Multi role ChatGPT framework for transforming medical data analysis.

The application of ChatGPTin the medical field has sparked debate regarding its accuracy. To address this issue, we present a Multi-Role ChatGPT Framework (MRCF), designed to improve ChatGPT's performance in medical data analysis by optimizing prompt words, integrating real-world data, and implementing quality control protocols. Compared to the singular ChatGPT model, MRCF significantly outperforms traditional manual analysis in interpreting medical data, exhibiting fewer random errors, higher accuracy, and better identification of incorrect information. Notably, MRCF is over 600 times more time-efficient than conventional manual annotation methods and costs only one-tenth as much. Leveraging MRCF, we have established two user-friendly databases for efficient and straightforward drug repositioning analysis. This research not only enhances the accuracy and efficiency of ChatGPT in medical data science applications but also offers valuable insights for data analysis models across various professional domains.

Impact of immunosenescence and inflammaging on the effects of immune checkpoint inhibitors.

Immune checkpoint inhibitors (ICIs) are employed in immunotherapeutic applications for patients with weakened immune systems and can improve the ability of T cells to kill cancer cells. Although ICIs can potentially treat different types of cancers in various groups of patients, their effectiveness may differ among older individuals. The reason ICIs are less effective in older adults is not yet clearly understood, but age-related changes in the immune system, such as immunosenescence and inflammation, may play a role. Therefore, this review focuses on recent advances in understanding the effects of immunosenescence and inflammation on the efficacy of ICIs.

The relationship between different interleukins and T helper cells count in patients with immune thrombocytopenia.

Immune thrombocytopenia is the most common autoimmune disorder involving blood types. In several studies, the role of T CD4+ cells in patients with immune thrombocytopenia has been associated with different results. Therefore, in this study, with the aim of applied research in the pathogenesis of immune thrombocytopenia, the relationship was investigated between the number of T CD4+ cells, serum levels of IL-11 and IL-17 cytokines, and platelet count. In this regard, 100 patients with immune thrombocytopenia and 100 healthy individuals were included in the study. The T CD4+ cell counts were examined by flow cytometry and in addition, serum levels of interleukins 11 and 17 were measured by ELISA. The results of this study showed that the number of T CD4+ cells and plasma level of IL-17 were not significantly different between the two groups, but plasma levels of IL-11 in the patient group were significantly higher than the control group (P = 0.286). Overall, in this study, the level of cytokine IL-11 was significantly increased in comparison with IL-17 and T CD4+ cells in patients with immune thrombocytopenia, so it is suggested that measurement of cytokine IL-11 level in these patients could be considered as a critical diagnostic marker and indicator in the stages of disease progression.