Objective: Several miRNAs have been identified as differentially expressed in patients with poor ovarian response (POR) compared to those with normal responses. This study aims to assess the potential of serum miR-329-3p as a biomarker for diagnosing POR. Methods: We conducted a Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis to confirm the target genes of miR-329-3p. KGN cells were transfected with both miR-329-3p mimic and inhibitor to assess the differential expression of these target genes. In accordance with the Bologna criteria, we enrolled 16 control patients and 16 patients with POR. We collected patient samples, including serum from day 2 and the human chorionic gonadotropin (hCG) day, as well as granulosa and cumulus cells, to validate the expression of miR-329-3p using quantitative real-time polymerase chain reaction. Results: KEGG pathway analysis revealed that miR-329-3p targeted adenylyl cyclase 9 (ADCY9) and protein kinase A subunit beta (PRKACB), both of which are involved in ovarian steroidogenesis. In KGN cells treated with a miR-329-3p mimic, ADCY9 and PRKACB expression levels were significantly reduced (p<0.05). Elevated levels of miR-329-3p suppressed aromatase expression and 17β-estradiol production by modulating ADCY9 and PRKACB in KGN cells. These effects were also observed in POR patients. Follicle-stimulating hormone receptor (FSHR) expression was diminished in the granulosa cells of POR patients. On day 2, on hCG day, and in granulosa cells, miR-329-3p exhibited high expression levels in the serum of POR patients. Conclusion miR-329-3p exhibited increased expression in granulosa cells and in the sera of POR patients. Consequently, we propose that miR-329-3p may be a potential biomarker for the diagnosis of POR.

Objective: We aimed to investigate the effectiveness of buspirone as an adjunctive therapy for alleviating anxiety symptoms in patients with depressive disorders who are already taking antidepressants. Methods: This was an open-label prospective multicenter non-interventional observational study conducted over 12 weeks. We enrolled 180 patients diagnosed with depressive disorders according to DSM-5 criteria and Hamilton Anxiety Rating Scale (HAMA) scores ≥ 18. Participants were already taking selective serotonin reuptake inhibitors or serotoninnorepinephrine reuptake inhibitors and were prescribed adjunctive buspirone. Efficacy was assessed using HAMA, Hamilton Depression Rating Scale (HAMD), Clinical Global Impression Scale-Improvement, Clinical Global Impression Scale-Severity, Sheehan Disability Scale (SDS), and WHO-5 Well-Being Index. Results: The efficacy analysis included 161 patients. HAMA scores decreased significantly from 25.2 ± 6.7 at baseline to 15.4 ± 8.6 at 12 weeks (p ＜ 0.001), whereas HAMD scores decreased from 19.4 ± 4.6 to 12.7 ± 5.7 (p ＜ 0.001).WHO-5 and SDS scores showed significant improvements. The HAMA response rate was 39.1% and the remission rate was 13.7% at 12 weeks. Adverse drug reactions were reported in 3.7% of participants. Subgroup analyses showed no significant differences in treatment response based on buspirone dosage, baseline anxiety/depression severity, or benzodiazepine use. Conclusion Adjunctive buspirone therapy effectively improved anxiety symptoms in depressed patients taking antidepressants, regardless of baseline symptom severity or buspirone dosage. The treatment was well-tolerated with few adverse events. Future studies using a control group are needed.

Background: The novel sodium-glucose cotransporter-2 (SGLT2) inhibitor enavogliflozin effectively lowers glycosylated hemoglobin levels and body weights without the increased risk of serious adverse events; however, the long-term clinical benefits of enavogliflozin in terms of cardiovascular and renal outcomes have not been investigated. Methods: This study is an investigator-initiated, multicenter, randomized, pragmatic, open-label, active-controlled, non-inferiority trial. Eligible participants are adults (aged ≥19 years) with type 2 diabetes mellitus (T2DM) who have a history of, or are at risk of, cardiovascular disease. A total of 2,862 participants will be randomly assigned to receive either enavogliflozin or other SGLT2 inhibitors with proven cardiorenal benefits, such as dapagliflozin or empagliflozin. The primary endpoint is the time to the first occurrence of a composite of major adverse cardiovascular or renal events (Clinical Research Information Service registration number: KCT0009243). Conclusion This trial will determine whether enavogliflozin is non-inferior to dapagliflozin or empagliflozin in terms of cardiorenal outcomes in patients with T2DM and cardiovascular risk factors. This study will elucidate the role of enavogliflozin in preventing vascular complications in patients with T2DM.

Background: Dapagliflozin, a sodium-glucose cotransporter 2 inhibitor, reduces hyperglycemia and obesity by inhibiting renal glucose reabsorption. This post hoc study evaluated clinical factors influencing patient response to dapagliflozin. Methods: The analysis focused on patients treated with dapagliflozin (10 mg/day for 52 weeks) within the randomized, double-blind, parallel-group BEYOND trial. Adequate glycemic control (GC) was defined as a reduction in glycated hemoglobin (HbA1c) of ≥ 1.0% or the achievement of an HbA1c level <7.0% at week 52. Significant weight loss (WL) referred to a reduction in body weight of ≥3.0% at week 52. Participants were classified into four groups based on their GC and WL responses: GC+/WL+, GC+/WL−, GC−/WL+, and GC−/WL−. Results: Among dapagliflozin recipients (n=56), at 52 weeks, HbA1c had decreased by 1.0%±0.8% from baseline, while body weight had declined by 2.4±3.1 kg. Overall, 69.6% of participants achieved GC+, and 57.1% achieved WL+. Male sex and shorter diabetes duration were significantly associated with achieving GC+. Conversely, higher estimated glomerular filtration rate was significantly linked to WL+. The only factor significantly associated with both GC+ and WL+ was shorter diabetes duration (odds ratio, 0.81; 95% confidence interval, 0.68 to 0.97; P=0.023). The GC+ and WL+ groups exhibited favorable responses beginning soon after dapagliflozin therapy was initiated. Furthermore, HbA1c decline was more strongly associated with reduction in visceral fat than with WL. Conclusion A short duration of diabetes and early response to treatment appear to represent key factors in maximizing the benefits of dapagliflozin for blood glucose and weight management.

Background: Active surveillance (AS) has emerged as a viable management strategy for low-risk papillary thyroid microcarcinoma (PTMC), following pioneering trials at Kuma Hospital and the Cancer Institute Hospital in Japan. Numerous prospective cohort studies have since validated AS as a management option for low-risk PTMC, leading to its inclusion in thyroid cancer guidelines across various countries. From 2016 to 2020, the Multicenter Prospective Cohort Study of Active Surveillance on Papillary Thyroid Microcarcinoma (MAeSTro) enrolled 1,177 patients, providing comprehensive data on PTMC progression, sonographic predictors of progression, quality of life, surgical outcomes, and cost-effectiveness when comparing AS to immediate surgery. The second phase of MAeSTro (MAeSTro-EXP) expands AS to low-risk papillary thyroid carcinoma (PTC) tumors larger than 1 cm, driven by the hypothesis that overall risk assessment outweighs absolute tumor size in surgical decision-making. Methods: This protocol aims to address whether limiting AS to tumors smaller than 1 cm may result in unnecessary surgeries for low-risk PTCs detected during their rapid initial growth phase. By expanding the AS criteria to include tumors up to 1.5 cm, while simultaneously refining and standardizing the criteria for risk assessment and disease progression, we aim to minimize overtreatment and maintain rigorous monitoring to improve patient outcomes. Conclusion This study will contribute to optimizing AS guidelines and enhance our understanding of the natural course and appropriate management of low-risk PTCs. Additionally, MAeSTro-EXP involves a multinational collaboration between South Korea and Australia. This cross-country study aims to identify cultural and racial differences in the management of low-risk PTC, thereby enriching the global understanding of AS practices and their applicability across diverse populations.

Background: Recombinant human follicle-stimulating hormone (rhFSH) is commonly used to treat female infertility, but its short half-life necessitates multiple doses. Even corifollitropin alfa, with an extended half-life, requires supplementary injections of rhFSH after 7 days. This study aimed to develop and evaluate a long-acting follicle-stimulating hormone (FSH) formulation using anti-serum albumin Fab-associated (SAFA) technology to avoid additional injections and enhance ovarian function. Methods: SAFA-FSH was synthesized using a Chinese hamster ovary expression system. Its biological efficacy was confirmed through assays measuring its ability to stimulate cyclic adenosine monophosphate (cAMP) production, estradiol synthesis, and the expression of human cytochrome P450 family 19 subfamily A member 1 (hCYP19α1) and human steroidogenic acute regulatory protein (hSTAR) in human ovarian granulosa (KGN) cells. To evaluate the effects of SAFA-FSH, we compared its impact on serum estradiol levels and ovarian weight increase with that of rhFSH in Sprague-Dawley (SD) rats using the modified Steelman-Pohley test. Results: The results indicated that SAFA-FSH induces cAMP synthesis in KGN cells and upregulates the expression of hCYP19α1 and hSTAR in a dose-dependent manner. Female SD rats, aged 21 days, receiving daily subcutaneous human chorionic gonadotropin injections for 5 days exhibited a significant increase in serum estradiol levels and ovarian weight when administered SAFA-FSH on the first day or when given nine injections of rhFSH over 5 days. Notably, the group receiving SAFA-FSH on the first and third days demonstrated an even greater rise in serum estradiol levels and ovarian weight. Conclusion These findings suggest that SAFA-FSH presents a promising alternative to current rhFSH treatments for female infertility. However, further research is essential to thoroughly assess its safety and efficacy in clinical contexts.

Background: In this comprehensive retrospective nationwide cohort study, we examined the relationships between various asthma medications and bone health, utilizing data from the National Health Insurance Service database of South Korea. Methods: From 2015 to 2019, the relevant dataset included 168,611 individuals aged 66 years, among whom 8,747 were diagnosed with asthma. We focused on a subset of 6,173 patients, all 66-year-old women. Participants were categorized into four groups: nonusers of asthma medication (n=2,868), leukotriene antagonist users (n=2,281), inhaled corticosteroid (ICS) users (n=517), and those using a combination of ICS and long-acting beta-agonist (ICS+LABA) medication (n=507). The primary outcomes measured were the incidences of major osteoporotic fractures and hip fractures during the follow-up period. Results: Over 2.7 years of follow-up, 615 cases of major osteoporotic fractures and 96 cases of hip fractures were recorded. ICS users exhibited a heightened risk of both injuries, with hazard ratios of 1.38 (95% confidence interval [CI], 1.18 to 1.63; P<0.001) for major osteoporotic fractures and 1.56 (95% CI, 1.33 to 1.83; P<0.001) for hip fractures. Similarly elevated risks were observed in the ICS+LABA group. Notably, the risk associated with ICS was particularly pronounced among patients with osteopenia for both fracture types. Overall, the use of ICS, alone or in combination with LABA, in patients with asthma is associated with significantly increased risks of osteoporotic fractures, especially among those with osteopenia. Conclusion These findings underscore the importance of considering bone health when managing asthma, especially in older patients and those with existing bone density issues.

Background/Aims: The incidence of steatotic liver disease (SLD) is increasing across all age groups as the incidence of obesity increases worldwide. The existing noninvasive prediction models for SLD require laboratory tests or imaging and perform poorly in the early diagnosis of infrequently screened populations such as young adults and individuals with healthcare disparities. We developed a machine learning-based point-of-care prediction model for SLD that is readily available to the broader population with the aim of facilitating early detection and timely intervention and ultimately reducing the burden of SLD. Methods: We retrospectively analyzed the clinical data of 28,506 adults who had routine health check-ups in South Korea from January to December 2022. A total of 229,162 individuals were included in the external validation study. Data were analyzed and predictions were made using a logistic regression model with machine learning algorithms. Results: A total of 20,094 individuals were categorized into SLD and non-SLD groups on the basis of the presence of fatty liver disease. We developed three prediction models: SLD model 1, which included age and body mass index (BMI); SLD model 2, which included BMI and body fat per muscle mass; and SLD model 3, which included BMI and visceral fat per muscle mass. In the derivation cohort, the area under the receiver operating characteristic curve (AUROC) was 0.817 for model 1, 0.821 for model 2, and 0.820 for model 3. In the internal validation cohort, 86.9% of individuals were correctly classified by the SLD models. The external validation study revealed an AUROC above 0.84 for all the models. Conclusions As our three novel SLD prediction models are cost-effective, noninvasive, and accessible, they could serve as validated clinical tools for mass screening of SLD.

Background/Aims: Inaccurate prediction of lymph node metastasis (LNM) may lead to unnecessary surgery following endoscopic resection of T1 colorectal cancer (CRC). We aimed to validate the usefulness of artificial intelligence (AI) models for predicting LNM in patients with T1 CRC. Methods: We analyzed the clinical data, laboratory results, pathological reports, and endoscopic findings of patients who underwent radical surgery for T1 CRC. We developed AI models to predict LNM using four algorithms: regularized logistic regression classifier (RLRC), random forest classifier (RFC), CatBoost classifier (CBC), and the voting classifier (VC). Four histological factors and four endoscopic findings were included to develop AI models. Areas under the receiver operating characteristics curves (AUROCs) were measured to distinguish AI model performance in accordance with the Japanese Society for Cancer of the Colon and Rectum guidelines. Results: Among 1,386 patients with T1 CRC, 173 patients (12.5%) had LNM. The AUROC values of the RLRC, RFC, CBC, and VC models for LNM prediction were significantly higher (0.673, 0.640, 0.679, and 0.677, respectively) than the 0.525 suggested in accordance with the Japanese Society for Cancer of the Colon and Rectum guidelines (vs RLRC, p<0.001; vs RFC, p=0.001; vs CBC, p<0.001; vs VC, p<0.001). The AUROC value was similar between T1 colon versus T1 rectal cancers (0.718 vs 0.615, p=0.700). The AUROC value was also similar between the initial endoscopic resection and initial surgery groups (0.581 vs 0.746, p=0.845). Conclusions AI models trained on the basis of endoscopic findings and pathological features performed well in predicting LNM in patients with T1 CRC regardless of tumor location and initial treatment method.