Corpus overview


MeSH Disease

HGNC Genes

There are no HGNC terms in the subcorpus

SARS-CoV-2 proteins

There are no SARS-CoV-2 protein terms in the subcorpus


SARS-CoV-2 Proteins
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    Management of COVID-19 MESHD in Liver Transplant Recipients with Immunosuppressant Therapy: Experiences of an Iranian Transplant Registry

    Authors: Zahra Sheikhalipour; Touraj Asvadi kermani; Farzad Kakaei; Azizeh Farshbaf Khalili; Leila Vahedi

    doi:10.21203/ Date: 2020-08-19 Source: ResearchSquare

    Background: Following the pandemic of COVID-19 MESHD and the increased  COVID-19 MESHD risk in transplant patient receptions, the authors assessed the prevalence, clinical course, and the outcome of the COVID-19 MESHD infection among liver transplant receptions. Methods: By designing and the use of researcher made questionnaire and the use of medical services, liver transplantation recipients under our center surveyed in terms of COVID-19 MESHD infection.Results: Seven patients infected with COVID-19 MESHD were identified from 265 liver transplantation recipients. The majority of patients were male and had COVID-19 MESHD despite being in-home quarantine. All patients received immunosuppressive drugs during infection with COVID-19 MESHD with no change in the routine immunosuppressive therapy. Among the identified patients, 5 recovered and 2 died. One of the dead patients, in addition to having a liver transplant, suffered brain cancer MESHD with metastasis MESHD to the lungs. Conclusion: It seems that the in liver transplants infected with COVID-19 MESHD, the immunosuppressive drugs causes mild to moderate illness, and even recover from the disease.However, more evidence is needed to prove this hypothesis. It is also recommended that transplant recipients should be warned about personal hygiene and closely be monitored by organ transplant centers. 

    MIXCAPS: A Capsule Network-based Mixture of Experts for Lung Nodule Malignancy Prediction

    Authors: Parnian Afshar; Farnoosh Naderkhani; Anastasia Oikonomou; Moezedin Javad Rafiee; Arash Mohammadi; Konstantinos N. Plataniotis

    id:2008.06072v1 Date: 2020-08-13 Source: arXiv

    Lung diseases including infections such as Pneumonia, Tuberculosis MESHD, and novel Coronavirus ( COVID-19 MESHD), together with Lung Cancer MESHD are significantly widespread and are, typically, considered life threatening. In particular, lung cancer MESHD is among the most common and deadliest cancers MESHD with a low 5-year survival rate. Timely diagnosis of lung cancer MESHD is, therefore, of paramount importance as it can save countless lives. In this regard, deep learning radiomics solutions have the promise of extracting the most useful features on their own in an end-to-end fashion without having access to the annotated boundaries. Among different deep learning models, Capsule Networks are proposed to overcome shortcomings of the Convolutional Neural Networks (CNN) such as their inability to recognize detailed spatial relations. Capsule networks have so far shown satisfying performance in medical imaging problems. Capitalizing on their success, in this study, we propose a novel capsule network-based mixture of experts, referred to as the MIXCAPS. The proposed MIXCAPS architecture takes advantage of not only the capsule network's capabilities to handle small datasets, but also automatically splitting dataset through a convolutional gating network. MIXCAPS enables capsule network experts to specialize on different subsets of the data. Our results show that MIXCAPS outperforms a single capsule network and a mixture of CNNs, with an accuracy of 92.88%, sensitivity of 93.2%, specificity of 92.3% and area under the curve of 0.963. Our experiments also show that there is a relation between the gate outputs and a couple of hand-crafted features, illustrating explainable nature of the proposed MIXCAPS. To further evaluate generalization capabilities of the proposed MIXCAPS architecture, additional experiments on a brain tumor MESHD dataset are performed showing potentials of MIXCAPS for detection of tumors MESHD related to other organs.

    Evaluation of COVID 19 infection in 279 cancer patients treated during a 90-day period in 2020 pandemic

    Authors: Mozaffar Aznab

    doi:10.1101/2020.05.26.20102889 Date: 2020-06-01 Source: medRxiv

    Background: The aim of this study was investigation of COVID-19 MESHD disease and its outcome in cancer MESHD patients who needed treatment, in a 90-day period. Methods: Cancer MESHD patient who required treatment, were evaluated for potential COVID-19 MESHD infection in a 90-day period, starting from beginning of this epidemic in Iran, January, to April 19, 2020. For treatment of solid tumor MESHD patients, if they did not have symptoms related to COVID-19 MESHD, just chest X-ray was requested. If they showed COVID-19 MESHD related symptoms, High Resolution CT scan of lungs was requested. For hematology cancer MESHD patients, PCR test for COVID-19 MESHD infection was requested as well. Protection measures were considered for personnel of oncology wards. Results: In this study, 279 patients were followed up in this 90-day period. No COVID-19 MESHD infection was observed in 92 cases of breast cancer MESHD, 72 cases of colon cancer MESHD, 14 cases of gastric cancer MESHD and 12 cases of pancreaticobiliary cancer MESHD .However, in 11 cases of lung cancer MESHD, 5 cases brain tumors MESHD and 12 cases ovarian cancer MESHD; 3 case of COVID-19 MESHD were observed. In the hematology cancers MESHD group, which included 14 cases of Hodgkin Lymphoma MESHD, 23 cases of lymphoproliferative disorder MESHD, 12 cases of acute leukemia MESHD and 12 cases of multiple myeloma MESHD; three of COVID-19 MESHD were observed. Conclusion: Patients with cancer MESHD who need treatment can be treated by taking some measures. These measures include observing individual and collective protection principles in patients and health-care personnel, increasing patients awareness particularly about self-care behavior, performing a COVID-19 MESHD test, and taking a chest X ray, before the treatment starts

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MeSH Disease
HGNC Genes
SARS-CoV-2 Proteins

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