Corpus overview


Overview

MeSH Disease

Human Phenotype

Pneumonia (231)

Fever (70)

Cough (38)

Hypertension (27)

Falls (24)


Transmission

Seroprevalence
    displaying 1371 - 1380 records in total 1730
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    Development of high affinity monobodies recognizing SARS-CoV-2 antigen

    Authors: Yushen Du; Tian-hao Zhang; Xiangzhi Meng; Yuan Shi; Menglong Hu; Shuofeng Yuan; Chit Ying La; Shu-xing Li; Siwei Liu; Jiayan Li; Haigen Huang; Hong Jian; Dongdong Chen; Li Sheng; Mengying Hong; Anders Olson; Hsiang-I Liao; Xiaojiang Chen; Xinmin Li; Gexin Zhao; Richard W. Roberts; Jasper F W Chan; Dong-Yan Jin; Irvin SY Chen; Honglin Chen; Kwok-Yung Yuen; Quan Hao; Ren Sun

    doi:10.21203/rs.3.rs-25828/v1 Date: 2020-04-27 Source: ResearchSquare

    The coronavirus disease MESHD 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 MESHD (SARS-CoV-2) has been a threat to global public health. Prompt patient identification and quarantine is the most effective way to control its rapid transmission TRANS, which can be facilitated by early detection of viral antigens. Here we present a platform to develop and optimize the fibronectin-based affinity-enhanced antibody SERO mimetics (monobodies) for recognizing viral antigens. Specifically, we developed monobodies targeting SARS-CoV-2 nucleocapsid (N) protein. We showed that two monobodies, NN2 and NC2, bind to N protein’s N- and C-terminal domains respectively with a Kd in nM range.The specificity of the recognition was confirmed with co-immunoprecipitation and immunofluorescence assays. Furthermore, we demonstrated that one round of in vitro maturation using mRNA display can improve the binding affinity of monobodies. Machine learning algorithms were integrated with deep sequencing data for selecting candidates that improve the detection sensitivity SERO of N. Using this pair of monobodies, we have developed an enzyme-linked immunosorbent assay SERO ( ELISA SERO) for viral detection. We were able to detect recombinant N at 4 pg/ml and detect N in viral culture supernatant, with no cross-reactivity with other CoV. Integrating high-dense mutagenesis, mRNA display, deep sequencing and machine learning, this platform can be applied through iterations to identify and optimize monobodies against emerging viral antigens, potentiating point-of-care detection of communicable diseases in a cost-and time-sensitive manner.Authors Yushen Du, Tian-hao Zhang, Xiangzhi Meng, Yuan Shi, and Menglong Hu contributed equally to this work.

    Clinical characteristics and laboratory indicator analysis of 67 COVID-19 pneumonia HP pneumonia MESHD patients in Suzhou, China

    Authors: Yi Wang; Lin Yao; Jian-Ping Zhang; Pei-Jun Tang; Zhi-Jian Ye; Xing-Hua Shen; Jun-Chi Xu; Mei-Ying Wu; Xin Yu

    doi:10.21203/rs.3.rs-25756/v2 Date: 2020-04-27 Source: ResearchSquare

    Background Sudden exacerbations and respiratory failure HP respiratory failure MESHD are major causes of death MESHD in patients with severe coronavirus disease MESHD 2019(COVID-19) pneumonia HP pneumonia MESHD, but indicators for the prediction and treatment of severe patients are still lacking. Methods A retrospective analysis of 67 collected cases was conducted and included approximately 67 patients with COVID-19 pneumonia HP pneumonia MESHD who were admitted to the Suzhou Fifth People’s Hospital from January 1, 2020 to February 8, 2020. The epidemiological, clinical and imaging characteristics as well as laboratory data of the 67 patients were analyzed.Results The study found that fibrinogen(FIB) was increased in 45 (65.2%) patients, and when FIB reached a critical value of 4.805 g/L, the sensitivity SERO and specificity、DA, helping to distinguish general and severe cases, were 100% and 14%、92.9%, respectively, which were significantly better than those for lymphocyte count and myoglobin. Chest CT images indicated that the cumulative number of lung lobes with lesions MESHD in severe patients was significantly higher than that in general patients (P<0.05), and the cumulative number of lung lobes MESHD with lesions was negatively correlated with lymphocyte count and positively correlated with myoglobin and FIB. Our study also found that there was no obvious effect of hormone therapy in patients with severe COVID-19.Conclusions Based on the retrospective analysis, FIB was found to be increased in severe patients and was better than lymphocyte count and myoglobin in distinguishing general and severe patients. The study also suggested that hormone treatment has no significant effect on COVID-19.

    Clinical characteristics and laboratory indicator analysis of 67 COVID-19 pneumonia HP pneumonia MESHD patients in Suzhou, China

    Authors: Yi Wang; Lin Yao; Jian-Ping Zhang; Pei-Jun Tang; Zhi-Jian Ye; Xing-Hua Shen; Jun-Chi Xu; Mei-Ying Wu; Xin Yu

    doi:10.21203/rs.3.rs-25756/v3 Date: 2020-04-27 Source: ResearchSquare

    BackgroundSudden exacerbations and respiratory failure HP respiratory failure MESHD are major causes of death MESHD in patients with severe coronavirus disease MESHD 2019(COVID-19) pneumonia HP pneumonia MESHD, but indicators for the prediction and treatment of severe patients are still lacking.MethodsA retrospective analysis of 67 collected cases was conducted and included approximately 67 patients with COVID-19 pneumonia HP pneumonia MESHD who were admitted to the Suzhou Fifth People’s Hospital from January 1, 2020 to February 8, 2020. The epidemiological, clinical and imaging characteristics as well as laboratory data of the 67 patients were analyzed.ResultsThe study found that fibrinogen(FIB) was increased in 45 (65.2%) patients, and when FIB reached a critical value of 4.805 g/L, the sensitivity SERO and specificity、DA, helping to distinguish general and severe cases, were 100% and 14%、92.9%, respectively, which were significantly better than those for lymphocyte count and myoglobin. Chest CT images indicated that the cumulative number of lung lobes with lesions MESHD in severe patients was significantly higher than that in general patients (P<0.05), and the cumulative number of lung lobes MESHD with lesions was negatively correlated with lymphocyte count and positively correlated with myoglobin and FIB. Our study also found that there was no obvious effect of hormone therapy in patients with severe COVID-19.ConclusionsBased on the retrospective analysis, FIB was found to be increased in severe patients and was better than lymphocyte count and myoglobin in distinguishing general and severe patients. The study also suggested that hormone treatment has no significant effect on COVID-19.

    Research on CNN-based Models Optimized by Genetic Algorithm and Application in the Diagnosis of Pneumonia HP and COVID-19

    Authors: Zihan Zeng; Bo Wang; Zhiwen Zhao

    doi:10.1101/2020.04.21.20072637 Date: 2020-04-26 Source: medRxiv

    In this research, an optimized deep learning method was proposed to explore the possibility and practicality of neural net-work applications in medical imaging. The method was used to achieve the goal of judging common pneumonia HP pneumonia MESHD and even COVID-19 more effectively. Where, the genetic algorithm was taken advantage to optimize the Dropout module, which is essential in neural networks so as to improve the performance SERO of typical neural network models. The experiment results demonstrate that the proposed method shows excellent performance SERO and strong practicability in judging pneumonia HP pneumonia MESHD, and the application of advanced artificial intelligence technology in the field of medical imaging has broad prospects.

    Qualitative and quantitative evaluation of COVID-19 outbreak severity with the use of meta-projections based on Richards' curve parameters

    Authors: Evagoras Xydas; Konstantinos Kostas

    id:2004.12398v1 Date: 2020-04-26 Source: arXiv

    Researchers have shown that even simple empirical models stemming from biological growth modeling have the potential to provide useful information on the development and severity of ongoing epidemics since they can be employed as tools for carrying out projections on the size of the affected population, timing of turning points, as well as best- and worst-case scenarios. Nevertheless, they commonly exhibit considerable sensitivity SERO to some input parameters' variance which results in large fluctuations in the generated projections, thus rendering predictions difficult and even risky. In this work we examine a novel meta-projections-based approach which allows us to evaluate the model's current trends and assess whether generated projections are at a transient or stable state. Meta-projections can be extracted from graphs of successive estimations of model's parameters and resulting projections, over a sequence of days being gradually added to the employed model. In other words, projections are carried out on truncated time series of cumulative numbers of confirmed cases TRANS with increased lengths at each successive evaluation. This allows us to trace TRANS the values of model parameters over a certain period of time and examine their trends which may converge to specific values for settled-growth cases or exhibit a changing or even an erratic behavior for cases that undergo epidemiological transitions and/or are inappropriately described by the current model instance(s). We have computed meta-projections and compared our findings for countries at different stages of the epidemic with stable or unstable behaviors and increasing or decreasing numbers of confirmed cases TRANS. Our results indicate that meta-projections can aid researchers in assessing the appropriateness of their relevant models and in effect decrease the uncertainty in their estimations of an epidemic's severity and development.

    Antibody tests SERO in detecting SARS-CoV-2 infection MESHD: a meta-analysis

    Authors: Panagiota I Kontou; Georgia G Braliou; Niki L Dimou; Georgios Nikolopoulos; Pantelis G Bagos

    doi:10.1101/2020.04.22.20074914 Date: 2020-04-25 Source: medRxiv

    With the emergence of SARS-CoV-2 and the associated Coronavirus disease 2019 (COVID-19), there is an imperative need for diagnostic tests that can identify the infection. Although Nucleic Acid Test (NAT) is considered to be the gold standard, serological tests SERO based on antibodies SERO could be very helpful. However, individual studies measuring the accuracy of the various tests are usually underpowered and inconsistent, thus, a comparison of different tests is needed. We performed a systematic review and meta-analysis following the PRISMA guidelines. We conducted the literature search in PubMed, medRxiv and bioRxiv. For the statistical analysis we used the bivariate method for meta-analysis of diagnostic tests pooling sensitivities SERO and specificities. We evaluated IgM and IgG tests based on Enzyme-linked immunosorbent assay SERO ( ELISA SERO), Chemiluminescence Enzyme Immunoassays SERO (CLIA), Fluorescence Immunoassays SERO (FIA) and the point-of-care (POC) Lateral Flow Immunoassays SERO (LFIA) that are based on immunochromatography. In total, we identified 38 eligible studies that include data from 7,848 individuals. The analyses showed that tests using the S antigen are more sensitive than N antigen-based tests. IgG tests perform better compared to IgM ones, and show better sensitivity SERO when the samples were taken longer after the onset of symptoms TRANS. Moreover, irrespective of the method, a combined IgG/IgM test seems to be a better choice in terms of sensitivity SERO than measuring either antibody SERO type alone. All methods yielded high specificity with some of them ( ELISA SERO and LFIA) reaching levels around 99%. ELISA SERO- and CLIA-based methods performed better in terms of sensitivity SERO (90-94%) followed by LFIA and FIA with sensitivities SERO ranging from 80% to 86%. ELISA SERO tests could be a safer choice at this stage of the pandemic. POC tests SERO (LFIA), that are more attractive for large seroprevalence SERO studies show high specificity but lower sensitivity SERO and this should be taken into account when designing and performing seroprevalence SERO studies.

    eCovSens-Ultrasensitive Novel In-House Built Printed Circuit Board Based Electrochemical Device for Rapid Detection of nCovid-19

    Authors: Subhasis Mahari; Akanksha Roberts; Deepshikha Shahdeo; Sonu Gandhi

    doi:10.1101/2020.04.24.059204 Date: 2020-04-25 Source: bioRxiv

    Severe acute respiratory syndrome coronavirus 2 MESHD (SARS-CoV-2 or nCovid-19) outbreak has become a huge public health issue due to its rapid transmission TRANS and global pandemic. Currently, there are no vaccines or drugs available for nCovid-19, hence early detection is crucial to help and manage the outbreak. Here, we report an in-house built biosensor device (eCovSens) and compare it with a commercial potentiostat for the detection of nCovid-19 spike antigen (nCovid-19Ag) in spiked saliva samples. A potentiostat based sensor was fabricated using fluorine doped tin oxide electrode (FTO) with gold nanoparticle (AuNPs) and immobilized with nCovid-19 monoclonal antibody SERO (nCovid-19Ab) to measure change in the electrical conductivity. Similarly, eCovSens was used to measure change in electrical conductivity by immobilizing nCovid-19 Ab on screen printed carbon electrode (SPCE). The performances SERO of both sensors were recorded upon interaction of nCovid-19Ab with its specific nCovid-19Ag. Under optimum conditions, the FTO based immunosensor and eCovSens displayed high sensitivity SERO for detection of nCovid-19Ag, ranging from 1 fM to 1 M. Our in-house developed device can successfully detect nCovid-19Ag at 10 fM concentration in standard buffer that is in close agreement with FTO/AuNPs sensor. The limit of detection (LOD) was found to be 90 fM with eCovSens and 120 fM with potentiostst in case of spiked saliva samples. The proposed portable eCovSens device can be used as a diagnostic tool for the rapid (within 10-30 s) detection of nCovid-19Ag traces TRANS directly in patient saliva in a non-invasive manner.

    MINERVA: A facile strategy for SARS-CoV-2 whole genome deep sequencing of clinical samples

    Authors: Chen Chen; Jizhou Li; Lin Di; Qiuyu Jing; Pengcheng Du; Chuan Song; Jiarui Li; Qiong Li; Yunlong Cao; Sunney Xie; Angela Ruohao Wu; Hui Zeng; Yanyi Huang; Jianbin Wang

    doi:10.1101/2020.04.25.060947 Date: 2020-04-25 Source: bioRxiv

    The novel coronavirus disease MESHD 2019 (COVID-19) pandemic poses a serious public health risk. Analyzing the genome of severe acute respiratory syndrome coronavirus 2 MESHD (SARS-CoV-2) from clinical samples is crucial for the understanding of viral spread and viral evolution, as well as for vaccine development. Existing sample preparation methods for viral genome sequencing are demanding on user technique and time, and thus not ideal for time-sensitive clinical samples; these methods are also not optimized for high performance SERO on viral genomes. We have developed MetagenomIc RNA EnRichment VirAl sequencing (MINERVA), a facile, practical, and robust approach for metagenomic and deep viral sequencing from clinical samples. This approach uses direct tagmentation of RNA/DNA hybrids using Tn5 transposase to greatly simplify the sequencing library construction process, while subsequent targeted enrichment can generate viral genomes with high sensitivity SERO, coverage, and depth. We demonstrate the utility of MINERVA on pharyngeal, sputum and stool samples collected from COVID-19 patients, successfully obtaining both whole metatranscriptomes and complete high-depth high-coverage SARS-CoV-2 genomes from these clinical samples, with high yield and robustness. MINERVA is compatible with clinical nucleic extracts containing carrier TRANS RNA. With a shortened hands-on time from sample to virus-enriched sequencing-ready library, this rapid, versatile, and clinic-friendly approach will facilitate monitoring of viral genetic variations during outbreaks, both current and future.

    POCOVID-Net: Automatic Detection of COVID-19 From a New Lung Ultrasound Imaging Dataset (POCUS)

    Authors: Jannis Born; Gabriel Brändle; Manuel Cossio; Marion Disdier; Julie Goulet; Jérémie Roulin; Nina Wiedemann

    id:2004.12084v3 Date: 2020-04-25 Source: arXiv

    With the rapid development of COVID-19 into a global pandemic, there is an ever more urgent need for cheap, fast and reliable tools that can assist physicians in diagnosing COVID-19. Medical imaging such as CT can take a key role in complementing conventional diagnostic tools from molecular biology, and, using deep learning techniques, several automatic systems were demonstrated promising performances SERO using CT or X-ray data. Here, we advocate a more prominent role of point-of-care ultrasound imaging to guide COVID-19 detection. Ultrasound is non-invasive and ubiquitous in medical facilities around the globe. Our contribution is threefold. First, we gather a lung ultrasound (POCUS) dataset consisting of (currently) 1103 images (654 COVID-19, 277 bacterial pneumonia HP pneumonia MESHD and 172 healthy controls), sampled from 64 videos. While this dataset was assembled from various online sources and is by no means exhaustive, it was processed specifically to feed deep learning models and is intended to serve as a starting point for an open-access initiative. Second, we train a deep convolutional neural network (POCOVID-Net) on this 3-class dataset and achieve an accuracy of 89% and, by a majority vote, a video accuracy of 92% . For detecting COVID-19 in particular, the model performs with a sensitivity SERO of 0.96, a specificity of 0.79 and F1-score of 0.92 in a 5-fold cross validation. Third, we provide an open-access web service (POCOVIDScreen) that is available at: https://pocovidscreen.org. The website deploys the predictive model, allowing to perform predictions on ultrasound lung images. In addition, it grants medical staff the option to (bulk) upload their own screenings in order to contribute to the growing public database of pathological lung ultrasound images. Dataset and code are available from: https://github.com/jannisborn/covid19_pocus_ultrasound

    A rapid, low cost, and highly sensitive SARS-CoV-2 diagnostic based on whole genome sequencing

    Authors: Brian Glenn St Hilaire; Neva C. Durand; Namita Mitra; Saul Godinez Pulido; Ragini Mahajan; Alyssa Blackburn; Zane L. Colaric; Joshua W. M. Theisen; David Weisz; Olga Dudchenko; Andreas Gnirke; Suhas S.P. Rao; Parwinder Kaur; Erez Lieberman Aiden; Aviva P Aiden

    doi:10.1101/2020.04.25.061499 Date: 2020-04-25 Source: bioRxiv

    Early detection of infection MESHD with SARS-CoV-2 is key to managing the current global pandemic, as evidence shows the virus is most contagious on or before symptom onset TRANS. Here, we introduce a low-cost, high-throughput method for diagnosis of SARS-CoV-2 infection MESHD, dubbed Pathogen-Oriented Low-Cost Assembly & Re-Sequencing (POLAR), that enhances sensitivity SERO by aiming to amplify the entire SARS-CoV-2 genome rather than targeting particular viral loci, as in typical RT-PCR assays. To achieve this goal, we combine a SARS-CoV-2 enrichment method developed by the ARTIC Network (https://artic.network/) with short-read DNA sequencing and de novo genome assembly. We are able to reliably (>95% accuracy) detect SARS-CoV-2 at concentrations of 84 genome equivalents per milliliter, better than the reported limits of detection of almost all diagnostic methods currently approved by the US Food and Drug Administration. At higher concentrations, we are able to reliably assemble the SARS-CoV-2 genome in the sample, often with no gaps and perfect accuracy. Such genome assemblies enable the spread of the disease TRANS to be analyzed much more effectively than would be possible with an ordinary yes/no diagnostic, and can help identify vaccine and drug targets. Finally, we show that POLAR diagnoses on 10 of 10 clinical nasopharyngeal swab samples (half positive, half negative) match those obtained in a CLIA-certified lab using the Center for Disease Controls 2019-Novel Coronavirus test. Using POLAR, a single person can process 192 samples over the course of an 8-hour experiment, at a cost of [~]$30/patient, enabling a 24-hour turnaround with sequencing and data analysis time included. Further testing and refinement will likely enable greater enhancements in the sensitivity SERO of the above approach.

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MeSH Disease
Human Phenotype
Transmission
Seroprevalence


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