Corpus overview


MeSH Disease

Human Phenotype

Pneumonia (37)

Fever (23)

Hypertension (17)

Cough (16)

Anxiety (9)


    displaying 1 - 10 records in total 204
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    Evaluating the impact of non-pharmaceutical interventions for SARS-CoV-2 on a global scale

    Authors: Rachel T Esra; Lise Jamesion; Matthew P Fox; Daniel Letswalo; Nkosinathi Ngcobo; Sithabile Mngadi; Janne Global Estill; Gesine Meyer-Rath; Olivia Keiser

    doi:10.1101/2020.07.30.20164939 Date: 2020-08-05 Source: medRxiv

    In the absence of a viable pharmaceutical intervention for SARS-CoV-2, governments have implemented a range of non-pharmaceutical interventions (NPIs) to curb the spread of infection MESHD of the virus and the disease MESHD caused by the virus, now known as COVID-19. Given the associated social and economic costs, it is critical to enumerate the individual impacts of NPIs to aid in decision-making moving forward. We used globally reported SARS-CoV-2 cases to fit a Bayesian model framework to estimate transmission TRANS associated with NPIs in 26 countries and 34 US states. Using a mixed effects model with country level random effects, we compared the relative impact of other NPIs to national-level household confinement measures and evaluated the impact of NPIs on the global trajectory of the COVID-19 pandemic over time. We observed heterogeneous impacts of the easing of restrictions and estimated an overall reduction in infection MESHD of 23% (95% CI: 18-27%) associated with household confinement, 10% (95% CI: 1-18%) with limits on gatherings, 12% (95% CI: 5-19%) with school closures and 17% (95% CI: 6-28%) with mask policies. We estimated a 12% (95% CI: 9-15%) reduction in transmission TRANS associated with NPIs overall. The implementation of NPIs have substantially reduced acceleration of COVID-19. At this early time point, we cannot determine the impact of the easing of restrictions and there is a need for continual assessment of context specific effectiveness of NPIs as more data become available.

    Corticosteroid therapy for corona virus disease MESHD 2019-related acute respiratory distress HP syndrome MESHD: a cohort study with propensity score analysis

    Authors: Chaomin Wu; Dongni Hou; Chunling Du; Yanping Cai; Junhua Zheng; Jie Xu; Xiaoyan Chen; Cuicui Chen; Xianglin Hu; Yuye Zhang; Juan Song; Lu Wang; Yen-cheng Chao; Yun Feng; Weining Xiong; Dechang Chen; Ming Zhong; Jie Hu; Jinjun Jiang; Chunxue Bai; Xin Zhou; Jinfu Xu; Fengyun Gong; Yuanlin Song

    doi:10.21203/ Date: 2020-08-01 Source: ResearchSquare

    Background The impact of corticosteroid therapy on outcomes of patients with Coronavirus disease MESHD-2019 (COVID-19) is highly controversial. We aimed to compare the risk of death MESHD between COVID-19-related ARDS patients with corticosteroid treatment and those without.Methods In this single-centre retrospective observational study, patients with ARDS caused by COVID-19 between 24 December 2019 and 24 February 2020 were enrolled. The primary outcome was 60-day in-hospital death MESHD. The exposure was prescribed systemic corticosteroids or not. Time-dependent Cox regression models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for 60-day in-hospital mortality.Results A total of 382 patients including 226 (59.2%) patients who received systemic corticosteroids and 156 (40.8%) patients with standard treatment were analyzed. The maximum dose of corticosteroids was 80.0 (IQR 40.0–80.0) mg equivalent methylprednisolone per day, and duration of corticosteroid treatment was 7.0 (4.0–12.0) days in total. In Cox regression analysis using corticosteroid treatment as a time-varying variable, corticosteroid treatment was associated with a significant reduction in risk of in-hospital death MESHD within 60 days (HR, 0.48; 95% CI, 0.25, 0.93; p = 0.0285). The association remained significantly after adjusting for age TRANS, sex, Sequential Organ Failure Assessment score at hospital admission, propensity score of corticosteroid treatment, and comorbidities (HR: 0.51; CI: 0.27, 0.99; p = 0.0471). Corticosteroids were not associated with delayed viral RNA clearance in our cohort.Conclusion In this clinical practice setting, low-to-moderate dose corticosteroid treatment was associated with reduced risk of death MESHD in COVID-19 patients who developed ARDS.

    Unsupervised machine learning reveals key immune cell subsets in COVID-19, rhinovirus infection MESHD, and cancer therapy

    Authors: Sierra M. Barone; Alberta G.A. Paul; Lyndsey M. Muehling; Joanne A. Lannigan; William W. Kwok; Ronald B. Turner; Judith A. Woodfolk; Jonathan M. Irish

    doi:10.1101/2020.07.31.190454 Date: 2020-08-01 Source: bioRxiv

    For an emerging disease MESHD like COVID-19, systems immunology tools may quickly identify and quantitatively characterize cells associated with disease progression MESHD or clinical response. With repeated sampling, immune monitoring creates a real-time portrait of the cells reacting to a novel virus before disease MESHD specific knowledge and tools are established. However, single cell analysis tools can struggle to reveal rare cells that are under 0.1% of the population. Here, the machine learning workflow Tracking Responders Expanding (T-REX) was created to identify changes in both very rare and common cells in diverse human immune monitoring settings. T-REX identified cells that were highly similar in phenotype and localized to hotspots of significant change during rhinovirus and SARS-CoV-2 infections MESHD. MHC tetramers were not used during unsupervised analysis and instead left out to serve as a test of whether T-REX identifies biologically significant cells. In the rhinovirus challenge study, T-REX identified virus-specific CD4+ T cells based on these cells being a distinct phenotype that expanded by [≥]95% following infection MESHD. T-REX successfully identified hotspots with virus-specific T cells using pairs of samples comparing Day 7 of infection MESHD to samples taken either after clearing the infection MESHD (Day 28) or samples taken prior to infection MESHD (Day 0). Mapping pairwise comparisons in samples according to both the direction and degree of change provided a framework to compare systems level immune changes during infectious disease MESHD or therapy response. This revealed that the magnitude and direction of systemic immune change in some COVID-19 patients was comparable to that of blast crisis MESHD acute myeloid leukemia MESHD acute myeloid leukemia HP patients undergoing induction chemotherapy and characterized the identity of the immune cells that changed the most. Other COVID-19 patients instead matched an immune trajectory like that of individuals with rhinovirus infection MESHD or melanoma MESHD melanoma HP patients receiving checkpoint inhibitor therapy. T-REX analysis of paired blood SERO samples provides an approach to rapidly identify and characterize mechanistically significant cells and to place emerging diseases MESHD into a systems immunology context.

    COVID-19 Pandemic and its Implication on Hand Hygiene Status by Alcohol-based Hand Sanitizers Among Healthcare Workers in Jimma University Medical Center, Ethiopia

    Authors: Desta Assefa; Tsegaye Melaku; Bodena Bayisa; Sintayehu Alemu

    doi:10.21203/ Date: 2020-07-30 Source: ResearchSquare

    Background: Pandemic corona virus disease MESHD (COVID-19) is a global health crisis of our time. The consistent practice of hand hygiene, especially by proper use of alcohol-based hand sanitizers in health facilities and community is a cardinal step in combating it. This study was designed to assess self-reported level of knowledge, attitude and compliance to WHO recommended hand hygiene status by alcohol-based hand sanitizers among healthcare workers during a COVID-19 pandemic in Jimma University Medical Center, Ethiopia.Methods: Questionnaire-based descriptive cross-sectional study was conducted between April and June 2020. Data were analyzed using SPSS version 21 with significance level at p<0.05.Results: From a total of 96 volunteer study participants (27nurses; 21pharmacists, 15academicians, 13medical laboratory technicians, 7physician, 7dental doctors, 6midwives) 61 were males TRANS. Their mean age TRANS was 28.69+4.048years. Alcohol-based hand sanitizers were used by 95.8% respondents to prevent spreading of COVID-19. The majority (93.8%) of the respondents had good knowledge; 74% had a good attitude and 76% had good hand hygiene practices by alcohol-based hand sanitizers. They got information about this technique mainly from mass media 71(74%) and training (40.6%). 84.5% respondents were facing challenges during alcohol-based hand sanitizer use due to it is unavailable 66(68.8%), expensive 50(52.1%), forgetting 11(11.5%), experiencing and/or fearing health-associated risks (skin irritation(28.1%), skin dryness(62.5%), ocular irritation(11.5%), etc).Conclusion and recommendationThe majority of respondents had good knowledge; but the attitude and adherence to standard guidelines need improvement. The hospital should catalyze behavioral change, provide emollient containing hand sanitizers and educational courses to achieve and sustain improvements.

    Social Listening: A Thematic Analysis of COVID-19 Discussion on Social Media

    Authors: Dr Sulaimon Atolagbe Afolabi; Sakinat Oluwabukonla Folorunso; Zinia Siphosethu Bunyula; Oluwatobi Oluwaseyi Banjo; Sibusiso Sibusiso Matshika; Warrie Usenobong Warrie; Naledi Ngqambela; Ayodeji Emmanuel Adepoju; Hendrica Rabophala; Olawale Victor Abimbola; Michael Segun Olanipekun; Adedayo Lateef Odukoya

    doi:10.1101/2020.07.25.20162040 Date: 2020-07-28 Source: medRxiv

    COVI19 is a variant of corona virus diseases MESHD that has destabilised the entire world and whose cure as at mid-2020 has become elusive. Social media is ablaze with discussions around the pandemic. There is the dire need to delineate the on-going conversations on the infection MESHD with the intention of creating awareness on peoples reaction, opinion, action and recommendation that are inimical to the well being of the populace. Hence, this study is geared towards performing thematic analysis of the discussions on social media about COVID19. We programmatically retrieved data from twitter between 1st March, 2020 to 30th June 2020 with covid19 related keywords. We processed the data and later categorized them into themes that evolved from the tweets namely Herbs and Vegetables as COVID-10 Panacea, Self-Medication Due to Prescription by Non-Medical Practitioners on Social Media, Conspiracy Theories on COVID19 and Fear and Anxiety HP Associated with COVID19. The results show that many are resulting to herbs to protect themselves against the disease MESHD; taking drugs without doctors prescription; believing in conspiracy theories and having certain degree of fear.

    Targeting the endolysosomal host-SARS-CoV-2 interface by the clinically licensed antidepressant fluoxetine

    Authors: Sebastian Schloer; Linda Brunotte; Jonas Goretzko; Angeles Mecate-Zambrano; Nadja Korthals; Volker Gerke; Stephan Ludwig; Ursula Rescher

    doi:10.1101/2020.07.27.222836 Date: 2020-07-27 Source: bioRxiv

    The Corona Virus Disease MESHD 2019 (COVID-19) pandemic caused by the Severe Acute Respiratory Syndrome MESHD Related Coronavirus 2 (SARS-CoV-2) is a global health emergency MESHD. As only very limited therapeutic options are clinically available, there is an urgent need for the rapid development of safe, effective, and globally available pharmaceuticals that inhibit SARS-CoV-2 entry and ameliorate COVID-19. In this study, we explored the use of small compounds acting on the homeostasis of the endolysosomal host-pathogen interface, to fight SARS-CoV-2 infection MESHD. We find that fluoxetine, a widely used antidepressant and a functional inhibitor of acid sphingomyelinase (FIASMA), efficiently inhibits the entry and propagation of SARS-CoV-2 in the cell culture model without cytotoxic effects. Mechanistically, fluoxetine induced both impaired endolysosomal acidification and the accumulation of cholesterol within the endosomes. As the FIASMA group consists of a large number of small compounds that are well-tolerated and widely used for a broad range of clinical applications, exploring these licensed pharmaceuticals may offer a variety of promising antivirals for host-directed therapy to counteract SARS-CoV-2 and COVID 19. SignificanceOnly very limited therapeutic options are clinically available for treatment of Corona Virus Disease MESHD 2019 (COVID-19) pandemic caused by the Severe Acute Respiratory Syndrome MESHD Related Coronavirus 2 (SARS-CoV-2), and the development of safe, effective, and globally available pharmaceuticals are urgently required. We report that the widely used antidepressant fluoxetine efficiently inhibits the early entry and propagation of SARS-CoV-2 in the cell culture model, and may offer a promising approach for host-directed therapy to counteract SARS-CoV-2 and COVID 19.

    Epidemiological investigation and prevention control analysis of longitudinal distribution of COVID-19 in Henan province, China

    Authors: Xianguang Yang; Xuelin Chen; Cuihong Ding; Zhibo Bai; Jingyi Zhu; Gege Sun; Guoying Yu

    doi:10.1101/2020.07.25.20161844 Date: 2020-07-27 Source: medRxiv

    Objective: To analyze the vertical distribution of six cities in Henan Province,China from January 21, 2020 to June17, 2020: Xinyang City (including Gushi County), Nanyang City (including Dengzhou City), Zhumadian City (including XincaiCounty), Zhengzhou City (including Gongyi City), Puyang City and Anyang City (including Hua County) corona virus disease MESHD 2019(COVID-19) epidemiological characteristics and local prevention and control measures.Methods: Data were collected and analyzed through the COVID-19 information published on the official websites of health commissions of Henan Province and six cities.Results: As of June 17, 2020, the cumulative incidence rate of COVID-19 in Henan province was 1.33/100,000, the cumulative cure rate was 98.27%, the cumulative mortality rate was 1.73%, the age TRANS range of diagnosed cases was 5days-85years old, and the male TRANS to female TRANS ratio was 1.09:1.The confirmed cases TRANS of COVID-19 in Henan province were mainly imported cases from Hubei, accounting for 87.74%, of which the highest number was 70.50% in Zhumadian. The contact cases and local cases increased in a fluctuating manner over time.Significance: In this paper, epidemiological characteristics of COVID-19 in Henan province from the outbreak to the effective control within 60 days were analyzed, and effective and distinctive prevention and control measures in various cities were summarized, so as to provide a favorable reference for the further formulation and implementation of epidemic prevention and control and a valuable theoretical basis for effectively avoiding the second outbreak.

    One Shot Cluster Based Approach for the Detection of COVID-19 from Chest X-Ray Images

    Authors: V.N. Manjunath Aradhya; Mufti Mahmud; Basant Agarwal; D.S. Guru; M. Shamim Kaiser

    id:10.20944/preprints202007.0656.v1 Date: 2020-07-26 Source:

    Corona virus disease MESHD (COVID-19) has infected over more than 10 million people around the globe and killed at least 500K worldwide by the end of June 2020. As this disease MESHD continues to evolve and scientists and researchers around the world now trying to find out the way to combat this disease MESHD in most effective way. Chest X-rays are widely available modality for immediate care in diagnosing COVID-19. Precise detection and diagnosis of COVID-19 from these chest X-rays would be practical for the current situation. This paper proposes one shot cluster based approach for the accurate detection of COVID-19 chest x-rays. The main objective of one shot learning (OSL) is to mimic the way humans learn in order to make classification or prediction on a wide range of similar but novel problems. The core constraint of this type of task is that the algorithm should decide on the class of a test instance after seeing just one test example. For this purpose we have experimented with widely known Generalized Regression and Probabilistic Neural Networks. Experiments conducted with publicly available chest x-ray images demonstrate that the method can detect COVID-19 accurately with high precision. The obtained results have outperformed many of the convolutional neural network based existing methods proposed in the literature.

    COVID TV-UNet: Segmenting COVID-19 Chest CT Images Using Connectivity Imposed U-Net

    Authors: Narges Saeedizadeh; Shervin Minaee; Rahele Kafieh; Shakib Yazdani; Milan Sonka

    id:2007.12303v2 Date: 2020-07-24 Source: arXiv

    The novel corona- virus disease MESHD (COVID-19) pandemic has caused a major outbreak in more than 200 countries around the world, leading to a severe impact on the health and life of many people globally. As of mid-July 2020, more than 12 million people were infected, and more than 570,000 death MESHD were reported. Computed Tomography (CT) images can be used as an alternative to the time-consuming RT-PCR test, to detect COVID-19. In this work we propose a segmentation framework to detect chest regions in CT images, which are infected by COVID-19. We use an architecture similar to U-Net model, and train it to detect ground glass regions, on pixel level. As the infected regions tend to form a connected component (rather than randomly distributed pixels), we add a suitable regularization term to the loss function, to promote connectivity of the segmentation map for COVID-19 pixels. 2D-anisotropic total-variation is used for this purpose, and therefore the proposed model is called "TV-UNet". Through experimental results on a relatively large-scale CT segmentation dataset of around 900 images, we show that adding this new regularization term leads to 2\% gain on overall segmentation performance SERO compared to the U-Net model. Our experimental analysis, ranging from visual evaluation of the predicted segmentation results to quantitative assessment of segmentation performance SERO (precision, recall SERO, Dice score, and mIoU) demonstrated great ability to identify COVID-19 associated regions of the lungs, achieving a mIoU rate of over 99\%, and a Dice score of around 86\%.

    A CNN Classification Model For Diagnosis Covid19

    Authors: Ahmed Abdullah Farid; hatem khater; gamal selim

    id:10.20944/preprints202007.0591.v1 Date: 2020-07-24 Source:

    The paper demonstrates the analysis of Corona Virus Disease MESHD based on a CNN probabilistic model. It involves a technique for classification and prediction by recognizing typical and diagnostically most important CT images features relating to Corona Virus. The main contributions of the research include predicting the probability of recurrences MESHD in no recurrence MESHD (first time detection) cases at applying our proposed Convolution neural network structure. The Study is validated on 2002 chest X-ray images with 60 confirmed positive covid19 cases and (650 bacterial – 412 viral -880 normal) x-ray images. The proposed CNN compared with traditional classifiers with proposed CHFS feature extraction model. The experimental study has done with real data demonstrates the feasibility and potential of the proposed approach for the said cause. The result of proposed CNN structure has been successfully done to achieve 98.20% accuracy of covid19 potential cases with comparable of traditional classifiers.

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MeSH Disease
Human Phenotype

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