The remarkable performance of ChatGPT, launched in November 2022, has significantly impacted the field of natural language processing, inspiring the application of large language models as supportive tools in clinical practice and research worldwide. Although GPT-3.5 recently scored high on the United States Medical Licensing Examination, its performance on medical licensing examinations of other nations, especially non-English speaking nations, has not been sufficiently evaluated. This study assessed GPT’s performance on the National Medical Licensing Examination (NMLE) in Japan and compared it with the actual minimal passing rate for this exam. In particular, the performances of both the GPT-3.5 and GPT-4 models were considered for the comparative analysis. We initially used the GPT models and several prompts for 290 questions without image data from the 116^th NMLE (held in February 2022 in Japan) to maximize the performance for delivering correct answers and explanations of the questions. Thereafter, we tested the performance of the best GPT model (GPT-4) with optimized prompts on a dataset of 262 questions without images from the latest 117^th NMLE (held in February 2023). The best model with the optimized prompts scored 82.7% for the essential questions and 77.2% for the basic and clinical questions, both of which sufficed the minimum passing scoring rates of 80.0% and 74.6%, respectively. After an exploratory analysis of 56 incorrect answers from the model, we identified the three major factors contributing to the generation of the incorrect answers—insufficient medical knowledge, information on Japan-specific medical system and guidelines, and mathematical errors. In conclusion, GPT-4 with our optimized prompts achieved a minimum passing scoring rate in the latest 117^th NMLE in Japan. Beyond its original design of answering examination questions for humans, these artificial intelligence (AI) models can serve as one of the best “sidekicks” for solving problems and addressing the unmet needs in the medical and healthcare fields.

Aldosterone and cortisol serve important roles in the pathogenesis of cardiovascular diseases and metabolic disorders. Epigenetics is a mechanism to control enzyme expression by genes without changing the gene sequence. Steroid hormone synthase gene expression is regulated by transcription factors specific to each gene, and methylation has been reported to be involved in steroid hormone production and disease. Angiotensin II or potassium regulates the aldosterone synthase gene, CYP11B2. The adrenocorticotropic hormone controls the 11b-hydroxylase, CYP11B1. DNA methylation negatively controls the CYP11B2 and CYP11B1 expression and dynamically changes the expression responsive to continuous stimulation of the promoter gene. Hypomethylation status of the CYP11B2 promoter region is seen in aldosterone-producing adenomas. Methylation of recognition sites of transcription factors, including cyclic AMP responsive element binding protein 1 or nerve growth factor-induced clone B, diminish their DNA-binding activity. A methyl-CpG-binding protein 2 cooperates directly with the methylated CpG dinucleotides of CYP11B2. A low-salt diet, treatment with angiotensin II, and potassium increase the CYP11B2 mRNA levels and induce DNA hypomethylation in the adrenal gland. A close association between a low DNA methylation ratio and an increased CYP11B1 expression is seen in Cushing’s adenoma and aldosterone-producing adenoma with autonomous cortisol secretion. Epigenetic control of CYP11B2 or CYP11B1 plays an important role in autonomic aldosterone or cortisol synthesis.

Objectives: Tirzepatide belongs to a new class of anti-diabetic agents that stimulate both glucagon-like peptide-1 and glucose-dependent insulinotropic polypeptide receptors, resulting in a greater blood glucose-lowering effect and body weight reduction than glucagon-like peptide-1 analogs. However, data on the effects of switching from glucagon-like peptide-1 analogs to tirzepatide on the blood glucose level, body weight, and liver functions are unavailable. Methods: Data from 40 patients with type 2 diabetes who received a prescription change from dulaglutide to tirzepatide were retrospectively analyzed at the 3 and 6 months after the switch. The analyzed data included glycosylated hemoglobin, body weight, aspartate aminotransferase, alanine aminotransferase, γ-glutamyl transpeptidase levels, and fibrosis-4 index. Results: Six months after the treatment switch, average reductions of 1.2% and 3.6 kg were observed in the glycosylated hemoglobin and body weight, respectively. The change in glycosylated hemoglobin level was negatively correlated with the baseline glycosylated hemoglobin level. However, body weight reduction was observed regardless of the baseline characteristics. Moreover, the aspartate aminotransferase, alanine aminotransferase, and γ-glutamyl transpeptidase levels decreased 6 months after the switch. Reductions in alanine aminotransferase levels was greater in patients with higher baseline aspartate aminotransferase, alanine aminotransferase, and γ-glutamyl transpeptidase levels. Although the fibrosis-4 index did not improve during the study period, a trend toward a decrease was observed in patients with a higher baseline fibrosis-4 index. Conclusions: Switching from dulaglutide to tirzepatide has a beneficial effect on the blood glucose level, body weight, and liver function in patients with type 2 diabetes.

Background: Some patients with COVID-19 experienced sudden death due to rapid symptom deterioration. Thus, it is important to predict COVID-19 symptom exacerbation at an early stage prior to increasing severity in patients. Patients with COVID-19 could experience a unique “silent hypoxia” at an early stage of the infection when they are apparently asymptomatic, but with rather low SpO2 (oxygen saturation) levels. In order to continuously monitor SpO2 in daily life, a high-performance wearable device, such as the Apple Watch or Fitbit, has become commercially available to monitor several biometric data including steps, resting heart rate (RHR), physical activity, sleep quality, and estimated oxygen variation (EOV). Objective: This study aimed to test whether EOV measured by the wearable device Fitbit can predict COVID-19 symptom exacerbation. Methods: We recruited patients with COVID-19 from August to November 2020. Patients were asked to wear the Fitbit for 30 days, and biometric data including EOV and RHR were extracted. EOV is a relative physiological measure that reflects users’ SpO2 levels during sleep. We defined a high EOV signal as a patient’s oxygen level exhibiting a significant dip and recovery within the index period, and a high RHR signal as daily RHR exceeding 5 beats per day compared with the minimum RHR of each patient in the study period. We defined successful prediction as the appearance of those signals within 2 days before the onset of the primary outcome. The primary outcome was the composite of deaths of all causes, use of extracorporeal membrane oxygenation, use of mechanical ventilation, oxygenation, and exacerbation of COVID-19 symptoms, irrespective of readmission. We also assessed each outcome individually as secondary outcomes. We made weekly phone calls to discharged patients to check on their symptoms. Results: We enrolled 23 patients with COVID-19 diagnosed by a positive SARS-CoV-2 polymerase chain reaction test. The patients had a mean age of 50.9 (SD 20) years, and 70% (n=16) were female. Each patient wore the Fitbit for 30 days. COVID-19 symptom exacerbation occurred in 6 (26%) patients. We were successful in predicting exacerbation using EOV signals in 4 out of 5 cases (sensitivity=80%, specificity=90%), whereas the sensitivity and specificity of high RHR signals were 50% and 80%, respectively, both lower than those of high EOV signals. Coincidental obstructive sleep apnea syndrome confirmed by polysomnography was detected in 1 patient via consistently high EOV signals. Conclusions: This pilot study successfully detected early COVID-19 symptom exacerbation by measuring EOV, which may help to identify the early signs of COVID-19 exacerbation. Trial Registration: University Hospital Medical Information Network Clinical Trials Registry UMIN000041421; https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000047290

Aldosterone, an effector molecule of the renin–angiotensin–aldosterone system (RAAS), has been receiving more attention in the field of ophthalmology because of its possible role in the pathogenesis of various eye diseases or abnormalities; it may even become a target for their treatment. Primary aldosteronism, a typical model of a systemic aldosterone excess, may cause vision loss due to various ocular diseases, such as retinal vein occlusion, central serous chorioretinopathy, and, possibly glaucoma. RAAS components are present in various parts and types of cells present in the eye. Investigations of the local RAAS in various animal models of diabetic macular edema, retinal vein occlusion, retinopathy of prematurity, central serous chorioretinopathy, and glaucoma have found evidence that aldosterone or mineralocorticoid receptors may exacerbate the pathology of these disorders. Further studies are needed to elucidate whether the modulation of aldosterone or mineralocorticoid receptors is an effective treatment for preventing vision loss in patients with eye diseases.