Objectives: . Allergic rhinitis (AR) significantly impacts quality of life and incurs socioeconomic costs. The influence of smoking habits, including the use of conventional cigarettes (CCs) and electronic cigarettes (ECs), on the prevalence and management of AR remains a subject of debate. This study aims to explore the association between smoking status (CC and EC use) and the prevalence and management of AR among Koreans by analyzing data from the Korea National Health and Nutrition Examination Survey (KNHANES) VII (2018) and VIII (2019–2021). Methods: . This cross-sectional study involved 22,290 participants aged 19 years and older from the KNHANES. Participants self-reported their smoking status, and urinary cotinine levels were measured to assess nicotine exposure. We employed statistical analyses, including logistic regression, to examine the relationships between smoking status, cotinine levels, and the prevalence and management of AR. Results: . In univariable logistic regression analysis, EC users exhibited a 35.8% increased risk of AR compared to non-smokers, whereas CC users experienced a 27.7% reduced risk. Multivariable logistic regression analysis showed a 20.3% lower risk of AR among CC users; however, no significant association was observed for EC users. Higher cotinine levels (>500 ng/mL) were associated with a lower prevalence of AR. Specifically, heavy CC users with high cotinine levels demonstrated a 35% reduced risk of AR. Nonetheless, after adjusting for confounders, this association was no longer significant, indicating that other variables might influence this relationship. Conclusion . Smoking status is associated with the prevalence of AR in Koreans. Notably, heavy use of CCs is negatively correlated with the prevalence of AR.

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.

Objective: Multiple cohort studies have investigated the potential link between anesthesia and dementia. However, mixed findings necessitate closer examination. This study aimed to investigate the association between anesthesia exposure and the incidence of dementia, considering different anesthesia types and anesthetic agents. Methods: This nationwide cohort study utilized data from the South Korean Health Insurance Review and Assessment Service database, covering 62,541 participants, to investigate the correlation between anesthesia exposure and dementia incidence. Results: Results revealed an increased risk of dementia in individuals who underwent general (hazard ratio [HR], 1.318;95% confidence interval [CI], 1.061−1.637) or regional/local anesthesia (HR, 2.097; 95% CI, 1.887−2.329) compared to those who did not. However, combined general and regional/local anesthesia did not significantly increase dementia risk (HR, 1.097; 95% CI, 0.937−1.284). Notably, individual anesthetic agents exhibited varying risks; desflurane and midazolam showed increased risks, whereas propofol showed no significant difference. Conclusion This study provides unique insights into the nuanced relationship between anesthesia, individual anesthetic agents, and the incidence of dementia. While confirming a general association between anesthesia exposure and dementia risk, this study also emphasizes the importance of considering specific agents. These findings under-score the need for careful evaluation and long-term cognitive monitoring after anesthesia.

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.

Alzheimer disease (AD) diagnosis is confirmed using a medley of modalities, such as the detection of amyloid-β (Aβ) neuritic plaques and neurofibrillary tangles with positron electron tomography (PET) or the appraisal of irregularities in cognitive function with examinations. Although these methods have been efficient in confirming AD pathology, the rising demand for earlier intervention during pathogenesis has led researchers to explore the diagnostic potential of fluid biomarkers in cerebrospinal fluid (CSF) and plasma. Since CSF sample collection is invasive and limited in quantity, biomarker detection in plasma has become more attractive and modern advancements in technology has permitted more efficient and accurate analysis of plasma biomolecules. In this study, we found that a composite of standard factors, Aβ40 and total tau levels in plasma, divided by the variation factor, plasma Aβ42 level, provide better correlation with amyloid neuroimaging and neuropsychological test results than a level comparison between total tau and Aβ42 in plasma. We collected EDTA-treated blood plasma samples of 53 subjects, of randomly selected 27 AD patients and 26 normal cognition (NC) individuals, who received amyloid-PET scans for plaque quantification, and measured plasma levels of Aβ40, Aβ42, and total tau with digital enzyme-linked immunosorbent assay (ELISA) in a blinded manner. There was difficulty distinguishing AD patients from controls when analyzing biomarkers independently. However, significant differentiation was observed between the two groups when comparing individual ratios of total-tau×Aβ40/Aβ42. Our results indicate that collectively comparing fluctuations of these fluid biomarkers could aid in monitoring AD pathogenesis.

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.