https://www.selleckchem.com/ Background This study is aimed at developing a prediction nomogram for subclinical coronary atherosclerosis in an Asian population with baseline zero score, and to compare its discriminatory ability with Framingham risk score (FRS) and atherosclerotic cardiovascular disease (ASCVD) models. Methods Clinical characteristics, physical examination, and laboratory profiles of 830 subjects were retrospectively reviewed. Subclinical coronary atherosclerosis in term of Coronary artery calcification (CAC) progression was the primary endpoint. A nomogram was established based on a least absolute shrinkage and selection operator (LASSO)-derived logistic model. The discrimination and calibration ability of this nomogram was evaluated by Hosmer-Lemeshow test and calibration curves in the training and validation cohort. Results Of the 830 subjects with baseline zero score with the average follow-up period of 4.55 ± 2.42 year in the study, these subjects were randomly placed into the training set or validation set at a ratiirmed by Hosmer-Lemeshow test with P-values of 0.654 and 0.979 in the training cohort and validation cohort. Conclusions This validated nomogram provided a useful predictive value for subclinical coronary atherosclerosis in subjects with baseline zero score, and could provide clinicians and patients with the primary preventive strategies timely in individual-based preventive cardiology.The COVID-19 pandemic caused by the SARS-CoV-2 coronavirus requires reliable assays for studying viral entry mechanisms which remains poorly understood. This knowledge is important for the development of therapeutic approaches to control SARS-CoV-2 infection by permitting the screening for neutralizing antibodies and other agents that can block infection. This is particularly important for patients who are at high risk for severe outcomes related to COVID-19. The production of pseudotyped viral particles may seem like a daunting task for a non-virology