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MeSH Disease

Human Phenotype

Transmission

Seroprevalence
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    Stochasticity and heterogeneity in the transmission TRANS dynamics of SARS-CoV-2

    Authors: Benjamin M. Althouse; Edward A. Wenger; Joel C. Miller; Samuel V. Scarpino; Antoine Allard; Laurent H├ębert-Dufresne; Hao Hu

    id:2005.13689v1 Date: 2020-05-27 Source: arXiv

    SARS-CoV-2 causing COVID-19 disease MESHD has moved rapidly around the globe, infecting millions and killing hundreds of thousands. The basic reproduction number TRANS, which has been widely used and misused to characterize the transmissibility TRANS of the virus, hides the fact that transmission TRANS is stochastic, is dominated by a small number of individuals, and is driven by super-spreading events (SSEs). The distinct transmission TRANS features, such as high stochasticity under low prevalence SERO, and the central role played by SSEs on transmission TRANS dynamics, should not be overlooked. Many explosive SSEs have occurred in indoor settings stoking the pandemic and shaping its spread, such as long-term care facilities, prisons, meat-packing plants, fish factories, cruise ships, family gatherings, parties and night clubs HP. These SSEs demonstrate the urgent need to understand routes of transmission TRANS, while posing an opportunity that outbreak can be effectively contained with targeted interventions to eliminate SSEs. Here, we describe the potential types of SSEs, how they influence transmission TRANS, and give recommendations for control of SARS-CoV-2.

    Knowledge synthesis from 100 million biomedical documents augments the deep expression profiling of coronavirus receptors

    Authors: AJ Venkatakrishnan; Arjun Puranik; Akash Anand; David Zemmour; Xiang Yao; Xiaoying Wu; Ramakrishna Chilaka; Dariusz K. Murakowski; Kristopher Standish; Bharathwaj Raghunathan; Tyler Wagner; Enrique Garcia-Rivera; Hugo Solomon; Abhinav Garg; Rakesh Barve; Anuli Anyanwu-Ofili; Najat Khan; Venky Soundararajan

    id:2003.12773v1 Date: 2020-03-28 Source: arXiv

    The COVID-19 pandemic demands assimilation of all available biomedical knowledge to decode its mechanisms of pathogenicity and transmission TRANS. Despite the recent renaissance in unsupervised neural networks for decoding unstructured natural languages, a platform for the real-time synthesis of the exponentially growing biomedical literature and its comprehensive triangulation with deep omic insights is not available. Here, we present the nferX platform for dynamic inference from over 45 quadrillion possible conceptual associations extracted from unstructured biomedical text, and their triangulation with Single Cell RNA-sequencing based insights from over 25 tissues. Using this platform, we identify intersections between the pathologic manifestations of COVID-19 and the comprehensive expression profile of the SARS-CoV-2 receptor ACE2. We find that tongue keratinocytes and olfactory epithelial cells are likely under-appreciated targets of SARS-CoV-2 infection MESHD, correlating with reported loss of sense of taste and smell as early indicators of COVID-19 infection MESHD, including in otherwise asymptomatic TRANS patients. Airway club HP cells, ciliated cells and type II pneumocytes in the lung, and enterocytes of the gut also express ACE2. This study demonstrates how a holistic data science platform can leverage unprecedented quantities of structured and unstructured publicly available data to accelerate the generation of impactful biological insights and hypotheses.

    A Hint on the COVID-19 Risk: Population Disparities in Gene Expression of Three Receptors of SARS-CoV

    Authors: Guoshuai Cai; Xiang Cui; Xia Zhu; Jun Zhou

    id:10.20944/preprints202002.0408.v1 Date: 2020-02-27 Source: Preprints.org

    The current spreading novel coronavirus SARS-CoV-2 is highly infectious and pathogenic and has attracted global attention. Recent studies have found that SARS-CoV-2 and SARS-CoV share around 80% of homology and use the same cell entry receptor, ACE2. These inspired us to study other receptors of SARS-CoV, which may be used for SARS-CoV-2 binding as well. In this study, we screened the gene expression of three receptors (ACE2, DC-SIGN and L-SIGN) in four datasets of normal lung tissue from lung adenocarcinoma MESHD lung adenocarcinoma HP patients and two single-cell RNA sequencing datasets from normal lung and bronchial epithelial cells separately. No significant difference in gene expression of these three receptors were found between gender TRANS groups ( male TRANS vs female TRANS). We found higher gene expression of DC-SIGN in elder with age TRANS>60 and higher gene expression of L-SIGN in Caucasian than Asian. Similar to ACE2, we observed significantly higher DC-SIGN gene expression in the lungs of smokers, especially former smokers. However, smokers upregulate ACE2 and DC-SIGN gene expression in different cell types. In the whole lung, ACE2 is actively expressed in remodeled Alveolar Type II cells of former smokers, while DC-SIGN is largely expressed in monocytes of former smokers and dendritic cells of current smokers. In bronchial epithelium, no obvious gene expression of DC-SIGN and L-SIGN was observed while ACE2 was found to be actively expressed in goblet cells of current smokers and club HP cells of non-smokers. In conclusion, our findings may indicate that smokers, especially former smokers, and people over 60 have higher risk and are more susceptible to SARS-CoV-2 infection MESHD. Also, this study provides hints on possible SARS-CoV-2 pathogenicity mechanisms in lung infection MESHD.

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MeSH Disease
Human Phenotype
Transmission
Seroprevalence


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