Background and Objectives: Dupilumab is approved for the treatment of uncontrolled chronic rhinosinusitis with nasal polyps (CRSwNP) and has been shown to be relatively safe and effective in randomized controlled trials. As such, real-world effectiveness and safety data should be obtained.Subjects and Method We performed a retrospective review of patients with CRSwNP who received monthly treatment of dupilumab between January 2022 and June 2023. Reviewed for the study were the following: demographic data, comorbidities, the visual analogue scale (VAS) for nasal obstruction and sense of smell, identification scores of the Korean version Sniffin’ stikc II (KVSS II) test, nasal polyp score (NPS), and serum eosinophil count. Statistical analyses were performed for each clinical variable. Results: A total of 76 patients (49 male, 27 female) were included in this study. The VAS scores decreased from 7.17 at the baseline to 4.51 at month 6; the KVSS II identification scores increased from 6.71 to 8.47, and the NPS decreased from 3.82 to 0.44. The sino-nasal outcome test-22 scores decreased from 36.29 at the baseline to 8.22 at month 6. The correlations between all clinical variables were statistically significant. Conclusion Monthly treatment of dupilumab is effective and safe for patients with CRSwNP. Further research is required to determine the predictive parameters for treatment responses and adverse events.

Objective: To prospectively evaluate the effect of accelerated deep learning-based reconstruction (Accel-DL) on improving brain magnetic resonance imaging (MRI) quality and reducing scan time compared to that in conventional MRI. Materials and Methods: This study included 150 participants (51 male; mean age 57.3 ± 16.2 years). Each group of 50 participants was scanned using one of three 3T scanners from three different vendors. Conventional and Accel-DL MRI images were obtained from each participant and compared using 2D T1- and T2-weighted and 3D gradient-echo sequences. Accel-DL acquisition was achieved using optimized scan parameters to reduce the scan time, with the acquired images reconstructed using U-Net-based software to transform low-quality, undersampled k-space data into high-quality images. The scan times of Accel-DL and conventional MRI methods were compared. Four neuroradiologists assessed the overall image quality, structural delineation, and artifacts using Likert scale (5- and 3-point scales). Inter-reader agreement was assessed using Fleiss’ kappa coefficient. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated, and volumetric quantification of regional structures and white matter hyperintensities (WMHs) was performed. Results: Accel-DL showed a mean scan time reduction of 39.4% (range, 24.2%–51.3%). Accel-DL improved overall image quality (3.78 ± 0.71 vs. 3.36 ± 0.61, P < 0.001), structure delineation (2.47 ± 0.61 vs. 2.35 ± 0.62, P < 0.001), and artifacts (3.73 ± 0.72 vs. 3.71 ± 0.69, P = 0.016). Inter-reader agreement was fair to substantial (κ = 0.34–0.50). SNR and CNR increased in Accel-DL (82.0 ± 23.1 vs. 31.4 ± 10.8, P = 0.02; 12.4 ± 4.1 vs. 4.4 ± 11.2, P = 0.02). Bland-Altman plots revealed no significant differences in the volumetric measurements of 98.2% of the relevant regions, except in the deep gray matter, including the thalamus. Five of the six lesion categories showed no significant differences in WMH segmentation, except for leukocortical lesions (r = 0.64 ± 0.29). Conclusion Accel-DL substantially reduced the scan time and improved the quality of brain MRI in both spin-echo and gradientecho sequences without compromising volumetry, including lesion quantification.

The development and implementation of a systematic program evaluation framework is critical for improving the quality of the undergraduate medical education. At Yonsei University College of Medicine, we established the following five evaluation domains that encompass various aspects of educational experiences: (1) preclinical curriculum; (2) clinical curriculum; (3) educational environment, resources, and systems; (4) performance of students and graduates and program outcomes; and (5) implementation and outcomes of the curriculum. Specific evaluation indicators were designed within these domains and validated through the Delphi technique, which integrated expert opinions. In total, 98 indicators were identified across five domains. These indicators will function as a comprehensive tool for assessing medical education programs. The proposed evaluation framework addresses both shortand long-term educational changes, facilitating systematic monitoring, continuous quality improvement of curricula, and better outcomes for students. As this framework is grounded in the unique context of the institution, it is appropriate for a comprehensive evaluation of interactions at various educational stages. Furthermore, it may serve as a strategic foundation for identifying areas that require improvement, ensuring that the curriculum aligns with current medical education standards and practices. The framework’s structured approach and continuing evaluation processes may make it possible to obtain essential data for ongoing development, potentially contributing to a robust system for quality improvement in medical education. The findings of this study are expected to serve as a valuable reference for developing similar evaluation frameworks in other medical schools.

RESULTS: Resveratrol significantly reduced cardiac hypertrophy and remodeling in aging hearts. In addition, resveratrol significantly ameliorated aging-induced mitochondrial dysfunction (e.g., decreased oxygen respiration and increased hydrogen peroxide emission) and mitochondria-dependent apoptotic signaling (the Bax/Bcl-2 ratio, mitochondrial permeability transition pore opening sensitivity, and cleaved caspase-3 protein levels).Resveratrol also significantly attenuated aging-induced apoptosis (determined via cleaved caspase-3 staining and TUNEL-positive myonuclei) in cardiac muscles. CONCLUSION This study demonstrates that resveratrol treatment has a beneficial effect on aging-induced cardiac remodeling by ameliorating mitochondrial dysfunction and inhibiting mitochondria-mediated apoptosis in the heart.

Objective: This study investigates the reciprocal, longitudinal relationship between smartphone dependence and externalizing behavior problems in children. Methods: A total of 379 school-aged children (7–12 years old) were assessed using the Smartphone Overdependency Observer Scale and the Korean Version of the Child Behavior Checklist for Ages 6–18 at four six-month intervals from June 2021 to June 2022. Among them, 338 children completed at least two assessments. An autoregressive cross-lagged model was employed to examine the bidirectional relationships and temporal stability between smartphone overdependence and externalizing behavior problems while controlling for gender, age, and baseline internalizing behavior problems. Results: Both variables demonstrated significant autoregressive effects, indicating stability over time. Cross-lagged analysis revealed that higher smartphone dependence predicted increased externalizing behavior problems in subsequent periods while externalizing behavior problems did not predict future smartphone dependence. Conclusion Smartphone dependence appears to contribute to externalizing behavior problems in children, highlighting the critical need for early interventions that promote healthy digital habits to mitigate behavioral challenges.

Objective: The clinical presentation of depressive disorders might be influenced by age, and its diagnosis and treatment can be affected by ageism-related bias. A network analysis can reveal symptom patterns unrecognized by the reductionistic approach. Therefore, this study explores the network structure of depression and anxiety symptoms in older Asian patients with depressive disorders and examines age-related differences in the context of ageism. Methods: We used data from the Research on Asian Psychotropic Prescription Patterns for Antidepressants, Phase 3 study and included 2,785 psychiatric patients from 11 Asian countries. Depression and anxiety symptoms were assessed using the Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7. Network analyses were conducted to identify symptom interconnections and centrality among older (>65 years), middle-aged (35–64 years), and young (18–34 years) adult groups. The network structures were also compared using a network comparison test. Results: Depressed mood was the most central symptom across all age groups. Network comparisons revealed no significant structural differences among the three age groups, despite several variations in terms of global strength. The network structure of the older group was characterized by strong interconnections between somatic symptoms (insomnia-energy) and core depressive symptoms (little interest or pleasure-feelings of hopelessness). Conclusion This study reveals that the network structures of depression and anxiety symptoms have relatively consistent interconnections across age groups, despite subtle age-based differences. Specifically, older adults tend to present anxiety and depression symptoms as physical complaints. These findings challenge ageist stereotypes and advocate for inclusive, age-neutral approaches to treatment.

The prevalence of postpartum depression (PPD) in Asia is reported to range from 13.53% to 22.31%. However, there remains a gap in the identification of PPD, particularly regarding cultural cutoff points. Therefore, the purpose of this scoping review was to determine the prevalence and associated factors of PPD in Eastern, South-eastern, Western, and Southern Asian countries and analyze the cutoff points of the Edinburgh Postnatal Depression Scale (EPDS) used across these countries. Following Arksey and O'Malley’s five-step scoping review framework, the population was defined as mothers, the concept as the EPDS, and the context as the Asian region. A literature search was conducted using PubMed, Embase, CINAHL, PsycINFO, and Web of Science. The data analysis focused on demographic characteristics, EPDS cutoffs and features, PPD prevalence, and its associated factors. Nineteen studies were selected. Most countries used translated versions of the EPDS with demonstrated reliability and validity. The cutoff scores varied, with most using scores of 10 or higher. The prevalence of PPD ranged from 5.1% to 78.7%. Key associated factors for PPD included cultural factors such as relationships with in-laws and preferences for the newborn’s sex. To improve the accuracy of PPD screening in Asia, the EPDS should be used consistently, and appropriate cutoff criteria must be established. In addition, prevention strategies and programs that reflect the cultural characteristics and social context of Asia need to be developed for the early detection and prevention of PPD.

Primary cholangiocarcinoma is a rare bile duct epithelial neoplasm that can present with atypical clinical manifestations, complicating its diagnosis. A 62-year-old male showed symptoms suggestive of a complicated hepatic cyst that was later identified as intrahepatic cholangiocarcinoma. The patient presented with abdominal discomfort without fever. Imaging revealed a large cystic lesion in the liver. Despite the initial treatment for a presumed abscess, a biopsy confirmed cholangiocarcinoma. This case highlights the diagnostic challenge of distinguishing between benign complicated hepatic cysts and malignancies, particularly when typical markers of infection are absent. Early biopsy and vigilant assessments are crucial in such presentations to avoid a delayed diagnosis and initiate appropriate treatment.

Hepatic tuberculosis, typically associated with miliary tuberculosis, can occasionally present as localized liver lesions. This case report describes a 77-year-old male presenting with persistent abdominal pain and fever, following an endoscopic retrograde cholangiopancreatography for bile duct sludge removal. Subsequent computed tomography revealed focal liver lesions. Despite initial treatment with antibiotics for a suspected inflammatory liver abscess, his condition did not improve. A liver biopsy was performed, revealing caseous granulomas, and the tuberculosis polymerase chain reaction result was positive. The patient was diagnosed with primary hepatic tuberculosis, which later disseminated. Oral anti-tuberculosis therapy was initiated and is currently being closely monitored. This case emphasizes the importance of considering hepatic tuberculosis in the differential diagnosis of liver lesions, particularly in cases involving cholestatic liver function tests, and persistent symptoms unresponsive to conventional antibiotics.

Background/Aims: Atrial fibrillation (AF) significantly contributes to global morbidity and mortality. Paroxysmal atrial fibrillation (PAF) is particularly common among patients with cryptogenic strokes or transient ischemic attacks and has a silent nature. This study aims to develop reliable artificial intelligence (AI) algorithms to detect early signs of AF in patients with normal sinus rhythm (NSR) using a 12-lead electrocardiogram (ECG). Methods: Between 2013 and 2020, 552,372 ECG traces from 318,321 patients were collected and split into training (n = 331,422), validation (n = 110,475), and test sets (n = 110,475). Deep neural networks were then trained to predict AF onset within one month of NSR. Model performance was evaluated using the area under the receiver operating characteristic curve (AUROC). An explainable AI technique was employed to identify the inference evidence underlying the predictions of deep learning models. Results: The AUROC for early diagnosis of PAF was 0.905 ± 0.007. The findings reveal that the vicinity of the T wave, including the ST segment and S-peak, significantly influences the ability of the trained neural network to diagnose PAF. Additionally, comparing the summarized ECG in NSR with those in PAF revealed that nonspecific ST-T abnormalities and inverted T waves were associated with PAF. Conclusions Deep learning can predict AF onset from NSR while detecting key features that influence decisions. This suggests that identifying undetected AF may serve as a predictive tool for PAF screening, offering valuable insights into cardiac dysfunction and stroke risk.