bluuebunny/crossref_metadata_2025_split huggingface dataset:
T cells Mediate Progression of Load-Induced Osteoarthritis
Authors: Wheeler Tibra A. , Antoinette Adrien Y. , Kim Matthew J. , van der Meulen Marjolein C. H. , Singh Ankur 
Published: May 2020

AbstractOsteoarthritis (OA) is a degenerative disease that manifests as joint damage and synovial inflammation. To date, most studies have focused on the decrease in cartilage stiffness, chondrocyte viability, and changes in matrix-degrading enzymes. With the exception of a few inflammatory cytokines and macrophages, the immune response in OA is poorly characterized, and the crosstalk of joint damage with T and B cells in local lymph nodes is unknown. Here, using anin vivomouse model of mechanical loading of mouse tibia, we demonstrate that CD8+ T cells and subsets of CD4+ T cells, and not B cells, increase in the local lymph nodes and contribute to the progression of load-induced OA pathology. We demonstrate that T cell response is sex- and age-dependent. Mechanical loading of T cell knock-out mice that lack αβ T cell receptor carrying cells resulted in attenuation of both cartilage degradation and osteophyte formation in loaded joints, with a concomitant increase in γδ+ T cells. Restricting the migration of T cells in lymphoid tissues through the systemic treatment using Sphingosine-1-phosphate (S1P) inhibitor, decreased localization of T cells in synovium, and attenuated cartilage degradation. Our results lay the foundation of the role T cells play in the joint damage of load-induced OA and allude to the use of S1P inhibitors and T cell immunotherapies for slowing the progression of OA pathology.
An unconventional cerebrospinal fluid-derived Semaphorin-signalling regulates apical progenitor dynamics in the developing neocortex
Authors: Gerstmann Katrin , Kindbeiter Karine , Telley Ludovic , Bozon Muriel , Charoy Camille , Jabaudon Denis , Moret Frédéric , Castellani Valerie 
Published: May 2020

SummaryIn the embryonic brain, dynamic regulation of apical adhesion is fundamental to generate correct numbers and identity of precursors and neurons. Radial glial cells (RGC) in the cerebral cortex are tightly attached to adjacent neighbours. However, cells committed to differentiate reduce their adhesiveness to detach and settle at distal position from the apical border. Whether diffusible signals delivered from the cerebrospinal fluid (CSF) contribute to the regulation of apical adhesion dynamics remain fully unknown. Here we report that unconventional pre-formed complexes of class3-Semaphorins (Sema) and Neuropilins (Nrp) are released into the cerebrospinal fluid (CSF) from sources including the choroid plexus. Through analysis of mutant mouse models and various ex vivo assays, we propose that two different complexes, Sema3B/Nrp2 and Sema3F/Nrp1, bind to apical endfeet of RGCs, and exert dual regulation of their attachment, nuclei dynamics, that oppositely promotes or inhibits basal progenitor and neuron differentiation. This reveals unexpected contributions of CSF-delivered guidance molecules during cortical development.
On the effectiveness of small, discriminatively pre-trained language representation models for biomedical text mining
Authors: Ozyurt Ibrahim Burak 
Published: May 2020

AbstractNeural language representation models such as BERT [1] have recently shown state of the art performance in downstream NLP tasks and bio-medical domain adaptation of BERT (Bio-BERT [2]) has shown same behavior on biomedical text mining tasks. However, due to their large model size and resulting increased computational need, practical application of models such as BERT is challenging making smaller models with comparable performance desirable for real word applications. Recently, a new language transformers based language representation model named ELECTRA [3] is introduced, that makes efficient usage of training data in a generative-discriminative neural model setting that shows performance gains over BERT. These gains are especially impressive for smaller models. Here, we introduce a small ELECTRA based model named Bio-ELECTRA that is eight times smaller than BERT BASE and achieves comparable performance on biomedical question answering and yes/no question answer classification tasks. The model is pre-trained from scratch on PubMed abstracts using a consumer grade GPU with only 8GB memory. For biomedical named entity recognition, however, large BERT Base model outperforms both Bio-ELECTRA and ELECTRA-Small++.
GraphGR: A graph neural network to predict the effect of pharmacotherapy on the cancer cell growth
Authors: Singha Manali , Pu Limeng , Shawky Abd-El-Monsif , Busch Konstantin , Wu Hsiao-Chun , Ramanujam J. , Brylinski Michal 
Published: May 2020

AbstractGenomic profiles of cancer cells provide valuable information on genetic alterations in cancer. Several recent studies employed these data to predict the response of cancer cell lines to treatment with drugs. Nonetheless, due to the multifactorial phenotypes and intricate mechanisms of cancer, the accurate prediction of the effect of pharmacotherapy on a specific cell line based on the genetic information alone is problematic. High prediction accuracies reported in the literature likely result from significant overlaps among training, validation, and testing sets, making many predictors inapplicable to new data. To address these issues, we developed GraphGR, a graph neural network with sophisticated attention propagation mechanisms to predict the therapeutic effects of kinase inhibitors across various tumors. Emphasizing on the system-level complexity of cancer, GraphGR integrates multiple heterogeneous data, such as biological networks, genomics, inhibitor profiling, and genedisease associations, into a unified graph structure. In order to construct diverse and information-rich cancer-specific networks, we devised a novel graph reduction protocol based on not only the topological information, but also the biological knowledge. The performance of GraphGR, properly cross-validated at the tissue level, is 0.83 in terms of the area under the receiver operating characteristics, which is notably higher than those measured for other approaches on the same data. Finally, several new predictions are validated against the biomedical literature demonstrating that GraphGR generalizes well to unseen data, i.e. it can predict therapeutic effects across a variety of cancer cell lines and inhibitors. GraphGR is freely available to the academic community athttps://github.com/pulimeng/GraphGR.
MACHINE LEARNING PREDICTION FOR COVID 19 PANDEMIC IN INDIA
Authors: Ogundokun Roseline Oluwaseun , Awotunde Joseph Bamidele 
Published: May 2020

ABSTRACTBackgroundCoronavirus was detected in December 2019 in a bulk seafood shop in Wuhan, China. The original incident of COVID-19 pandemic in India was conveyed on 30th January 2020 instigating from the nation called china. As of 25th April 2020, the Ministry of Health and Family Welfare has established a total of 24, 942 incidents, 5, 210 recuperation including 1 relocation, and 779 demises in the republic.ObjectiveThe objective of the paper is to formulate a simple average aggregated machine learning method to predict the number, size, and length of COVID-19 cases extent and wind-up period crosswise India.MethodThis study examined the datasets via the Autoregressive Integrated Moving Average Model (ARIMA). The study also built a simple mean aggregated method established on the performance of 3 regression techniques such as Support Vector Regression (SVR, NN, and LR), Neural Network, and Linear Regression.ResultThe results showed that COVID-19 disease can correctly be predicted. The result of the prediction shows that COVID-19 ailment could be conveyed through water and air ecological variables and so preventives measures such as social distancing, wearing of mask and hand gloves, staying at home can help to avert the circulation of the sickness thereby resulting in reduced active cases and even mortality.ConclusionIt was established that the projected method outperformed when likened to previously obtainable practical models on the bases of prediction precision. Hence, putting in place the preventive measures can effectively manage the spread of COVID-19, and also the death rate will be reduced and eventually be over in India and other nations.
Normal Olfactory Functional Connectivity Despite Life-Long Absence of Olfactory Experiences
Authors: Peter Moa G. , Fransson Peter , Mårtensson Gustav , Postma Elbrich M. , Nordin Love Engström , Westman Eric , Boesveldt Sanne , Lundström Johan N. 
Published: May 2020

ABSTRACTCongenital blindness is associated with atypical morphology, and functional connectivity within and from, visual cortical regions; changes that are hypothesized to originate from a life-long absence of visual input and could be regarded as a general (re)organization principle of sensory cortices. Challenging this is the fact that individuals with congenital anosmia (life-long olfactory sensory loss) display little to no morphological changes in primary olfactory cortex. To determine whether olfactory input from birth is essential to establish and maintain normal functional connectivity in olfactory processing regions, akin to the visual system, we assessed differences in functional connectivity within olfactory cortex between individuals with congenital anosmia (n=33) and matched controls (n=34). Specifically, we assessed differences in connectivity between core olfactory processing regions as well as differences in regional homogeneity and homotopic connectivity within primary olfactory cortex. In contrast to congenital blindness, none of the analyses indicated atypical connectivity in individuals with congenital anosmia. In fact, post-hoc Bayesian analysis provided support for an absence of group differences. These results suggest that a lifelong absence of olfactory experience has limited impact on the functional connectivity in olfactory cortex, a finding that indicates a clear difference between sensory modalities in how sensory cortical regions develop.
Intestinal inflammation modulates the expression of ACE2 and TMPRSS2 and potentially overlaps with the pathogenesis of SARS-CoV-2 related disease
Authors: Suárez-Fariñas Mayte , Tokuyama Minami , Wei Gabrielle , Huang Ruiqi , Livanos Alexandra , Jha Divya , Levescot Anais , Kosoy Roman , Irizar Haritz , Cording Sascha , Wang Wenhui , Ungaro Ryan , Di’Narzo Antonio , Martinez Gustavo , Suprun Maria , Corley Michael J. , Stojmirovic Aleksandar , Houten Sander M. , Curran Mark , Brodmerkel Carrie , Perrigoue Jacqueline , Friedman Joshua R. , Hao Ke , Schadt Eric E. , Zhu Jun , Ko Huaibin M. , Cho Judy , Dubinsky Marla C. , Sands Bruce E. , Ndhlovu Lishomwa , Cerf-Benssusan Nadine , Kasarskis Andrew , Colombel Jean Frederic , Harpaz Noam , Argmann Carmen , Mehandru Saurabh 
Published: May 2020

AbstractImmune dysregulation and cytokine release syndrome have emerged as pathological hallmarks of severe Coronavirus Disease 2019 (COVID-19), leading to the evaluation of cytokine antagonists as therapeutic agents. A number of immune-directed therapies being considered for COVID-19 patients are already in clinical use in chronic inflammatory conditions like inflammatory bowel disease (IBD). These considerations led us to systematically examine the intersections between COVID-19 and the GI tract during health and intestinal inflammation. We have observed that IBD medications, both biologic and non-biologic, do not significantly impact ACE2 and TMPRSS2 expression in the uninflamed intestines. Additionally, by comparing SARS CoV2-induced epithelial gene signatures with IBD-associated genes, we have identified a shared molecular subnetwork between COVID-19 and IBD. These data generate a novel appreciation of the confluence of COVID-19- and IBD-associated inflammation and provide mechanistic insights supporting further investigation of specific IBD drugs in the treatment of COVID-19.
Using high abundance proteins as guides for fast and effective peptide/protein identification from metaproteomic data
Authors: Stamboulian Moses H. , Li Sujun , Ye Yuzhen 
Published: May 2020

AbstractBackgroundA few recent large efforts significantly expanded the collection of human-associated bacterial genomes, which now contains thousands of entities including reference complete/draft genomes and metagenome assembled genomes (MAGs). These genomes provide useful resource for studying the functionality of the human-associated microbiome and their relationship with human health and diseases. One application of these genomes is to provide a universal reference for database search in metaproteomic studies, when matched metagenomic/metatranscriptomic data are unavailable. However, a greater collection of reference genomes may not necessarily result in better peptide/protein identification because the increase of search space often leads to fewer spectrum-peptide matches, not to mention the drastic increase of computation time.MethodsHere, we present a new approach that uses two steps to optimize the use of the reference genomes and MAGs as the universal reference for human gut metaproteomic MS/MS data analysis. The first step is to use only the High Abundance Proteins (HAPs) (i.e., ribosomal proteins and elongation factors) for metaproteomic MS/MS database search and, based on the identification results, to derive the taxonomic composition of the underlying microbial community. The second step is to expand the search database by including all proteins from identified abundant species. We call our approach HAPiID (HAPs guided metaproteomics IDentification).ResultsWe tested our approach using human gut metaproteomic datasets from a previous study and compared it to the state-of-the-art reference database search method MetaPro-IQ for metaproteomic identification in studying human gut microbiota. Our results show that our two-steps method not only performed significantly faster but also was able to identify more peptides. We further demonstrated the application of HAPiID to revealing protein profiles of individual human-associated bacterial species, one or a few species at a time, using metaproteomic data.ConclusionsThe HAP guided profiling approach presents a novel effective way for constructing target database for metaproteomic data analysis. The HAPiID pipeline built upon this approach provides a universal tool for analyzing human gut-associated metaproteomic data.
Leukopenia of Asymptomatic COVID-19 Infections under 18 Years Old in Recovery Stage
Authors: Zhang Wei , Yuan Youshu , Yang Zhengqiao , Fu Jinxia , Zhang Yun , Ma Ming , Wu Weidong , Zhou Hourong 
Published: May 2020

ABSTRACTObjectivesIn December, 2019, a type of novel coronavirus which was designated novel coronavirus 2019 (2019-nCoV) by World Health Organization (WHO) occurred in Wuhan, Hubei, China. The epidemiological and clinical characteristics of those patients under 18 years old in the recovery stage are limited. To compare the difference of epidemiological and clinical characteristics of COVID-19 involving 25 patients under 18 years old in recovery stage between confirmed and asymptomatic infections.MethodsRetrospective, single-center cohort study of COVID-19 involving 25 patients under 18 years old in the recovery stage at Guizhou Provincial Staff Hospital in Guiyang, China, from January 29, to March 31, 2020; final date of follow-up was April 22. Epidemiological, demographic, clinical, laboratory, radiological, and treatment data were collected and analyzed. Epidemiological and clinical characteristics of confirmed COVID-19 infections and asymptomatic infections were compared.ResultsAmong the 25 COVID infections under 18 years old, 16 (64%) were mild or moderate confirmed cases, and 9 (36%) were asymptomatic. The shortest treatment period was 6 days, the longest 26 days, and the average treatment period 14 days. Four cases (44.4%) had visited Wuhan or had a living story in the city. There were 9 (100%) asymptomatic cases were familial cluster outbreak, with an average infection number was 6 cases among all families. The number of asymptomatic COVID-19 infections with leukopenia were significantly more than confirmed cases (p=0.04).ConclusionsLeukopenia mostly occurred in asymptomatic COVID-19 infections under 18 years old compared with the confirmed patients.Key PointIn this single-center case series involving 25 cases under 18 years old with COVID-19 infections, leukopenia mostly occurred in asymptomatic infections.
Clinical Utility of SARS-CoV-2 Whole Genome Sequencing in Deciphering Source of Infection
Authors: Takenouchi Toshiki , Iwasaki Yuka W. , Harada Sei , Ishizu Hirotsugu , Uwamino Yoshifumi , Uno Shunsuke , Osada Asami , Hasegawa Naoki , Murata Mitsuru , Takebayashi Toru , Fukunaga Koichi , Saya Hideyuki , Kitagawa Yuko , Amagai Masayuki , Siomi Haruhiko , Kosaki Kenjiro ,   Keio Donner Project
Published: May 2020

AbstractThe novel coronavirus disease (COVID-19) pandemic caused by SARS-CoV-2 is a major threat to humans. Recently, we encountered two seemingly separate COVID-19 clusters in a tertiary care medical center. Whole viral genome sequencing detected the haplotype of the SARS-CoV-2 genome and the two clusters were successfully distinguished by the viral genome haplotype. Concurrently, there were nine COVID-19 patients clinically unlinked to clusters #1 or #2 that necessitated the determination of the source of infection. Such patients had similar haplotypes to those in cluster #2 but were devoid of two rare mutations characteristic to cluster #2. This suggested that these nine cases of “probable community infection” indeed had community infection and were not derived from cluster #2. Whole viral genome sequencing of SARS-CoV-2 is a powerful measure not only for monitoring the global trend of SARS-CoV-2 but also for identifying the source of infection of COVID-19 at a level of institution.
Does Copper treating of commonly touched surfaces reduce healthcare acquired infections? A Systematic Review and meta-analysis
Authors: Albarqouni Loai , Byambasuren Oyuka , Clark Justin , Scott Anna Mae , Looke David , Glasziou Paul 
Published: May 2020

AbstractBackgroundHealthcare acquired infections (HAIs) cause substantial morbidity and mortality. Copper appears to have strong viricidal properties under laboratory conditions.AimWe conducted a systematic review to examine the potential effect of copper treating of commonly touched surfaces in healthcare facilities.MethodsWe included controlled trials comparing the effect of copper-treated surfaces (furniture or bed linens) in hospital rooms versus standard rooms on hospital acquired infections (HAIs). Two reviewers independently screened retrieved articles, extracted data, and assessed the risk of bias of included studies. The primary outcome was the occurrence of healthcare acquired infections.FindingsWe screened 638 records; 7 studies comprising 12362 patients were included. All of included studies were judged to be at high risk in ≥2 of the 7 domains of bias. All 7 included studies reported the effect of copper-treated surfaces HAIs. Overall, we found low quality evidence of a potential clinical importance that copper-treated hard surfaces and/or bed linens and clothes reduced healthcare acquired infections by 27% (RR 0.73; 95% CI 0.57 to 0.94).ConclusionGiven the clinical and economic costs of healthcare acquired infections, the potentially protective effect of copper-treated surfaces appears important. The current evidence is insufficient to make a strong positive recommendation. However, it would appear worthwhile and urgent to conduct larger-scale publicly funded clinical trials of the impact of copper coating.
Global evolutionary epidemiology, phylogeography and resistome dynamics of Citrobacter species, Enterobacter hormaechei, Klebsiella variicola, and Proteeae clones: A One Health analyses
Authors: Osei Sekyere John , Reta Melese Abate 
Published: May 2020

AbstractBackground.The global epidemiology and resistomes dynamics of multidrug-resistant Citrobacter spp., Enterobacter hormaechei, Klebsiella variicola, morganella morganii, Proteus mirabilis and Providencia spp. have not been described, despite their importance as emerging opportunistic clinical pathogens.Methods.The genomes of the above-mentioned organisms were curated from PATRIC and NCBI and used for evolutionary epidemiology, phylogeography and resistome analyses. The phylogeny trees were drawn using RAXmL and edited with Figtree. The resistomes were curated from GenBank and the phylogeography was manually mapped.Results and conclusion.Mcr-9 and other mcr variants were highly prevalent in E. hormaechei subsp. and substantial in C. freundii whilst KPC, OXA-48, NDM, IMP, VIM, TEM, OXA and SHV were abundant in global E. hormaechei subsp., Citrobacter freundii, P. mirabilis, P. stuartii and P. rettgeri clones/clades. Species-specific ampCs were highly conserved in respective species whilst fluoroquinolones, aminoglycosides, macrolides, fosfomycin, chloramphenicol, tetracycline, sulphamethoxazole and trimethoprim resistance mechanisms were abundantly enriched in almost all clades of most of the species, making them extensively and pandrug resistant; K. variicola, C. amalonaticus and C, koseri had relatively few resistance genes. Vertical and horizontal resistome transmissions as well as local and international dissemination of strains evolving from common ancestors were observed, suggesting the anthroponotic, zoonotic, and food-/water-borne infectiousness of these pathogens. There is a global risk of pandrug resistant strains escalating local and international outbreaks of antibiotic-insensitive infections, initiating the dawn of a post-antibiotic era.
Somatostatin neurons of the bed nucleus of stria terminalis enhance associative fear memory consolidation in mice
Authors: Bruzsik Biborka , Biro Laszlo , Zelena Dora , Sipos Eszter , Szebik Huba , Sarosdi Klara Rebeka , Horvath Orsolya , Farkas Imre , Csillag Veronika , Finszter Cintia Klaudia , Mikics Eva , Toth Mate 
Published: May 2020

AbstractExcessive fear learning and extinction-resistant fear memories are core symptoms of anxiety and trauma-related disorders. Despite significant evidence from clinical studies reporting hyperactivity of the bed nucleus of stria terminalis (BNST) under these conditions, the role of BNST in fear learning and expression is still not clarified. Here, we tested how BNST modulates fear learning in mice using a chemogenetic approach. Activation of GABAergic neurons of BNST during fear acquisition, more specifically the consolidation phase, resulted in enhanced cued fear recall. Importantly, BNST activation had no acute impact on fear expression during conditioning or recalls, but it enhanced cued fear recall subsequently, potentially via altered activity of downstream regions as indicated by c-Fos. Enhanced fear memory consolidation could be replicated by selectively activating somatostatin neurons (but not corticotropin releasing factor neurons), suggesting significant modulation of fear memory strength by specific circuits of BNST.