bluuebunny/crossref_metadata_2025_split huggingface dataset:
COVID-19 research in Wikipedia
Authors: Colavizza Giovanni 
Published: May 2020

AbstractWikipedia is one of the main sources of free knowledge on the Web. During the first few months of the pandemic, over 5,200 new Wikipedia pages on COVID-19 have been created and have accumulated over 400M pageviews by mid June 2020.1At the same time, an unprecedented amount of scientific articles on COVID-19 and the ongoing pandemic have been published online. Wikipedia’s contents are based on reliable sources such as scientific literature. Given its public function, it is crucial for Wikipedia to rely on representative and reliable scientific results, especially so in a time of crisis. We assess the coverage of COVID-19-related research in Wikipedia via citations to a corpus of over 160,000 articles. We find that Wikipedia editors are integrating new research at a fast pace, and have cited close to 2% of the COVID-19 literature under consideration. While doing so, they are able to provide a representative coverage of COVID-19-related research. We show that all the main topics discussed in this literature are proportionally represented from Wikipedia, after accounting for article-level effects. We further use regression analyses to model citations from Wikipedia and show that Wikipedia editors on average rely on literature which is highly cited, widely shared on social media, and has been peer-reviewed.
Attributable mortality of vancomycin resistance in ampicillin-resistant Enterococcus faecium bacteremia in Denmark and the Netherlands: a matched cohort study
Authors: Rottier Wouter C. , Pinholt Mette , van der Bij Akke K. , Arpi Magnus , Blank Sybrandus N. , Nabuurs-Franssen Marrigje H. , Ruijs Gijs J.H.M. , Tersmette Matthijs , Ossewaarde Jacobus M. , Groenwold Rolf H. , Westh Henrik , Bonten Marc J.M. 
Published: May 2020

AbstractBackgroundIn many European hospitals, ampicillin-resistant Enterococcus faecium (ARE) is endemic, while outbreaks of vancomycin-resistant E. faecium (VRE), belonging to the same genetic lineage, are increasingly reported. We studied the attributable mortality due to vancomycin resistance in patients with E. faecium bacteremia and evaluated whether this is mediated by a delay in appropriate antibiotic therapy.MethodsIn a retrospective matched cohort study, patients with VRE bacteremia occurring between 2009 and 2014 in 20 Dutch and Danish hospitals were matched to patients with ARE bacteremia, on hospital, ward, length of hospital stay prior to bacteremia, and age. The risk ratio (RR) for 30-day mortality contrasting VRE with ARE was estimated with further analytic control for confounding factors.ResultsIn all, 63 VRE and 234 ARE episodes were matched (36 and 130 for the Netherlands and 27 and 104 for Denmark). Crude 30-day mortality was 27% and 38% for ARE in the Netherlands and Denmark, respectively, and 33% and 48% for VRE in the respective countries. The adjusted RR for 30-day mortality for VRE was 1.54 (95% confidence interval (CI) 1.06-2.25). Although appropriate therapy was initiated later for VRE than for ARE bacteremia, this did not appear to mediate the increased mortality risk.ConclusionsCompared to ARE bacteremia, VRE bacteremia was associated with higher 30-day mortality. One explanation for this association would be increased virulence of VRE, although both phenotypes belong to the same well-characterized core genomic lineage. Alternatively, it may be the result of unmeasured confounding.
The association of cardiovascular disease and other pre-existing comorbidities with COVID-19 mortality: A systematic review and meta-analysis
Authors: Ssentongo Paddy , Ssentongo Anna E. , Heilbrunn Emily S. , Ba Djibril M. , Chinchilli Vernon M. 
Published: May 2020

AbstractBackgroundExploring the association of coronavirus-2019 disease (COVID-19) mortality with chronic pre-existing conditions may promote the importance of targeting these populations during this pandemic to optimize survival. The objective of this systematic review and meta-analysis is to explore the association of pre-existing conditions with COVID-19 mortality.MethodsWe searched MEDLINE, OVID databases, SCOPUS, and medrxiv.org for the period December 1, 2019, to May 1, 2020. The outcome of interest was the risk of COVID-19 mortality in patients with and without pre-existing conditions. Comorbidities explored were cardiovascular diseases (coronary artery disease, hypertension, cardiac arrhythmias, and congestive heart failure), chronic obstructive pulmonary disease, type 2 diabetes, cancer, chronic kidney disease, chronic liver disease, and stroke. Two independent reviewers extracted data and assessed the risk of bias. All analyses were performed using random-effects models and heterogeneity was quantified.ResultsTen chronic conditions from 19 studies were included in the meta-analysis (n = 61,455 patients with COVID-19; mean age, 61 years; 57% male). Overall the between-study study heterogeneity was medium and studies had low publication bias and high quality. Coronary heart disease, hypertension, congestive heart failure, and cancer significantly increased the risk of mortality from COVID-19. The risk of mortality from COVID-19 in patients with coronary heart disease was 2.4 times as high as those without coronary heart disease (RR= 2.40, 95%CI=1.71-3.37, n=5) and twice as high in patients with hypertension as high as that compared to those without hypertension (RR=1.89, 95%CI= 1.58-2.27, n=9). Patients with cancer also were at twice the risk of mortality from COVID-19 compared to those without cancer (RR=1.93 95%CI 1.15-3.24, n=4), and those with congestive heart failure were at 2.5 times the risk of mortality compared to those without congestive heart failure (RR=2.66, 95%CI 1.58-4.48, n=3).ConclusionsCOVID-19 patients with all any cardiovascular disease, coronary heart disease, hypertension, congestive heart failure, and cancer have an increased risk of mortality. Tailored infection prevention and treatment strategies targeting this high-risk population are warranted to optimize survival.
Machine learning model estimating number of COVID-19 infection cases over coming 24 days in every province of South Korea (XGBoost and MultiOutputRegressor)
Authors: Suzuki Yoshiro , Suzuki Ayaka , Nakamura Shun , Ishikawa Toshiko , Kinoshita Akira 
Published: May 2020

AbstractWe built a machine learning model (ML model) which input the number of daily infection cases and the other information related to COVID-19 over the past 24 days in each of 17 provinces in South Korea, and output the total increase in the number of infection cases in each of 17 provinces over the coming 24 days. We employ a combination of XGBoost and MultiOutputRegressor as machine learning model (ML model). For each province, we conduct a binary classification whether our ML model can classify provinces where total infection cases over the coming 24 days is more than 100. The result is Sensitivity = 3/3 = 100%, Specificity = 11/14 = 78.6%, False Positive Rate = 3/11 = 21.4%, Accuracy = 14/17 = 82.4%. Sensitivity = 100% means that we did not overlook the three provinces where the number of COVID-19 infection cases increased by more than100. In addition, as for the provinces where the actual number of new COVID-19 infection cases is less than 100, the ratio (Specificity) that our ML model can correctly estimate was 78.6%, which is relatively high. From the above all, it is demonstrated that there is a sufficient possibility that our ML model can support the following four points. (1) Promotion of behavior modification of residents in dangerous areas, (2) Assistance for decision to resume economic activities in each province, (3) Assistance in determining infectious disease control measures in each province, (4) Search for factors that are highly correlated with the future increase in the number of COVID-19 infection cases.
REV-ERBα mediates complement expression and circadian regulation of microglial synaptic phagocytosis
Authors: Griffin Percy , Sheehan Patrick W. , Dimitry Julie M. , Guo Chun , Kanan Michael F. , Lee Jiyeon , Zhang Jinsong , Musiek Erik S. 
Published: May 2020

ABSTRACTThe circadian clock has been shown to regulate various aspects of brain health including microglial and astrocyte activation. Here we report that deletion of the master clock protein BMAL1 induces robust increases in the expression of complement genes such asC3, C4bandC1qin the hippocampus. Loss of downstream REV-ERBα-mediated transcriptional repression led to increases inC4bin neurons and astrocytes as well as C3 protein in microglia and astrocytes. REV-ERBα deletion induced complementC3/C4bgene expression and increased microglial phagocytosis of synapses in the CA3 region of the hippocampus. Finally, we observed diurnal variation in the degree of microglial synaptic phagocytosis in wild type mice which was abrogated by REV-ERBα deletion. This work uncovers the BMAL1-REV-ERBα axis as a regulator of complement expression and synaptic phagocytosis in the brain, thereby illuminating a novel mechanism of synaptic regulation by the circadian clock.
Immune landscape of a genetically-engineered murine model of glioma relative to human glioma by single-cell sequencing
Authors: Zamler Daniel B. , Shingu Takashi , Kahn Laura M. , Kassab Cynthia , Ott Martina , Tomczak Katarzyna , Liu Jintan , Li Yating , Lai Ivy , Yee Cassian , Rai Kunal , Watowich Stephanie S. , Heimberger Amy B. , Draetta Giulio F. , Hu Jian 
Published: May 2020

SUMMARYBackgroundThis study focuses on the evaluation of intratumoral immune infiltrates of theQk/trp53/Pten(QPP) triple-knockout mouse model of glioblastoma with the purpose of establishing its relevance compared to the human disease. This included an analysis at the single cell level, of immune cells composition in both spontaneous and implanted mouse tumors and of samples obtained from human tumor resections.MethodsWe analyzed a cohort of fifteen spontaneous QPP mice, nine implanted QPP mice and 10 glioma patients by standard immune profiling methods such as IHC. Of those, we analyzed three spontaneous QPP mice, three implanted QPP mice, and 10 glioma patients by single cell RNA sequencing.ResultsIn the QPP samples we identified a predominantly myeloid cell population of monocytes, macrophages, and microglia, with minor populations of T, B, and NK cells. When comparing spontaneous and implanted mouse samples, we found that there were more neutrophil, T and NKT cells in the implanted model. In human samples, most of the lymphoid and myeloid compartments were immunosuppressive. While the complexity of the myeloid cell populations is preserved between the QPP model and the human disease, we observed significantly more immune-stimulatory populations in the implanted mouse model.ConclusionsWe found that, despite differences at the subpopulation level, the immunosuppressive nature of the immune system in glioma, is recapitulated in our mouse model. Although we observed differences in the proportions of immune infiltrates derived from the spontaneous and implanted mouse models and in LGG compared to GBM, the major constituents are present in all cases and these differences may be caused by various etiological or pathogenic influences on tumor-immune interactions.Key PointsNew GBM mouse model for immunotherapySingle cell profiling of the immune systems in human and mouse GBM
Gfral-expressing Neurons Suppress Food Intake via Aversive Pathways
Authors: Sabatini Paul V. , Frikke-Schmidt Henriette , Arthurs Joe , Gordian Desiree , Patel Anita , Adams Jessica M. , Wang Jine , Jørgensen Sebastien Beck , Olson David P. , Palmiter Richard D. , Myers Martin G , Seeley Randy J. 
Published: May 2020

AbstractTo determine the function and mechanisms of action for hindbrain neurons that express GFRAL, the receptor for the anorexigenic peptide, GDF-15, we generatedGfralcreand conditionalGfralCreERTmice. While signals of infection or pathophysiologic states (rather than meal ingestion) stimulate GFRAL neurons, the artificial activation ofGfralCre- expressing neurons inhibited feeding, decreased gastric emptying, and promoted a conditioned taste aversion (CTA). Additionally, activation of the smaller population of GFRAL neurons captured by theGfralCreERTallele decreased gastric emptying and produced a CTA without suppressing food intake, suggesting that GFRAL neurons primarily modulate gastric physiology and stimulate aversive responses. GFRAL neurons most strongly innervated the parabrachial nucleus (PBN), where they targeted CGRP-expressing (CGRPPBN) neurons. Silencing CGRPPBNneurons abrogated the aversive and anorexic effects of GDF-15. These findings suggest that GFRAL neurons link non-meal-associated, pathophysiologic signals to the aversive suppression of nutrient uptake and absorption.
A solvation induced ring puckering effect in fluorinated prolines and its inclusion in classical force-fields
Authors: Muralidharan Ajay , Schmidt J.R. , Yethiraj Arun 
Published: May 2020

AbstractStrategic incorporation of fluorinated prolines can accelerate folding and increase thermal stability of proteins. It has been suggested that this behavior emerges from puckering effects induced by fluorination of the proline ring. We use electronic structure calculations to characterize the potential energy surface (PES) along puckering coordinates for a simple dipeptide model of proline and its fluorinated derivatives. Comparison of gas phase and implicit solvent calculations shed light on the effect of solvation on electronic structure and conformational preferences of the ring. This effect is unknown in the context of prolines, however, recently reported for furanoses in carbohydrates. The PES based on implicit solvent is then utilized to construct a correction for a classical force-field. The corrected force-field accurately captures the experimental conformational equilibrium including the coupling between ring puckering and cis-trans isomerism in fluorinated prolines. This method can be extended to other rings and substituents besides fluorine.
The scaffold protein IQGAP1 links heat-induced stress signals to alternative splicing regulation in gastric cancer cells
Authors: Birladeanu Andrada , Rogalska Malgorzata , Potiri Myrto , Papadaki Vasiliki , Andreadou Margarita , Kontoyiannis Dimitris , Lewis Joe D. , Erpapazoglou Zoi , Kafasla Panagiota 
Published: May 2020

ABSTRACTIn response to oncogenic signals, Alternative Splicing (AS) regulators such as SR and hnRNP proteins show altered expression levels, subnuclear distribution and/or post-translational modification status, but the link between signals and these changes remains unknown. Here, we report that a cytosolic scaffold protein, IQGAP1, performs this task in response to heat-induced signals. We show that in gastric cancer cells, a nuclear pool of IQGAP1 acts as a tethering module for a group of spliceosome components, including hnRNPM, a splicing factor critical for the response of the spliceosome to heat-shock. IQGAP1 controls hnRNPM’s sumoylation, subnuclear localization and the relevant response of the AS machinery to heat-induced stress. Genome-wide analyses reveal that IQGAP1 and hnRNPM co-regulate the AS of a cell cycle-related RNA regulon in gastric cancer cells, thus favouring the accelerated proliferation phenotype of gastric cancer cells. Overall, we reveal a missing link between stress signals and AS regulation.
Attention Towards Emotions is Modulated by Familiarity with the Expressor. A Comparison Between Bonobos and Humans
Authors: van Berlo Evy , Bionda Thomas , Kret Mariska E. 
Published: May 2020

AbstractWhy can humans be intolerant of, yet also be empathetic towards strangers? This cardinal question has rarely been studied in our closest living relatives, bonobos. Yet, their striking xenophilic tendencies make them an interesting model for reconstructing the socio-emotional capacities of the last common ancestor of hominids. Within a series of dot-probe experiments, we compared bonobos’ and humans’ attention towards scenes depicting familiar (kith and kin) or unfamiliar individuals with emotional or neutral expressions. Results show that attention of bonobos is immediately captured by emotional scenes depicting unfamiliar bonobos, but not by emotional groupmates (Experiment 1) or expressions of humans, irrespective of familiarity (Experiment 2). Using a large community sample, Experiment 3 shows that human attention is mostly captured by emotional rather than neutral expressions of family and friends. On the one hand, our results show that an attentional bias towards emotions is a shared phenomenon between humans and bonobos, but on the other, that both species have their own unique evolutionarily informed bias. These findings support previously proposed adaptive explanations for xenophilia in bonobos which potentially biases them towards emotional expressions of unfamiliar conspecifics, and parochialism in humans, which makes them sensitive to the emotional expressions of close others.
Evaluation of a Loop-Mediated Isothermal Amplification assay to detect carbapenemases fromAcinetobacterspp. directly from bronchoalveolar lavage fluid
Authors: Moreno-Morales J. , Vergara A. , Kostyanev T. , Rodriguez-Baño J. , Goossens H. , Vila J. 
Published: May 2020

AbstractCarbapenem-resistantAcinetobacterspp. mainlyAcinetobacter baumanniiare frequently causing nosocomial infections with high mortality. In this study, the efficacy of the Eazyplex®SuperBug Complete A system (Amplex Diagnostics GmbH, Gars-Bahnhof, Germany), based on loop-mediated isothermal amplification (LAMP), to detect the presence of carbapenemases inAcinetobacterspp. directly from bronchoalveolar lavage samples was assessed, detecting all tested carbapenemases in less than 30 minutes with a sensitivity of 103CFU/ml.
Systemic corticosteroids show no benefit in severe and critical COVID-19 patients in Wuhan, China: A retrospective cohort study
Authors: Wu Jianfeng , Huang Jianqiang , Zhu Guochao , Liu Yihao , Xiao Han , Zhou Qian , Si Xiang , Yi Hui , Wang Cuiping , Yang Daya , Chen Shuling , Liu Xin , Liu Zelong , Wang Qiongya , Lv Qingquan , Huang Ying , Yu Yang , Guan Xiangdong , Li Yanbing , Nirantharakumar Krishnarajah , Cheng KarKeung , Peng Sui , Xiao Haipeng 
Published: May 2020

Background: Systemic corticosteroids are recommended by some treatment guidelines and used in severe and critical COVID-19 patients, though evidence supporting such use is limited.
Methods: From December 26, 2019 to March 15, 2020, 1514 severe and 249 critical hospitalized COVID-19 patients were collected from two medical centers in Wuhan, China. We performed multivariable Cox models, Cox model with time-varying exposure and propensity score analysis (both inverse-probability-of-treatment-weighting (IPTW) and propensity score matching (PSM)) to estimate the association of corticosteroid use with the risk of in-hospital mortality among severe and critical cases.
Results: Corticosteroids were administered in 531 (35.1%) severe and 159 (63.9%) critical patients. Compared to no corticosteroid use group, systemic corticosteroid use showed no benefit in reducing in-hospital mortality in both severe cases (HR=1.77, 95% CI: 1.08-2.89, p=0.023), and critical cases (HR=2.07, 95% CI: 1.08-3.98, p=0.028). In the time-varying Cox analysis that with time varying exposure, systemic corticosteroid use still showed no benefit in either population (for severe patients, HR=2.83, 95% CI: 1.72-4.64, p<	0.001; for critical patients, HR=3.02, 95% CI: 1.59-5.73, p=0.001). Baseline characteristics were matched after IPTW and PSM analysis. For severe COVID-19 patients at admission, corticosteroid use was not associated with improved outcome in either the IPTW analysis. For critical COVID-19 patients at admission, results were consistent with former analysis that corticosteroid use did not reduce in-hospital mortality.
Conclusions: Corticosteroid use showed no benefit in reducing in-hospital mortality for severe or critical cases. The routine use of systemic corticosteroids among severe and critical COVID-19 patients was not recommended.
Online COVID-19 diagnosis with chest CT images: Lesion-attention deep neural networks
Authors: Liu Bin , Gao Xiaoxue , He Mengshuang , Lv Fengmao , Yin Guosheng 
Published: May 2020

AbstractChest computed tomography (CT) scanning is one of the most important technologies for COVID-19 diagnosis and disease monitoring, particularly for early detection of coronavirus. Recent advancements in computer vision motivate more concerted efforts in developing AI-driven diagnostic tools to accommodate the enormous demands for the COVID-19 diagnostic tests globally. To help alleviate burdens on medical systems, we develop a lesion-attention deep neural network (LA-DNN) to predict COVID-19 positive or negative with a richly annotated chest CT image dataset. Based on the textual radiological report accompanied with each CT image, we extract two types of important information for the annotations: One is the indicator of a positive or negative case of COVID-19, and the other is the description of five lesions on the CT images associated with the positive cases. The proposed data-efficient LA-DNN model focuses on the primary task of binary classification for COVID-19 diagnosis, while an auxiliary multi-label learning task is implemented simultaneously to draw the model’s attention to the five lesions associated with COVID-19. The joint task learning process makes it a highly sample-efficient deep neural network that can learn COVID-19 radiology features more effectively with limited but high-quality, rich-information samples. The experimental results show that the area under the curve (AUC) and sensitivity (recall), precision, and accuracy for COVID-19 diagnosis are 94.0%, 88.8%, 87.9%, and 88.6% respectively, which reach the clinical standards for practical use. A free online system is currently alive for fast diagnosis using CT images at the websitehttps://www.covidct.cn/, and all codes and datasets are freely accessible at our github address.