bluuebunny/crossref_metadata_2025_split huggingface dataset:
Risk factors for outbreaks of COVID-19 in care homes following hospital discharge: a national cohort analysis
Authors: Emmerson Chris , Adamson James P , Turner Drew , Gravenor Mike B , Salmon Jane , Cottrell Simon , Middleton Victoria , Thomas Buffy , Mason Brendan W , Williams Chris J 
Published: August 2020

AbstractBackgroundAdult residential and nursing care homes are settings in which older and often vulnerable people live in close proximity. This population experiences a higher proportion of respiratory and gastrointestinal illnesses than the general population and has been shown to have a high morbidity and mortality in relation to COVID-19.MethodsWe examined 3,115 hospital discharges to 1,068 Welsh adult care homes and the subsequent outbreaks of COVID-19 occurring over an 18 week period between 22 February and 27 June 2020. A Cox proportional hazards regression model was used to assess the impact of time-dependent exposure to hospital discharge on the incidence of the first known outbreak, over a window of 7-21 days after discharge, and adjusted for care home characteristics, including size, type of provision and health board.ResultsA total of 330 homes experienced an outbreak of COVID-19, and 544 homes received a discharge from hospital over the study period. The exposure to discharge from hospital was not associated with a significant increase in the risk of a new outbreak (hazard ratio 1·15, 95% CI 0·89, 1·47, p = 0·29) after adjusting for care home characteristics. Care home size was by far the most significant predictor. Hazard ratios (95% CI) in comparison to homes of <10 residents were: 3·40 (1·99, 5·80) for 10-24 residents; 8·25 (4·93, 13·81) for 25-49 residents; and 17·35 (9·65, 31·19) for homes of 50+ residents. When stratified for care home size, the outbreak rates were similar for periods when homes were exposed to a hospital discharge, in comparison to periods when homes were unexposed.ConclusionOur analyses showed that large homes were at considerably greater risk of outbreaks throughout the epidemic, and after adjusting for care home size, a discharge from hospital was not associated with a significant increase in risk.Research in contextWhat is already known on this subjectCare home populations experience more respiratory outbreaks than the general population1 and older people have been more severely affected by COVID-19, with a case fatality proportion of 2·3% overall but 8% in those aged 70-79 and 14·8% in those aged over 802Evidence and modelling suggested that up to half of all COVID-19 fatalities could come from the care home population3 and that testing prior to hospital discharge was not always available or undertaken9Type and use of PPE6 and the number of staff employed can have an impact on care home outbreaks of COVID-196,7What this study addsOur analysis found no effect of hospital discharges on care home outbreaks once care home size had been adjusted for. In line with previous studies, larger care homes were much more likely to experience an outbreak
The effectiveness of a FY-1 doctor preparation course for final year medical students
Authors: Beedham William , Wanigasooriya Kasun , Layton Georgia R. , Chan Ley Taing , Darr Adnan , Mittapalli Devender 
Published: August 2020

AbstractBackgroundStarting work as a junior doctor can be daunting for any medical student. There are numerous aspects of the hidden or informal curriculum which many students fail to acquire during their training.ObjectivesTo evaluate the effectiveness of a novel foundation year one (FY1) doctor preparation course focusing on certain core topics, practical tips and components of the hidden curriculum. The primary objective was to improve the confidence level and knowledge of final year medical student transition to FY1 doctors.MethodA two-day, practical course titled “Preparation 2 Practice” delivering hands-on, small-group and lecture-based teaching, covering core medical student undergraduate curriculum topics in medicine and surgery. The course content spanned therapeutics, documentation skills and managing acute clinical tasks encountered by FY1 doctors during an on-call shift. A pre- and post-course survey and knowledge assessment were carried out to assess the effectiveness of the course. The assessment was MCQ-based, derived from topics covered within our course. The 20-question test and a short survey were administered electronically.ResultsTwenty students from a single UK medical school attended the course. 100% participation was observed in the pre- and post-course test and survey. The median post-course test result was 22 (IQR 20.25 –23.75) which was higher than the median pre course test score of 18.75 (IQR 17–21.75). A Wilcoxon sign rank test revealed a statistically significant difference between the pre- and post-course test results (p=0.0003). The self-reported confidence score of delegates on starting work as a junior doctor was also significantly higher following the course (p=0.004).ConclusionThe results show a significant improvement in perceived confidence and knowledge on core curriculum topics amongst final year medical students having attended our FY1 doctor preparation course. We conclude that there is scope for similar supplementary courses as an adjunct to the undergraduate medical curriculum.
Parameter Estimation of COVID-19 Pandemic Model with Self Protection Behavior Changes
Authors: Mekonen Kassahun Getnet , H/Michael Tatek Getachew , Feyissa Shiferaw 
Published: August 2020

AbstractA mathematical model for the transmission dynamics of Coronavirus diseases (COVID-19) is proposed by incorporating self-protection behavior changes in the population. The disease-free equilibrium point is computed and its stability analysis is studied. The basic reproduction number(R0) of the model is computed and the disease-free equilibrium point is locally and globally stable forR0< 1 and unstable forR0>1. Based on the available data the unknown model parameters are estimated using a combination of least square and Bayesian estimation methods for different countries. Using forward sensitivity index the model parameters is carried out to determine and identify the key factors for the spread of disease dynamics. From country to country the sensitive parameters for the spread of the virus varies. It is found out that the reproduction number depends mostly on the infection rates, the threshold value of the force of infection for a population, the recovery rates, and the virus decay rate in the environment. It is also demonstrated that control of the effective transmission rate (recommended human behavioral change towards self-protective measures) is essential to stop the spreading of the virus. Numerical simulations also show that the virus’s transmission dynamics depend mostly on those sensitive parameters.
Sociodemographic disparities in knowledge, practices, and ability to comply with COVID-19 public health measures in Canada
Authors: Brankston Gabrielle , Merkley Eric , Fisman David N. , Tuite Ashleigh R. , Poljak Zvonimir , Loewen Peter J. , Greer Amy L. 
Published: August 2020

AbstractThe effectiveness of public health interventions for mitigation of the coronavirus (COVID-19) pandemic depends on individual attitudes and the level of compliance toward these measures. We surveyed a representative sample of the Canadian population about risk perceptions, attitudes, and behaviours towards the Canadian COVID-19 public health response. Our analysis demonstrates that these risk perceptions, attitudes, and behaviours varied by several demographic variables identifying a number of areas in which policies could help address issues of public adherence. Examples include targeted messaging for men and younger age groups, social supports for those who need to self-isolate but may not have the means to do so, changes in workplace policies to discourage presenteeism, and provincially co-ordinated masking and safe school reopening policies. Taken together such measures are likely to mitigate the impact of the next pandemic wave in Canada.
SARS-CoV-2 phylodynamics differentiates the effectiveness of non-pharmaceutical interventions
Authors: Rasigade Jean-Philippe , Barray Anaïs , Shapiro Julie Teresa , Coquisart Charlène , Vigouroux Yoann , Bal Antonin , Destras Grégory , Vanhems Philippe , Lina Bruno , Josset Laurence , Wirth Thierry 
Published: August 2020

AbstractQuantifying the effectiveness of large-scale non-pharmaceutical interventions against COVID-19 is critical to adapting responses against future waves of the pandemic. By combining phylogenetic data of 5,198 SARS-CoV-2 genomes with the chronology of non-pharmaceutical interventions in 57 countries, we examine how interventions and combinations thereof alter the divergence rate of viral lineages, which is directly related to the epidemic reproduction number. Home containment and education lockdown had the largest independent impacts and were predicted to reduce the reproduction number by 35% and 26%, respectively. However, we find that in contexts with a reproduction number >2, no individual intervention is sufficient to stop the epidemic and increasingly stringent intervention combinations may be required. Our phylodynamic approach can complement epidemiological models to inform public health strategies against COVID-19.
SARS-CoV-2 3CLpro whole human proteome cleavage prediction and enrichment/depletion analysis
Authors: Prescott Lucas 
Published: August 2020

AbstractA novel coronavirus (SARS-CoV-2) has devastated the globe as a pandemic that has killed more than 1,600,000 people. Widespread vaccination is still uncertain, so many scientific efforts have been directed toward discovering antiviral treatments. Many drugs are being investigated to inhibit the coronavirus main protease, 3CLpro, from cleaving its viral polyprotein, but few publications have addressed this protease’s interactions with the host proteome or their probable contribution to virulence. Too few host protein cleavages have been experimentally verified to fully understand 3CLpro’s global effects on relevant cellular pathways and tissues. Here, I set out to determine this protease’s targets and corresponding potential drug targets. Using a neural network trained on cleavages from 388 coronavirus proteomes with a Matthews correlation coefficient of 0.983, I predict that a large proportion of the human proteome is vulnerable to 3CLpro, with 4,460 out of approximately 20,000 human proteins containing at least one putative cleavage site. These cleavages are nonrandomly distributed and are enriched in the epithelium along the respiratory tract, brain, testis, plasma, and immune tissues and depleted in olfactory and gustatory receptors despite the prevalence of anosmia and ageusia in COVID-19 patients. Affected cellular pathways include cytoskeleton/motor/cell adhesion proteins, nuclear condensation and other epigenetics, host transcription and RNAi, ribosomal stoichiometry and nascent-chain detection and degradation, coagulation, pattern recognition receptors, growth factors, lipoproteins, redox, ubiquitination, and apoptosis. This whole proteome cleavage prediction demonstrates the importance of 3CLpro in expected and nontrivial pathways affecting virulence, lead me to propose more than a dozen potential therapeutic targets against coronaviruses, and should therefore be applied to all viral proteases and subsequently experimentally verified.
Experimental infection of cattle with SARS-CoV-2
Authors: Ulrich Lorenz , Wernike Kerstin , Hoffmann Donata , Mettenleiter Thomas C. , Beer Martin 
Published: August 2020

AbstractSix cattle (Bos taurus) were intranasally inoculated with SARS-CoV-2 and kept together with three naïve in-contact animals. Low-level virus replication and a specific sero-reactivity were observed in two inoculated animals, despite the presence of high antibody titers against a bovine betacoronavirus. The in-contact animals did not become infected.
The tumor microenvironment drives transcriptional phenotypes and their plasticity in metastatic pancreatic cancer
Authors: Raghavan Srivatsan , Winter Peter S. , Navia Andrew W. , Williams Hannah L. , DenAdel Alan , Kalekar Radha L. , Galvez-Reyes Jennyfer , Lowder Kristen E. , Mulugeta Nolawit , Raghavan Manisha S. , Borah Ashir A. , Kapner Kevin S. , Väyrynen Sara A. , Costa Andressa Dias , Ng Raymond W.S. , Wang Junning , Reilly Emma , Ragon Dorisanne Y. , Brais Lauren K. , Jaeger Alex M. , Spurr Liam F. , Li Yvonne Y. , Cherniack Andrew D. , Wakiro Isaac , Rotem Asaf , Johnson Bruce E. , McFarland James M. , Sicinska Ewa T. , Jacks Tyler E. , Clancy Thomas E. , Perez Kimberly , Rubinson Douglas A. , Ng Kimmie , Cleary James M. , Crawford Lorin , Manalis Scott R. , Nowak Jonathan A. , Wolpin Brian M. , Hahn William C. , Aguirre Andrew J. , Shalek Alex K. 
Published: August 2020

SUMMARYBulk transcriptomic studies have defined classical and basal-like gene expression subtypes in pancreatic ductal adenocarcinoma (PDAC) that correlate with survival and response to chemotherapy; however, the underlying mechanisms that govern these subtypes and their heterogeneity remain elusive. Here, we performed single-cell RNA-sequencing of 23 metastatic PDAC needle biopsies and matched organoid models to understand how tumor cell-intrinsic features and extrinsic factors in the tumor microenvironment (TME) shape PDAC cancer cell phenotypes. We identify a novel cancer cell state that co-expresses basal-like and classical signatures, demonstrates upregulation of developmental and KRAS-driven gene expression programs, and represents a transitional intermediate between the basal-like and classical poles. Further, we observe structure to the metastatic TME supporting a model whereby reciprocal intercellular signaling shapes the local microenvironment and influences cancer cell transcriptional subtypes. In organoid culture, we find that transcriptional phenotypes are plastic and strongly skew toward the classical expression state, irrespective of genotype. Moreover, we show that patient-relevant transcriptional heterogeneity can be rescued by supplementing organoid media with factors found in the TME in a subtype-specific manner. Collectively, our study demonstrates that distinct microenvironmental signals are critical regulators of clinically relevant PDAC transcriptional states and their plasticity, identifies the necessity for considering the TME in cancer modeling efforts, and provides a generalizable approach for delineating the cell-intrinsic versus -extrinsic factors that govern tumor cell phenotypes.
In Vitro Inactivation of Human Coronavirus by Titania Nanoparticle Coatings and UVC Radiation: Throwing Light on SARS-CoV-2
Authors: Khaiboullina Svetlana , Uppal Timsy , Dhabarde Nikhil , Subramanian Vaidyanathan Ravi , Verma Subhash C. 
Published: August 2020

AbstractThe newly identified pathogenic human coronavirus, SARS-CoV-2, led to an atypical pneumonia-like severe acute respiratory syndrome (SARS) outbreak calledcoronavirusdisease 2019 (COVID-19). Currently, nearly 23 million cases have been confirmed worldwide with the highest COVID-19 cases been confirmed in the United States. As there is no vaccine or any effective interventions, massive efforts to create a postential vaccine to combat COVID-19 is underway. In the meantime, safety precautions and effective disease control strategies appear to be vital for preventing the virus spread in the public places. Due to the longevity of the virus on smooth surfaces, photocatalytic properties of self-disinfecting/cleaning surfaces appear to be a promising tool to help guide disinfection policies to control infectious SAR-CoV-2 spread in high-traffic areas such as hospitals, grocery stores, airports, schools, and stadiums. Here, we explored the photocatalytic properties of nanosized TiO2(TNPs) as induced by the UV radiation, towards virus deactivation. Our preliminary results using close genetic relative of SAR-CoV-2, HCoV-NL63, showed the virucidal efficacy of photoactive TNPs deposited on glass coverslips, as examined by quantitative RT-PCR and virus culture assays. Efforts to extrapolate the underlying concepts described in this study to SARS-CoV-2 are currently underway.
Phenotype prediction from genome-wide genotyping data: a crowdsourcing experiment
Authors: Naret Olivier , Baranger David AA , Mohanty Sharada Prasanna , Tzovaras Bastian Greshake , Salathé Marcel , Fellay Jacques ,   with the openSNP and crowdAI community
Published: August 2020

AbstractBackgroundThe increasing statistical power of genome-wide association studies is fostering the development of precision medicine through genomic predictions of complex traits. Nevertheless, it has been shown that the results remain relatively modest. A reason might be the nature of the methods typically used to construct genomic predictions. Recent machine learning techniques have properties that could help to capture the architecture of complex traits better and improve genomic prediction accuracy.MethodsWe relied on crowd-sourcing to efficiently compare multiple genomic prediction methods. This represents an innovative approach in the genomic field because of the privacy concerns linked to human genetic data. There are two crowd-sourcing elements building our study. First, we constructed a dataset from openSNP (opensnp.org), an open repository where people voluntarily share their genotyping data and phenotypic information in an effort to participate in open science. To leverage this resource we release the ‘openSNP Cohort Maker’, a tool that builds a homogeneous and up-to-date cohort based on the data available on opensnp.org. Second, we organized an open online challenge on the CrowdAI platform (crowdai.org) aiming at predicting height from genome-wide genotyping data.ResultsThe ‘openSNP Height Prediction’ challenge lasted for three months. A total of 138 challengers contributed to 1275 submissions. The winner computed a polygenic risk score using the publicly available summary statistics of the GIANT study to achieve the best result (r2= 0.53 versusr2= 0.49 for the second-best).ConclusionWe report here the first crowd-sourced challenge on publicly available genome-wide genotyping data. We also deliver the ‘openSNP Cohort Maker’ that will allow people to make use of the data available on opensnp.org.
Predicting drug sensitivity of cancer cells based on DNA methylation levels
Authors: Miranda Sofia P. , Baião Fernanda A. , Maçaira Paula M. , Fleck Julia L. , Piccolo Stephen R. 
Published: August 2020

AbstractCancer cell lines, which are cell cultures developed from tumor samples, represent one of the least expensive and most studied preclinical models for drug development. Accurately predicting drug response for a given cell line based on molecular features may help to optimize drug-development pipelines and explain mechanisms behind treatment responses. In this study, we focus on DNA methylation profiles as one type of molecular feature that is known to drive tumorigenesis and modulate treatment responses. Using genome-wide, DNA methylation profiles from 987 cell lines from the Genomics of Drug Sensitivity in Cancer database, we applied machine-learning algorithms to evaluate the potential to predict cytotoxic responses for eight anti-cancer drugs. We compared the performance of five classification algorithms and four regression algorithms that use diverse methodologies, including tree-, probability-, kernel-, ensemble-, and distance-based approaches. For both types of algorithm, we artificially subsampled the data to varying degrees, aiming to understand whether training models based on relatively extreme outcomes would yield improved performance. We also performed an information-gain analysis to examine which genes were most predictive of drug responses. Finally, we used tumor data from The Cancer Genome Atlas to evaluate the feasibility of predicting clinical responses in humans based on models derived from cell lines. When using classification or regression algorithms to predict discrete or continuous responses, respectively, we consistently observed excellent predictive performance when the training and test sets both consisted of cell-line data. However, classification models derived from cell-line data failed to generalize effectively for tumors.
Medial prefrontal activity at encoding determines enhanced recognition of threatening faces after 1.5 years
Authors: Liu Xiqin , Zhou Xinqi , Zeng Yixu , Li Jialin , Zhao Weihua , Xu Lei , Zheng Xiaoxiao , Fu Meina , Yao Shuxia , Cannistraci Carlo V. , Kendrick Keith M. , Becker Benjamin 
Published: August 2020

AbstractStudies demonstrated that faces with threatening emotional expressions are better remembered than non-threatening faces. However, whether this memory advantage persists over years and which neural systems underlie such an effect remains unknown. Here, we investigated recognition of incidentally encoded faces with angry, fearful, happy, sad and neutral expressions over >1.5 years (N= 89). Univariate analyses showed that threatening faces (angry, fearful) were better recognized than happy and neutral faces after >1.5 years, and that the threat-related memory enhancement was driven by forgetting of non-threatening faces. Multivariate principal component analysis (PCA) confirmed the discriminative performance between threatening and non-threatening faces. With an innovative Behavioral Pattern Similarity Analysis (BPSA) approach and functional magnetic resonance imaging (fMRI) acquisition during encoding, we further found that the long-term memory advantage for threatening faces were underpinned by differential neural encoding in the left inferior occipital gyrus (IOG) and right ventromedial prefrontal/orbitofrontal cortex (vmPFC/OFC). Our study provides the first evidence that threatening facial expressions lead to persistent face recognition over periods of >1.5 years and differential encoding-related activity in the visual cortex and medial prefrontal cortex may underlie this effect.
piRNA-mediated gene regulation and adaptation to sex-specific transposon expression inD. melanogastermale germline
Authors: Chen Peiwei , Kotov Alexei A. , Godneeva Baira K. , Bazylev Sergei S. , Olenina Ludmila V. , Aravin Alexei A. 
Published: August 2020

SUMMARYSmall non-coding piRNAs act as sequence-specific guides to repress complementary targets in Metazoa. Prior studies inDrosophilaovaries have demonstrated the function of piRNA pathway in transposon silencing and therefore genome defense. However, the ability of piRNA program to respond to different transposon landscape and the role of piRNAs in regulating host gene expression remain poorly understood. Here, we comprehensively analyzed piRNA expression and defined the repertoire of their targets inDrosophila melanogastertestes. Comparison of piRNA programs between sexes revealed sexual dimorphism in piRNA programs that parallel sex-specific transposon expression. Using a novel bioinformatic pipeline, we identified new piRNA clusters and established complex satellites as dual-strand piRNA clusters. While sharing most piRNA clusters, two sexes employ them differentially to combat sex-specific transposon landscape. We found several host genes targeted by piRNAs in testis, includingCG12717/pita, a SUMO protease gene. piRNAs encoded on Y chromosome silencepita, but not its paralog, to exert sex- and paralog-specific gene regulation. Interestingly,pitais targeted by endogenous siRNAs in a sibling species,Drosophila mauritiana, suggesting distinct but related silencing strategies invented in recent evolution to regulate a conserved protein-encoding gene.