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/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.

BACKGROUND: Exosomes, nano-sized vesicles ranging between 30 and 150 nm secreted by human cells, play a pivotal role in long-range intercellular communication and have attracted significant attention in the field of regenerative medicine. Nevertheless, their limited productivity and cost-effectiveness pose challenges for clinical applications. These issues have recently been addressed by cell-derived nanovesicles (CDNs), which are physically synthesized exosome-mimetic nanovesicles from parent cells, as a promising alternative to exosomes. CDNs exhibit structural, physical, and biological properties similar to exosomes, containing intracellular protein and genetic components encapsulated by the cell plasma membrane. These characteristics allow CDNs to be used as regenerative medicine and therapeutics on their own, or as a drug delivery system. METHODS: The paper reviews diverse methods for CDN synthesis, current analysis techniques, and presents engineering strategies to improve lesion targeting efficiency and/or therapeutic efficacy. RESULTS: CDNs, with their properties similar to those of exosomes, offer a cost-effective and highly productive alternative due to their non-living biomaterial nature, nano-size, and readiness for use, allowing them to overcome several limitations of conventional cell therapy methods. CONCLUSION Ongoing research and enhancement of CDNs engineering, along with comprehensive safety assessments and stability analysis, exhibit vast potential to advance regenerative medicine by enabling the development of efficient therapeutic interventions.

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.

Background: Atopic dermatitis (AD) patients usually wonder if their condition will worsen after vaccination or if they should continue with the treatment they are receiving. Considering that many patients treated with dupilumab had previously experienced severe AD symptoms and flares, the concerns are more understandable. Objective: This study aimed to investigate the safety of the coronavirus disease 2019 (COVID-19) vaccination in patients with AD treated with dupilumab. Methods: We enrolled 133 patients (101 dupilumab-treated and 32 systemic oral agentstreated as control group) with AD from six hospitals. Patients were asked about worsening pruritus and AD (5-point Likert scale) after vaccination. AD variables (eczema area and severity index [EASI], investigator’s global assessment [IGA], itch numerical rating scale [NRS], sleep NRS, and patient-oriented eczema measure [POEM]) were compared pre- and postvaccination. Adverse reactions to the COVID-19 vaccination were observed. Results: The incidence of adverse reactions to COVID-19 vaccines and worsening AD symptoms in dupilumab-treated patients were not significantly different compared with that in the control group. The itch NRS score increased significantly after vaccination (p<0.001).However, there were no statistically significant differences between the pre-and post-EASI, IGA, and POEM scores. Eight patients (7.9%) had worse EASI scores and required rescue therapy; however, most were easily managed with low-dose steroids or topical agents. None of the patients discontinued dupilumab treatment. Conclusion No serious adverse reactions were observed in patients with AD after COVID-19 vaccination. Exacerbation of pruritus and AD symptoms was observed but was mostly mild and transient.