Cross-sectional analysis of tobacco addiction in hospitalized COVID-19 patients.

Introduction: The COVID-19 pandemic has become an important health issue with consequences for special populations since 2019. Tobacco use is an important public health issue and tobacco users are a risk group for lung infections. Materials and Methods: The aim of this study is to obtain information about disease prevalence and severity, laboratory parameters, and changes in radiological findings between smokers and non-smokers who were hospitalized, followed up, and treated for COVID-19, and to find answers to critical questions regarding the response to antiviral and supportive therapy. Two hundred eighty-six patients who were hospitalized and treated between March 2020-February 2021 in the COVID-19 Isolation Ward of Baskent University Hospital were included in the study. The patients were grouped as current smokers, non-smokers, and ex-smokers. The groups were compared in terms of symptoms, laboratory findings, radiological findings, and treatment response. Result: The median age of the patients included in the study was 59 (IQR= 32). Of the patients, 40.6% were female and 59.4% were male. In our study, we discovered that there were fewer female smokers (p<0.001). When the current smokers (n= 56), non-smokers (n= 159), and ex-smokers (n= 71) were compared based on their findings, it was found that dyspnea was more common in current smokers (p= 0.009). Lung involvement was found to be more common (p= 0.002) and multifocal in the current smokers group (p= 0.038). The levels of oxygen saturation at the times of admission and discharge were lower in current smokers (p= 0.002 and p= 0.038). The need for nasal oxygen and noninvasive mechanical ventilation was also found to be higher in current smokers (p= 0.008 and p= 0.039). Systemic steroid requirement was higher in current smokers (p= 0.013). There was no statistically significant difference in terms of mortality between current smokers, ex-smokers, and non-smokers (p= 0.662). Conclusions: The analysis of the findings of the patients hospitalized in the COVID-19 isolation ward indicated that COVID-19 leads to a more serious course in patients with a history of smoking.

A coarse-grained Langevin molecular dynamics approach to de novo protein structure prediction.

De novo prediction of protein structures, the prediction of structures from amino acid sequences which are not similar to those of hitherto resolved structures, has been one of the major challenges in molecular biophysics. In this paper, we develop a new method of de novo prediction, which combines the fragment assembly method and the simulation of physical folding process: structures which have consistently assembled fragments are dynamically searched by Langevin molecular dynamics of conformational change. The benchmarking test shows that the prediction is improved when the candidate structures are cross-checked by an empirically derived score function.