This paper details the development and implementation of Yonsei Medical E-Learning System 3.0 (YES 3.0), a new learning management system (LMS) for Yonsei University College of Medicine. Driven by the need to adapt to a rapidly changing medical education landscape, YES 3.0 addresses the previous system’s limitations and incorporates advanced features designed to improve learning experiences and educational outcomes. The development process involved extensive collaboration among faculty, students, staff, and the system developer, ensuring the system's alignment with the unique needs of the medical education environment. YES 3.0 features real-time monitoring of learning progress, comprehensive evaluation and grade management, personalized learning path recommendations, effective learner history management, and interview/guidance management functionalities. The system also supports the newly revised CDP2023 (Curriculum Development Project 2023) curriculum, with integrated learning across all courses and a strengthened scholarly advanced course. By automating and streamlining various educational processes, YES 3.0 enables maximized learning efficiency, promotes learner-centered education, and supports the cultivation of future medical professionals equipped to navigate the evolving healthcare environment. Implementing the system is expected to have positive impacts on both educational and economic aspects, contributing to the advancement of medical education at Yonsei University College of Medicine. This study also aims to offer insights and expected outcomes that can serve as a reference for other medical schools in adopting and operating LMS, ultimately providing useful information to educators considering establishing a digital learning environment.

Bioassay-guided fractionation of the methanolic extract of Artemisia iwayomogi Kitamura led to the isolation of 12 known compounds (1‒12). Notably, this study marks the first report of 3-epimeridinol (1) being isolated and structurally characterized from a natural source. Additionally, compounds 3, 4, and 7 were isolated from the Asteraceae family for the first time. The structural elucidation of the isolated compound was achieved through analysis of 1D, 2D NMR, and MS data. Upon evaluation of their inhibitory effects against lipopolysaccharideinduced nitric oxide production, compound 12 demonstrated significant inhibitory activity with greater potency than the reference compound quercetin. These results established A. iwayomogi as a promising source of antiinflammatory agents.

The roots of Astragalus membranaceus Bunge have long been used in herbal medicine for their diversebiological activities. Notably, its potential anti-diabetic properties have been extensively studied, highlighting promising therapeutic prospects. In this study, we conducted a comprehensive investigation focusing on flavonoid components from the roots of A. membranaceus and their PTP1B inhibitory activity. As a result, we isolated a total of 24 flavonoids, among which formonentin (1), pratensein (3), and vesticarpan (19) emerged as the most potent inhibitors against PTP1B with IC50 value of 10.9 ± 1.09 μM, 10.0 ± 1.71 μM, and 10.3 ± 1.31 μM, respectively.Additionally, through the enzyme kinetic analysis, the inhibition mode of compound 19 was determined as a competitive inhibitor, with Ki value of 7.6 ± 1.17 μM. Furthermore, the molecular docking simulation elucidated the binding mechanism of compound 19 with PTP1B, mainly through van der Waals forces and hydrogen bonds.This study highlights the PTP1B inhibitory potential of the flavonoid constituents derived from the roots of A. membranaceus. Moreover, discovering vesticarpan (19) as a novel PTP1B inhibitor provides a significant foundation for further investigations to develop innovative therapeutic strategies for diabetes treatment.

Objective: As the demand for community mental health services continues to grow, the need for well-equipped and organized services has become apparent. This study aimed to optimize the roles and infrastructure of mental health services, by establishing, among other initiatives, standardized operating models. Methods: The study was conducted in multiple phases from May 12, 2021, to December 29, 2021. Stakeholders within South Korea and metropolitan mental health welfare centers were targeted, but addiction management support centers, including officials, patients, and their families, were integrated as well. A literature review and survey, focus group interviews, a Delphi survey, and expert consultation contributed to comprehensive revisions and improvements of the mental health service model. Results: The proposed model for community mental health welfare centers emphasizes the expansion of personnel and infrastructure, with a focus on severe mental illnesses and suicide prevention. The model for metropolitan mental health welfare centers delineates essential tasks in areas such as project planning and establishment, community research, and education about severe mental illnesses. The establishment of a 24-hour emergency intervention center was a crucial feature. In the integrated addiction support center model, the need to promote addiction management is defined as an essential task and the establishment of national governance for addiction policies is recommended. Conclusion This study proposed standard operating models for three types of mental health service centers. To meet the increasing need for community care, robust mental health service delivery systems are of primary importance.

BACKGROUND: Exogenous Cushing’s syndrome, which results from prolonged glucocorticoid treatment, is associated with metabolic abnormalities. Previously, we reported the inhibitory effect of tonsil-derived mesenchymal stem cell conditioned medium (T-MSC CM) on glucocorticoid signal transduction. In this study, we investigated the therapeutic efficacy of T-MSCs in a mouse model of exogenous Cushing’s syndrome. METHODS: Exogenous Cushing’s syndrome model mice was generated by corticosterone administration in the drinking water for 5 weeks, and T-MSCs were injected intraperitoneally twice during the third week. Serum lipid profiles were measured using a chemistry analyzer. HepG2 cells were treated with dexamethasone and co-cultured with T-MSCs.Expression levels of genes involved in cholesterol metabolism were examined using real-time PCR. Low-density lipoprotein receptor (LDLR) protein levels were determined using western blotting and immunohistochemistry. Liver RNA extracted from the CORT and CORT ? MSC mouse groups was used for transcriptome sequencing analysis and protein– protein interaction analysis. RESULTS: Weight reduction and improvements in dyslipidemia by T-MSC administration were observed only in female mice. T-MSCs reduce circulating LDL cholesterol levels by downregulating liver X receptor a (LXRa) and inducible degrader of LDLR (IDOL) expression, thereby stabilizing LDLRs in the liver. Transcriptome analysis of liver tissue revealed pathways that are regulated by T-MSCs administration. CONCLUSION Administration of MSCs to female mice receiving chronic corticosterone treatment reduced the circulating LDL cholesterol level by downregulating the LXRa–IDOL axis in hepatocytes. These results suggest that T-MSCs may offer a novel therapeutic strategy for managing exogenous Cushing’s syndrome by regulating cholesterol metabolism.

Background: Traditionally, dental implants require a healing period of 4 to 9 months for osseointegration, with longer recovery times considered when bone grafting is needed. This retrospective study evaluates the clinical efficacy of demineralized dentin matrix (DDM) combined with recombinant human bone morphogenetic protein-2 (rhBMP-2) during dental implant placement to expedite the osseointegration period for early loading. Methods: Thirty patients (17 male, 13 female; mean age 55.0 ± 8.8 years) requiring bone grafts due to implant fixture exposure (more than four threads; ≥ 3.2 mm) were included, with a total of 96 implants placed. Implants were inserted using a two-stage protocol with DDM/rhBMP-2 grafts. Early loading was initiated at two months postoperatively in the mandible and three months in the maxilla. Clinical outcomes evaluated included primary and secondary stability (implant stability quotient values), healing period, bone width, and marginal bone level assessed via cone-beam computed tomography. Results: All implants successfully supported final prosthetics with a torque of 50Ncm, without any osseointegration failures. The average healing period was 69.6 days in the mandible and 90.5 days in the maxilla, with significantly higher secondary stability in the mandible (80.7 ± 6.7) compared to the maxilla (73.0 ± 9.2, p < 0.001). Histological analysis confirmed new bone formation and vascularization. Conclusion DDM/rhBMP-2 grafting appears to significantly reduce the healing period, enabling early loading with stable and favorable clinical outcomes.

Purpose: To develop a machine learning (ML) classifier for predicting post-induction hypotension (PIH) in non-cardiac surgeries. Materials and Methods: Preoperative data and early vital signs were obtained from 3669 cases in the VitalDB database, an opensource registry. PIH was defined as sustained mean arterial pressure (MAP) <65 mm Hg within 20 minutes since induction or from induction to incision. Six different ML algorithms were used to create binary classifiers to predict PIH. The primary outcome was the area under the receiver operating characteristic curve (AUROC) of ML classifiers. Results: A total of 2321 (63.3%) cases exhibited PIH. Among ML classifiers, the random forest regressor and extremely gradient boosting regressor showed the highest AUROC, both recording a value of 0.772. Excluding these models, the light gradient boosting machine regressor showed the second highest AUROC [0.769; 95% confidence interval (CI), 0.767–0.771], followed by the gradient boosting regressor (0.768; 95% CI, 0.763–0.772), AdaBoost regressor (0.752; 95% CI, 0.743–0.761), and automatic relevance determination regression (0.685; 95% CI, 0.669–0.701). The top three important features were mean diastolic blood pressure (DBP), minimum MAP, and minimum DBP from anesthetic induction to tracheal intubation, and these features were lower in cases with PIH (all p<0.001). Conclusion ML classifiers exhibited moderate performance in predicting PIH, and have the potential for real-time prediction.

Objective: This study aims to objectively evaluate turning gait parameters in Parkinson’s disease (PD) patients using 2D-RGB video-based analysis and explore their relationships with imbalance. Methods: We prospectively enrolled PD patients for clinical assessment, balance analysis and gait with 180º turning. Spatiotemporal gait parameters during turning were derived using video-based analysis and correlated with modified Hoehn and Yahr (mHY) stages and center of pressure (COP) oscillations. Results: A total of 64 PD patients were enrolled. The PD patients with higher mHY stages (≥2.5) had significantly longer turning times, greater numbers of steps, wider step bases and less variability in step length during turns. COP oscillations were positively correlated with the mean turning time on both the anterior-posterior and right-left axes. Conclusion Spatiotemporal gait parameter during turning, derived from video-based gait analysis, may represent apromising biomarker for monitoring postural instability in PD patients.