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MeSH Disease

Human Phenotype

Transmission

Seroprevalence

There are no seroprevalence terms in the subcorpus

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    Impact of the COVID-19 epidemic on outpatient visits of common respiratory diseases MESHD

    Authors: Weiyi Wang; Yulu Zheng; Libin Jiang

    doi:10.21203/rs.3.rs-34656/v1 Date: 2020-06-11 Source: ResearchSquare

    Background/Purpose The outbreak of corona virus disease MESHD 2019 (COVID-19) has become a worldwide threat to public health. The purpose of this study is to analyze the impact of COVID-19 epidemic on outpatient visits of common respiratory diseases MESHD. Methods Through statistics and comparing the data with the same period last year,we present the changes of outpatient visits of 14 common respiratory diseases MESHD in an upper first-class hospital in China from January to May,2020. Results From January to May,2020, the number of outpatient visits of most common respiratory diseases MESHD fell HP below the previous year,and total number of outpatient visits of 14 common respiratory diseases MESHD decreased by 58.07% year-on-year. Bronchitis MESHD Bronchitis HP, pneumonia MESHD pneumonia HP, cough MESHD cough HP, acute upper respiratory infection MESHD and bronchiectasis MESHD bronchiectasis HP infection MESHD are in our top 5 drop list,decreased by 76.79%,71.03%,66.51%56.87% and 56.31% respectively. Conclusion COVID-19 epidemic had a strong influence on the outpatient visits of common respiratory diseases MESHD, particularly for infectious diseases MESHD.

    In silico screening of JAK-STAT modulators from the antiviral plants of Indian traditional system of medicine with the potential to inhibit 2019 novel coronavirus

    Authors: Pukar Khanal; Taaza Duyu; BM Patil; Yadu Nandan Dey; Ismail Pasha; Rohini S. Kavalapure

    doi:10.21203/rs.3.rs-32233/v1 Date: 2020-05-28 Source: ResearchSquare

    Aim. The present study was aimed to identify the lead hits from reported anti-viral Indian medicinal plants to modulate the proteins through the JAK-STAT pathway and to identify the proteins that share the domain with coronavirus (COVID19) associated proteins i.e. 3CLpro, PLpro, and spike protein. Methods. The reported anti-viral plants were screened from the available databases and published literature; their phytoconstituents were retrieved, gene-expression was predicted and the modulated proteins in JAK-STAT pathway were predicted. The interaction between proteins was evaluated using STRING and the network between phytoconstituents and proteins was constructed using Cytoscape. The druglikeness score was predicted using MolSoft and the ADMET profile of phytoconstituents was evaluated using admetSAR2.0. The domain of three proteins i.e. 3CLpro, PLpro, and spike protein of coronavirus was compared using NCBI blastP against the RCSB database. Results. The majority of the phytoconstituents from the anti-viral plants were predicted to target TRAF5 protein in the JAK-STAT pathway; among them, vitexilactone was predicted to possess the highest druglikeness score. Proteins targeted in the JAK-STAT pathways were also predicted to modulate the immune system. Similarly, the docking study identified sesaminol 2-O-β-D-gentiobioside to possess the highest binding affinity with spike protein. Similarly, phylogeny comparison also identified the common protein domains with other stains of microbes like murine hepatitis MESHD hepatitis MESHD hepatitis HP virus strain A59, avian infectious bronchitis MESHD bronchitis HP virus, and porcine epidemic diarrhea MESHD diarrhea HP virus CV777. Conclusion. Although, the present study is based on computer simulations and database mining, it provides two important aspects in identifying the lead hits against coronavirus. First, targeting the JAK-STAT pathway in the corona-infected host by folk anti-viral agents can regulate the immune system which would inhibit spreading the virus inside the subject. Secondly, the well-known targets of coronavirus i.e. 3CLpro, PLpro, and spike protein share some common domains with other proteins of different microbial strains.

    COVIDier: A Deep-learning Tool For Coronaviruses Genome And Virulence Proteins Classification

    Authors: Peter Habib; Alsamman M Alsamman; Maha Saber-Ayad; Sameh E. Hassanein; Aladdin Hamwieh

    doi:10.1101/2020.05.03.075549 Date: 2020-05-05 Source: bioRxiv

    COVID-19, caused by SARS-CoV-2 infection MESHD, has already reached pandemic proportions in a matter of a few weeks. At the time of writing this manuscript, the unprecedented public health crisis caused more than 2.5 million cases with a mortality range of 5-7%. The SARS-CoV-2, also called novel Coronavirus, is related to both SARS-CoV and bat SARS. Great efforts have been spent to control the pandemic that has become a significant burden on the health systems in a short time. Since the emergence of the crisis, a great number of researchers started to use the AI tools to identify drugs, diagnosing using CT scan images, scanning body temperature, and classifying the severity of the disease MESHD. The emergence of variants of the SARS-CoV-2 genome is a challenging problem with expected serious consequences on the management of the disease MESHD. Here, we introduce COVIDier, a deep learning-based software that is enabled to classify the different genomes of Alpha coronavirus, Beta coronavirus, MERS, SARS-CoV-1, SARS-CoV-2, and bronchitis MESHD bronchitis HP-CoV. COVIDier was trained on 1925 genomes, belonging to the three families of SARS retrieved from NCBI Database to propose a new method to train deep learning model trained on genome data using Multi-layer Perceptron Classifier (MLPClassifier), a deep learning algorithm, that could blindly predict the virus family name from the genome of by predicting the statistically similar genome from training data to the given genome. COVIDier able to predict how close the emerging novel genomes of SARS to the known genomes with accuracy 99%. COVIDier can replace tools like BLAST that consume higher CPU and time.

    Clinical characteristics of non-pneuminia COVID-19 infection MESHD adults TRANS in Shanghai, China

    Authors: Tao Li; Linjing Gong; Lijuan Hu; Haiying Ji; Zhilong Jiang; Lei Zhu

    doi:10.21203/rs.3.rs-23976/v1 Date: 2020-04-21 Source: ResearchSquare

    Background Adult TRANS patients diagnosed as COVID-19 in Shanghai were accepted in Shanghai Public Health Clinical Center. We found around 4.91% of cases showed non- pneumonia MESHD pneumonia HP on CT imaging when they were confirmed. Understanding the characteristics of non- pneumonia MESHD pneumonia HP cases is of great significance to guide clinical treatment and improve prevention and control measures.Methods All dataset of demography, epidemiology, clinical manifestation, laboratory test, diagnosis, classification, condition change, treatment and outcome were obtained by retrospective investigation.Results 16 cases were confirmed TRANS COVID-19 with non- pneumonia MESHD pneumonia HP with clear epidemiological history. The median age TRANS of patients was 37 years old and 81.25% were female TRANS. The median incubation period TRANS was 15.25 days. 75% patients were familial clusters. These patients were presented with mild clinical manifestations, such as bronchitis MESHD bronchitis HP, common cold MESHD and asymptomatic infection MESHD asymptomatic TRANS with or without laboratory abnormalities. 4(25%)cases had underlying diseases MESHD. 3 of them had mild pneumonia MESHD pneumonia HP on chest CT imaging during hospitalization. All of the cases were cured and discharged after support treatment.Conclusions A few of adult TRANS patients after COVID-19 infection MESHD had non- pneumonia MESHD pneumonia HP, with mild clinical manifestations and long incubation time. It usually occurred in young women and history of family aggregation. The mild clinical symptom may be caused by the decreasing pathogenicity after multiple generation of virus replication. However, we should be on alert that the virus is still contagious to human. Therefore, an intensive attention should be paid to these patients to avoid misdiagnosis and overlook, because these patients are potential viral source in infection MESHD of other people.

    Chest CT imaging characteristics of COVID-19 pneumonia MESHD pneumonia HP in preschool children TRANS: a retrospective study

    Authors: Yang Li; Jianghui Cao; Xiaolong Zhang; Guangzhi Liu; Xiaxia Wu; Baolin Wu

    doi:10.21203/rs.3.rs-21851/v2 Date: 2020-04-07 Source: ResearchSquare

    Background: Recently, the World Health Organization has declared the coronavirus disease MESHD 2019 (COVID-19) outbreak a public health emergency MESHD of international concern. So far, however, limited data are available for children TRANS. Therefore, we aimed to investigate the clinical and chest CT imaging characteristics of COVID-19 in preschool children TRANS.Methods: From January 26, 2020 to February 20, 2020, the clinical and initial chest CT imaging data of eight preschool children TRANS with laboratory-confirmed COVID-19 from two hospitals were retrospectively collected. The chest CT imaging characteristics, including the distribution, shape, and density of lesions, and the pleural effusion MESHD pleural effusion HP, pleural changes, and enlarged lymph nodes were evaluated. Results: Two cases (25%) were classified as mild type, and they showed no obvious abnormal CT findings or minimal pleural thickening HP on the right side. Five cases (62.5%) were classified as moderate type. Among these patients, one case showed consolidation located in the subpleural region of the right upper lobe, with thickening in the adjacent pleura; one case showed multiple consolidation and ground-glass opacities with blurry margins; one case displayed bronchial pneumonia MESHD pneumonia HP-like changes in the left upper lobe; and two cases displayed asthmatic bronchitis MESHD bronchitis HP-like changes. One case (12.5%) was classified as critical type and showed bronchial pneumonia MESHD pneumonia HP-like changes in the bilateral lungs, presenting blurred and messy bilateral lung markings and multiple patchy shadows scattered along the lung markings with blurry margins.Conclusions: The chest CT findings of COVID-19 in preschool children TRANS are atypical and various. Accurate diagnosis requires a comprehensive evaluation of epidemiological, clinical, laboratory and CT imaging data. 

    Old Drugs for Newly Emerging Viral Disease MESHD, COVID-19: Bioinformatic Prospective

    Authors: Mohammad Reza Dayer

    id:2003.04524v1 Date: 2020-03-10 Source: arXiv

    Coronavirus (COVID-19) outbreak in late 2019 and 2020 comprises a serious and more likely a pandemic threat worldwide. Given that the disease MESHD has not approved vaccines or drugs up to now, any efforts for drug design and or clinical trails of old drugs based on their mechanism of action are worthy and creditable in such circumstances. Experienced docking experiments using the newly released coordinate structure for COVID-19 protease as a receptor and thoughtfully selected chemicals among antiviral and antibiotics drugs as ligands may be leading in this context. We selected nine drugs from HIV-1 protease inhibitors and twenty-one candidates from anti bronchitis MESHD bronchitis HP drugs based on their chemical structures and enrolled them in blind and active site-directed dockings in different modes and in native-like conditions of interactions. Our findings suggest the binding capacity and the inhibitory potency of candidates are as follows Tipranavir>Indinavir>Atazanavir>Darunavir>Ritonavir>Amprenavir for HIV-1 protease inhibitors and Cefditoren>Cefixime>Erythromycin>Clarithromycin for anti bronchitis MESHD bronchitis HP medicines. The drugs bioavailability, their hydrophobicity and the hydrophobic properties of their binding sites and also the rates of their metabolisms and deactivations in the human body are the next determinants for their overall effects on viral infections MESHD, the net results that should survey by clinical trials to assess their therapeutic usefulness for coronavirus infections MESHD.

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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