Objective: To evaluate the potential immunostimulant activity of glucosamine from Azadirachtaindica leaves in mice. Methods: The hexane, chloroform, methanol and aqueous extracts of Azadirachta indica leaves were prepared and its immunostimulant activity was studied. The aqueous extract of Azadirachta indica leaves (AEAIL) showed significant (P<0.001) higher immunostimulant activity than other extracts. Hence, isolation of possible phytoconstituent(s) from AEAIL was carried out and glucosamine was isolated. The Azadirachta indica leaves glucosamine (AILG) was administered at 266, 400 and 800 μg/kg of mice, intraperitoneal route weekly for 4 weeks to evaluate immunostimulant activity. The serum interleukin-2 (IL-2) level and histopathological studies on thymus were performed to confirm AILG immunostimulant activity. Results: The administration of above doses of AILG has significantly (P<0.001) increased serum IL-2 levels in mice than control mice. The dose dependent effect on IL-2 was noticed in AILG treated mice. The weight of thymus, liver and kidney were significantly (P<0.001) increased after the AILG treatments compared to control mice. Also, body weight of AILG treated mice showed significant (P<0.001) increment from second week to fourth week than control mice. The proliferation of T-lymphocytes in thymus after the administration of AILG was observed in histopathological study. Conclusion: The glucosamine was isolated from Azadirachta indica leaves aqueous extract and its immunostimulant activity was confirmed in mice.

Objectives: The integration of large language models (LLMs), particularly those based on the generative pre-trained transformer (GPT) architecture, has begun to revolutionize various fields, including dentistry. Despite these promising applications, the use of GPT in dentistry presents several challenges. Ongoing research and the development of robust ethical frameworks are essential to mitigate these issues and enhance the responsible deployment of GPT technologies in clinical settings. Hence, this systematic review aims to explore the trends, applications, strengths, and challenges associated with the use of GPT in dentistry. Methods: Articles were selected if they contained detailed information on the application of GPT in dentistry. The search strategy used in systematic reviews follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Our search of databases and other sources yielded a total of 704 studies. After removing duplicates and conducting a full-text screening, 16 articles were included in the review. The methodological quality of the research was evaluated using the Critical Appraisal Skills Programme (CASP) checklist. Results: Out of a total of 91 articles published on GPT in dentistry, 20 were editorials and 11 were narrative reviews; these were excluded, leaving 60 original research articles for further analysis. The articles were assessed based on the type of results they provided. Ultimately, 16 articles that reported positive findings with robust methodology were included in this review Conclusions The results highlight mixed responses; therefore, further research on integration into clinical workflows must be conducted with extensive methodological rigor.

Objectives: The integration of large language models (LLMs), particularly those based on the generative pre-trained transformer (GPT) architecture, has begun to revolutionize various fields, including dentistry. Despite these promising applications, the use of GPT in dentistry presents several challenges. Ongoing research and the development of robust ethical frameworks are essential to mitigate these issues and enhance the responsible deployment of GPT technologies in clinical settings. Hence, this systematic review aims to explore the trends, applications, strengths, and challenges associated with the use of GPT in dentistry. Methods: Articles were selected if they contained detailed information on the application of GPT in dentistry. The search strategy used in systematic reviews follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Our search of databases and other sources yielded a total of 704 studies. After removing duplicates and conducting a full-text screening, 16 articles were included in the review. The methodological quality of the research was evaluated using the Critical Appraisal Skills Programme (CASP) checklist. Results: Out of a total of 91 articles published on GPT in dentistry, 20 were editorials and 11 were narrative reviews; these were excluded, leaving 60 original research articles for further analysis. The articles were assessed based on the type of results they provided. Ultimately, 16 articles that reported positive findings with robust methodology were included in this review Conclusions The results highlight mixed responses; therefore, further research on integration into clinical workflows must be conducted with extensive methodological rigor.

Objectives: The integration of large language models (LLMs), particularly those based on the generative pre-trained transformer (GPT) architecture, has begun to revolutionize various fields, including dentistry. Despite these promising applications, the use of GPT in dentistry presents several challenges. Ongoing research and the development of robust ethical frameworks are essential to mitigate these issues and enhance the responsible deployment of GPT technologies in clinical settings. Hence, this systematic review aims to explore the trends, applications, strengths, and challenges associated with the use of GPT in dentistry. Methods: Articles were selected if they contained detailed information on the application of GPT in dentistry. The search strategy used in systematic reviews follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Our search of databases and other sources yielded a total of 704 studies. After removing duplicates and conducting a full-text screening, 16 articles were included in the review. The methodological quality of the research was evaluated using the Critical Appraisal Skills Programme (CASP) checklist. Results: Out of a total of 91 articles published on GPT in dentistry, 20 were editorials and 11 were narrative reviews; these were excluded, leaving 60 original research articles for further analysis. The articles were assessed based on the type of results they provided. Ultimately, 16 articles that reported positive findings with robust methodology were included in this review Conclusions The results highlight mixed responses; therefore, further research on integration into clinical workflows must be conducted with extensive methodological rigor.