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AIM: To evaluate the performance of three distinct large language models(LLM), including GPT-3.5, GPT-4, and PaLM2, in responding to queries within the field of ophthalmology, and to compare their performance with three different levels of medical professionals: medical undergraduates, master of medicine, and attending physicians.METHODS: A total of 100 ophthalmic multiple-choice tests, which covered ophthalmic basic knowledge, clinical knowledge, ophthalmic examination and diagnostic methods, and treatment for ocular disease, were conducted on three different kinds of LLM and three different levels of medical professionals(9 undergraduates, 6 postgraduates and 3 attending physicians), respectively. The performance of LLM was comprehensively evaluated from the aspects of mean scores, consistency and confidence of response, and it was compared with human.RESULTS: Notably, each LLM surpassed the average performance of undergraduate medical students(GPT-4:56, GPT-3.5:42, PaLM2:47, undergraduate students:40). Specifically, performance of GPT-3.5 and PaLM2 was slightly lower than those of master's students(51), while GPT-4 exhibited a performance comparable to attending physicians(62). Furthermore, GPT-4 showed significantly higher response consistency and self-confidence compared with GPT-3.5 and PaLM2.CONCLUSION: LLM represented by GPT-4 performs well in the field of ophthalmology, and the LLM model can provide clinical decision-making and teaching aids for clinicians and medical education.
ABSTRACT
Interleukin-17 (IL-17) plays an important role in the body′s immune response and inflammatory response.High levels of IL-17 are associated with a variety of autoimmune diseases, acute and chronic neurodegenerative diseases, and psychiatric disorders.Autism spectrum disorder (ASD) is a group of common neurodevelopmental disorders in childhood.Recent clinical and experimental studies have linked maternal immune activation (MIA) during pregnancy to the risk of ASD in offspring.Significantly increased IL-17 level is found in MIA-induced progeny ASD, which is the key factor leading to neurodevelopmental abnormalities in progeny mice.This article reviews the latest research progress on the relationship between IL-17 and progeny ASD, and provides new ideas for the prevention and treatment of ASD.
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OBJECTIVE@#To investigate the effect of glucagon-like peptide 1 receptor agonists (GLP-1RAs) on body fat redistribution and muscle mass in overweight/obese patients with type 2 diabetes (T2DM).@*METHODS@#We retrospectively analyzed the data of 76 patients with body mass indexes (BMI)≥24 kg/m, who had an established diagnosis of T2DM in our department between December, 2014 and September, 2015. We divided these patients according to their BMI in overweight group (BMI of 24-27.9 kg/m, =14), obese group (BMI of 28-31.9 kg/m, =35) and severely obese group (BMI≥32 kg/m, =27). All the patients received treatment with GLP-1RAs (Exenatide or Liraglutide) for 3.0 to 29.0 weeks (mean 8.9 weeks), and their blood glucose, HbA1c and serum lipids were analyzed. For each patient, the fat and muscle masses were analyzed using a human body composition analyzer (JAWON-IOI353, Korea) before and after GLP-1RAs treatment.@*RESULTS@#Treatment with GLP-1RAs significantly decreased BMI and visceral adiposity index (VAI) in all the patients in the 3 groups ( < 0.05). The treatment significantly decreased the body weight in the overweight group and obese group by 2.70 kg (0.60-4.95 kg) and 2.65 kg (1.45-6.40 kg), respectively ( < 0.05), and significantly decreased the waist-to-hip ratio (WHR) in the overweight group ( < 0.05). The obese and severely obese patients showed significantly decreased percentage body fat (including both subcutaneous and visceral fat) and increased muscle mass after the treatment ( < 0.05). Compared with those in the overweight group, the percentage body fat and VAI were significantly decreased in the obese group after the treatment ( < 0.05), and the percentage of subcutaneous fat reduced and the muscle ratio increased more obviously in the obese and severely obese patients ( < 0.05).@*CONCLUSIONS@#GLP-1RAs treatment can significantly lower BMI and improve body fat distribution in obese patients with T2DM, especially in patients with a greater BMI.