown. Here we use a combination of multiple bioinformatic and microbiological techniques to define resistomes of widely used biopesticides and determine how the presence of suspected antibiotic resistance genes translates to observable resistance phenotypes in several biopesticide products. Our results demonstrate that biopesticide products are reservoirs of clinically relevant antibiotic resistance genes and bear resistance to multiple drug classes.ImportanceThis is the first study to specifically address antibiotic resistance in widely distributed bacterial strains used as commercial biopesticides. Safety assessments of commercial live bacterial biopesticide products do not include antibiotic resistance phenotype identification. We identify antibiotic resistance genes in all live bacterial strains examined, and resistant phenotypes in all strains tested for antibiotic susceptibility. This work demonstrates that biopesticides potentially play a critical role as reservoirs and vectors of antibiotic resistance in the broader environmental resistome that is to date, unstudied.
The course of the UK COVID 19 pandemic; no measurable impact of new variants
Authors: Ellis D , Papadopoulos D , Mukherjee S , Ukwu U , Chari N , Charitopoulos K , Donkov I , Bishara S 
Published: March 2021

AbstractIntroductionIn November 2020, a new SARS-COV-2 variant or the ‘Kent variant’ emerged in the UK, and became the dominant UK SARS-COV-2 variant, demonstrating faster transmission than the original variant, which rapidly died out. However, it is unknown if this altered the overall course of the pandemic as genomic analysis was not common place at the outset and other factors such as the climate could alter the viral transmission rate over time. We aimed to test the hypothesis that the overall observed viral transmission was not altered by the emergence of the new variant, by testing a model generated earlier in the pandemic based on lockdown stringency, temperature and humidity.MethodsFrom 1/1/20 to 4/2/21, the daily incidence of SARS-COV-2 deaths and the overall stringency of National Lockdown policy on each day was extracted from the Oxford University Government response tracker. The daily average temperature and humidity for London was extracted from Wunderground.com.The viral reproductive rate was calculated on a daily basis from the daily mortality data for each day. The correlation between log10 of viral reproductive rate and lockdown stringency and weather parameters were compared by Pearson correlation to determine the time lag associated with the greatest correlation.A multivariate model for the log10 of viral reproductive rate was constructed using lockdown stringency, temperature and humidity for the period 1/1/20 to 30/9/20. This model was extrapolated forward from 1/10/20 to 4/2/21 and the predicted viral reproductive rate, daily mortality and cumulative mortality were compared with official data.ResultsOn multivariate linear regression, the optimal model had and R2 0f 0.833 for prediction of log10 viral reproductive rate 13 days later in the model construction period, with (coefficient, probability) lockdown stringency (−0.0109, p=0.0000), humidity (0.0038, p=0.0041) and temperature (−0.0035, p=0.0008). When extrapolated to the validation period (1/10/20 to 4/2/21), the model was highly correlated with daily (Pearson coefficient 0.88, p=0.0000) and cumulated SARS-COV-2 mortality (Pearson coefficient 0.99, p=0.0000).ConclusionThe course of the SARS-COV-2 pandemic in the UK seems highly predicted by an earlier model based on the lockdown stringency, humidity and temperature and unaltered by the emergence of a newer viral genotype.
Patterns of compliance with COVID-19 preventive behaviours: a latent class analysis of 20,000 UK adults
Authors: Wright Liam , Steptoe Andrew , Fancourt Daisy 
Published: March 2021

AbstractBackgroundGovernments have implemented a range of measure to tackle COVID-19, primarily focusing on changing citizens’ behaviours in order to lower transmission of the virus. Few studies have looked at the patterns of compliance with different measures within individuals: whether people comply with all measures or selectively choose some but not others. Such research is important for designing interventions to increase compliance.MethodsWe used cross-sectional data from 20,947 UK adults in the COVID-19 Social Study collected 17 November – 23 December 2020. Self-report compliance was assessed with six behaviours: mask wearing, hand washing, indoor household mixing, outdoor household mixing, social distancing, and compliance with other guidelines. Patterns of compliance behaviour were identified using latent class analysis, and multinomial logistic regression was used to assess demographic, socioeconomic and personality predictors of behaviour patterns.ResultsWe selected a four latent class solution. Most individuals reported similar levels of compliance across the six behaviour measures. High levels of compliance was the modal response. Lower self-reported compliance was related to young age, high risk-taking behaviour, low confidence in government, and low empathy, among other factors. Looking at individual behaviours, mask wearing had the highest level of compliance whilst compliance with social distancing was relatively low.ConclusionResults suggest that individuals choose to comply with all guidelines, rather than some but not others. Strategies to increase compliance should focus on increasing general motivations to comply alongside specifically encouraging social distancing.
RCytoGPS: An R Package for Reading and Visualizing Cytogenetics Data
Authors: Abrams Zachary B. , Tally Dwayne G. , Abruzzo Lynne V. , Coombes Kevin R. 
Published: March 2021

AbstractSummaryCytogenetics data, or karyotypes, are among the most common clinically used forms of genetic data. Karyotypes are stored as standardized text strings using the International System for Human Cytogenomic Nomenclature (ISCN). Historically, these data have not been used in large-scale computational analyses due to limitations in the ISCN text format and structure. Recently developed computational tools such as CytoGPS have enabled large-scale computational analyses of karyotypes. To further enable such analyses, we have now developed RCytoGPS, an R package that takes JSON files generated from CytoGPS.org and converts them into objects in R. This conversion facilitates the analysis and visualizations of karyotype data. In effect this tool streamlines the process of performing large-scale karyotype analyses, thus advancing the field of computational cytogenetic pathology.Availability and ImplementationFreely available athttps://CRAN.R-project.org/package=RCytoGPSSupplementary informationSupplementary data are available atBioinformaticsonline.
BugSeq 16S: NanoCLUST with Improved Consensus Sequence Classification
Authors: Jung Ana , Chorlton Samuel D 
Published: March 2021

AbstractNanoCLUST has enabled species-level taxonomic classification from noisy nanopore 16S sequencing data for BugSeq’s users and the broader nanopore sequencing community. We noticed a high misclassification rate of NanoCLUST-derived consensus 16S sequences due to its use of BLAST top hit taxonomy assignment. We replaced the consensus sequence classifier of NanoCLUST with QIIME2’s VSEARCH-based classifier to enable greater accuracy. We use mock microbial community and clinical 16S sequencing data to show that this replacement results in significantly improved nanopore 16S accuracy (over 5% recall and 19% precision), and make this new tool (BugSeq 16S) freely available for academic use atBugSeq.com/free.
Response of soil and vegetation in a warm-temperate Pine forest to intensive biomass harvests, phosphorus fertilisation, and wood ash application
Authors: Augusto Laurent , Beaumont Florent , Nguyen Christophe , Fraysse Jean-Yves , Trichet Pierre , Meredieu Céline , Vidal David , Sappin-Didier Valérie 
Published: March 2021

AbstractBackground and AimsConcerns about climate change and carbon economy have prompted the promotion of alternative energy sources, including forest-based bioenergy. An evaluation of the environmental consequences of intensive harvests (stumps and roots, and also branches and foliage) for energy wood supply, and use of wood-ash recycling as a compensatory practice, helps in the evaluation of the use of forest biomass for energy production.MethodsWe made use of records from a split-plot experimental site crossing four different intensities of biomass harvesting (Stem-Only Harvest [SOH], Aboveground Additional Harvest [AAH], Belowground Additional Harvest [BAH], and Whole-Tree Harvest [WTH]) and three compensation methods (control [C], wood ash application [A] and phosphorus fertilisation [P]) to evaluate, in the 11-years-old stand (maritime pine:Pinus pinaster) that followed the biomass exports of the former stand, their effects on nutrient budgets, tree growth, soil fertility, chemical properties and soil carbon. This site is located in a forest on a poor soil, under a warm temperate climate (SW France).Key resultsDespite their low additional biomass exports (+10% for AAH to +34% for WTH), the non-conventional harvest practices exported much higher quantities of nutrients than the conventional SOH technique (for example +145% for N and K in WTH). Consequently, these treatments had negative effects on the soil nutritive status. Additional biomass harvests impacted the soil organic matter content, with negative effects on P-organic, soil cation exchange capacity, exchangeable Ca, and most extractible nutrients. However, data suggested that tree growth and foliage nutrient content had not yet been significantly impacted by harvest treatments, whereas tree nutritional status was improved by P-fertiliser or wood ash. As expected, we observed a positive effect of wood ash application on soil pH and nutrient content but, like additional harvests, wood ash application decreased the pool of soil organic carbon (~10% of the initial stock with ~7% of N-totallosses).ConclusionsOverall, this factorial experiment showed that exporting more forest biomass due to the additional harvesting of tree canopies, stumps and roots had negative consequences on the ecosystem biogeochemistry. Additional harvests have aggravated the poverty of the already oligotrophic soil, and decreased the soil organic carbon content. Importantly, applying nutrients as fertiliser or wood ash did not compensate for all the negative impacts of biomass exports and the method of wood ash recycling in forests could even decrease the soil organic carbon.
Response ofrhizobialstrains on biochemical traits and nutrient uptake in Mungbean Vigna radiata L. Wilczek under moisture stress
Authors: Sapna  , Sharma K. D 
Published: March 2021

AbstractThe present study was conducted to assess the biochemical responses and nutrient uptake in response torhizobialinoculations in mungbean, and to screen therhizobialisolates for drought tolerance. A field experiment was designed in randomized block design and replicated thrice duringkharif2016 at Crop Physiology Field Area, CCS, Hisar. The experiment consisted of two levels of treatments (1) without inoculation (only RDF) and (2) with inoculation (RDF with combination of fiverhizobialstrains viz.Vigna703 + PSB strain P-36, MR 63, MR 54, MB 17a and MH 8b2) and two environments i.e. rainfed (no post sowing irrigation) and irrigated. Membrane stability index, leghaemoglobin content, chlorophyll content reduced by 17.7 %, 24.5% and 2.9% resp. under rainfed conditions while the plants inoculated withrhizobialisolate MR63 and MB 17a showed greater chlorophyll content (20.2% and 16.2%), LHb (29.1% and 22.9%) and MSI (19.4% and 17.9%) and enhanced nutrient uptake over RDF.
Thermal biology of two sympatric Lacertids lizards (Lacerta diplochondrodesandParvilacerta parva) from Western Anatolia
Authors: Şahin Mehmet Kürşat , Kuyucu Arda Cem 
Published: March 2021

AbstractSympatric lizard species differing in morphology present convenient models for studying the differentiation in thermal behavior and the role of morphological differences in thermal biology. Here we studied the thermal biology of two sympatric lizard species which occur together sympatrically in western Anatolia, Frig Valley. These two species differ in body size, with the largerLacerta diplochondrodesand smallerParvilacerta parva. Field body temperatures of the individuals belonging to both species were recorded in the activity period. Additionally, several environmental parameters including solar radiation, substrate temperature, air temperature and wind speed were also monitored to investigate the relative effect of these abiotic parameters on thermal biology of the two species. The field body temperature and temperature excess (difference between body and substrate temperature) of two species while being relatively close to each other, showed seasonal differences. Solar radiation, substrate temperature and air temperature were the main effective factors on thermal biology in the field. Additionally, although body size did not have a direct significant effect on body temperature or temperature excess, the interaction between body size and wind were effective on temperature excess. In conclusion, our study partially supports the conservation of thermal biology of related lizard species.
Proteome remodeling in theMycobacterium tuberculosisPknG knockout: molecular evidence for the role of this kinase in cell envelope biogenesis and hypoxia response
Authors: Lima Analía , Leyva Alejandro , Rivera Bernardina , Portela María Magdalena , Gil Magdalena , Cascioferro Alessandro , Lisa María-Natalia , Wehenkel Annemarie , Bellinzoni Marco , Carvalho Paulo C. , Batthyány Carlos , Alvarez María N. , Brosch Roland , Alzari Pedro M. , Durán Rosario 
Published: March 2021

ABSTRACTMycobacterium tuberculosis, the etiological agent of tuberculosis, is among the deadliest human pathogens. One ofM. tuberculosis’s pathogenic hallmarks is its ability to persist in a dormant state in the host for long periods, reinitiating the infectious cycle when favorable environmental conditions are found. Thus, it is not surprising that this pathogen has developed different mechanisms to withstand the stressful conditions found in the host. In particular, the Ser/Thr protein kinase PknG has gained special relevance since it regulates nitrogen metabolism and facilitates bacterial survival inside macrophages. Nevertheless, the molecular mechanisms underlying these effects are far from being elucidated. To further investigate these issues, we performed quantitative proteomics analyses of protein extracts fromM. tuberculosisH37Rv and a mutant derivative lackingpknG. Our results showed that in the absence of PknG the mycobacterial proteome was remodeled since 5.7% of the proteins encoded byM. tuberculosispresented significant changes in its relative abundance when compared to the wild-type strain. The main biological processes affected bypknGdeletion were the biosynthesis of cell envelope components and the response to hypoxic conditions. As many as 13 DosR-regulated proteins were underrepresented in thepknGdeletion mutant, including the distinctive Hrp-1, which was found to be 12-fold decreased according to Parallel Reaction Monitoring experiments. Altogether, the results presented here allow us to postulate that PknG regulation of bacterial adaptation to stress conditions might be an important mechanism underlying its reported effect on intracellular bacterial survival.
Moving outside the lab: markerless motion capture accurately quantifies sagittal plane kinematics during the vertical jump
Authors: Drazan John F , Phillips William T , Seethapathi Nidhi , Hullfish Todd J , Baxter Josh R 
Published: March 2021

ABSTRACTMarkerless motion capture using deep learning approaches have potential to revolutionize the field of biomechanics by allowing researchers to collect data outside of the laboratory environment, yet there remain questions regarding the accuracy and ease of use of these approaches. The purpose of this study was to apply a markerless motion capture approach to extract lower limb angles in the sagittal plane during the vertical jump and to evaluate agreement between the custom trained model and gold stand motion capture. We performed this study using a large open source data set (N=84) that included synchronized commercial video and gold standard motion capture. We split these data into a training set for model development (n=69) and test set to evaluate capture performance relative to gold standard motion capture using coefficient of multiple correlations (CMC) (n=15). We found very strong agreement between the custom trained markerless approach and marker-based motion capture within the test set across the entire movement (CMC>0.991, RMSE<3.22°), with at least strong CMC values across all trials for the hip (0.853 ± 0.23), knee (0.963 ± 0.471), and ankle (0.970 ± 0.055). The strong agreement between markerless and marker-based motion capture provides evidence that markerless motion capture is a viable tool to extend data collection to outside of the laboratory. As biomechanical research struggles with representative sampling practices, markerless motion capture has potential to transform biomechanical research away from traditional laboratory settings into venues convenient to populations that are under sampled without sacrificing measurement fidelity.
Decoding the Information Structure Underlying the Neural Representation of Concepts
Authors: Fernandino Leonardo , Tong Jia-Qing , Conant Lisa L. , Humphries Colin J. , Binder Jeffrey R. 
Published: March 2021

AbstractThe nature of the representational code underlying conceptual knowledge remains a major unsolved problem in cognitive neuroscience. We assessed the extent to which different representational systems contribute to the instantiation of lexical concepts in high-level, heteromodal cortical areas previously associated with semantic cognition. We found that lexical semantic information can be reliably decoded from a wide range of heteromodal cortical areas in frontal, parietal, and temporal cortex. In most of these areas, we found a striking advantage for experience-based representational structures (i.e., encoding information about sensory-motor, affective, and other features of phenomenal experience), with little evidence for independent taxonomic or distributional organization. These results were found independently for object and event concepts. Our findings indicate that concept representations in heteromodal cortex are based, at least in part, on experiential information. They also reveal that, in most heteromodal areas, event concepts have more heterogeneous representations (i.e., they are more easily decodable) than object concepts, and that other areas beyond the traditional “semantic hubs” contribute to semantic cognition, particularly the posterior cingulate gyrus and the precuneus.
Buffering Updates Enables Efficient Dynamic de Bruijn Graphs
Authors: Alanko Jarno , Alipanahi Bahar , Settle Jonathen , Boucher Christina , Gagie Travis 
Published: March 2021

AbstractMotivationThe de Bruijn graph has become a ubiquitous graph model for biological data ever since its initial introduction in the late 1990s. It has been used for a variety of purposes including genome assembly (Zerbino and Birney, 2008; Bankevich et al., 2012; Peng et al., 2012), variant detection (Alipanahi et al., 2020b; Iqbal et al., 2012), and storage of assembled genomes (Chikhi et al., 2016). For this reason, there have been over a dozen methods for building and representing the de Bruijn graph and its variants in a space and time efficient manner.ResultsWith the exception of a few data structures (Muggli et al., 2019; Holley and Melsted, 2020; Crawford et al., 2018), compressed and compact de Bruijn graphs do not allow for the graph to be efficiently updated, meaning that data can be be added or deleted. The most recent compressed dynamic de Bruijn graph (Alipanahi et al., 2020a), relies on dynamic bit vectors which are slow in theory and practice. To address this shortcoming, we present a compressed dynamic de Bruijn graph that removes the necessity of dynamic bit vectors by buffering data that should be added or removed from the graph. We implement our method, which we refer to as BufBOSS, and compare its performance to Bifrost, DynamicBOSS, and FDBG. Our experiments demonstrate that BufBOSS achieves attractive trade-offs compared to other tools in terms of time, memory and disk, and has the best deletion performance by an order of magnitude.Contactalanko.jarno@gmail.com