Corpus overview


Overview

MeSH Disease

Human Phenotype

Transmission

There are no transmission terms in the subcorpus


Seroprevalence
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    Automatic Detection of Coronavirus Disease MESHD (COVID-19) in X-ray and CT Images: A Machine Learning-Based Approach

    Authors: Sara Hosseinzadeh Kassani; Peyman Hosseinzadeh Kassasni; Michal J. Wesolowski; Kevin A. Schneider; Ralph Deters

    id:2004.10641v1 Date: 2020-04-22 Source: arXiv

    The newly identified Coronavirus pneumonia MESHD pneumonia HP, subsequently termed COVID-19, is highly transmittable and pathogenic with no clinically approved antiviral drug or vaccine available for treatment. The most common symptoms of COVID-19 are dry cough HP, sore throat, and fever HP fever MESHD. Symptoms can progress to a severe form of pneumonia HP pneumonia MESHD with critical complications, including septic shock MESHD shock HP, pulmonary edema HP pulmonary edema MESHD, acute respiratory distress syndrome MESHD respiratory distress HP syndrome and multi-organ failure MESHD. While medical imaging is not currently recommended in Canada for primary diagnosis of COVID-19, computer-aided diagnosis systems could assist in the early detection of COVID-19 abnormalities and help to monitor the progression of the disease, potentially reduce mortality rates. In this study, we compare popular deep learning-based feature extraction frameworks for automatic COVID-19 classification. To obtain the most accurate feature, which is an essential component of learning, MobileNet, DenseNet, Xception, ResNet, InceptionV3, InceptionResNetV2, VGGNet, NASNet were chosen amongst a pool of deep convolutional neural networks. The extracted features were then fed into several machine learning classifiers to classify subjects as either a case of COVID-19 or a control. This approach avoided task-specific data pre-processing methods to support a better generalization ability for unseen data. The performance SERO of the proposed method was validated on a publicly available COVID-19 dataset of chest X-ray and CT images. The DenseNet121 feature extractor with Bagging tree classifier achieved the best performance SERO with 99% classification accuracy. The second-best learner was a hybrid of the a ResNet50 feature extractor trained by LightGBM with an accuracy of 98%.

    Kinins and Cytokines in COVID-19: A Comprehensive Pathophysiological Approach

    Authors: Frank van de Veerdonk; Mihai G. Netea; Marcel van Deuren; Jos W.M. van der Meer; Quirijn de Mast; Roger J. Bruggemann; Hans van der Hoeven

    id:10.20944/preprints202004.0023.v1 Date: 2020-04-03 Source: Preprints.org

    Most striking observations in COVID-19 patients are the hints on pulmonary edema HP pulmonary edema MESHD (also seen on CT scans as ground glass opacities), dry cough MESHD cough HP, fluid restrictions to prevent more severe hypoxia MESHD, the huge PEEP that is needed while lungs are compliant, and the fact that anti-inflammatory therapies are not powerful enough to counter the severity of the disease. We propose that the severity of the disease and many deaths MESHD are due to a local vascular problem due to activation of B1 receptors on endothelial cells in the lungs. SARS-CoV-2 enters the cell via ACE2, a cell membrane bound molecule with enzymatic activity that next to its role in RAS is needed to inactivate des-Arg9 bradykinin, the potent ligand of the bradykinin receptor type 1 (B1). In contrast to bradykinin receptor 2 (B2), the B1 receptor on endothelial cells is upregulated by proinflammatory cytokines. Without ACE2 acting as a guardian to inactivate the ligands of B1, the lung environment is prone for local vascular leakage leading to angioedema HP angioedema MESHD. Angioedema HP Angioedema MESHD is likely a feature already early in disease, and might explain the typical CT scans and the feeling of people that they drown. In some patients, this is followed by a clinical worsening of disease around day 9 due to the formation antibodies SERO directed against the spike (S)-antigen of the corona-virus that binds to ACE2 that could contribute to disease by enhancement of local immune cell influx and proinflammatory cytokines leading to damage. In parallel, inflammation MESHD induces more B1 expression, and possibly via antibody SERO-dependent enhancement of viral infection MESHD leading to continued ACE2 dysfunction in the lung because of persistence of the virus. In this viewpoint we propose that a bradykinin-dependent local lung angioedema HP angioedema MESHD via B1 and B2 receptors is an important feature of COVID-19, resulting in a very high number of ICU admissions. We propose that blocking the B1 and B2 receptors might have an ameliorating effect on disease caused by COVID-19. This kinin-dependent pulmonary edema HP pulmonary edema MESHD is resistant to corticosteroids or adrenaline and should be targeted as long as the virus is present. In addition, this pathway might indirectly be responsive to anti-inflammatory agents or neutralizing strategies for the anti-S- antibody SERO induced effects, but by itself is likely to be insufficient MESHD to reverse all the pulmonary edema HP pulmonary edema MESHD. Moreover, we provide a suggestion of how to ventilate in the ICU in the context of this hypothesis.

The ZB MED preprint Viewer preVIEW includes all COVID-19 related preprints from medRxiv and bioRxiv, from ChemRxiv, from ResearchSquare, from arXiv and from Preprints.org and is updated on a daily basis (7am CET/CEST).
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MeSH Disease
Human Phenotype
Transmission
Seroprevalence


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