In late December 2019, several cases of pneumonia of unknown origin were reported from China, which in early January 2020 were announced to be caused by a novel coronavirus. The virus was later denominated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and defined as the causal agent of coronavirus disease 2019 (COVID-19). Despite massive attempts to contain the disease in China, the virus has spread globally, and COVID-19 was declared a pandemic by the World Health Organization (WHO) in March 2020. Here we provide a short background on coronaviruses, and describe in more detail the novel SARS-CoV-2 and attempts to identify effective therapies against COVID-19.
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| http://dx.doi.org/10.1213/ANE.0000000000004845 | DOI Listing |
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Division of Neonatology, Department of Pediatrics, Faculty of Medicine Vajira Hospital, Navamindradhiraj University, Bangkok, Thailand.
Background: Multisystem inflammatory syndrome in neonates (MIS-N) is a rare condition thought to be associated with prenatal exposure to maternal severe acute respiratory syndrome coronavirus 2 infection. This immune-mediated hyperinflammation has been described in neonates with multiorgan dysfunction, including cardiopulmonary, encephalopathy, coagulopathy, and vascular complications. However, renovascular complications in MIS-N are rare.
View Article and Find Full Text PDFObjective: To determine how many people with long COVID also meet diagnostic criteria for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS).
Methods: We identified which participants with long COVID also met the Institute of Medicine (IOM) or the 2003 Canadian Consensus Criteria (CCC) for ME/CFS at approximately 6-8 months post-SARS-CoV-2 infection in two cohorts: (1) the JHU COVID Recovery cohort, which enrolled participants within 4 weeks of infection and (2) the Long-term Impact of Infection with Novel Coronavirus (LIINC) cohort, which enriched for participants with long COVID. Neither study administered ME/CFS-specific surveys, so available data elements were mapped onto each ME/CFS diagnostic criteria.
Clinical characteristics and the role of IL-6 in acute-on-chronic liver failure patients with or without COVID-19: a multicenter paired cohort study.
Front Cell Infect Microbiol
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Department of Gastroenterology, Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China.
Background And Aims: The impact of coronavirus disease 2019 (COVID-19) on patients with acute-on-chronic liver failure (ACLF) remains unclear. To investigate the clinical characteristics of patients with ACLF complicated with COVID-19 in order to provide evidence for the precise treatment of this patient population.
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The Role of Structural Flexibility in Hydrocarbon-Stapled Peptides Designed to Block Viral Infection via Human ACE2 Mimicry.
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Department of Pediatrics, Section of Hematology/Oncology, The University of Chicago, Chicago, Illinois 60637, United States of America.
The COVID-19 pandemic drove a uniquely fervent pursuit to explore the potential of peptide, antibody, protein, and small-molecule based antiviral agents against severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2). The interaction between the SARS-CoV2 spike protein with the angiotensin-converting enzyme 2 (ACE2) receptor that mediates viral cell entry was a particularly interesting target given its well described protein-protein interaction (PPI). This PPI is mediated by an α-helical portion of ACE2 binding to the receptor binding domain (RBD) of the spike protein and thought to be susceptible to blockade through molecular mimicry.
View Article and Find Full Text PDFDeep Drug-Target Binding Affinity Prediction Base on Multiple Feature Extraction and Fusion.
ACS Omega
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School of Computer Science and Technology, Zhejiang Sci-Tech University, Hangzhou 310018, China.
Accurate drug-target binding affinity (DTA) prediction is crucial in drug discovery. Recently, deep learning methods for DTA prediction have made significant progress. However, there are still two challenges: (1) recent models always ignore the correlations in drug and target data in the drug/target representation process and (2) the interaction learning of drug-target pairs always is by simple concatenation, which is insufficient to explore their fusion.
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