Background: A systematic evaluation of potential living liver donors is essential to ensure donor safety and optimize recipient outcomes in living donor liver transplantation (LDLT). This study aimed to assess donor acceptance rates and reasons for disqualification among individuals evaluated for LDLT at a high-volume transplant center over a one-year period. Methods: We retrospectively reviewed 1,087 potential living liver donors who presented for LDLT evaluation in 2023. Of these, 991 candidates advanced beyond the initial screening (Stage 1) and underwent comprehensive clinical, imaging, and pathological assessments (Stages 2 and 3). Candidates who discontinued after Stage 1 were excluded due to the absence of documented reasons for non-progression. Results: Among the 991 candidates who proceeded beyond initial screening, 473 (47.7%) completed the full donor evaluation, of whom 466 were judged to be suitable donors. Among suitable donors, 384 (82.4%) proceeded to donor hepatectomy, whereas 82 did not, primarily due to recipient-related factors such as clinical deterioration or withdrawal of consent. Donor ineligibility was determined in 422 candidates (42.6%), most commonly due to inadequate remnant liver volume (52.8%), hepatic steatosis (20.6%), and insufficient graft size (10.2%). Among candidates undergoing Stage 2 evaluation, 162 (16.3%) failed to meet steatosis criteria; 126 were excluded solely for steatosis and advised weight reduction, and 39 subsequently became eligible and successfully donated. Conclusion In this high-volume LDLT center, donor disqualification was primarily driven by remnant liver volume and hepatic steatosis. Targeted interventions such as weight reduction enabled successful donation in a subset of initially ineligible candidates, underscoring the importance of individualized donor evaluation and pre-donation optimization.

Purpose: This study was performed to predict individualized treatment strategies in ruptured abdominal aortic aneurysm (rAAA) by estimating the survival benefit of endovascular aneurysm repair (EVAR) and open surgical repair (OSR) based on anatomical and physiological features using a causal inference model. Methods: This retrospective study included 45 patients with de novo rAAA who underwent EVAR or OSR between 2012 and 2024. Thirty-three variables were analyzed. The model estimated individualized treatment effects (ITE) for 30-day survival.Model interpretability was assessed using Shapley Additive Explanations (SHAP) analysis. Five-fold cross-validation, receiver operating characteristic (ROC) analysis, and calibration plots were used for model evaluation. A clinical decision tree was developed to derive simplified decision rules. Results: The mean ITE was 0.22 ± 0.42, with 33% of patients classified as OSR-benefit candidates. SHAP analysis revealed that suprarenal angle, infrarenal angle, iliac anatomy, and proximal neck characteristics strongly influenced treatment effects. However, some predictors, such as low hemoglobin and systolic blood pressure favoring OSR, conflicted with clinical intuition. ROC analysis showed an area under the curve of 1.00, but calibration suggested overfitting due to a small sample size. Treatment-matched patients had a higher 30-day mortality rate than mismatched patients, suggesting potential bias or unmeasured confounding. The decision tree identified clinically relevant features but displayed structural inconsistencies and impractical cutoff values due to the limited sample size. Conclusion The X-learner model demonstrated the feasibility of individualized treatment prediction in rAAA but suffered from overfitting and limited generalizability. Validation with larger multicenter cohorts is necessary to confirm clinical applicability.

Metabolic dysfunction-associated steatotic liver disease (MASLD) has emerged as a global health issue due to its increasing prevalence associated with lifestyle changes and its strong correlation with metabolic syndrome. Farnesoid X receptor (FXR) is a nuclear receptor that plays a pivotal role in regulating bile acid, lipid, and glucose metabolism, making it an attractive therapeutic target for liver and metabolic diseases. In this study, we investigated the effects of MHY5456, a synthetic agonist of FXR, on hepatic metabolism and fibrosis. MHY5456 enhanced the transcriptional activity of FXR in a concentration-dependent manner.Treatment of AC2F rat liver-derived cells with MHY5456 resulted in the downregulation of genes involved in lipid accumulation and an upregulation of mitochondrial-related gene expression. Additionally, MHY5456 significantly reduced oleic acid (OA)-induced lipid accumulation. To assess its anti-fibrotic potential, we tested its effects on transforming growth factor-beta (TGF-β)-induced fibrosis in LX2 human hepatic stellate cells (HSCs). MHY5456 significantly suppressed the expression of fibrosis-related genes and proteins. In vivo, administration of MHY5456 to mice fed a methionine-choline-deficient (MCD) diet alleviated hepatic fibrosis, inflammation, and lipid accumulation. These results show that FXR activation by MHY5456 modulates lipid metabolism and fibrotic pathways, suggesting its potential as a pharmacological candidate for liver and metabolic disorders, including MASLD. Further pharmacological and toxicological studies are needed to confirm its therapeutic relevance.

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: Circulating tumor DNA (ctDNA) profiling from peripheral blood allows relatively noninvasive monitoring of solid tumors; however, its utility post-surgery or chemotherapy in colorectal cancer remains underexplored. We evaluated the clinical implications of a ctDNA next-generation sequencing (NGS) panel post-surgery or chemotherapy in patients with colorectal cancer. Methods: We collected samples from 23 patients with colorectal cancer (17 men, median age 65 yrs) at baseline and post-surgery or chemotherapy at the National Cancer Center, Korea, between January 2021 and September 2023. ctDNA was analyzed using an NGS panel including 46 genes, and variant allele frequencies (VAFs) were determined. Followup samples were analyzed using the NGS panel or droplet digital PCR (ddPCR) when probes were available. Clinical status was compared with ctDNA results, and survival was analyzed using a time-dependent Cox model. Results: Mutations were identified in 13 out of 14 patients (92.8%) with stage II/III cancer and in all nine patients (100%) with stage IV cancer. Mutations were detected in KRAS (N = 15, 65%), APC (N = 8, 35%), TP53 (N = 7, 30%), PIK3CA (N = 5, 22%), and RET (N = 4, 17%). A 1% increase in KRAS and TP53 VAFs was associated with 48% and 32% increased mortality risk, respectively. Changes in VAF correlated well with clinical findings. Conclusions The detection of and an increase in KRAS and TP53 VAFs were associated with poor prognosis. ddPCR-based ctDNA monitoring results were comparable to those obtained with the NGS panel. ctDNA monitoring during treatment is clinically informative in managing colorectal cancer.

Peyronie’s disease is an acquired condition characterized by penile deformities caused by fibrosis of the penile tunica albuginea, leading to symptoms such as penile pain, erectile dysfunction, and other associated issues. Despite extensive research, the pathophysiology of this condition remains poorly understood, and standardized diagnostic and treatment protocols are lacking. While clinical guidelines from several professional societies exist, they do not consistently account for factors such as patient ethnicity, geography, and socioeconomic status. Thus, the Korean Society for Sexual Medicine and Andrology (KSSMA) aimed to develop recommendations tailored to clinical practice in Korea. These recommendations summarize the latest evidence, including clinical practice guidelines from various international professional societies, and represent the consensus opinion of an expert group within the KSSMA. They encompass all aspects of Peyronie’s disease, including the definition, diagnosis, non-surgical interventions, and surgical treatment options.

Background: The 16S rRNA-targeted next-generation sequencing (NGS) has been widely used as the primary tool for microbiome analysis. However, whether the sequenced microbial diversity absolutely represents the original sample composition remains unclear. This study aimed to evaluate whether 16S rRNA gene-targeted NGS accurately captures bacterial community composition. Methods: Mock communities were constructed using equal amounts of DNA from 18 bacterial strains in three formats: genomic DNA, recombinant plasmids, and polymerase chain reaction (PCR) templates. The V3V4 region of the 16S rRNA gene was amplified and sequenced using the Illumina MiSeq. Results: Data regression analysis revealed that the recombinant plasmid produced more accurate and precise correlation curve than that by the gDNA and PCR products, with a slope closest to 1 (1.0082) and the highest R² value (0.9975). Despite the same input amount of bacterial DNA, the NGS read distribution varied across all three mock communities. Using multiple regression analysis, we found that the guanine-cytosine (GC) content of the V3V4 region, 16S rRNA gene, size of gDNA, and copy number of 16S rRNA were significantly associated with the NGS output of each bacterial species. Conclusion This study demonstrated that recombinant plasmids are the preferred option for quality control and that NGS output is biased owing to certain bacterial characteristics, such as %GC content, gDNA size, and 16S rRNA gene copy number. Further research is required to develop a system that compensates for NGS process biases using mock communities.

Background: The 16S rRNA-targeted next-generation sequencing (NGS) has been widely used as the primary tool for microbiome analysis. However, whether the sequenced microbial diversity absolutely represents the original sample composition remains unclear. This study aimed to evaluate whether 16S rRNA gene-targeted NGS accurately captures bacterial community composition. Methods: Mock communities were constructed using equal amounts of DNA from 18 bacterial strains in three formats: genomic DNA, recombinant plasmids, and polymerase chain reaction (PCR) templates. The V3V4 region of the 16S rRNA gene was amplified and sequenced using the Illumina MiSeq. Results: Data regression analysis revealed that the recombinant plasmid produced more accurate and precise correlation curve than that by the gDNA and PCR products, with a slope closest to 1 (1.0082) and the highest R² value (0.9975). Despite the same input amount of bacterial DNA, the NGS read distribution varied across all three mock communities. Using multiple regression analysis, we found that the guanine-cytosine (GC) content of the V3V4 region, 16S rRNA gene, size of gDNA, and copy number of 16S rRNA were significantly associated with the NGS output of each bacterial species. Conclusion This study demonstrated that recombinant plasmids are the preferred option for quality control and that NGS output is biased owing to certain bacterial characteristics, such as %GC content, gDNA size, and 16S rRNA gene copy number. Further research is required to develop a system that compensates for NGS process biases using mock communities.

Background: Gout is a type of inflammatory arthritis caused by monosodium urate crystal deposits, and the prevalence of this condition has been increasing. This study aimed to determine the combined effects of genetic risk factors and lifestyle habits on gout, using data from a Korean cohort study. Identifying high-risk individuals in advance can help prevent gout and its associated disorders. Methods: We analyzed data from the Korean Genome and Epidemiology Study-Urban Health Examinees cohort (KoGES-HEXA). Genetic information of the participants was collected at baseline, and gout cases were identified based on patient statements. The polygenic risk score (PRS) was calculated using nine independent genome-wide association study datasets, and lifestyle factors and metabolic syndrome status were measured for each participant using the KoGES. Logistic regression models were used to estimate the odds ratios (ORs) for gout in relation to genetic risk, lifestyle habits, and metabolic health status, after adjusting for age and sex. Results: Among 44,605 participants, 617 were diagnosed with gout. Gout was associated with older age, higher body mass index, and higher prevalence of hypertension, diabetes, and hypertriglyceridemia. High PRS, unfavorable lifestyle habits, and poor metabolic profiles were significantly associated with an increased risk of gout. Compared with that in the low-genetic-risk and healthy lifestyle group or ideal metabolic profile group, the risk of gout was increased in the high-genetic-risk plus unfavorable lifestyle (OR, 3.64; 95% confidence interval [CI], 2.32–6.03) or poor metabolic profile (OR, 7.78; 95% CI, 4.61–13.40) group.Conversely, adherence to favorable lifestyle habits significantly reduced gout risk, especially in high-genetic-risk groups. Conclusion Genetic predisposition and unhealthy lifestyle habits significantly increase the risk of gout. Promoting healthy lifestyle habits is crucial to prevent the development of gout, particularly in individuals with high genetic susceptibility.