This study compared key health indicators of poor, older urban adults attending a free clinic with those of the general older population, using data from the 2023 Korea National Health and Nutrition Examination Survey (KNHANES). Methods: This cross-sectional comparative study included 60 adults aged ≥60 years who attended the Raphael Nanum Homeless Clinic in Seoul. Participants completed a questionnaire, underwent anthropometric assessment, and provided fasting blood samples for measurement of total cholesterol, low density lipoprotein (LDL)-cholesterol, and triglycerides (TG). Obesity, current smoking, monthly alcohol use, poor self-rated health, and strength exercise (≥ 2 days/week) were defined according to 2023 KNHANES criteria and compared with age-matched 2023 KNHANES estimates for adults aged ≥ 60 years using independent t-tests and two-proportion z-tests. Results: Participants were predominantly men (80.0%) with a mean age of 79.9 years; 70.0% reported no regular income, and 46.7% rated their health as poor. Compared with their 2023 KNHANES counterparts, the clinic group had a higher prevalence of obesity (50.0% vs. 35.0%), particularly among men, and a more atherogenic lipid profile characterized by higher LDL-cholesterol despite similar total cholesterol levels and lower TG. The prevalence of current smoking (3.3% vs. 10.6%) and monthly alcohol use (31.7% vs. 53.0%) was significantly lower, whereas participation in strength exercise was low in both groups, with no significant differences observed. Conclusion: Poor, older urban adults exhibited multidimensional health disparities, including obesity, adverse lipid profiles, and markedly poorer self-rated health, despite lower levels of smoking and alcohol consumption. Community-based interventions targeting nutrition, physical activity, and chronic disease management are needed to reduce health inequalities in this vulnerable population.

Objectives: This study aimed to explore factors influencing satisfaction with medical services among medically underserved populations at the free medical clinic, providing data to improve free medical services for these populations. Methods: We employed a descriptive correlational study design involving 112 individuals (aged 19 years and older) from medically underserved populations who visited the clinic. Data were collected through face-to-face surveys from September to October 2023, and statistical analyses (t-tests, analysis of variance, Pearson correlation, and hierarchical multiple regression) were used to identify key predictors of satisfaction. Results: Perceived support from healthcare providers emerged as the strongest predictor ofsatisfaction with medical services, demonstrating a significant positive association. While socialsupport was positively correlated with perceived support from healthcare providers, it did not independently predict satisfaction. Conclusion These findings underscore the importance of healthcare provider and social supportin increasing satisfaction with medical services among medically underserved populations.Developing tailored healthcare programs and specialized healthcare provider training are essential strategies to improve healthcare access and outcomes for these vulnerable groups.

Objectives: This study aimed to explore factors influencing satisfaction with medical services among medically underserved populations at the free medical clinic, providing data to improve free medical services for these populations. Methods: We employed a descriptive correlational study design involving 112 individuals (aged 19 years and older) from medically underserved populations who visited the clinic. Data were collected through face-to-face surveys from September to October 2023, and statistical analyses (t-tests, analysis of variance, Pearson correlation, and hierarchical multiple regression) were used to identify key predictors of satisfaction. Results: Perceived support from healthcare providers emerged as the strongest predictor ofsatisfaction with medical services, demonstrating a significant positive association. While socialsupport was positively correlated with perceived support from healthcare providers, it did not independently predict satisfaction. Conclusion These findings underscore the importance of healthcare provider and social supportin increasing satisfaction with medical services among medically underserved populations.Developing tailored healthcare programs and specialized healthcare provider training are essential strategies to improve healthcare access and outcomes for these vulnerable groups.

Objectives: This study aimed to explore factors influencing satisfaction with medical services among medically underserved populations at the free medical clinic, providing data to improve free medical services for these populations. Methods: We employed a descriptive correlational study design involving 112 individuals (aged 19 years and older) from medically underserved populations who visited the clinic. Data were collected through face-to-face surveys from September to October 2023, and statistical analyses (t-tests, analysis of variance, Pearson correlation, and hierarchical multiple regression) were used to identify key predictors of satisfaction. Results: Perceived support from healthcare providers emerged as the strongest predictor ofsatisfaction with medical services, demonstrating a significant positive association. While socialsupport was positively correlated with perceived support from healthcare providers, it did not independently predict satisfaction. Conclusion These findings underscore the importance of healthcare provider and social supportin increasing satisfaction with medical services among medically underserved populations.Developing tailored healthcare programs and specialized healthcare provider training are essential strategies to improve healthcare access and outcomes for these vulnerable groups.

Objectives: This study aimed to explore factors influencing satisfaction with medical services among medically underserved populations at the free medical clinic, providing data to improve free medical services for these populations. Methods: We employed a descriptive correlational study design involving 112 individuals (aged 19 years and older) from medically underserved populations who visited the clinic. Data were collected through face-to-face surveys from September to October 2023, and statistical analyses (t-tests, analysis of variance, Pearson correlation, and hierarchical multiple regression) were used to identify key predictors of satisfaction. Results: Perceived support from healthcare providers emerged as the strongest predictor ofsatisfaction with medical services, demonstrating a significant positive association. While socialsupport was positively correlated with perceived support from healthcare providers, it did not independently predict satisfaction. Conclusion These findings underscore the importance of healthcare provider and social supportin increasing satisfaction with medical services among medically underserved populations.Developing tailored healthcare programs and specialized healthcare provider training are essential strategies to improve healthcare access and outcomes for these vulnerable groups.

Objectives: This study aimed to explore factors influencing satisfaction with medical services among medically underserved populations at the free medical clinic, providing data to improve free medical services for these populations. Methods: We employed a descriptive correlational study design involving 112 individuals (aged 19 years and older) from medically underserved populations who visited the clinic. Data were collected through face-to-face surveys from September to October 2023, and statistical analyses (t-tests, analysis of variance, Pearson correlation, and hierarchical multiple regression) were used to identify key predictors of satisfaction. Results: Perceived support from healthcare providers emerged as the strongest predictor ofsatisfaction with medical services, demonstrating a significant positive association. While socialsupport was positively correlated with perceived support from healthcare providers, it did not independently predict satisfaction. Conclusion These findings underscore the importance of healthcare provider and social supportin increasing satisfaction with medical services among medically underserved populations.Developing tailored healthcare programs and specialized healthcare provider training are essential strategies to improve healthcare access and outcomes for these vulnerable groups.

Background: Primary cutaneous CD30+ lymphoproliferative disorders (pcCD30-LPDs) are a diseases with various clinical and prognostic characteristics. Objective: Increasing our knowledge of the clinical characteristics of pcCD30-LPDs and identifying potential prognostic variables in an Asian population. Methods: Clinicopathological features and survival data of pcCD30-LPD cases obtained from 22 hospitals in South Korea were examined. Results: A total of 413 cases of pcCD30-LPDs (lymphomatoid papulosis [LYP], n=237; primary cutaneous anaplastic large cell lymphoma [C-ALCL], n=176) were included. Ninety percent of LYP patients and roughly 50% of C-ALCL patients presented with multiple skin lesions. Both LYP and C-ALCL affected the lower limbs most frequently. Multiplicity and advanced T stage of LYP lesions were associated with a chronic course longer than 6 months. Clinical morphology with patch lesions and elevated serum lactate dehydrogenase were significantly associated with LPDs during follow-up in LYP patients. Extracutaneous involvement of C-ALCL occurred in 13.2% of patients. Lesions larger than 5 cm and increased serum lactate dehydrogenase were associated with a poor prognosis in C-ALCL. The survival of patients with C-ALCL was unaffected by the anatomical locations of skin lesions or other pathological factors. Conclusion The multiplicity or size of skin lesions was associated with a chronic course of LYP and survival among patients with C-ALCL.

Objective: Primary frozen shoulder causes significant pain and progressively restricts shoulder movements. Diagnosis is made clinically based on patient history and physical examination. Management is mainly non-invasive owing to its self-limiting clinical course. However, clinical practice guidelines for frozen shoulder have not yet been developed in Korea. The developed guidelines aim to provide evidence-based recommendations for the diagnosis and treatment of frozen shoulder. Methods: A guideline development committee reviewed the literature from four databases (PubMed, Embase, Cochrane Library, and KMbase). Using the Population, Intervention, Comparator, and Outcome (PICO) framework, the committee formulated two backgrounds and 16 key questions to address common clinical concerns. Recommendations were made using the Grading of Recommendations, Assessment, Development, and Evaluation framework. Results: Diabetes, thyroid disease, and dyslipidemia significantly increase the risk of developing a frozen shoulder. Although frozen shoulder is often self-limiting, some patients may experience long-term functional disabilities. Ultrasound and magnetic resonance imaging should be used as adjunctive tools alongside clinical diagnosis, and rather than as independent diagnostic methods. Noninvasive approaches, such as medications, physical modalities, exercises, electrical stimulation, and manual therapy, may reduce pain and improve shoulder function. Other noninvasive interventions have limited evidence, and their application should be based on clinical judgment. Intra-articular steroid injections are recommended for treatment, and physiotherapy or hydrodilation with steroid injections can also be beneficial. Conclusion These guidelines provide evidence-based recommendations for diagnosing and treating primary frozen shoulder.

Background/Aims: Metabolic dysfunction-associated steatotic liver disease (MASLD) is characterized by fat accumulation in the liver. MASLD encompasses both steatosis and MASH. Since MASH can lead to cirrhosis and liver cancer, steatosis and MASH must be distinguished during patient treatment. Here, we investigate the genomes, epigenomes, and transcriptomes of MASLD patients to identify signature gene set for more accurate tracking of MASLD progression. Methods: Biopsy-tissue and blood samples from patients with 134 MASLD, comprising 60 steatosis and 74 MASH patients were performed omics analysis. SVM learning algorithm were used to calculate most predictive features. Linear regression was applied to find signature gene set that distinguish the stage of MASLD and to validate their application into independent cohort of MASLD. Results: After performing WGS, WES, WGBS, and total RNA-seq on 134 biopsy samples from confirmed MASLD patients, we provided 1,955 MASLD-associated features, out of 3,176 somatic variant callings, 58 DMRs, and 1,393 DEGs that track MASLD progression. Then, we used a SVM learning algorithm to analyze the data and select the most predictive features. Using linear regression, we identified a signature gene set capable of differentiating the various stages of MASLD and verified it in different independent cohorts of MASLD and a liver cancer cohort. Conclusions We identified a signature gene set (i.e., CAPG, HYAL3, WIPI1, TREM2, SPP1, and RNASE6) with strong potential as a panel of diagnostic genes of MASLD-associated disease.

Patients with non-small-cell lung cancer (NSCLC) with epidermal growth factor receptor (EGFR) amplification or sensitive muta-tions initially respond to the tyrosine kinase inhibitor gefitinib, however, the treatment becomes less effective over time by resis-tance mechanism including mesenchymal-epithelial transition (MET) overexpression. A therapeutic strategy targeting MET and EGFR may be a means to overcoming resistance to gefitinib. In the present study, we found that picropodophyllotoxin (PPT), derived from the roots of Podophyllum hexandrum, inhibited both EGFR and MET in NSCLC cells. The antitumor efficacy of PPT in gefitinib-resistant NSCLC cells (HCC827GR), was confirmed by suppression of cell proliferation and anchorage-independent colony growth. In the targeting of EGFR and MET, PPT bound with EGFR and MET, ex vivo, and blocked both kinases activity. The binding sites between PPT and EGFR or MET in the computational docking model were predicted at Gly772/Met769 and Arg1086/Tyr1230 of each ATP-binding pocket, respectively. PPT treatment of HCC827GR cells increased the number of annexin V-positive and subG1 cells. PPT also caused G2/M cell-cycle arrest together with related protein regulation. The inhibition of EGFR and MET by PPT treatment led to decreases in the phosphorylation of the downstream-proteins, AKT and ERK. In addition, PPT induced reactive oxygen species (ROS) production and GRP78, CHOP, DR5, and DR4 expression, mitochondrial dysfunc-tion, and regulated involving signal-proteins. Taken together, PPT alleviated gefitinib-resistant NSCLC cell growth and induced apoptosis by reducing EGFR and MET activity. Therefore, our results suggest that PPT can be a promising therapeutic agent for gefitinib-resistant NSCLC.