bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Direct Capture Method for Purification and Detection of Viral Nucleic Acid Enables Epidemiological Surveillance of SARS-CoV-2
Authors: Mondal Subhanjan , Feirer Nathan , Brockman Michael , Preston Melanie A. , Teter Sarah J. , Ma Dongping , Goueli Said A. , Moorji Sameer , Saul Brigitta , Cali James J. 
Published: May 2021

AbstractStudies have demonstrated that SARS-CoV-2 RNA can be detected in the feces of infected individuals. This finding spurred investigation into using wastewater-based epidemiology (WBE) to monitor SARS-CoV-2 RNA and track the appearance and spread of COVID-19 in communities. SARS-CoV-2 is present at low levels in wastewater, making sample concentration a prerequisite for sensitive detection and utility in WBE. Whereas common methods for isolating viral genetic material are biased toward intact virus isolation, it is likely that a relatively low percentage of the total SARS-CoV-2 RNA genome in wastewater is contained within intact virions. Therefore, we hypothesized that a direct unbiased total nucleic acid extraction method could overcome the cumbersome protocols, variability and low recovery rates associated with the former methods. This led to development of a simple, rapid, and modular alternative to existing purification methods. In an initial concentration step, chaotropic agents are added to raw sewage allowing binding of nucleic acid from free nucleoprotein complexes, partially intact, and intact virions to a silica matrix. The eluted nucleic acid is then purified using manual or semi-automated methods. RT-qPCR enzyme mixes were formulated that demonstrate substantial inhibitor resistance. In addition, multiplexed probe-based RT-qPCR assays detecting the N1, N2 (nucleocapsid) and E (envelope) gene fragments of SARS-CoV-2 were developed. The RT-qPCR assays also contain primers and probes to detect Pepper Mild Mottle Virus (PMMoV), a fecal indicator RNA virus present in wastewater, and an exogenous control RNA to measure effects of RT-qPCR inhibitors. Using this workflow, we monitored wastewater samples from three wastewater treatment plants (WWTP) in Dane County, Wisconsin. We also successfully sequenced a subset of samples to ensure compatibility with a SARS-CoV-2 amplicon panel and demonstrated the potential for SARS-CoV-2 variant detection. Data obtained here underscore the potential for wastewater surveillance of SARS-CoV-2 and other infectious agents in communities.
Prodromal Progressive Supranuclear Palsy – insights from the UK Biobank
Authors: Street Duncan , Whiteside David , Rittman Timothy , Rowe James B 
Published: May 2021

AbstractBackgroundProdromal Parkinson’s Disease is well described but prodromal Progressive Supranuclear Palsy (PSP) is much less understood. The diagnosis of PSP is typically delayed by an average of three years after symptom onset. Understanding the changes that occur in the prodromal and pre-diagnostic period will aid earlier diagnosis, clarify the natural history, and aid the design of early disease-modifying therapy trials.ObjectivesTo determine motor and cognitive markers of prodromal PSP, with Parkinson’s disease as a comparator condition, in a large prospective cohort.MethodsBaseline UK Biobank data from 502,504 individuals were collected between 2006 and 2010. Subsequent PSP and Parkinson’s disease cases were identified from primary and secondary care electronic health records’ diagnostic coding data and death registry, with 5,404 matched controls.Results176 PSP cases (time to diagnosis 7.8±2.8 years) and 2,526 Parkinson’s disease cases (time to diagnosis 7.8±2.9 years) were identified. At baseline, those later diagnosed with PSP had slower reaction times, weaker hand grip, lower fluid intelligence, poorer prospective memory, worse self-rated health score and lower digit recall than controls. They had higher mortality than both Parkinson’s disease and control groups.ConclusionsMotor slowing, cognitive dysfunction, and postural instability are clinical diagnostic features of PSP and are typically symptomatic three years before diagnosis. However, objective markers of these features are evident over seven years before diagnosis. This suggests a long prodromal course in PSP with subtle changes in motor and cognitive function.
FishPhyloMaker: An R package to generate phylogenies for ray-finned fishes
Authors: Nakamura Gabriel , Richter Aline , Soares Bruno E. 
Published: May 2021

AbstractPhylogenies summarize evolutionary information that is essential in the investigation of ecological and evolutionary causes of diversity patterns. They allow investigating hypotheses from trait evolution to the relationship between evolutionary diversity and ecosystem functioning. However, obtaining a comprehensive phylogenetic hypothesis can be difficult for some groups, especially those with a high number of species, that is the case for fishes, particularly tropical ones. The lack of species in phylogenetic hypotheses, called Darwinian shortfalls, can hinder ecological and evolutionary studies involving this group. To tackle this problem, we developed FishPhyloMaker, an R package that facilitates the generation of phylogenetic trees through a reliable and reproducible procedure, even for a large number of species. The package adopts well-known rules of insertion based on cladistic hierarchy, allowing its use by specialists and non-specialists in fish systematics. We tested the reliability of our algorithm in maintaining important properties of phylogenetic distances running a sensitivity analysis. We also exemplified the use of the FishPhyloMaker package by constructing complete phylogenies for fishes inhabiting the four richest freshwater ecoregions of the world. Furthermore, we proposed a new method to calculate Darwinian shortfalls and mapped this information for the major freshwater drainages of the world. FishPhyloMaker will expand the range of evolutionary and ecological questions that can be addressed using ray-finned fishes as study models, mainly in the field of community phylogenetics, by providing an easy and reliable way to obtain comprehensive phylogenies. Further, FishPhyloMaker presents the potential to be extended to other taxonomic groups that suffer from the same difficulty in the obtention of comprehensive phylogenetic hypothesis.HighlightsWe provide the first automated procedure to check species names, construct phylogenetic trees and calculate Darwinian shortfalls for ray-finned fishes (Actinopterygii) by the R package FishPhyloMaker.This package provides functions to assemble phylogenies through a fast, reliable, and reproducible method, allowing its use and replicability by specialists and non-specialists in fish systematics.The package also provides an interactive procedure that gives more flexibility to the user when compared with other existing tools that construct phylogenetic trees for other highly speciose groups.The package includes a new method to compute Darwinian shortfalls for ray-finned fishes, but the rationale of the provided algorithm can be extended in future studies to be used in other groups of organisms
ENIGMA HALFpipe: Interactive, reproducible, and efficient analysis for resting-state and task-based fMRI data
Authors: Waller Lea , Erk Susanne , Pozzi Elena , Toenders Yara J. , Haswell Courtney C. , Büttner Marc , Thompson Paul M. , Schmaal Lianne , Morey Rajendra A. , Walter Henrik , Veer Ilya M. 
Published: May 2021

AbstractThe reproducibility crisis in neuroimaging has led to an increased demand for standardized data processing workflows. Within the ENIGMA consortium, we developedHALFpipe(HarmonizedAnaLysis ofFunctional MRI pipeline), an open-source, containerized, user-friendly tool that facilitates reproducible analysis of task-based and resting-state fMRI data through uniform application of preprocessing, quality assessment, single-subject feature extraction, and group-level statistics. It provides state-of-the-art preprocessing usingfMRIPrepwithout the requirement for input data in Brain Imaging Data Structure (BIDS) format.HALFpipeextends the functionality offMRIPrepwith additional preprocessing steps, which include spatial smoothing, grand mean scaling, temporal filtering, and confound regression.HALFpipegenerates an interactive quality assessment (QA) webpage to assess the quality of key preprocessing outputs and raw data in general.HALFpipefeatures myriad post-processing functions at the individual subject level, including calculation of task-based activation, seed-based connectivity, network-template (or dual) regression, atlas-based functional connectivity matrices, regional homogeneity (ReHo), and fractional amplitude of low frequency fluctuations (fALFF), offering support to evaluate a combinatorial number of features or preprocessing settings in one run. Finally, flexible factorial models can be defined for mixed-effects regression analysis at the group level, including multiple comparison correction. Here, we introduce the theoretical framework in whichHALFpipewas developed, and present an overview of the main functions of the pipeline.HALFpipeoffers the scientific community a major advance toward addressing the reproducibility crisis in neuroimaging, providing a workflow that encompasses preprocessing, post-processing, and QA of fMRI data, while broadening core principles of data analysis for producing reproducible results. Instructions and code can be found athttps://github.com/HALFpipe/HALFpipe.
Expansion of tissue-resident CD8+ T cells and CD4+ Th17 cells in the nasal mucosa following mRNA COVID-19 vaccination
Authors: Ssemaganda Aloysious , Nguyen Huong Mai , Nuhu Faisal , Jahan Naima , Card Catherine M. , Kiazyk Sandra , Severini Giulia , Keynan Yoav , Su Ruey-Chyi , Ji Hezhao , Abrenica Bernard , McLaren Paul J. , Ball T. Blake , Bullard Jared , Van Caeseele Paul , Stein Derek , McKinnon Lyle R. 
Published: May 2021

AbstractVaccines against SARS-CoV-2 have shown high efficacy in clinical trials, yet a full immunologic characterization of these vaccines, particularly within the upper respiratory tract, remains lacking. We enumerated and phenotyped T cells in nasal mucosa and blood before and after vaccination with the Pfizer-BioNTech COVID-19 vaccine (n =21). Tissue-resident memory (Trm) CD8+ T cells expressing CD69+CD103+ expanded ∼12 days following the first and second doses, by 0.31 and 0.43 log10cells per swab respectively (p=0.058 and p=0.009 in adjusted linear mixed models). CD69+CD103+CD8+ T cells in the blood decreased post-vaccination. Similar increases in nasal CD8+CD69+CD103-T cells were observed, particularly following the second dose. CD4+ Th17 cells were also increased in abundance following both doses. Following stimulation with SARS-CoV-2 spike peptides, CD8+ T cells increased expression of CD107a and CD154. These data suggest that nasal T cells may be induced and contribute to the protective immunity afforded by this vaccine.
Surface-based tracking for short association fibre tractography
Authors: Shastin Dmitri , Genc Sila , Parker Greg D. , Koller Kristin , Tax Chantal M.W. , Evans John , Hamandi Khalid , Gray William P. , Jones Derek K. , Chamberland Maxime 
Published: May 2021

AbstractIt is estimated that in the human brain, short association fibres (SAF) represent more than half of the total white matter volume and their involvement has been implicated in a range of neurological and psychiatric conditions. This population of fibres, however, remains relatively understudied in the neuroimaging literature. Some of the challenges pertinent to the mapping of SAF include their variable anatomical course and proximity to the cortical mantle, leading to partial volume effects and potentially affecting streamline trajectory estimation. This work considers the impact of seeding and filtering strategies and choice of scanner, acquisition, data resampling to propose a whole-brain, surface-based short (≤30-40 mm) SAF tractography approach. The framework is shown to produce longer streamlines with a predilection for connecting gyri as well as high cortical coverage. We further demonstrate that certain areas of subcortical white matter become disproportionally underrepresented in diffusion-weighted MRI data with lower angular and spatial resolution and weaker diffusion weighting; however, collecting data with stronger gradients than are usually available clinically has minimal impact, making our framework translatable to data collected on commonly available hardware. Finally, the tractograms are examined using voxel- and surfacebased measures of consistency, demonstrating moderate reliability, low repeatability and high between-subject variability, urging caution when streamline count-based analyses of SAF are performed.
The P2RX7B splice variant modulates osteosarcoma cell behaviour and metastatic properties
Authors: Tattersall Luke , Shah Karan M. , Lath Darren L. , Singh Archana , Down Jennifer M. , De Marchi Elena , Williamson Alex , Di Virgilio Francesco , Heymann Dominique , Adinolfi Elena , Fraser William D. , Green Darrell , Lawson Michelle A. , Gartland Alison 
Published: May 2021

AbstractOsteosarcoma (OS) is the most common type of primary bone cancer affecting children and adolescents. OS has a high propensity to spread, meaning the disease is often incurable and fatal. There have been no improvements in survival rates for decades. This highlights an urgent need for development of novel therapeutic strategies. In this study, we have producedin vitroandin vivodata that demonstrates the role of purinergic signalling, specifically, the B isoform of the purinergic receptor P2RX7 (herein termed “ P2RX7B”), in OS progression and metastasis. Our data shows that P2RX7B expression confers a survival advantage in TE85+P2RX7B and MNNG-HOS+ P2RX7B human OS cell linesin vitrothat is minimised following treatment with A740003, a specific P2RX7 antagonist. P2RX7B expression reduced cell adhesion and P2RX7B activation promoted invasion and migrationin vitro, suggesting a probable metastatic phenotype. Using anin vivoOS xenograft model, MNNG-HOS+P2RX7B tumours exhibited ectopic bone formation that was abrogated with A740003 treatment. An increased metastatic phenotype was further demonstratedin vivoas expression of P2RX7B in primary tumour cells increased the propensity of the tumour to metastasise to the lungs. RNA-seq identified a novel gene axis,FN1/LOX/PDGFB/IGFBP3/BMP4, downregulated in response to A740003 treatment. In conclusion, our data indicates for the first time a role for P2RX7B in OS tumour growth, progression and metastasis. We show that P2RX7B is a potential therapeutic target in human OS.Novelty and ImpactWe provide evidence for the pro-tumorigenic role of the B isoform of the P2RX7 purinergic receptor in osteosarcoma (OS). In addition to increasing proliferation, P2RX7B increases the cancerous properties of OS cells, reducing adhesion and increasing migration and invasion.In vivo, P2RX7B does not affect primary tumour growth, but does lead to an increased propensity to metastasize. RNA-seq revealed a new axis of oncogenic genes inhibited by the P2RX7 antagonist and this data could potentially lead to new targets for OS treatment.
Embeddings of genomic region sets capture rich biological associations in lower dimensions
Authors: Gharavi Erfaneh , Gu Aaron , Zheng Guangtao , Smith Jason P. , Zhang Aidong , Brown Donald E. , Sheffield Nathan C. 
Published: May 2021

MotivationGenomic region sets summarize functional genomics data and define locations of interest in the genome such as regulatory regions or transcription factor binding sites. The number of publicly available region sets has increased dramatically, leading to challenges in data analysis.ResultsWe propose a new method to represent genomic region sets as vectors, or embeddings, using an adapted word2vec approach. We compared our approach to two simpler methods based on interval unions or term frequency-inverse document frequency and evaluated the methods in three ways: First, by classifying the cell line, antibody, or tissue type of the region set; second, by assessing whether similarity among embeddings can reflect simulated random perturbations of genomic regions; and third, by testing robustness of the proposed representations to different signal thresholds for calling peaks. Our word2vec-based region set embeddings reduce dimensionality from more than a hundred thousand to 100 without significant loss in classification performance. The vector representation could identify cell line, antibody, and tissue type with over 90% accuracy. We also found that the vectors could quantitatively summarize simulated random perturbations to region sets and are more robust to subsampling the data derived from different peak calling thresholds. Our evaluations demonstrate that the vectors retain useful biological information in relatively lower-dimensional spaces. We propose that vector representation of region sets is a promising approach for efficient analysis of genomic region data.Availabilityhttps://github.com/databio/regionset-embedding
The Impact of Control Interface on Features of Heart Rate Variability
Authors: Javaremi Mahdieh Nejati , Wu Di , Argall Brenna 
Published: May 2021

AbstractShared human-robot control for assistive machines can improve the independence of individuals with motor impairments. Monitoring elevated levels of workload can enable the assistive autonomy to adjust the control-sharing in an assist-as-needed way, to achieve a balance between user fatigue, stress and independent control. In this work, we aim to investigate how heart-rate variability features can be utilized to monitor elevated levels of mental workload while operating a powered wheelchair, and how that utilization might vary under different control interfaces. To that end, we conducted a 22 person study with three commercial interfaces. Our results show that the validity and reliability of using the ultra-short-term heart-rate variability features as predictors for workload indeed are affected by the type of interface in use.
Multi-Modal Data Analysis for Alzheimer’s Disease Diagnosis: An Ensemble Model Using Imagery and Genetic Features
Authors: Ying Qi , Xing Xin , Liu Liangliang , Lin Ai-Ling , Jacobs Nathan , Liang Gongbo 
Published: May 2021

AbstractAlzheimer’s disease (AD) is a devastating neurological disorder primarily affecting the elderly. An estimated 6.2 million Americans age 65 and older are suffering from Alzheimer’s dementia today. Brain magnetic resonance imaging (MRI) is widely used for the clinical diagnosis of AD. In the meanwhile, medical researchers have identified 40 risk locus using single-nucleotide polymorphisms (SNPs) information from Genome-wide association study (GWAS) in the past decades. However, existing studies usually treat MRI and GWAS separately. For instance, convolutional neural networks are often trained using MRI for AD diagnosis. GWAS and SNPs are frequently used to identify genomic traits. In this study, we propose a multi-modal AD diagnosis neural network that uses both MRIs and SNPs. The proposed method demonstrates a novel way to use GWAS findings by directly including SNPs in predictive models. We test the proposed methods on the Alzheimer’s Disease Neuroimaging Initiative dataset. The evaluation results show that the proposed method improves the model performance on AD diagnosis and achieves 93.5% AUC and 96.1% AP, respectively, when patients have both MRI and SNP data. We believe this work brings exciting new insights to GWAS applications and sheds light on future research directions.
The integrated role of resource memory and scent-based territoriality in the emergence of home-ranges
Authors: Theng Meryl , Prowse Thomas A. A. , Delean Steven , Cassey Phillip , Bracis Chloe 
Published: May 2021

AbstractDespite decades of animal movement research, an integrated understanding of the processes underlying the emergence of home-ranges remains inadequate. We explored the effects of integrating two key processes of home-ranging arising from individual movement decisions: (i) memory-based resource use; and (ii) scent-based territoriality. Both mechanisms together led to the formation of exclusive, resource- and population density-dependent home-ranges, which were responsive to perturbations in the conspecific environment (i.e., removing individuals). Home-range patterns (size, size skewness and overlap) were primarily influenced by memory and scent decay rate parameters, demonstrating that home-ranging is ultimately a balance between an animal’s inherent exploratory tendency and its desire to avoid conspecifics. Model application to a population of feral cats demonstrated that general space use patterns could be approximated through simulation, and replication of finer-scale space use patterns is plausible with further model development. Our modelling framework provides a foundation for sophisticated theoretical models of space use in interacting animals.
Short-interval fires and vegetation change in southern California
Authors: Lucero Stephanie M. , Emery Nathan C. , D’Antonio Carla M. 
Published: May 2021

AbstractQuestionsIn southern California, shortened fire return intervals may contribute to a decrease in native chaparral shrub presence and an increase in non-native annual grass presence. To test the hypothesis that short-fire return intervals promote a loss in shrub cover, we examined the contribution of single short-interval fires and abiotic conditions on the change of shrub cover within Ventura and Los Angeles counties. Through evaluating pre- and post-fire historical aerial images, we answered the following questions, 1) How has vegetation type cover changed after repeat fires? and 2) What landscape variables contribute the most to the observed change?LocationVentura County and Los Angeles County, California, USA.MethodsWe assessed the impact of a single short-interval fire by comparing vegetation recovery in adjacent once- and twice-burned fire burn polygons (long- and short-interval respectively). Pixel plots were examined within each polygon and vegetation cover was classified to vegetation type. We determined the best predictor of vegetation type cover with a linear mixed effects model comparison using Akaike Information Criterion.ResultsPre-fire and post-fire community type cover was highly correlated. Burn interval was the best predictor of tree cover change (lower cover in twice-burned pixel plots). Aspect was the best predictor of sage scrub cover change (greater cover on north-facing aspects). Years since fire was the best predictor of chaparral cover change (positive correlation) and sage scrub cover change (negative correlation). Conversion of chaparral to sage scrub cover was more likely to occur than conversion of chaparral to annual grass cover.ConclusionsOur study did not find extensive evidence of a decrease in chaparral shrub cover due to a single short-interval fire. Instead, post-fire cover was highly correlated with pre-fire cover. Chaparral recovery, however, was dynamic suggesting that stand recovery may be strongly influenced by local scale conditions and processes.