Unlabelled: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the COVID-19 pandemic. Computer simulations of complete viral particles can provide theoretical insights into large-scale viral processes including assembly, budding, egress, entry, and fusion. Detailed atomistic simulations, however, are constrained to shorter timescales and require billion-atom simulations for these processes. Here, we report the current status and on-going development of a largely "bottom-up" coarse-grained (CG) model of the SARS-CoV-2 virion. Structural data from a combination of cryo-electron microscopy (cryo-EM), x-ray crystallography, and computational predictions were used to build molecular models of structural SARS-CoV-2 proteins, which were then assembled into a complete virion model. We describe how CG molecular interactions can be derived from all-atom simulations, how viral behavior difficult to capture in atomistic simulations can be incorporated into the CG models, and how the CG models can be iteratively improved as new data becomes publicly available. Our initial CG model and the detailed methods presented are intended to serve as a resource for researchers working on COVID-19 who are interested in performing multiscale simulations of the SARS-CoV-2 virion.
Significance Statement: This study reports the construction of a molecular model for the SARS-CoV-2 virion and details our multiscale approach towards model refinement. The resulting model and methods can be applied to and enable the simulation of SARS-CoV-2 virions.
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http://dx.doi.org/10.1101/2020.10.02.323915 | DOI Listing |
J Clin Med
January 2025
Division of Neonatal-Perinatal Medicine, Department of Pediatrics, University of Texas, Southwestern Medical Center, Dallas, TX 75390, USA.
The risk of neonatal SARS-CoV-2 infection from the mother's own milk (MoM) in neonates who are exposed to maternal SARS-CoV-2 during the perinatal period remains unclear. We conducted a systematic review to assess the association between MoM feeding and neonatal SARS-CoV-2 infection in neonates who were born to SARS-CoV-2-positive pregnant persons. PubMed Central and Google Scholar were searched for studies published by 14 March 2024 that reported neonatal SARS-CoV-2 infection by feeding type.
View Article and Find Full Text PDFNutrients
January 2025
Center for Health Outcomes & Evaluation, Splaiul Unirii 45, 030126 Bucharest, Romania.
Background: The global rise in obesity has been significantly influenced by shifts in dietary habits that have been exacerbated by external factors such as the COVID-19 pandemic. This study aims to analyze the trends in Romanian dietary habits from 2015 to 2023, focusing on the impact of the COVID-19 pandemic and the role of socio-economic factors, seasonality, and cultural practices.
Methods: For dietary habits, we used nationally representative data from the Romanian Household Budget Survey provided by the Romanian National Institute of Statistics.
Nutrients
December 2024
Department of Community Health Sciences, Boston University School of Public Health, 801 Massachusetts Ave. 4th Floor, Boston, MA 02118, USA.
Background/objectives: This paper examines hunger over time to analyze how food insecurity is impacted by reduced income, including household funding from the government. Federal policies and community-based programs have the ability to prevent increases in food insecurity, particularly for populations that have risk factors, such as households with children; single-parent households; low-income households, especially those in rural areas; Black and Hispanic households; and, households experiencing economic hardships.
Methods: This study is bas ed on a cross-sectional survey that was administered in 2018 and 2019 to food pantry clients, an already food insecure population accessing resources, in Eastern Massachusetts.
BMC Public Health
January 2025
Zambia Field Epidemiology Training Program, Lusaka, Zambia.
Background: Geographical factors can affect infectious disease transmission, including SARS-CoV-2, a virus that is spread through respiratory secretions. Prioritization of surveillance and response activities during a pandemic can be informed by a pathogen's geographical transmission patterns. We assessed the relationship between geographical factors and SARS-CoV-2 prevalence in Zambia.
View Article and Find Full Text PDFNat Commun
January 2025
Center for Digital Health, Berlin Institute of Health (BIH), Charite - University Medicine Berlin, Berlin, Germany.
The COVID-19 pandemic exposed a global deficiency of systematic, data-driven guidance to identify high-risk individuals. Here, we illustrate the utility of routinely recorded medical history to predict the risk for 1741 diseases across clinical specialties and support the rapid response to emerging health threats such as COVID-19. We developed a neural network to learn from health records of 502,489 UK Biobank participants.
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