bluuebunny/crossref_metadata_2025_split huggingface dataset:
Divergent impact of grazing on plant communities of created wetlands with varying hydrology and antecedent land use
Authors: Lodge Kimberly A. , Tyler Anna Christina 
Published: June 2020

AbstractDestruction of natural wetlands has warranted the creation of wetlands to mitigate the reduction of valuable ecosystem functions and services. However, the complex interactions between key drivers of wetland community structure – hydrology, nutrient availability and herbivory – makes creation of functional wetland replacements challenging. We examined interactions among these drivers, and their impacts on plant communities and soil characteristics in two created wetlands with different hydrology and land use histories: a shallow emergent marsh on a previous gravel depository and a seasonally flooded marsh on a former cattle pasture. In paired plots open to or protected from large wetland grazers we observed seasonal variation in grazing impacts on plant communities and an increase in effect size over time. At the permanently flooded marsh with high grazing waterfowl densities and low nutrients, open plots had significantly reduced plant growth and diversity, and an increase in submerged vegetation. In contrast, grazer density was lower and nutrients were higher in the seasonally flooded marsh, where grazer access enhanced plant diversity and reduced invasive plant cover. These results suggest the possibility of long-term grazer-induced shifts in community composition and delivery of key ecosystem services in young, vulnerable created wetlands. To improve created wetland design and function, we suggest that in addition to hydrologic conditions, the impact of prior land use on present nutrient availability be considered. Further, enhanced heterogeneity of spatial and bathymetric structure can provide conditions for diverse plant communities and balanced habitat use by wetland grazers.
A visual atlas of meiotic protein dynamics in living fission yeast
Authors: Escorcia Wilber , Tripathi Vishnu P. , Yuan Ji-Ping , Forsburg Susan L. 
Published: June 2020

AbstractMeiosis is a carefully choreographed dynamic process that re-purposes proteins from somatic/vegetative cell division, as well as meiosis-specific factors, to carry out the differentiation and recombination pathway common to sexually reproducing eukaryotes. Studies of individual proteins from a variety of different experimental protocols can make it difficult to compare details between them. Using a consistent protocol in otherwise wild type fission yeast cells, this report provides an atlas of dynamic protein behavior of representative proteins at different stages during normal zygotic meiosis in fission yeast. This establishes common landmarks to facilitate comparison of different proteins and shows that initiation of S phase likely occurs prior to nuclear fusion/karyogamy.SummaryMeiosis is an important process for sexually reproducing organisms. Unique dynamics of recombination and chromosome segregation are required for this differentiation process. Fission yeast is an excellent model to study meiotic progression and chromosome dynamics. Historically, different methodologies have been used to examine protein dynamics in fixed or live cells, which makes comparisons more difficult. In this report, we use fluorescently tagged proteins and live-cell microscopy under uniform conditions to compare meiotic signposts that define dynamic behavior of proteins during meiotic DNA synthesis, nuclear fusion, chromosome alignment, genetic recombination, metaphase, and meiosis. This establishes a reference atlas of protein behavior during meiotic differentiation.
Predicting tumour mutational burden from histopathological images using multiscale deep learning
Authors: Jain Mika S , Massoud Tarik F 
Published: June 2020

ABSTRACTTumour mutational burden (TMB) is an important biomarker for predicting response to immunotherapy in cancer patients. Gold-standard measurement of TMB is performed using whole exome sequencing (WES), which is not available at most hospitals owing to its high cost, operational complexity, and long turnover times. We developed a machine learning algorithm, Image2TMB, which can predict TMB from readily available lung adenocarcinoma histopathological images. Image2TMB integrates the predictions of three deep learning models that operate at different resolution scales (5X, 10X, and 20X magnification) to determine if the TMB of a cancer is high or low. On a held-out set of patients, Image2TMB achieves an area under the precision recall curve of 0.92, an average precision of 0.89, and has the predictive power of a targeted sequencing panel of approximately 100 genes. This study demonstrates that it is possible to infer genomic features from histopathology images, and potentially opens avenues for exploring genotype-phenotype relationships.
Differences in movement and dynamic resource selection between breeders and floaters revealed with an Ornstein-Uhlenbeck space use model
Authors: Eisaguirre Joseph M. , Booms Travis L. , Barger Christopher P. , Lewis Stephen B. , Breed Greg A. 
Published: June 2020

AbstractIn populations of many taxa, a large fraction of sexually mature individuals do not breed but are attempting to enter the breeding population. Such individuals, often referred to as “floaters” play critical roles in determining dynamics and stability of these populations. Floaters are difficult to study, however, so we lack data on the roles they play in population ecology and conservation status of many species. Here, we paired satellite telemetry and a new mechanistic space use model based on an Ornstein-Uhlenbeck process to study the differential habitat selection and space use of floater and territorial golden eaglesAquila chrysaetos. Our sample consisted of 49 individuals tracked over complete breeding seasons across four years, totalling 104 eagle breeding seasons. Modeling these data with the new mechanistic approach was required to parse key differences in movement and separate aspects of resource selection from central place behavior. We found that floaters generally had more expansive space use patterns and larger home ranges, partitioning space with territorial individuals seemingly on fine scales through differential habitat and resource selection. Floater and territorial eagle home ranges overlapped markedly, suggesting floaters use the interstices between territories. Further, floater and territorial eagles differed in how they selected for uplift variables, key components of soaring birds’ energy landscape, with territorial eagles apparently better able to find and use thermal uplift. We also found relatively low individual heterogeneity in resource selection, especially among territorial individuals, suggesting a narrow realized niche for breeding individuals. This work furthers our understanding of floaters’ potential roles in population ecology of territorial species, as well as suggests that conserving landscapes occupied by territorial eagles also protects floaters.
Protective Antibodies Against Human Parainfluenza Virus Type 3 (HPIV3) Infection
Authors: Boonyaratanakornkit Jim , Singh Suruchi , Weidle Connor , Rodarte Justas , Bakthavatsalam Ramasamy , Perkins Jonathan , Stewart-Jones Guillaume B.E. , Kwong Peter D. , McGuire Andrew T. , Pancera Marie , Taylor Justin J. 
Published: June 2020

ABSTRACTHuman parainfluenza virus type III (HPIV3) is a common respiratory pathogen that afflicts children and can be fatal in vulnerable populations, including the immunocompromised. Unfortunately, an effective vaccine or therapeutic is not currently available, resulting in tens of thousands of hospitalizations per year. In an effort to discover a protective antibody against HPIV3, we screened the B cell repertoires from peripheral blood, tonsils, or spleen from healthy children and adults. These analyses yielded five monoclonal antibodies that potently neutralized HPIV3in vitro. These HPIV3 neutralizing antibodies targeted two non-overlapping epitopes of the HPIV3 F protein, with most targeting the apex. Importantly, prophylactic administration of one of these antibodies, named PI3-E12, resulted in potent protection against HPIV3 infection in cotton rats. Additionally, PI3-E12 could also be used therapeutically to suppress HPIV3 in immunocompromised animals. These results demonstrate the potential clinical utility of PI3-E12 for the prevention or treatment of HPIV3 in both immunocompetent and immunocompromised individuals.
Red fox viromes across an urban-rural gradient
Authors: Campbell Sarah J , Ashley Wilbur , Gil-Fernandez Margarita , Newsome Thomas M. , Di Giallonardo Francesca , Ortiz-Baez Ayda Susana , Mahar Jackie E , Towerton Alison L , Gillings Michael , Holmes Edward C , Carthey Alexandra JR , Geoghegan Jemma L 
Published: June 2020

AbstractThe Red fox (Vulpes vulpes) has established large populations in Australia’s urban and rural areas since its introduction following European settlement. Foxes’ cryptic and highly adaptable nature allows them to invade cities and live among humans while remaining largely unnoticed. Urban living and access to anthropogenic food resources also influences fox ecology. Urban foxes grow larger, live at higher densities and are more social than their rural counterparts. These ecological changes in urban red foxes are likely to impact the pathogens that they harbour, and foxes could pose a disease risk to humans and other species that share these urban spaces. To assess this possibility, we used a meta-transcriptomic approach to characterise the viromes of urban and rural foxes across the Greater Sydney region in Australia. Urban and rural foxes differed significantly in virome composition, with rural foxes harbouring a greater abundance of viruses compared to their urban counterparts. In contrast, urban fox viromes comprised a greater diversity of viruses compared to rural foxes. We identified nine potentially novel vertebrate-associated viruses in both urban and rural foxes, some of which are related to viruses associated with disease in domestic species and humans. These included members of theAstroviridae, Picobirnaviridae, HepeviridaeandPicornaviridaeas well as rabbit haemorrhagic disease virus-2 (RHDV2). This study sheds light on the viruses carried by urban and rural foxes and emphasises the need for greater genomic surveillance of foxes and other invasive species at the human-wildlife interface.ImportanceUrbanisation of wild environments is increasing as human populations continue to expand. Remnant pockets of natural environments and other green spaces in urban landscapes provide invasive wildlife such as red foxes with refuges within urban areas, where they thrive on the food resources provisioned by humans. Close contact between humans, domestic species and foxes likely increases the risk of novel pathogen emergence. Indeed, the vast majority of emerging infectious diseases in humans originate in wild animals. Here, we explored potential differences in viromes between urban fox invaders and their rural counterparts. Viromes of foxes and their ectoparasites comprise a diversity of viruses including those from theAstroviridae, Picobirnaviridae, Hepeviridae, CaliciviridaeandPicornaviridae. Microbial surveillance in foxes and other urban wildlife is vital for monitoring viral emergence and for the prevention of infectious diseases.
An integrated gene catalog of the zebrafish gut microbiome reveals significant homology with mammalian microbiomes
Authors: Gaulke Christopher A. , Beaver Laura M. , Armour Courtney R. , Humphreys Ian R. , Barton Carrie L. , Tanguay Robyn L. , Ho Emily , Sharpton Thomas J. 
Published: June 2020

AbstractGut microbiome research increasingly utilizes zebrafish (Danio rerio) given their amenability to high-throughput experimental designs. However, the utility of zebrafish for discerning translationally relevant host-microbiome interactions is constrained by a paucity of knowledge about the biological functions that zebrafish gut microbiota can execute, how these functions associate with zebrafish physiology, and the degree of homology between the genes encoded by the zebrafish and human gut microbiomes. To address this knowledge gap, we generated a foundational catalog of zebrafish gut microbiome genomic diversity consisting of 1,569,102 non-redundant genes from twenty-nine individual fish. We identified hundreds of novel microbial genes as well as dozens of biosynthetic gene clusters of potential clinical interest. The genomic diversity of the zebrafish gut microbiome varied significantly across diets and this variance associated with altered expression of intestinal genes involved in inflammation and immune activation. Zebrafish, mouse, and human fecal microbiomes shared > 50% of their total genomic diversity and the vast majority of gene family abundance for each individual metagenome (∼99%) was accounted for by genes that comprised this shared fraction. These results indicate that the zebrafish gut houses a functionally diverse microbial community that manifests extensive homology to that of humans and mice despite substantial disparities in taxonomic composition. We anticipate that the gene catalog developed here will enable future mechanistic study of host-microbiome interactions using the zebrafish model.ImportanceZebrafish have emerged as an important model system for defining host-microbiome interactions. However, the utility of this model is blunted by limited insight into the functions that are carried by zebrafish gut microbiota, their relationship with zebrafish physiology, and their consistency with the functions carried by human gut microbiota. To address these limitations, we constructed the first genomic database of zebrafish gut microbiome diversity. We use this novel resource to demonstrate that the genomic diversity of the zebrafish gut microbiome varies with diet and this variance links with altered intestinal gene expression. We also identify substantial homology between zebrafish, human, and mouse metagenomic diversity, indicating that these microbiomes may operate similarly.
The role of hippocampal theta oscillations in working memory impairment in multiple sclerosis
Authors: Costers Lars , Van Schependom Jeroen , Laton Jorne , Baijot Johan , Sjøgård Martin , Wens Vincent , De Tiège Xavier , Goldman Serge , D’Haeseleer Miguel , D’hooghe Marie Beatrice , Woolrich Mark , Nagels Guy 
Published: June 2020

AbstractWorking memory (WM) problems are frequent in persons with multiple sclerosis (MS). Even though hippocampal damage has been repeatedly shown to play an important role, the underlying neurophysiological mechanisms remain unclear. This study aimed to investigate the neurophysiological underpinnings of WM impairment in MS using magnetoencephalography (MEG) data from a verbal n-back task. We analysed MEG recordings of 79 MS patients and 38 healthy subjects through event-related fields (ERFs) and theta (4-8 Hz) and alpha (8-13 Hz) oscillatory processes. Data was source reconstructed and parcellated based on previous findings in the healthy subject sample. MS patients showed a smaller maximum theta power increase in the right hippocampus between 0 and 400 ms than healthy subjects (p = 0.014). This theta power increase value correlated strongly and negatively with reaction time on the task in MS (r = −0.32, p = 0.029). Evidence was provided that this relationship could not be explained by a confounding relationship with MS-related neuronal damage. This study provides the first neurophysiological evidence of the influence of hippocampal dysfunction on WM performance in MS.
Variations in the Circle of Willis in a large population sample using 3D TOF angiography: The Tromsø Study
Authors: Hindenes Lars B. , Håberg Asta K. , Johnsen Liv Hege , Mathiesen Ellisiv B. , Robben David , Vangberg Torgil R. 
Published: June 2020

AbstractThe main arteries that supply blood to the brain originate from the Circle of Willis (CoW). The CoW exhibit considerable anatomical variations which may have clinical importance, but the variability is insufficiently characterised in the general population. We assessed the anatomical variability of CoW variants in a community-dwelling sample (N = 1,864, 874 men, mean age = 65.4, range 40 – 87 years), and independent and conditional frequencies of the CoW’s artery segments. CoW segments were classified as present or missing/hypoplastic (w/1mm diameter threshold) on 3T time-of-flight magnetic resonance angiography images. We also examined whether age and sex were associated with CoW variants. We identified 47 unique CoW variants, of which five variants constituted 68.5% of the sample. The complete variant was found in 11.9% of the subjects, and the most common variant (27.8%) was missing both posterior communicating arteries. Conditional frequencies showed patterns of interdependence across most missing segments in the CoW. CoW variants were associated with mean-split age (P = .0147), and there was a trend showing more missing segments with increasing age. We found no association with sex (P = .0526). Our population study reinforced age as associated with CoW variants, suggesting reduced collateral supply with older age.
BingleSeq: A user-friendly R package for Bulk and Single-cell RNA-Seq Data Analysis
Authors: Dimitrov Daniel , Gu Quan 
Published: June 2020

AbstractRNA sequencing is a high-throughput sequencing technique considered as an indispensable research tool used in a broad range of transcriptome analysis studies. The most common application of RNA Sequencing is Differential Expression analysis and it is used to determine genetic loci with distinct expression across different conditions. On the other hand, an emerging field called single-cell RNA sequencing is used for transcriptome profiling at the individual cell level. The standard protocols for both these types of analyses include the processing of sequencing libraries and result in the generation of count matrices. An obstacle to these analyses and the acquisition of meaningful results is that both require programming expertise.BingleSeq was developed as an intuitive application that provides a user-friendly solution for the analysis of count matrices produced by both Bulk and Single-cell RNA-Seq experiments. This was achieved by building an interactive dashboard-like user interface and incorporating three state-of-the-art software packages for each type of the aforementioned analyses, alongside additional features such as key visualisation techniques, functional gene annotation analysis and rank-based consensus for differential gene analysis results, among others. As a result, BingleSeq puts the best and most widely used packages and tools for RNA-Seq analyses at the fingertips of biologists with no programming experience.
Quantitative comparison ofDrosophilabehavior annotations by human observers and a machine learning algorithm
Authors: Leng Xubo , Wohl Margot , Ishii Kenichi , Nayak Pavan , Asahina Kenta 
Published: June 2020

AbstractAutomated quantification of behavior is increasingly prevalent in neuroscience research. Human judgments can influence machine-learning-based behavior classification at multiple steps in the process, for both supervised and unsupervised approaches. Such steps include the design of the algorithm for machine learning, the methods used for animal tracking, the choice of training images, and the benchmarking of classification outcomes. However, how these design choices contribute to the interpretation of automated behavioral classifications has not been extensively characterized. Here, we quantify the effects of experimenter choices on the outputs of automated classifiers ofDrosophilasocial behaviors.Drosophilabehaviors contain a considerable degree of variability, which was reflected in the confidence levels associated with both human and computer classifications. We found that a diversity of sex combinations and tracking features was important for robust performance of the automated classifiers. In particular, features concerning the relative position of flies contained useful information for training a machine-learning algorithm. These observations shed light on the importance of human influence on tracking algorithms, the selection of training images, and the quality of annotated sample images used to benchmark the performance of a classifier (the ‘ground truth’). Evaluation of these factors is necessary for researchers to accurately interpret behavioral data quantified by a machine-learning algorithm and to further improve automated classifications.Significance StatementAccurate quantification of animal behaviors is fundamental to neuroscience. Here, we quantitatively assess how human choices influence the performance of automated classifiers trained by a machine-learning algorithm. We found that human decisions about the computational tracking method, the training images, and the images used for performance evaluation impact both the classifier outputs and how human observers interpret the results. These factors are sometimes overlooked but are critical, especially because animal behavior is itself inherently variable. Automated quantification of animal behavior is becoming increasingly prevalent: our results provide a model for bridging the gap between traditional human annotations and computer-based annotations. Systematic assessment of human choices is important for developing behavior classifiers that perform robustly in a variety of experimental conditions.
Robust framework and software implementation for fast speciation mapping
Authors: Cohen Serge X. , Webb Samuel M. , Gueriau Pierre , Curis Emmanuel , Bertrand Loïc 
Published: June 2020

One of the greatest benefits of synchrotron radiation is the ability to perform chemical speciation analysis through X-ray absorption spectroscopies (XAS). XAS imaging of large sample areas can be performed with either full-field or raster-scanning modalities. A common practice to reduce acquisition time while decreasing dose and/or increasing spatial resolution is to compare X-ray fluorescence images collected at a few diagnostic energies. Several authors have used different multivariate data processing strategies to establish speciation maps. In this manuscript, the theoretical aspects and assumptions that are often made in the analysis of these datasets are focused on. A robust framework is developed to perform speciation mapping in large bulk samples at high spatial resolution by comparison with known references. Two fully operational software implementations are provided: a user-friendly implementation within the MicroAnalysis Toolkit software, and a dedicated script developed under the R environment. The procedure is exemplified through the study of a cross section of a typical fossil specimen. The algorithm provides accurate speciation and concentration mapping while decreasing the data collection time by typically two or three orders of magnitude compared with the collection of whole spectra at each pixel. Whereas acquisition of spectral datacubes on large areas leads to very high irradiation times and doses, which can considerably lengthen experiments and generate significant alteration of radiation-sensitive materials, this sparse excitation energy procedure brings the total irradiation dose greatly below radiation damage thresholds identified in previous studies. This approach is particularly adapted to the chemical study of heterogeneous radiation-sensitive samples encountered in environmental, material, and life sciences.