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.

Background: Postoperative liver regeneration is essential for maintaining hepatic function. This study evaluated the rate, determinants, and volumetric patterns of early liver regeneration after hemihepatectomy. Methods: A retrospective review was conducted of 50 patients who underwent right or left hemihepatectomy between April 2019 and March 2025. Liver and spleen volumes (SV) were assessed preoperatively, at postoperative day (POD) 1 week, and at POD 3 months. Early liver regeneration rate (LRR) was defined as the percentage increase in remnant liver volume at POD 1 week relative to the preoperative future liver remnant (FLR), and patients were categorized into low (<50%) and high (≥50%) LRR groups. Clinical, biochemical, and volumetric variables were compared, and predictors of regeneration were identified using multivariable analyses. Regeneration patterns were also examined according to whether the FLR/standard liver volume (SLV) ratio was <50% or ≥50%. Results: FLR/SLV was the strongest independent predictor of rapid early liver regeneration (p<0.001). Remnants with FLR/SLV <50% exhibited rapid and sustained regeneration, whereas those with FLR/SLV ≥50% showed slower regrowth that plateaued after reaching approximately 90% of SLV. SV increased at POD 1 week in all patients; however, only the FLR/SLV ≥50% group showed a reduction by POD 3 months, whereas the <50% group maintained elevated volumes. Conclusions FLR/SLV reliably predicts early postoperative liver regeneration. Smaller remnants regenerate more rapidly, whereas persistent splenic enlargement suggests a sustained portal hemodynamic burden. Combined evaluation of FLR/SLV and SV may enhance perioperative risk assessment and surgical planning.

Purpose: Accurate identification of the bile duct bifurcation site is crucial in pure laparoscopic donor right hepatectomy (PLDRH) for living donor liver transplantation. This study aimed to develop and evaluate a deep learning model to predict the bile duct bifurcation site for surgical precision. Methods: We retrospectively analyzed 55 PLDRH procedures conducted between August 2021 and April 2022. A deep learning model combining UNet with a MiT-B3 encoder was trained on 150 manually annotated frames. We then incorporated expert-reviewed pseudo-labels from an additional 901 frames to refine the model. Performance was evaluated using 5-fold cross-validation and an independent test set. Results: Clinical evaluation showed a 97% accuracy in 5-fold cross-validation and 93.3% accuracy in the independent test set. From the initial to final model, dice similarity coefficient improved from 0.392 to 0.472, intersection over union from 0.279 to 0.339, and sensitivity from 0.487 to 0.643, while specificity remained consistent at 0.993. Conclusion The proposed artificial intelligence (AI) model demonstrated strong clinical performance in predicting the bile duct bifurcation site during PLDRH. Despite modest quantitative scores, the high clinical accuracy highlights the potential of integrating AI for precise donor hepatectomy.

Tuberculosis survivors often face long-term physical, psychological, and social challenges that extend beyond microbiological cure. Post-tuberculosis complications include pulmonary damage, cardiovascular and neurological sequelae, as well as significant impacts on overall wellbeing and livelihoods. Despite increasing awareness, most care continues to focus primarily on lung disease, overlooking the multisystem and social needs of survivors. A holistic, people-centered framework that integrates medical, rehabilitative, and community-based strategies is essential for restoring health and facilitating societal participation among tuberculosis survivors.

Background: Tacrolimus is a key immunosuppressant after liver transplantation.Although guideline-recommended trough levels are 4–10 ng/mL, concerns about nephrotoxicity, metabolic complications, and malignancies have led to interest in minimizing tacrolimus use. However, the effects of lower tacrolimus levels on graft rejection and hepatocellular carcinoma (HCC) recurrence remain unclear. Methods: We conducted a single-center, retrospective study of adult patients (≥19 years) who underwent living donor liver transplantation between January 2000 and December 2021. Patients were divided into low tacrolimus (FK) (<6 ng/mL) and high FK (≥6 ng/mL) groups based on tacrolimus levels measured 1–2 years post-transplantation. We analyzed overall survival, biopsy-proven rejection-free survival, and HCC recurrence-free survival in relevant subgroups. Cox proportional hazards regression identified predictors of mortality, rejection, and HCC recurrence. Results: Among 1,117 recipients, 941 were in the low FK group and 176 in the high FK group. Landmark analysis showed significantly better 10-year overall survival in the low FK group (82.8% vs. 68.8%, p=0.016), while rejection-free survival did not differ significantly beyond 2 years (p=0.098), despite early separation favoring the low FK group (p<0.001). Higher tacrolimus levels independently predicted increased mortality (hazard ratio [HR]=1.98, 95% confidence interval [CI] 1.35–2.89; p<0.001) and rejection (HR=2.20, 95% CI 1.48–3.27; p<0.001). Among 614 HCC patients, landmark analysis revealed no significant difference in recurrence-free survival (77.7% vs. 81.2%, p=0.288) or overall survival (77.3% vs. 65.8%, p=0.215), and FK levels were not independently associated with either outcome. Conclusion Maintaining tacrolimus levels below 6 ng/mL was associated with better survival and rejection outcomes without increasing HCC recurrence, suggesting dose minimization may be feasible in selected patients.

Background: The increasing incidence and mortality rates of tuberculosis among older individuals who suffer from multiple morbidities and are vulnerable to malnutrition are major obstacles to efforts to eradicate tuberculosis in the Republic of Korea. Herein, we identified the factors associated with mortality during anti-tuberculosis treatment in patients with pulmonary tuberculosis. Methods: We conducted a case-control study and extracted data from the database of a multi-center prospective observational cohort study in Korea. Among the participants with rifampicin-susceptible pulmonary tuberculosis, the survival group was defined as those who successfully completed treatment within one year, whereas the mortality group was defined as those who died during treatment. Univariable and multivariable logistic regression analyses were performed to identify factors associated with TB mortality. Results: Among 1,119 participants with pulmonary TB registered between 2019 and 2021, 799 and 59 were grouped in the survival and mortality groups, respectively. Age, positive smear results, alarming symptoms, nutrition risk score, Charlson comorbidity index score, and initial standard treatment regimen were significant based on univariable analysis and were selected for the multivariable logistic regression model. Nutrition risk score (adjusted odds ratio, 2.44; 95% confidence interval, 1.72–3.48) and Charlson comorbidity index score (adjusted odds ratio, 1.62; 95% confidence interval, 1.35–1.94) remained statistically significant in the multivariate analysis. Conclusion Nutritional status and comorbidities at baseline were identified as important factors associated with mortality in patients with pulmonary tuberculosis.

Background: The increasing incidence and mortality rates of tuberculosis among older individuals who suffer from multiple morbidities and are vulnerable to malnutrition are major obstacles to efforts to eradicate tuberculosis in the Republic of Korea. Herein, we identified the factors associated with mortality during anti-tuberculosis treatment in patients with pulmonary tuberculosis. Methods: We conducted a case-control study and extracted data from the database of a multi-center prospective observational cohort study in Korea. Among the participants with rifampicin-susceptible pulmonary tuberculosis, the survival group was defined as those who successfully completed treatment within one year, whereas the mortality group was defined as those who died during treatment. Univariable and multivariable logistic regression analyses were performed to identify factors associated with TB mortality. Results: Among 1,119 participants with pulmonary TB registered between 2019 and 2021, 799 and 59 were grouped in the survival and mortality groups, respectively. Age, positive smear results, alarming symptoms, nutrition risk score, Charlson comorbidity index score, and initial standard treatment regimen were significant based on univariable analysis and were selected for the multivariable logistic regression model. Nutrition risk score (adjusted odds ratio, 2.44; 95% confidence interval, 1.72–3.48) and Charlson comorbidity index score (adjusted odds ratio, 1.62; 95% confidence interval, 1.35–1.94) remained statistically significant in the multivariate analysis. Conclusion Nutritional status and comorbidities at baseline were identified as important factors associated with mortality in patients with pulmonary tuberculosis.

Background: s/Aims: While large-for-size syndrome is uncommon in liver transplantation (LT), it can result in fatal outcome. To prevent such fatality, we manufactured 3D-printed intra-abdominal cavity replicas to provide intuitive understanding of the sizes of the graft and the patient’s abdomen in patients with small body size between July 2020 and February 2022. Methods: Clinical outcomes were compared between patients using our 3D model during LT, and patients who underwent LT without 3D model by using 1 : 5 ratio propensity score-matched analysis. Results: After matching, a total of 20 patients using 3D-printed abdominal cavity model and 100 patients of the control group were included in this study. There were no significant differences in 30-day postoperative complication (50.0% vs. 64.0%, p = 0.356) and the incidence of large-for-size syndrome (0% vs. 7%, p = 0.599). Overall survival of the 3D-printed group was similar to that of the control group (p = 0.665), but graft survival was significantly superior in the 3D-printed group, compared to the control group (p = 0.034). Conclusions Since it showed better graft survival, as well as low cost and short production time, our 3D-printing protocol can be a feasible option for patients with small abdominal cavity to prevent large-for-size syndrome after LT.

Recent advancements in tuberculosis treatment research emphasize innovative strategies that enhance treatment efficacy, reduce adverse effects, and adhere to patient-centered care principles. As tuberculosis remains a significant global health challenge, integrating new and repurposed drugs presents promising avenues for more effective management, particularly against drug-resistant strains. Recently, the spectrum concept in tuberculosis infection and disease has emerged, underscoring the need for research aimed at developing treatment plans specific to each stage of the disease. The application of precision medicine to tailor treatments to individual patient profiles is crucial for addressing the diverse and complex nature of tuberculosis infections. Such personalized approaches are essential for optimizing therapeutic outcomes and improving patient adherence—both of which are vital for global tuberculosis eradication efforts. The role of tuberculosis cohort studies is also emphasized, as they provide critical data to support the development of these tailored treatment plans and deepen our understanding of disease progression and treatment response. To advance these innovations, a robust tuberculosis policy framework is required to foster the integration of research findings into practice, ensuring that treatment innovations are effectively translated into improved health outcomes worldwide.