RESUMO
Sulindac sulfone, an active metabolite of sulindac, a non-steroidal anti-inflammatory drug, has good anti-inflammatory potential. The antineoplastic effect of sulindac sulfone is mediated through a cyclooxygenase inhibitory mechanism, followed by apoptosis and inhibition of cell proliferation. Mounting studies have explored the anti-neoplastic effect of sulindac sulfone in various types of cancers in a dose-dependent manner. In this backdrop, we have conducted a systematic review to evaluate the efficacy and dose of sulindac sulfone as an anti-neoplastic agent in human head and neck squamous cell carcinoma cell lines (HNSCCs). In this study, we used a systematic literature review approach, and articles were searched in PubMed, and Medline with the keywords "sulindac sulfone," "anti-neoplastic activity," "chemopreventive," and "head and neck squamous cell carcinoma". A hand-search of journals was also performed. Articles were reviewed and analyzed. The analysis reveals that, based on the in vitro studies on various tumor models, the optimum concentration of sulindac sulfone which elicits anti-neoplastic effects is 200-800 µM. The anti-neoplastic effect is mediated through inhibition of cell proliferation and apoptosis. The results of our systematic review show that the anti-neoplastic activity of pharmacologic Sulindac sulfone is part of its dose-dependent activity, which can be safely employed in the therapy for human HNSCCs and would be responsible for a beneficial outcome of the treatment.
RESUMO
BACKGROUND: Artificial intelligence (AI) is the process by which it is possible to program computers to mimic human thoughts. AI and its subsets machine learning and deep learning have been developed to analyze complicated data gathered from many sources using algorithms built into decision support systems. It has been widely used in the field of dentistry. AIM: The study aimed to evaluate the knowledge, attitude, and practice (KAP) of AI among dental students and dentists. METHODOLOGY: The present study is a descriptive cross-sectional online survey that was carried out among dentists and dental students in South India. A self-structured, close-ended questionnaire that was administered that consisted of 25 questions was included. The questions were circulated through Google Forms (Google LLC, Mountain View, California, United States), and it was circulated among the study participants through online mode. The data were collected systematically, and SPSS Statistics version 22.0 (IBM Corp. Released 2013. IBM SPSS Statistics for Windows, Version 22.0. Armonk, NY: IBM Corp.) was used for data analysis. RESULTS: One thousand (595 dental surgeons and 405 dental students) participated in the study through Google Forms. Among these, 700 (70%) were females and 300 (30%) were males. In the study group, 635 (63.5%) were aware of AI, and 365 (36.5%) were not aware (p-value 0.000). Among the 21 questions used to assess the KAP, 14 questions were significant with a p-value less than 0.05. More than 60% agreed that the dental curriculum has to be updated with AI. About 269 (26.9%) agreed that AI will replace the role of dentists in the future. There were no significant results in comparing dental surgeons and dental students. CONCLUSION: The present study showed that the KAP among dental surgeons and dental students was the same. They believe that the dental curriculum has to be updated with AI. This study shows that there is a lack of knowledge about deep learning models and websites used for AI among dentists. Thus, it is necessary to include evidence-based teaching and training about the application of AI in dental practice to improve the future of dentistry.
