Objectives: In alignment with the World Health Organization’s goal of eliminating hepatitis C, this study assessed the current treatment status and reasons for non-treatment among patients with hepatitis C in Jeonbuk State, Republic of Korea, to inform strategies for improving care engagement. Methods: Among 311 individuals diagnosed with hepatitis C and reported through the NationalNotifiable Infectious Disease Surveillance system between January 2023 and June 2024, 208 patients were surveyed after excluding those who had died or could not be contacted.Statistical analyses included the chi-square test, the Cochran-Armitage test for trend, and logistic regression. Results: Overall, 116 participants (55.8%) reported having received antiviral therapy. Among the 92 untreated individuals, the most common reason for non-treatment was the absence of symptoms (n = 23; 25.0%), followed by the burden of drug costs (n = 21; 22.8%). Conclusion These findings highlight suboptimal treatment uptake and key barriers that may hinder progress toward hepatitis C elimination. Expanding screening and strengthening linkage-to-care strategies, while addressing financial barriers, will be essential to achievingnational elimination targets.

Purpose: Patient-derived cells (PDCs) and patient-derived organoids (PDOs) are complementary preclinical models widely used in translational cancer research. However, their molecular and functional differences have not been systematically characterized. This study established and analyzed paired PDC and PDO models derived from the same gastric cancer ascites to delineate platform-dependent molecular and functional profiles. Materials and Methods: Malignant ascites or pleural fluid obtained from 6 patients with advanced gastric cancer were used to establish paired PDC and PDO models. All pairs underwent comprehensive multi-omics profiling, integrating genomic, transcriptomic, and proteomic data. Phenotypic characterization included morphological, histological, proliferative, and cell cycle analyses. Drug sensitivity assays were performed using 4 chemotherapeutic agents commonly used to treat gastric cancer. Results: The 6 paired PDC and PDO models exhibited distinct morphological characteristics.Whole-genome analyses demonstrated high concordance among primary tumors, PDCs, and PDOs, confirming tumor representation across platforms. Multi-omics profiling identified platform-dependent molecular signatures; PDOs were enriched for extracellular matrix remodeling and stemness, whereas PDCs displayed proliferation- and immune-related signatures. Clinically relevant biomarkers, including HER2 and MET alterations, were concordant with primary tumors. Notably, drug responses differed between platforms and patients, indicating platform-dependent and patient-specific chemosensitivity. Conclusions Paired PDC and PDO models derived from the same patients preserved core patient-specific tumor characteristics while exhibiting distinct molecular and functional profiles. These findings underscore the culture platform as a critical determinant of experimental outcomes and therapeutic responses. Therefore, careful selection of an appropriate preclinical model is essential to accurately address biological questions and optimize precision oncology strategies.

Genetic variation in the leptin receptor (LEPR) gene has been implicated in metabolic regulation, while the gut microbiome and circulating metabolites are increasingly recognized as mediators of host metabolic phenotype. However, the systems-level interactions among LEPR genotypes, gut microbial composition, and serum metabolomic profiles remain poorly understood, particularly in healthy individuals. We conducted a cross-sectional study involving 37 healthy Korean adults. Three LEPR single nucleotide polymorphisms (rs1137101, rs1173100, rs790419) were genotyped. Untargeted metabolomics of fasting serum was performed using gas chromatography–time-of-flight mass spectrometry, and gut microbiome composition was profiled by 16S rRNA gene sequencing. Statistical analysis included principal component analysis, Mann–Whitney U tests, and Spearman correlations. Network analysis integrating microbiome, metabolomic, and clinical phenotype data was conducted using Cytoscape. A total of 54 serum metabolites were identified. LEPR genotypes, particularly rs1137101 and rs1173100, were associated with differences in metabolites such as pimelic acid, malonic acid, and 2,4-dihydroxybutyric acid. Firmicutes negatively correlated with saturated fatty acids and organic acids, whereas Actinobacteria positively correlated with cholesterol and amino acids. Network analysis revealed indole-3-acetate and cholesterol as central nodes linking microbial taxa with body mass index and leptin levels. However, no direct molecular pathways connecting leptin or its receptor were identified. LEPR genetic variation is associated with distinct serum metabolomic patterns and microbiome–host networks in healthy adults. Although no direct leptin signaling links were found, network-level associations suggest indirect genetic influences on metabolic states through microbiome–metabolome interactions.These findings advance understanding of personalized metabolic regulation and gene–microbiome interplay.

Autophagy is a conserved catabolic process that degrades proteins and damaged organelles to maintain cellular homeostasis, and its role in cancer depends on stage and context. Farnesyl-diphosphate farnesyltransferase 1 (FDFT1) is an essential enzyme in the sterol branch of the mevalonate pathway, but its functions in hepatocellular carcinoma (HCC) and in the regulation of autophagy remain poorly understood. In this study, we show that FDFT1 acts as a negative regulator of autophagy in HCC cells. Loss of FDFT1 led to increased autophagosome formation and fusion with lysosomes, whereas its overexpression suppressed both basal and induced autophagy. These changes were associated with AMPK–ULK1 signaling, suggesting that FDFT1 influences a central pathway controlling autophagy. Our findings connect cholesterol metabolism with autophagy regulation and tumor growth, highlighting FDFT1 as a potential prognostic marker and therapeutic target in liver cancer.

Purpose: The aim of this study is to compare the detection ability of quality of life (QoL) changes and responsiveness of the KOrean QUality of life in Stomach cancer patients Study group (KOQUSS)-40 and European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ). Materials and Methods: A multicenter prospective observational study was conducted to evaluate QoL changes after various gastrectomies between January 2021 and April 2022. Participants were instructed to complete the KOQUSS-40 and EORTC QLQ-C30/STO22 preoperatively and at 1, 3, 6, and 12 months postoperatively. QoL changes over time and QoL responsiveness were assessed for each questionnaire. Results: Data from 491 patients who underwent curative gastrectomy for gastric cancer at 22 institutions were analyzed. The summary scores of the KOQUSS-40 and EORTC QLQ-STO22 showed significant differences between the total and proximal gastrectomy groups (p=0.044 and p=0.038, respectively), but no difference was observed for the EORTC QLQ-C30. Dysphagia on the KOQUSS-40 was significantly different between the total and proximal gastrectomy groups (p=0.031); however, dysphagia on the EORTC QLQ-STO22 did not differ. The responsiveness of the KOQUSS-40 was similar to that of the EORTC QLQ in patients who experienced ≥ 10% body weight loss, but approximately 10% less in patients receiving adjuvant chemotherapy than the EORTC QLQ. Conclusion KOQUSS-40 has several advantages over EORTC QLQ-C30/STO22 when comparing QoL between the total and proximal gastrectomy groups. The findings provide information for researchers investigating the QoL of patients who have undergone curative gastrectomy for gastric cancer.

In patients with differentiated thyroid cancer (DTC), initial recurrence risk stratification based on clinical, histopathological, and perioperative data remains the key determinant for guiding management strategies during the first 1-2 years post-treatment. However, the adoption of ongoing risk stratification (ORS), which dynamically reassesses risk by integrating longitudinal clinical data and treatment response, enables more precise long-term prognostic assessment and facilitates highly individualized management. Building upon recent guidelines, the 2026 KTA guideline has been further refined by incorporating robust evidence from large-scale national cohorts and comprehensive systematic reviews. These updated recommendations outline contemporary concepts of ORS, risk-adapted TSH suppression targets, optimized surveillance modalities for recurrence detection, and disease-specific long-term follow-up strategies. Reflecting the paradigm shift toward de-escalated treatment, this revision integrates evolved perspectives on TSH suppression intensity, the clinical interpretation of thyroglobulin levels, and tailored follow-up intervals. These evidence-based recommendations aim to minimize unnecessary treatment and excessive surveillance in the large proportion of patients with excellent prognosis after initial therapy, while ensuring that each patient receives appropriately tailored and effective long-term management.

Background: There are limited long-term clinical outcome data comparing first-generation (1G) versus second-generation (2G) drug-eluting stents (DES) in patients with single-vessel disease (SVD). We sought to compare the efficacy and safety of 1G- and 2G-DES in SVD patients who underwent successful percutaneous coronary intervention (PCI) over 10 years of clinical follow-up. Methods: A total of 2,312 consecutive patients with SVD who underwent PCI with 1G-DES (paclitaxel- or sirolimus-eluting stents, n = 811) or 2G-DES (zotarolimus [Endeavor, Endeavor Resolute]- or everolimus-eluting stents [Promus Element, Xience], n = 1,082) were enrolled.After propensity score matching, 2 matched groups (538 pairs) were generated. Study endpoints included individual and composite clinical outcomes through 10 years. Results: During the 10-year follow-up, the 2G-DES group had lower incidences of myocardial infarction (MI; hazard ratio [HR], 0.44; 95% confidence interval [CI], 0.22–0.92; P = 0.028) and target lesion revascularization (TLR; HR, 0.54; 95% CI, 0.32–0.91; P = 0.021) than the 1G-DES group. Rates of total death, cardiac death, non-target vessel revascularization, stroke, major adverse cardiac events, and major adverse cardiac and cerebrovascular events were similar between groups. Conclusions In our single-center, all-comer registry, 2G-DES were associated with lower incidence rates of MI and TLR compared to 1G-DES in SVD patients over 10 years of followup, indicating a safer and more durable effect than 1G-DES.

Reference management software (RMS) represents a cornerstone of modern academic writing and publishing. For decades, programs such as EndNote, Zotero, and Mendeley have played central roles in facilitating citation organization, bibliography formatting, and collaborative scholarship. Although each platform has introduced unique innovations, persistent limitations remain, particularly with respect to usability, accessibility, and accuracy. In parallel, the rise of generative artificial intelligence has introduced an unprecedented challenge: the inadvertent inclusion of fabricated or incorrect references mistakenly incorporated into manuscripts. This phenomenon has exposed a critical limitation of traditional RMS platforms, namely their inability to verify reference authenticity. Against this backdrop, new solutions have emerged. One such example is CiteWell (https://citewell.org/), an artificial intelligence (AI)-era RMS that introduces several notable innovations, including PubMed-integrated verification, an intuitive interface for new users, customizable journal-specific styles, and multilingual accessibility. This review provides a comprehensive historical overview of RMS, evaluates the strengths and weaknesses of major platforms, and positions emerging AI-based tools as a new paradigm that combines traditional reference management with essential safeguards for contemporary academic challenges.

Background/Aims: Elevated troponin levels predict in-hospital mortality and influence decisions regarding thrombolytic therapy in patients with acute pulmonary embolism (PE). However, the usefulness of high-sensitivity troponin T (hsTnT) regarding PE remains uncertain. We aimed to establish the optimal cut-off level and compare its performance for precise risk stratification. Methods: 374 patients diagnosed with acute PE were reviewed. PE-related adverse outcomes, a composite of PE-related deaths, cardiopulmonary resuscitation incidents, systolic blood pressure < 90 mmHg, and all-cause mortality within 30 days were evaluated. The optimal hsTnT cut-off for all-cause mortality, and the net reclassification index (NRI) was used to assess the incremental value in risk stratification. Results: Among 343 normotensive patients, 17 (5.0%) experienced all-cause mortality, while 40 (10.7%) had PE-related adverse outcomes. An optimal hsTnT cut-off value of 60 ng/L for all-cause mortality (AUC 0.74, 95% CI 0.61–0.85, p < 0.001) was identified, which was significantly associated with PE-related adverse outcomes (OR 4.07, 95% CI 2.06–8.06, p < 0.001). Patients with hsTnT ≥ 60 ng/L were older, hypotensive, had higher creatinine levels, and right ventricular dysfunction signs. Combining hsTnT ≥ 60 ng/L with simplified pulmonary embolism severity index ≥1 provided additional prognostic information. Reclassification analysis showed a significant shift in risk categories, with an NRI of 1.016 ± 0.201 (p < 0.001). Conclusions We refined troponin’s predictive value in patients with acute PE, proposing a new cut-off value of hsTnT ≥ 60 ng/L. Validation through large-scale studies is essential to offer clinically useful guidance for managing patient population.