高神大学

The rapid growth of the secondary battery industry for electric vehicles has introduced underexplored occupational hazards. This study investigated the characteristics and causes of skin disorders among workers in lithium production and battery recycling facilities to identify preventive measures. In 2024, walkthrough surveys and health interviews were conducted with 127 male workers at two newly established plants selected based on visible symptoms or involvement in high-risk processes. Skin lesions were reported by 38.8% of workers in the lithium production plant, mainly chemical burns caused by lithium hydroxide dust reacting with sweat to form a strong alkali, with the wrist being the most frequently affected site. In the recycling plant, 35.0% experienced skin lesions, predominantly contact dermatitis associated with exposure to metal dusts and acids. These findings indicate substantial risks of chemical burns and contact dermatitis, highlighting the need for improved protective equipment, ventilation, and safety management in this expanding industry.

While much is known about the identity and regulation of cytokine-producing cells, the cell types that respond to cytokines remain largely uncharacterized. To address this knowledge gap, we developed “cytokine cellular locating platforms” (CyCLoPs), a reporter system that translates cytokine receptor engagement into a genetically traceable signal. In vitro, CyCLoPs demonstrated high specificity, robust signal-to-background ratios, and broad applicability for probing diverse cytokine receptor interactions. In vivo, interleukin (IL)-17A-CyCLoPs reporter mice enabled the identification of IL-17A-responsive intestinal epithelial cells predominantly localized in the ileal villi following commensal bacterial colonization. Interferon-gamma (IFN-γ)-CyCLoPs reporter mice allowed for the detection of IFN-γ-exposed CD8+ T cells within tumors, which expressed CD36, CD38, and leptin receptor and displayed gene signatures associated with reduced effector function. Collectively, CyCLoPs offers a platform for the direct visualization and characterization of cytokine-induced cellular responses and provides a tool for investigating how cytokines orchestrate distinct immunological outcomes in health and disease.

OBJECTIVES:This study aimed to identify high-risk factors for type 2 diabetes and develop a machine learning (ML)-based diabetes prediction model using nursing notes from home health care. DESIGN:Retrospective cohort study. SAMPLE:A total 7896 medical records from 1747 patients aged ≥ 20 years who received home health care at a university hospital in South Korea over 10 years. MEASUREMENTS:The patient's sociodemographic characteristics, diagnosis codes, and clinical history as well as narrative nursing notes detailing nursing assessments and descriptions of the patient's condition were recorded. Logistic regression was used to identify risk factors, and five machine learning models were constructed using 10-fold cross-validation. RESULTS:Female sex, depression, hypertension, hyperlipidemia, nursing services such as dressing and nutritional care, and dysuria were identified as prediabetes-related symptoms extracted from nursing notes using natural language processing (NLP). The Random Forest model demonstrated the highest predictive performance (AUC = 0.985). CONCLUSIONS:Nursing documentation is a valuable resource for early diabetes risk screening. High predictive performance was achieved by integrating structured and unstructured data, prediabetes-related symptoms extracted from nursing notes. This approach enhances nurses' ability to deliver timely, personalized interventions and improve preventive care outcomes, with significant benefits for patients receiving home care who require continuous support.

Objectives: This study investigated the sequential mediating roles of protein intake and handgrip strength (HGS) in the association between socioeconomic status (SES) and 10-year atherosclerotic cardiovascular disease (ASCVD) risk within the social determinants of health (SDOH) framework. Methods: We conducted a complex survey analysis using data from 6281 adults without baseline ASCVD from the Korea National Health and Nutrition Examination Survey (2016-2018), accounting for stratification, clustering, and weighting. The 10-year ASCVD risk was estimated using the pooled cohort risk equations. SES was classified into three groups based on educational attainment and household income. Relative HGS was calculated as the sum of maximal grip strength in both hands divided by body mass index. Indirect effects were assessed using bootstrap-based confidence intervals (CIs). Results: Compared with the low-SES group, the high-SES group showed a lower 10-year ASCVD risk in both the total effect model (B = -1.630, 95% CI: -2.250 to -1.010) and the direct effect model (B = -1.550, 95% CI: -2.170 to -0.927). The total indirect effect was also significant in both the high-versus-low and middle-versus-low SES comparisons. Protein intake and relative HGS partially mediated the association between SES and 10-year ASCVD risk, and the sequential mediation pathway was also significant. Conclusions: Within the SDOH framework, these findings suggest that nutritional and muscle-strength-related pathways may link socioeconomic disadvantage to ASCVD risk and support integrated interventions targeting nutritional support and muscle-strength improvement for life-course prevention.

Abstract Background: The MELD 3.0 policy, implemented by UNOS on July 13, 2023, updated the liver allocation scoring system to better reflect 90-day mortality risk. While intended to improve transplant equity, questions remain about its impact on socioeconomic disparities. We examined how MELD 3.0 affected DDLT access across socioeconomic groups and whether it narrowed or widened existing disparities. Methods: We analyzed 12,479 adult HCC patients in the 21-month periods before (n=6,154) and after (n=6,325) MELD 3.0 implementation using UNOS data. Competing risks analysis with Aalen-Johansen estimators assessed DDLT rates accounting for death/deterioration. Gray's test evaluated socioeconomic disparities in DDLT access by race/ethnicity, insurance, education, employment, citizenship, gender, and region. Era-specific censoring used listing date as time origin. Results: MELD 3.0 implementation significantly improved DDLT rates at 12 months: 53.3% pre-policy vs. 62.2% post-policy (+8.9 percentage points, p<0.001). Socioeconomic disparities showed mixed patterns. Race/ethnicity disparities persisted and slightly widened: Asian patients improved from 49.0% to 54.7%, while White patients increased from 55.1% to 64.3%. Black patients rose from 55.1% to 59.5%, and Hispanic patients from 46.1% to 64.8%, with differences remaining significant (pre p<0.001, post p<0.001). Education disparities remained minimal: less than college vs. college graduates had similar rates pre-policy (53.0% vs. 53.2%) and post-policy (62.5% vs. 62.1%), with significance reflecting sample size rather than meaningful differences (p<0.001 both eras). Insurance disparities showed mixed results: private insurance maintained advantage over public insurance, though significance weakened (p=0.015 pre, p=0.043 post). Citizenship disparities showed a slight reduction in absolute difference (US vs. non-US: 53.4% vs. 51.0% pre; 62.3% vs. 60.7% post), while statistical significance strengthened (p=0.047 pre, p=0.010 post). Employment and regional disparities persisted: post-policy, employed patients had slightly higher access, and substantial regional variation continued (p<0.001 both eras). Gender differences remained non-significant. Conclusions: MELD 3.0 improved overall DDLT access for HCC patients but had varied effects on socioeconomic disparities. Education disparities remained minimal, while race/ethnicity, insurance, employment, citizenship, and regional differences continued. Although MELD 3.0 enhanced transplant access, persistent disparities highlight the need for additional interventions targeting socioeconomic determinants beyond allocation score refinements. Citation Format: Tehyun Phillip Eom, Junho Song, Hyungjune Ku, Sungsu Park, Minkwan Kim, Sunghan Kim, Sangsoo Lee, Heekyoo Kim, Seoyeong Ku, Hyewon Kim, Amy Choi, Changmin Jo. MELD 3.0 policy and evolving socioeconomic disparities in liver transplantation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 2361.