Yongtaek Oh

Vascular dementia (VaD), accounting for up to 20% of dementia cases globally, is primarily driven by chronic cerebral hypoperfusion (CCH), which leads to progressive cognitive impairment. Despite the increasing prevalence of VaD, effective treatments remain limited. Natural products—including herbal formulas, single herbs, and phytochemicals—have emerged as promising candidates due to their multi‐targeted biological activities. This review aimed to evaluate the efficacy and underlying mechanisms of natural products in ameliorating CCH‐induced VaD in experimental rodent models, and to identify feasible mechanistic pathways and targets. Protective effects of natural products were mediated by enhanced vascular regeneration, BBB stability, synaptic plasticity, and neurotrophic signaling along with reduced oxidative stress, neuroinflammation, and apoptosis. Among the proteins concerned, the serine/threonine kinase Akt1 emerged as a primary regulatory protein involved in coordinating survival and inflammatory responses. Predominantly male rat models were subjected to bilateral common carotid artery occlusion (BCCAo) or bilateral common carotid artery stenosis (BCAS) to mimic clinical features of CCH. These two models provided a robust and translational strategy for a preclinical approach against VaD. The interconnected network analysis facilitated the discovery of core anti‐VaD interventions by linking established herbal formulas with promising, yet understudied, botanical resources. Natural products demonstrate multitargeted protective potential in VaD animal models by targeting multiple pathological processes. Further investigation of underexplored herbs and phytochemicals may expand treatment strategies and support the development of novel and multi‐targeted interventions for VaD.

Psoriatic arthritis (PsA) is a chronic immune-mediated arthropathy characterized by synovitis, enthesitis, and coupled bone erosion and pathological new-bone formation. Although biologics have improved outcomes, incomplete or lost response and safety constraints motivate the search for complementary multi-target candidates. Here, herb–compound records from OASIS; compound–target interactions from DrugBank, TTD, and STITCH; and curated PsA disease genes from DisGeNET were integrated into a multiscale interactome, and a biased random walk with restart was applied to prioritize herbs and constituents. Herbs were ranked by diffusion-profile similarity to PsA together with disease–target overlap. The prioritized set comprised three literature-supported comparator herbs and six candidate herbs without prior PsA evidence. Enrichment of the shared targets against PsA-relevant KEGG pathways returned IL-17 signaling, TNF signaling, Th17-cell differentiation, and osteoclast differentiation, while integrated network analyses—rather than pathway enrichment alone—identified TRAF3IP2 and RUNX2, together with BMP4, as recurrent nodes linking inflammation to bone remodeling. Compound-resolved subnetworks nominated constituent-level mechanisms, and site-resolved docking identified α-asarone as the most ligand-efficient molecule within the tested candidate panel and, provisionally, iNOS as the target with the most consistently favorable ligand efficiency in that panel. These convergent computational findings are hypothesis-generating and define candidates for experimental evaluation.

This study addresses the limitations of Standardized Patients (SPs) in Traditional Korean Medicine (TKM) by developing an AI-driven CPX platform. By integrating Large Language Models (LLMs) with Retrieval-Augmented Generation (RAG) and multimodal clinical cues, the system automates scenario generation and provides quantitative feedback. Expert validation (N=10) demonstrated high validity with an overall mean score of 4.61/5.0 (SD=0.52) and a Scale-level Content Validity Index (S-CVI/Ave) of 0.98, confirming its effectiveness for clinical training.

Eun-Byul Cho, Jae-Chang Lee, Eun-Jung Kim, Hak-Jun Jo, Seon-Kyoung Kim, Yong-Taek Oh, Ji-Seong Hong, Son-Hwan Choi, Soo-Bo Shim. J Pharmacopuncture 2025;28:201-10. https://doi.org/10.3831/KPI.2025.28.3.201

Time-restricted eating (TRE), a dietary strategy that aligns food intake with circadian rhythms, has emerged as a promising non-pharmacological approach for improving glycemic control in patients with type 2 diabetes. This systematic review and meta-analysis evaluated the effects of TRE on glycemic outcomes by analyzing eight randomized controlled trials involving 312 participants with type 2 diabetes or impaired fasting glucose. Meta-analyses of six eligible studies demonstrated that TRE significantly reduced fasting glucose (mean difference [MD]: −0.74 mmol/L; 95% CI: −1.13 to −0.36) and glycated hemoglobin (ΔHbA1c) (MD: −0.11%; 95% CI: −0.15 to −0.07) and increased time in range (TIR) for blood glucose (MD: +10.51%; 95% CI: 6.81 to 14.21). Improvements in fasting glucose and HbA1c were modest but consistent, while the increase in TIR showed no between-study heterogeneity, suggesting a robust and reproducible benefit of TRE on glycemic stability. These findings support the clinical feasibility and effectiveness of TRE as a dietary intervention in diabetes management. However, further high-quality trials with standardized protocols and longer follow-up are needed to confirm long-term efficacy and inform guidelines.

Diabetes affects one in eleven adults globally, with rising cases in the past 30 years. Type 1 and type 2 cause blood sugar problems, increasing cardiovascular risks. Dietary control, including chickpeas, is suggested but needs more research. Comprehensive searches were conducted across multiple databases for the randomized controlled trial efficacy of chickpea consumption to lower blood sugar levels to a healthy range, with data extraction and risk of bias assessment performed independently by two researchers. Statistical analysis was performed using RevMan 5.4, expressing continuous data as mean differences and risk ratios with 95% confidence intervals, and a summary of the findings is provided considering the variations in study characteristics. A total of 118 articles were initially identified from seven databases, primarily from Anglo–American countries, resulting in 12 selected studies after the identification and screening processes. These studies involved 182 participants, focusing on healthy or normoglycemic adults, and assessed the effects of chickpeas compared to various foods such as wheat, potatoes, pasta, sauce, cheese, rice, and corn. A meta-analysis involving a subset of studies demonstrated that chickpeas were more effective in reducing blood glucose iAUC compared to potatoes and wheat. Chickpeas offer the potential for blood sugar control through low starch digestibility, high fiber, protein, and hormonal effects. Although insulin benefits are seen, statistical significance varies, supporting their role in diabetic diets focusing on nutrient-rich foods over processed carbs.

Junyeop Oh, Anna Kim, Jongran Lee, Yongtaek Oh. Korean J Acupunct 2022;39:117-25. https://doi.org/10.14406/acu.2022.018

Byung Wook Lee, Yong Taek Oh, Hansol Jang, Seong-Kyeong Choi, Hyo Rim Jo, Won-Suk Sung, Eun-Jung Kim. Korean J Acupunct 2021;38:282-9. https://doi.org/10.14406/acu.2021.029

Anna Kim, Sang-Hyun Kim, Yong-Taek Oh. J Pharmacopuncture 2021;24:138-41. https://doi.org/10.3831/KPI.2021.24.3.138

Much research on Korean medicine has been recently published in Korea. The aim of this study was to determine the research trends in Korean medicine by performing a comprehensive analysis of articles that have been published in Korea using temporal and network analysis methods. A total of 29,876 articles from 1963 to 2018 were prepared from OASIS (Oriental Medicine Advanced Searching Integrated System), the largest portal for Korean medicine. After the keywords and years were extracted from the metadata of the articles, an annual frequency matrix was obtained for the keywords. By using the matrix, the temporal trends of the keywords were analyzed by comparing the changes in similarity between the lists of keywords by year. Moreover, to analyze the relationship among research topics, a clustered network was constructed in which a node was a keyword and an edge was a similarity between two keywords. The temporal trend of the keywords was classified into six chronological phases. The appearance frequency of most keywords tended to increase gradually, but only the keywords “mibyeong,” “systems biology” and “korean medicine hospital” appeared in the most recent phase. The network of keywords was clustered and visualized into thirteen groups with the Gephi software. The main keywords in each group were related to effects such as “anti-inflammation” and “antioxidant,” to diseases such as “allergic rhinitis” and “diabetes” and to therapies such as “herbal acupuncture” and “herbal formula.” The analysis of the trends determined in this study provides a systematic understanding as well as future research directions in Korean medicine to researchers. In the future, an overall analysis of the research trends in Korean medicine will be done by analyzing articles published in Korea and other countries.