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Objective: To study autonomic imbalance if any in normal tension glaucoma (NTG)patients by heart rate variability (HRV)and head-up tilt (HUT)test. Methods:The study subjects of age between 45 and 65 years of either sex comprised 20 patients with NTG (Group ІІ)and 20 age-and sex-matched healthy controls (Group І). Different variables of time and frequency domain of HRV were analyzed at rest, during HUT and the recovery period.Results: Highly significant decrease in value of root mean square successive difference observed in Group ІІ (p<0.000)in comparison to controls. The high-frequency variables (HF [nu]and HF [ms 2 ])were significantly less (p<0.000)and low frequency (LF)/HF ratio was significantly high (p<0.000) in Group ІІ. Conclusion:During stress test, i.e., HUT there was the greater withdrawal of parasympathetic input to heart; hence, there was relatively over sympathetic activity due to sympatho-vagal imbalance.

Purpose:To assess cognitive performance differences , if any,among primary open-angle glaucoma (POAG) patients, normal-tension glaucoma (NTG) patients, and healthy control (C) subjects.Methods:60 age and sex matched subjects (20 POAG, 20 NTG, and 20 C subjects) were included in this study. Following routine ophthalmological examination the cognitive performance of all participants, detailed neurological examinations, including the mini-mental state examination (MMSE), were done.Results:The mean RNFL thicknesses were significantly different among the groups in the POAG, NTG, and C subjects, respectively; p <0.001). MMSE scores were 24.1 ± 2.4, 25.2  ± 3.8 and 28.9 ± 0.9 in the POAG, NTG, and Controls groups, respectively. There were significant differences among the three groups (p <0.001). Moreover, there were significant differences between the NTG and Controls groups (p <0.001), and between the POAG and Controls groups (p<0.001).Conclusions:The overlapping pathogenesis in glaucoma and neurodegenerative disorders cause deterioration in cognitive performance. Decreased values of MMSE scores  in POAG and NTG patients compared to the scores of healthy controls suggest a detailed neurological examination of glaucoma patients. Keywords: neurodegenerative disease, cognition, dementia, open angle glaucoma

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Background and objective ChatGPT is a large language model (LLM) generative artificial intelligence (AI) chatbot trained through deep learning to produce human-like language skills and analysis of simple problems across a wide variety of subject areas. However, in terms of facilitating the transfer of learning in medical education, a concern has arisen that while AI is adept at applying surface-level understanding, it does not have the necessary in-depth knowledge to act at an expert level, particularly in addressing the core concepts. In this study, we explored the efficacy of ChatGPT in solving various reasoning questions based on the five core concepts applied to different modules in the subject of physiology. Materials and methods In this study, a total of 82 reasoning-type questions from six modules applicable to the five core concepts were created by the subject experts. The questions were used to chat with the conversational AI tool and the responses generated at first instance were considered for scoring and analysis. To compare the scores among various modules and five core concepts separately, the Kruskal-Wallis test along with post hoc analysis were used. Results The overall mean score for the modules (60 questions) was 3.72 ±0.26 while the average score obtained for the core concepts (60 questions) was 3.68 ±0.30. Furthermore, statistically significant differences (p=0.05 for modules and p=0.024 for core concepts) were observed among various modules as well as core concepts. Conclusion The significant differences observed in the scores among various modules and core concepts highlight the varying execution of the same software tool, thereby necessitating the need for further evaluation of AI-enabled learning applications to enhance the transfer of learning among undergraduates.