Background: Acute deterioration of patients in general wards often leads to major adverse events (MAEs), including unplanned intensive care unit transfers, cardiac arrest, or death. Traditional early warning scores (EWSs) have shown limited predictive accuracy, with frequent false positives. We conducted a prospective observational external validation study of an artificial intelligence (AI)-based EWS, the VitalCare - Major Adverse Event Score (VC-MAES), at a tertiary medical center in the Republic of Korea. Methods: Adult patients from general wards, including internal medicine (IM) and obstetrics and gynecology (OBGYN)—the latter were rarely investigated in prior AI-based EWS studies—were included. The VC-MAES predictions were compared with National Early Warning Score (NEWS) and Modified Early Warning Score (MEWS) predictions using the area under the receiver operating characteristic curve (AUROC), area under the precision-recall curve (AUPRC), and logistic regression for baseline EWS values. False-positives per true positive (FPpTP) were assessed based on the power threshold. Results: Of 6,039 encounters, 217 (3.6%) had MAEs (IM: 9.5%, OBGYN: 0.26%). Six hours prior to MAEs, the VC-MAES achieved an AUROC of 0.918 and an AUPRC of 0.352, including the OBGYN subgroup (AUROC, 0.964; AUPRC, 0.388), outperforming the NEWS (0.797 and 0.124) and MEWS (0.722 and 0.079). The FPpTP was reduced by up to 71%. Baseline VC-MAES was strongly associated with MAEs (P<0.001). Conclusions The VC-MAES significantly outperformed traditional EWSs in predicting adverse events in general ward patients. The robust performance and lower FPpTP suggest that broader adoption of the VC-MAES may improve clinical efficiency and resource allocation in general wards.

Background: Ensuring reference material (RM) commutability is crucial for evaluating measurement traceability in order to standardize laboratory tests. However, commutability assessment is not routinely performed. We assessed whether RMs prepared following CLSI C37-A guidelines could be used without assessing commutability by evaluating their commutability for four lipid measurements using the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) and CLSI EP14 protocols. Methods: We analyzed total cholesterol (TC), triglycerides (TGs), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) in frozen sera from 20 individuals and 11 RMs, prepared by the Korea Disease Control and Prevention AgencyLaboratory Standardization Project (per CLSI C37-A), using six routine measurement procedures (MPs). Regression equations and 95% prediction intervals derived from single-donor sera were analyzed following CLSI EP14. The IFCC protocol was used to assess differences in inter-MP biases between RM and clinical samples. The effect of the TG concentration on commutability was evaluated by analyzing biases between MP results and reference procedure-assigned values. Results: RMs were commutable for most MP pairs for TC and TG. Commutability for HDL-C and LDL-C varied across RMs, with RM10 and RM11 showing higher TG levels (2.38 and 2.95 mmol/L, respectively) and lower commutability. Increased bias percentages from assigned values were observed for RMs with higher TG levels. Conclusions RMs prepared per CLSI C37-A were commutable with most MP pairs for TC and TG. Elevated TG levels affected HDL-C and LDL-C commutability, highlighting the need to consider TG concentrations during RM preparation and assess commutability to standardize laboratory tests.

Background: School food service workers are highly likely to develop heat-related illnesses because of their work environment. However, studies that have examined the risk of heat-related illnesses among them are limited. The purpose of this study was to investigate the status of heat exposure, implementation of heat wave countermeasures, and prevalence of heat-related illness symptoms among school food service workers in Korea, and to explore the relationship between them. Methods: A cross-sectional study was conducted through an online survey of school food service workers from May 25 to June 12, 2023, via three labor unions. We analyzed 6,244 valid responses. We assessed general characteristics, heat-related illness symptoms (heat rash, heat cramps, heat edema, heat exhaustion, heat syncope), duration of heat exposure during heat waves, and heat wave preventive measures. Multiple logistic regression analyses were performed, with adjustments for age, occupation, hypertension, diabetes, and school type. Results: More than one-third of school food service workers reported heat exposure between May and September exceeding 4 hours daily, and 94.6% experienced at least one heat-related illness symptom during the last year. A dose-response relationship was observed between heat exposure duration and heat-related illness symptoms (p for trend < 0.001). School food service workers who did not have increased rest periods or did not reduce high-heat prepared foods showed significantly higher odds ratios for heat-related illness symptoms. Conclusions School food service workers experience substantial heat exposure and a high prevalence of heat-related illness symptoms. The risk of heat-related illness symptoms was associated with extended duration of heat exposure. Increasing rest periods and reducing high-heat food preparation were effective preventive measures. These findings underscore the need for improved heat exposure management and implementation of effective preventive measures to protect the health of school food service workers, with particular attention to appropriate rest periods.

Background: The aim of this study is to evaluate the prevalence and associated psychosocial factors of behavioral addictions among school adolescents living in the Gwangju and Jeonnam regions in Korea. Methods: A self-reported survey was conducted from December 4, 2023, to January 31, 2024, including 855 middle and high school students residing in the Gwangju-Jeonnam regions. Aside from the information on demographic characteristics, data on depression, anxiety, Internet gaming addiction, gambling problems, and resilience was obtained. Results: The prevalence of Internet gaming addiction among adolescents was 5.4%, while the prevalence of gambling problems was 3.3%. The male adolescents had a significantly higher risk of behavioral addiction compared with the female adolescents. The logistic regression analysis revealed that male and depression were significant risk factors for Internet gaming addiction. For gambling problems, male was identified as a significant risk factor. Conclusion The findings of this study suggested that the prevalence of behavioral addiction among school adolescents has been relatively higher than that of previous studies, emphasizing the need for community-based prevention and intervention strategies tailored to the sex difference and psychological factors associated with adolescent behavioral addictions.

Purpose: 11C-Methionine PET/CT is a promising method for detecting parathyroid lesions in patients with primary hyperparathyroidism (PHPT). We aimed to determine the diagnostic ability and correlation of digital 11C-Methionine PET/CT for parathyroid lesions in patients with PHPT, particularly in cases where standard imaging methods yielded inconclusive results. Methods: This retrospective analysis was conducted on patients diagnosed with PHPT who underwent digital 11C-Methionine PET/CT imaging because of ambiguous results on standard imaging work-up ( 99m Tc-MIBI parathyroid scan and/or neck ultrasonography). Quantitative 11C-Methionine PET/CT parameters, including maximum standardized uptake value (SUVmax), mean SUV (SUVmean), peak SUV (SUVpeak), parathyroid methionine volume (PMV), and whole methionine uptake(WMU: PMV multiplied by SUVmean) were calculated with various thresholds, and their correlations with biochemical andpathologic parameters were investigated. Results: This study included 22 consecutive patients (10 men and 12 women) with a median age of 64.0 years. The lesion detection rate and sensitivity of digital 11C-Methionine PET/CT were 81.8% (18/22) and 100.0% (18/18), respectively.Quantitative analysis revealed that serum PTH (r = 0.490, P = 0.039) and serum calcium (r = 0.583, P = 0.011) were signifi-cantly correlated with PMV50%. Conclusion Digital 11C-Methionine PET/CT offers good performance in the detection of parathyroid lesions in PHPT patients with inconclusive standard imaging work-up. The volume parameter of PMV50% significantly correlated biochemi-cal parameters and can serve as a complementary diagnostic tool.

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.

Synthetic data, generated using advanced artificial intelligence (AI) techniques, replicates the statistical properties of real-world datasets while excluding identifiable information.Although synthetic data does not consist of actual data points, it is derived from original datasets, thereby enabling analyses that yield results comparable to those obtained with real data. Synthetic datasets are evaluated based on their utility—a measure of how effectively they mirror real data for analytical purposes. This paper presents the generation of synthetic datasets through the Healthcare Big Data Showcase Project (2019–2023). The original dataset comprises comprehensive multi-omics data from 400 individuals, including cancer survivors, chronic disease patients, and healthy participants. Synthetic data facilitates efficient access and robust analyses, serving as a practical tool for research and education. It addresses privacy concerns, supports AI research, and provides a foundation for innovative applications across diverse fields, such as public health and precision medicine.

This study explores the development, roles, and key initiatives of the Regional Environmental Health Centers in Korea, detailing their evolution through four distinct phases and their impact on environmental health policy and local governance. It chronicles the establishment and transformation of these centers from their inception in May 2007, through four developmental stages. Originally named Environmental Disease Research Centers, they were subsequently renamed Environmental Health Centers following legislative changes. The analysis includes the expansion in the number of centers, the transfer of responsibilities to local governments, and the launch of significant projects such as the Korean Children’s Environmental Health Study (Ko-CHENS ). During the initial phase (May 2007–February 2009), the 10 centers concentrated on research-driven activities, shifting from a media-centered to a receptor-centered approach. In the second phase, prompted by the enactment of the Environmental Health Act, six additional centers were established, broadening their scope to address national environmental health issues. The third phase introduced Ko-CHENS, a 20-year national cohort project designed to influence environmental health policy by integrating research findings into policy frameworks. The fourth phase marked a decentralization of authority, empowering local governments and redefining the centers' roles to focus on regional environmental health challenges. The Regional Environmental Health Centers have significantly evolved and now play a crucial role in addressing local environmental health issues and supporting local government policies. Their capacity to adapt and respond to region-specific challenges is essential for the effective implementation of environmental health policies, reflecting geographical, socioeconomic, and demographic differences.