Discovering the strength of immunometabolism in cancer therapy: Employing metabolic pathways to enhance immune responses.

Immunometabolism, which studies cellular metabolism and immune cell function, is a possible cancer treatment. Metabolic pathways regulate immune cell activation, differentiation, and effector functions, crucial to tumor identification and elimination. Immune evasion and tumor growth can result from tumor microenvironment metabolic dysregulation. These metabolic pathways can boost antitumor immunity. This overview discusses immune cell metabolism, including glycolysis, oxidative phosphorylation, amino acid, and lipid metabolism. Amino acid and lipid metabolic manipulations may improve immune cell activity and antitumor immunity. Combination therapy using immunometabolism-based strategies may enhance therapeutic efficacy. The complexity of the metabolic network, biomarker development, challenges, and future approaches are all covered, along with a summary of case studies demonstrating the effectiveness of immunometabolism-based therapy. Metabolomics, stable isotope tracing, single-cell analysis, and computational modeling are also reviewed for immunometabolism research. Personalized and combination treatments are considered. This review adds to immunometabolism expertise and sheds light on metabolic treatments' ability to boost cancer treatment immunological response. Also, in this review, we discussed the immune response in cancer treatment and altering metabolic pathways to increase the immune response against malignancies.

ChatGPT and Clinical Training: Perception, Concerns, and Practice of Pharm-D Students.

Background: The emergence of Chat-Generative Pre-trained Transformer (ChatGPT) by OpenAI has revolutionized AI technology, demonstrating significant potential in healthcare and pharmaceutical education, yet its real-world applicability in clinical training warrants further investigation. Methods: A cross-sectional study was conducted between April and May 2023 to assess PharmD students' perceptions, concerns, and experiences regarding the integration of ChatGPT into clinical pharmacy education. The study utilized a convenient sampling method through online platforms and involved a questionnaire with sections on demographics, perceived benefits, concerns, and experience with ChatGPT. Statistical analysis was performed using SPSS, including descriptive and inferential analyses. Results: The findings of the study involving 211 PharmD students revealed that the majority of participants were male (77.3%), and had prior experience with artificial intelligence (68.2%). Over two-thirds were aware of ChatGPT. Most students (n= 139, 65.9%) perceived potential benefits in using ChatGPT for various clinical tasks, with concerns including over-reliance, accuracy, and ethical considerations. Adoption of ChatGPT in clinical training varied, with some students not using it at all, while others utilized it for tasks like evaluating drug-drug interactions and developing care plans. Previous users tended to have higher perceived benefits and lower concerns, but the differences were not statistically significant. Conclusion: Utilizing ChatGPT in clinical training offers opportunities, but students' lack of trust in it for clinical decisions highlights the need for collaborative human-ChatGPT decision-making. It should complement healthcare professionals' expertise and be used strategically to compensate for human limitations. Further research is essential to optimize ChatGPT's effective integration.