bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploratory movement analysis and report building with R package stmove
Authors: Seidel Dana P. , Dougherty Eric R. , Getz Wayne M. 
Published: September 2019

AbstractBackgroundAs GPS tags and data loggers have become lighter, cheaper, and longer-lasting, there has been a growing influx of data on animal movement. Simultaneously, methods of analyses and software to apply such methods to movement data have expanded dramatically. Even so, for many interdisciplinary researchers and managers without familiarity with the field of movement ecology and the open-source tools that have been developed, the analysis of movement data has remained an overwhelming challenge.DescriptionHere we present stmove, an R package designed to take individual relocation data and generate a visually rich report containing a set of preliminary results that ecologists and managers can use to guide further exploration of their data. Not only does this package make report building and exploratory data analysis (EDA) simple for users who may not be familiar with the extent of available analytical tools, but it sets forth a framework of best practice analyses, which offers a common starting point for the interpretation of terrestrial movement data.ResultsUsing data from African elephants (Loxodonta africana) collected in southern Africa, we demonstrate stmove’s report building function through the main analyses included: path visualization, primary statistic calculation, summary in space and time, and space-use construction.ConclusionsThe stmove package provides consistency and increased accessibility to managers and researchers who are interested in movement analysis but who may be unfamiliar with the full scope of movement packages and analytical tools. If widely adopted, the package will promote comparability of results across movement ecology studies.
Multidimensional and Multiresolution Ensemble Networks for Brain Tumor Segmentation
Authors: Murugesan Gowtham Krishnan , Nalawade Sahil , Ganesh Chandan , Wagner Ben , Yu Fang F. , Fei Baowei , Madhuranthakam Ananth J. , Maldjian Joseph A. 
Published: September 2019

AbstractIn this work, we developed multiple 2D and 3D segmentation models with multiresolution input to segment brain tumor components, and then ensembled them to obtain robust segmentation maps. This reduced overfitting and resulted in a more generalized model. Multiparametric MR images of 335 subjects from BRATS 2019 challenge were used for training the models. Further, we tested a classical machine learning algorithm (xgboost) with features extracted from the segmentation maps to classify subject survival range. Preliminary results on the BRATS 2019 validation dataset demonstrasted this method can achieve excellent performance with DICE scores of 0.898, 0.784, 0.779 for whole tumor, tumor core and enhancing tumor respectively and accuracy 34.5 % for survuval prediction.
PK-DB: PharmacoKinetics DataBase for Individualized and Stratified Computational Modeling
Authors: Grzegorzewski Jan , Brandhorst Janosch , Eleftheriadou Dimitra , Green Kathleen , König Matthias 
Published: September 2019

ABSTRACTA multitude of pharmacokinetics studies have been published. However, due to the lack of an open database, pharmacokinetics data, as well as the corresponding meta-information, have been difficult to access. We present PK-DB (https://pk-db.com), an open database for pharmacokinetics information from clinical trials including pre-clinical research. PK-DB provides curated information on (i) characteristics of studied patient cohorts and subjects (e.g. age, bodyweight, smoking status); (ii) applied interventions (e.g. dosing, substance, route of application); (iii) measured pharmacokinetic time-courses; (iv) pharmacokinetic parameters (e.g. clearance, half-life, area under the curve). Key features are the representation of experimental errors, the normalization of measurement units, annotation of information to biological ontologies, calculation of pharmacokinetic parameters from concentration-time profiles, a workflow for collaborative data curation, strong validation rules on the data, computational access via a REST API as well as human access via a web interface. PK-DB enables meta-analysis based on data from multiple studies and data integration with computational models. A special focus lies on meta-data relevant for individualized and stratified computational modeling with methods like physiologically based pharmacokinetic (PBPK), pharmacokinetic/pharmacodynamic (PK/DB), or population pharmacokinetic (pop PK) modeling.
The gammaherpesvirus 68 viral cyclin facilitates reactivation by promoting latent gene expression
Authors: Niemeyer Brian F , Gibson Joy E , Berger Jennifer N , Oko Lauren M , Medina Eva , Clambey Eric T , van Dyk Linda F 
Published: September 2019

AbstractGammaherpesviruses establish life-long infections within their host and have been shown to be the causative agents of devastating malignancies. Chronic infection within the host is mediated through cycles of transcriptionally quiescent stages of latency with periods of reactivation into more active lytic and productive infection. The mechanisms that regulate reactivation from latency remain poorly understood. Previously, we defined a critical role for the viral cyclin in promoting reactivation from latency. Disruption of the viral cyclin had no impact on the frequency of cells containing viral genome during latency, yet it remains unclear whether the viral cyclin influences latently infected cells in a qualitative manner. To define the impact of the viral cyclin on latent gene expression, we utilized a viral cyclin deficient variant expressing a LANA-beta-lactamase fusion protein (LANA::βla), to enumerate both the cellular distribution and frequency of latent gene expression. Disruption of the viral cyclin did not affect the cellular distribution of latently infected cells, but did result in a significant decrease in the frequency of cells that expressed LANA::βla across multiple tissues and in both immunocompetent and immunodeficient hosts. Strikingly, whereas the cyclin-deficient virus had a reactivation defect in bulk culture, sort purified cyclin-deficient LANA::βla expressing cells were fully capable of reactivation. These data emphasize that the γHV68 latent reservoir is comprised of at least two distinct stages of infection characterized by differential latent gene expression, and that a primary function of the viral cyclin is to promote latent gene expression within infected cells in vivo.AUTHOR SUMMARYGammaherpesviruses are ubiquitous viruses with oncogenic potential that establish latency for the life of the host. These viruses can emerge from latency through reactivation, a process that is controlled by the immune system. Control of viral latency and reactivation is thought to be critical to prevent γHV-associated disease. This study focuses on a virally-encoded cyclin that is required for reactivation from latency. By characterizing how the viral cyclin influences latent infection in pure cell populations, we find that the viral cyclin has a vital role in promoting viral gene expression during latency. This work provides new insight into the function of a virally encoded cyclin in promoting reactivation from latency.
A kinetic operational model of agonism incorporating receptor desensitization for G-protein-coupled receptors
Authors: Hoare Sam R.J. , Hall David A. , Bridge Lloyd J. 
Published: September 2019

AbstractPharmacological responses are modulated over time by regulation of signaling mechanisms. The canonical short-term regulation mechanisms are receptor desensitization and degradation of the response. Here for the first time a pharmacological model for measuring drug parameters is developed that incorporates short-term mechanisms of regulation of signaling. The model is formulated in a manner that enables measurement of drug parameters using familiar curve fitting methods. The efficacy parameter iskτ, which is simply the initial rate of signaling before it becomes limited by regulation mechanisms. The regulation parameters are rate constants,kDESfor receptor desensitization andkDfor response degradation. Efficacy and regulation are separate parameters, meaning these properties can be optimized independently of one another in drug discovery. The parameters can be applied to translate in vitro findings to in vivo efficacy in terms of the magnitude and duration of drug effect. When the time course data conform to certain shapes, for example the association exponential curve, a mechanism-agnostic approach can be applied to estimate agonist efficacy, without the need to know the underlying regulatory mechanisms. The model was verified by comparison with historical data and by fitting these data to estimate the model parameters. This new model for quantifying drug activity can be broadly applied to the short-term cell signaling assays used routinely in drug discovery and to aid their translation to in vivo efficacy, facilitating the development of new therapeutics.HighlightsRegulation of signaling impacts measurement of drug effectReceptor desensitization is incorporated here into a kinetic model of signalingDrug effect and signaling regulation can now be measured independentlyThe analysis framework is designed for signaling assays used in drug discoveryThese new analysis capabilities will aid development of new therapeutics
In your phase: Neural phase synchronisation underlies visual imagery of faces
Authors: Canales-Johnson Andrés , Lanfranco Renzo C. , Morales Juan Pablo , Martínez-Pernía David , Valdés Joaquín , Ezquerro-Nassar Alejandro , Rivera-Rei Álvaro , Ibanez Agustín , Chennu Srivas , Bekinschtein Tristan A. , Huepe David , Noreika Valdas 
Published: September 2019

ABSTRACTMental imagery is the process through which we retrieve and recombine information from our memory to elicit the subjective impression of “seeing with the mind’s eye”. In the social domain, we imagine other individuals while recalling our encounters with them or modelling alternative social interactions in future. Many studies using imaging and neurophysiological techniques have shown several similarities in brain activity between visual imagery and visual perception, and have identified frontoparietal, occipital and temporal neural components of visual imagery. However, the neural connectivity between these regions during visual imagery of socially relevant stimuli have not been studied. Here we used electroencephalography to investigate neural connectivity and its dynamics between frontal, parietal, occipital and temporal electrodes during visual imagery of faces. We found that voluntary visual imagery of faces is associated with long-range phase synchronisation in the gamma frequency range between frontoparietal electrode pairs and between occipitoparietal electrode pairs. In contrast, no effect of imagery was observed in the connectivity between occipitotemporal electrode pairs. Gamma range synchronisation between occipitoparietal electrode pairs predicted subjective ratings of the contour definition of imagined faces. Furthermore, we found that visual imagery of faces is associated with an increase of short-range frontal synchronisation in the theta frequency range, which temporally preceded the long-range increase in the gamma synchronisation. We speculate that the local frontal synchrony in the theta frequency range might be associated with an effortful top-down mnemonic reactivation of faces. In contrast, the long-range connectivity in the gamma frequency range along the fronto-parieto-occipital axis might be related to the endogenous binding and subjective clarity of facial visual features.
Multiple incursion pathways forHelicoverpa armigerain Brazil show its genetic diversity spreading in a connected world
Authors: Arnemann Jonas A. , Roxburgh Stephen H. , Walsh Tom , Guedes Jerson V.C. , Gordon Karl H.J. , Smagghe Guy , Tay Wee Tek 
Published: September 2019

AbstractThe Old World cotton bollwormHelicoverpa armigerawas first detected in Brazil with subsequent reports from Paraguay, Argentina, Bolivia, and Uruguay. This pattern suggests that theH. armigeraspread across the South American continent following incursions into northern/central Brazil, however, this hypothesis has not been tested. Here we compare northern and central BrazilianH. armigeramtDNA COI haplotypes with those from southern Brazil, Uruguay, Argentina, and Paraguay. We infer spatial genetic and gene flow patterns of this dispersive pest in the agricultural landscape of South America. We show that the spatial distribution ofH. armigeramtDNA haplotypes and its inferred gene flow patterns in the southwestern region of South America exhibited signatures inconsistent with a single incursion hypothesis. Simulations on spatial distribution patterns show that the detection of rare and/or the absence of dominant mtDNA haplotypes in southernH. armigerapopulations are inconsistent with genetic signatures observed in northern and central Brazil. Incursions ofH. armigerainto the New World are therefore likely to have involved independent events in northern/central Brazil, and southern Brazil/Uruguay-Argentina-Paraguay. This study demonstrates the significant biosecurity challenges facing the South American continent, and highlights alternate pathways for introductions of alien species into the New World.
Ifnar1 signaling breaks the hepatic urea cycle to regulate adaptive immunity
Authors: Lercher Alexander , Bhattacharya Anannya , Popa Alexandra M. , Caldera Michael , Schlapansky Moritz F. , Baazim Hatoon , Majek Peter , Brunner Julia S. , Kosack Lindsay J. , Vitko Dijana , Pinter Theresa , Gürtl Bettina , Reil Daniela , Kalinke Ulrich , Bennett Keiryn L. , Menche Jörg , Cheng Paul N. , Schabbauer Gernot , Trauner Michael , Klavins Kristaps , Bergthaler Andreas 
Published: September 2019

AbstractInfections induce complex host responses linked to antiviral defense, inflammation and tissue damage and repair. These processes are increasingly understood to involve systemic metabolic reprogramming. We hypothesized that the liver as a central metabolic hub may orchestrate many of these changes during infection. Thus, we investigated the systemic interplay between inflammation and metabolism in a mouse model of chronic viral infection and hepatitis. Here we show that virus-induced type I interferon (IFN-I) modulates wide-spread metabolic alterations of the liver in a hepatocyte-intrinsic Ifnar1-dependent way. Specifically, IFN-I repressed the transcription of numerous genes with metabolic function including Otc and Ass1, which encode enzymes of the urea cycle. This led to decreased arginine and increased ornithine concentrations in the circulation, resulting in suppressed virus-specific CD8 T cell responses and ameliorated liver pathology. These findings establish IFN-I-induced modulation of hepatic metabolism and the urea cycle as an endogenous mechanism of immunoregulation.
Thirty two novel nsSNPs May effect onHEXAprotein Leading to Tay-Sachs disease (TSD) Using a Computational Approach
Authors: Abdelhameed Tebyan A. , Osman Fadul Mohamed Mustafa , Abdelrahman Mohamed Dina Nasereldin , Mohamed Mudawi Amal , Fadul Allah Sayaf Kamal Khalifa , Elnour Ahmed Ola Ahmed , Idrees Mohammeddeen Sogoud Mohammednour , Taha khairi Aya Abdelwahab , Osman Soada Ahmed , Al-Hajj Ebrahim Mohammed , Elhag Mustafa , Hassan Salih Mohamed Ahmed 
Published: September 2019

ABSTRACTBackgroundGenetic polymorphisms in theHEXAgene are associated with a neurodegenerative disorder called Tay-Sachs disease (TSD) (GM2 gangliosidosis type 1). This study aimed to predict the possible pathogenic SNPs of this gene and their impact on the protein using different bioinformatics tools.MethodsSNPs retrieved from the NCBI database were analyzed using several bioinformatics tools. The different algorithms collectively predicted the effect of single nucleotide substitution on both structure and function of the hexosaminidase A protein.ResultsFifty nine mutations were found to be highly damaging to the structure and function of theHEXAgene protein.ConclusionAccording to this study, thirty two novel nsSNP inHEXAare predicted to have possible role in Tay-Saches Disease using different bioinformatics tools. Our findings could help in genetic study and diagnosis of Tay-Saches Disease.
High pressure inhibits signaling protein binding to the flagellar motor and bacterial chemotaxis through enhanced hydration
Authors: Hata Hiroaki , Nishihara Yasutaka , Nishiyama Masayoshi , Sowa Yoshiyuki , Kawagishi Ikuro , Kitao Akio 
Published: September 2019

AbstractIn the chemotaxis ofEscherichia coli, the cell’s behavioral switch involves binding of the phosphorylated form of the chemotaxis signaling protein CheY (CheYp) to the flagellar motor protein FliM, which induces the motor to rotate clockwise; otherwise, the motor rotates counterclockwise. To investigate high-pressure effects on CheYp–FliM binding at atomic resolution, we conduct molecular dynamics simulations of monomeric CheYp, the N-terminal fragment of the FliM (FliMN) that binds to CheYp, and the complex that forms between those proteins at pressures ranging from 0.1 to 100 MPa. The results show that the active form of monomeric CheYp is maintained even at 100 MPa but high pressure increases the water density in the first hydration shell and can cause conformational change of the C-terminal helix. The dissociation process of the complex is investigated by parallel cascade selection molecular dynamics (PaCS-MD), revealing that high pressure considerably induces water penetration into the complex interface. Pressure dependence of standard binding free energy calculated by the Markov state model indicates that the increase of pressure from 0.1 to 100 MPa weakens the binding by ∼ 10 kcal/mol. Using high-pressure microscopy, we observed that high hydrostatic pressure reversibly fixes the motor rotation in the counter-clockwise orientation, which supports the notion that high pressure inhibits the binding of CheYp to FliM. We conclude that high pressure induces water penetration into the complex interface, which interferes with CheYp–FliM binding and prevents motor reversal.
Annual replication is essential in evaluating the response of the soil microbiome to the genetic modification of maize in different biogeographical regions
Authors: Szoboszlay Márton , Näther Astrid , Mullins Ewen , Tebbe Christoph C. 
Published: September 2019

AbstractThe importance of geographic location and annual variation on the detection of differences in the rhizomicrobiome caused by the genetic modification of maize (Bt-maize, event MON810) was evaluated at experimental field sites across Europe including Sweden, Denmark, Slovakia and Spain. DNA of the rhizomicrobiome was collected at the maize flowering stage in three consecutive years and analyzed for the abundance and diversity of PCR-amplified structural genes ofBacteria,ArchaeaandFungi, and functional genes for bacterial nitrite reductases (nirS,nirK). ThenirKgenes were always more abundant thannirS. Maize MON810 did not significantly alter the abundance of any microbial genetic marker, except for sporadically detected differences at individual sites and years. In contrast, annual variation between sites was often significant and variable depending on the targeted markers. Distinct, site-specific microbial communities were detected but the sites in Denmark and Sweden were similar to each other. A significant effect of the genetic modification of the plant on the community structure in the rhizosphere was detected among thenirKdenitrifiers at the Slovakian site in only one year. However, mostnirKsequences with opposite response were from the same or related source organisms suggesting that the transient differences in community structure did not translate to the functional level. Our results show a lack of effect of the genetic modification of maize on the rhizosphere microbiome that would be stable and consistent over multiple years. This demonstrates the importance of considering annual variability in assessing environmental effects of genetically modified crops.
Convolutional neural networks for mild diabetic retinopathy detection: an experimental study
Authors: Sarki Rubina , Michalska Sandra , Ahmed Khandakar , Wang Hua , Zhang Yanchun 
Published: September 2019

AbstractCurrently, Diabetes and the associated Diabetic Retinopathy (DR) instances are increasing at an alarming rate. Numerous previous research has focused on automated DR detection from fundus photography. The classification ofseverecases of pathological indications in the eye has achieved over 90% accuracy. Still, themildcases are challenging to detect due to CNN inability to identify the subtle features, discrimnative of disease. The data used (i.e. annotated fundus photographies) was obtained from 2 publicly available sources – Messidor and Kaggle. The experiments were conducted with 13 Convolutional Neural Networks architectures, pre-trained on large-scale ImageNet database using the concept of Transfer Learning. Several performance improvement techniques were applied, such as: (i) fine-tuning, (ii) data augmentation, and (iii) volume increase. The results were measured against the standard Accuracy metric on the testing dataset. After the extensive experimentation, the maximum Accuracy of 86% on No DR/Mild DR classification task was obtained forResNet50model with fine-tuning (un-freeze and re-train the layers from 100 onwards), and RMSProp Optimiser trained on the combined Messidor + Kaggle (aug) datasets. Despite promising results, Deep learning continues to be an empirical approach that requires extensive experimentation in order to arrive at the most optimal solution. The comprehensive evaluation of numerous CNN architectures was conducted in order to facilitate an early DR detection. Furthermore, several performance improvement techniques were assessed to address the CNN limitation in subtle eye lesions identification. The model also included various levels of image quality (low/high resolution, under/over-exposure, out-of-focus etc.), in order to prove its robustness and ability to adapt to real-world conditions.
Efficacy of aerial forward-looking infrared surveys for detecting polar bear maternal dens
Authors: Smith Tom S. , Amstrup Steven C. , Kirschhoffer John , York Geoffrey 
Published: September 2019

AbstractDenned polar bears are invisible under the snow, therefore winter-time petroleum exploration and development activities in northern Alaska have potential to disturb maternal polar bears and their cubs. Previous research determined forward looking infrared (FLIR) imagery could detect many polar bear maternal dens under the snow, but also identified limitations of FLIR imagery. We evaluated the efficacy of FLIR-surveys conducted by oil-field operators from 2004-2016. Aerial FLIR surveys detected 15 of 33 (45%) and missed 18 (55%) of the dens known to be within surveyed areas. While greater adherence to previously recommended protocols may improve FLIR detection rates, the physical characteristics of polar bear maternal dens, increasing frequencies of weather unsuitable for FLIR detections—caused by global warming, and competing “hot spots” are likely to prevent FLIR surveys from detecting maternal dens reliably enough to afford protections consonant with increasing global threats to polar bear welfare.