Tobacco Smoking among the Online Respondent Dental Students of a Dental College: A Descriptive Cross-sectional Study.

Introduction: Smoking tobacco is most common nowadays among dental students due to stress induced by practical workloads and exams. There is limited data regarding tobacco smoking among dental students. The aim of this study was to determine the prevalence of tobacco smoking among online respondent dental students of a dental college. Methods: This was a descriptive cross-sectional study conducted on dental students from 15 July 2021 to 15 August 2021. Ethical approval was obtained from the Institutional Review Committee of K.D. Dental College and Hospital (Reference number: KDDC/Admin/2021/9990A). Data was collected through a structured questionnaire and responses were gathered using an online Google form survey with informed consent. A convenience sampling method was used. Point estimate and 95% confidence interval were calculated. Results: Among 60 online respondents, the prevalence of tobacco smoking was found to be 11 (18.33%) (17.04-24.56, 95% Confidence Interval). The percentage of participants who wanted to stop smoking now was 11 (18.33%). Conclusions: The prevalence of tobacco smoking among the online dental respondents of a dental college was similar to the other studies done in similar settings. Keywords: dental students; smoking; tobacco cessation.

Quantitative structure activity relationship studies of androgen receptor binding affinity of endocrine disruptor chemicals with index of ideality of correlation, their molecular docking, molecular dynamics and ADME studies.

Endocrine disrupter chemicals (EDCs) are both natural and man-made chemicals that mimic, block or interfere with human hormonal system. In the present manuscript, QSAR modeling was performed for the androgen disruptors that interfere with biosynthesis, metabolism or action of androgens that causes adverse effects on male reproductive system. A set of 96 EDCs that exhibited affinity towards androgen receptors (Log RBA) in rats were employed for carrying out QSAR studies using Hybrid descriptors (combination of HFG and SMILES) through Monte Carlo Optimization. Using index of ideality of correlation (TF2), five splits were formed and predictability of five models resulting from these splits was assessed by various validation parameters. Models resulted from first split was the top most one with R2validation = 0.7878. Structural attributes responsible for change in endpoint were studied by employing correlation weights of structural attributes. In order to further validate the model, new EDCs were designed using these attributes. In silico molecular modelling studies were performed to assess the detailed interactions with the receptor. The binding energies of all the designed compounds were observed to be better than lead and are in the range of -10.46 to -14.80. Molecular dynamics simulation of 100 ns was performed for ED01 and NED05. The results revealed that the protein-ligand complex bearing NED05 was more stable than lead ED01 exhibiting better interactions with the receptor. Further, in an attempt to assess their metabolism, ADME studies were evaluated using SwissADME. The developed model enables to predict the characteristics of designed compounds in an authentic way.Communicated by Ramaswamy H. Sarma.