Background/Aims: This study aimed to evaluate the performance of the Model for End-Stage Liver Disease (MELD) 3.0 for predicting mortality and liver-related complications compared with the Child-Pugh classification, albumin-bilirubin (ALBI) grade, the MELD, and the MELD sodium (MELDNa) score. Methods: We evaluated a multicenter retrospective cohort of incorporated patients with cirrhosis between 2013 and 2019. We conducted comparisons of the area under the receiver operating characteristic curve (AUROC) of the MELD3.0 and other models for predicting 3-month mortality. Additionally, we assessed the risk of cirrhosis-related complications according to the MELD3.0 score. Results: A total of 3,314 patients were included. The mean age was 55.9±11.3 years, and 70.2% of the patients were male. Within the initial 3 months, 220 patients (6.6%) died, and the MELD3.0had the best predictive performance among the tested models, with an AUROC of 0.851, outperforming the Child-Pugh classification, ALBI grade, MELD, and MELDNa. A high MELD3.0score was associated with an increased risk of mortality. Compared with that of the group with a MELD3.0 score <10 points, the adjusted hazard ratio of the group with a score of 10–20 pointswas 2.176, and that for the group with a score of ≥20 points was 4.892. Each 1-point increase inthe MELD3.0 score increased the risk of cirrhosis-related complications by 1.033-fold. The risk of hepatorenal syndrome showed the highest increase, with an adjusted hazard ratio of 1.149, followed by hepatic encephalopathy and ascites. Conclusions The MELD3.0 demonstrated robust prognostic performance in predicting mortality in patients with cirrhosis. Moreover, the MELD3.0 score was linked to cirrhosis-related complications, particularly those involving kidney function, such as hepatorenal syndrome and ascites.

Background/Aims: Hepatocellular carcinoma (HCC) exhibits significant sex disparities in incidence, yet its molecular mechanisms remain unclear. We explored the role of telomerase reverse transcriptase (TERT) genetic alterations and hepatitis B virus (HBV) integration, both known major contributors to HCC, in sex-specific risk for HBV-related HCC. Methods: We examined 310 HBV-related HCC tissues to investigate sex-specific TERT promoter (TERT-pro) mutations and HBV integration profiles, stratified by sex and age, and validated with single-cell RNA sequencing (scRNA-seq) data. Results: Tumors predominantly exhibited TERT-pro mutations (26.0% vs. 0%) and HBV-TERT integration (37.0% vs. 3.0%) compared to non-tumorous tissues. While TERT-pro mutations increased with age in both sexes, younger males (≤60 years) showed marked predominance compared to younger females. Males had significantly more HBV integrations at younger ages, while females initially had fewer integrations that gradually increased with age. Younger males' integrations showed significantly greater enrichment in the TERT locus compared to younger females, alongside a preference for promoters, PreS/S regions, and CpG islands. Overall, TERT genetic alterations were significantly sex-differential in younger individuals (75.3% in males vs. 23.1% in females) but not in older individuals (76.9% vs. 83.3%, respectively). These alterations were associated with increased TERT expression. The skewed TERT abnormalities in younger males were further corroborated by independent scRNA-seq data. Conclusions Our findings highlight the critical role of TERT alterations and HBV integration patterns in the male predominance of HCC incidence among younger HBV carriers, offering insights for future exploration to optimize sex-specific patient care and HCC surveillance strategies.

Background/Aims: This study aimed to evaluate the performance of the Model for End-Stage Liver Disease (MELD) 3.0 for predicting mortality and liver-related complications compared with the Child-Pugh classification, albumin-bilirubin (ALBI) grade, the MELD, and the MELD sodium (MELDNa) score. Methods: We evaluated a multicenter retrospective cohort of incorporated patients with cirrhosis between 2013 and 2019. We conducted comparisons of the area under the receiver operating characteristic curve (AUROC) of the MELD3.0 and other models for predicting 3-month mortality. Additionally, we assessed the risk of cirrhosis-related complications according to the MELD3.0 score. Results: A total of 3,314 patients were included. The mean age was 55.9±11.3 years, and 70.2% of the patients were male. Within the initial 3 months, 220 patients (6.6%) died, and the MELD3.0had the best predictive performance among the tested models, with an AUROC of 0.851, outperforming the Child-Pugh classification, ALBI grade, MELD, and MELDNa. A high MELD3.0score was associated with an increased risk of mortality. Compared with that of the group with a MELD3.0 score <10 points, the adjusted hazard ratio of the group with a score of 10–20 pointswas 2.176, and that for the group with a score of ≥20 points was 4.892. Each 1-point increase inthe MELD3.0 score increased the risk of cirrhosis-related complications by 1.033-fold. The risk of hepatorenal syndrome showed the highest increase, with an adjusted hazard ratio of 1.149, followed by hepatic encephalopathy and ascites. Conclusions The MELD3.0 demonstrated robust prognostic performance in predicting mortality in patients with cirrhosis. Moreover, the MELD3.0 score was linked to cirrhosis-related complications, particularly those involving kidney function, such as hepatorenal syndrome and ascites.

Background/Aims: Hepatocellular carcinoma (HCC) exhibits significant sex disparities in incidence, yet its molecular mechanisms remain unclear. We explored the role of telomerase reverse transcriptase (TERT) genetic alterations and hepatitis B virus (HBV) integration, both known major contributors to HCC, in sex-specific risk for HBV-related HCC. Methods: We examined 310 HBV-related HCC tissues to investigate sex-specific TERT promoter (TERT-pro) mutations and HBV integration profiles, stratified by sex and age, and validated with single-cell RNA sequencing (scRNA-seq) data. Results: Tumors predominantly exhibited TERT-pro mutations (26.0% vs. 0%) and HBV-TERT integration (37.0% vs. 3.0%) compared to non-tumorous tissues. While TERT-pro mutations increased with age in both sexes, younger males (≤60 years) showed marked predominance compared to younger females. Males had significantly more HBV integrations at younger ages, while females initially had fewer integrations that gradually increased with age. Younger males' integrations showed significantly greater enrichment in the TERT locus compared to younger females, alongside a preference for promoters, PreS/S regions, and CpG islands. Overall, TERT genetic alterations were significantly sex-differential in younger individuals (75.3% in males vs. 23.1% in females) but not in older individuals (76.9% vs. 83.3%, respectively). These alterations were associated with increased TERT expression. The skewed TERT abnormalities in younger males were further corroborated by independent scRNA-seq data. Conclusions Our findings highlight the critical role of TERT alterations and HBV integration patterns in the male predominance of HCC incidence among younger HBV carriers, offering insights for future exploration to optimize sex-specific patient care and HCC surveillance strategies.

Background/Aims: This study aimed to evaluate the performance of the Model for End-Stage Liver Disease (MELD) 3.0 for predicting mortality and liver-related complications compared with the Child-Pugh classification, albumin-bilirubin (ALBI) grade, the MELD, and the MELD sodium (MELDNa) score. Methods: We evaluated a multicenter retrospective cohort of incorporated patients with cirrhosis between 2013 and 2019. We conducted comparisons of the area under the receiver operating characteristic curve (AUROC) of the MELD3.0 and other models for predicting 3-month mortality. Additionally, we assessed the risk of cirrhosis-related complications according to the MELD3.0 score. Results: A total of 3,314 patients were included. The mean age was 55.9±11.3 years, and 70.2% of the patients were male. Within the initial 3 months, 220 patients (6.6%) died, and the MELD3.0had the best predictive performance among the tested models, with an AUROC of 0.851, outperforming the Child-Pugh classification, ALBI grade, MELD, and MELDNa. A high MELD3.0score was associated with an increased risk of mortality. Compared with that of the group with a MELD3.0 score <10 points, the adjusted hazard ratio of the group with a score of 10–20 pointswas 2.176, and that for the group with a score of ≥20 points was 4.892. Each 1-point increase inthe MELD3.0 score increased the risk of cirrhosis-related complications by 1.033-fold. The risk of hepatorenal syndrome showed the highest increase, with an adjusted hazard ratio of 1.149, followed by hepatic encephalopathy and ascites. Conclusions The MELD3.0 demonstrated robust prognostic performance in predicting mortality in patients with cirrhosis. Moreover, the MELD3.0 score was linked to cirrhosis-related complications, particularly those involving kidney function, such as hepatorenal syndrome and ascites.

Background/Aims: Hepatocellular carcinoma (HCC) exhibits significant sex disparities in incidence, yet its molecular mechanisms remain unclear. We explored the role of telomerase reverse transcriptase (TERT) genetic alterations and hepatitis B virus (HBV) integration, both known major contributors to HCC, in sex-specific risk for HBV-related HCC. Methods: We examined 310 HBV-related HCC tissues to investigate sex-specific TERT promoter (TERT-pro) mutations and HBV integration profiles, stratified by sex and age, and validated with single-cell RNA sequencing (scRNA-seq) data. Results: Tumors predominantly exhibited TERT-pro mutations (26.0% vs. 0%) and HBV-TERT integration (37.0% vs. 3.0%) compared to non-tumorous tissues. While TERT-pro mutations increased with age in both sexes, younger males (≤60 years) showed marked predominance compared to younger females. Males had significantly more HBV integrations at younger ages, while females initially had fewer integrations that gradually increased with age. Younger males' integrations showed significantly greater enrichment in the TERT locus compared to younger females, alongside a preference for promoters, PreS/S regions, and CpG islands. Overall, TERT genetic alterations were significantly sex-differential in younger individuals (75.3% in males vs. 23.1% in females) but not in older individuals (76.9% vs. 83.3%, respectively). These alterations were associated with increased TERT expression. The skewed TERT abnormalities in younger males were further corroborated by independent scRNA-seq data. Conclusions Our findings highlight the critical role of TERT alterations and HBV integration patterns in the male predominance of HCC incidence among younger HBV carriers, offering insights for future exploration to optimize sex-specific patient care and HCC surveillance strategies.

Background/Aims: This study aimed to evaluate the performance of the Model for End-Stage Liver Disease (MELD) 3.0 for predicting mortality and liver-related complications compared with the Child-Pugh classification, albumin-bilirubin (ALBI) grade, the MELD, and the MELD sodium (MELDNa) score. Methods: We evaluated a multicenter retrospective cohort of incorporated patients with cirrhosis between 2013 and 2019. We conducted comparisons of the area under the receiver operating characteristic curve (AUROC) of the MELD3.0 and other models for predicting 3-month mortality. Additionally, we assessed the risk of cirrhosis-related complications according to the MELD3.0 score. Results: A total of 3,314 patients were included. The mean age was 55.9±11.3 years, and 70.2% of the patients were male. Within the initial 3 months, 220 patients (6.6%) died, and the MELD3.0had the best predictive performance among the tested models, with an AUROC of 0.851, outperforming the Child-Pugh classification, ALBI grade, MELD, and MELDNa. A high MELD3.0score was associated with an increased risk of mortality. Compared with that of the group with a MELD3.0 score <10 points, the adjusted hazard ratio of the group with a score of 10–20 pointswas 2.176, and that for the group with a score of ≥20 points was 4.892. Each 1-point increase inthe MELD3.0 score increased the risk of cirrhosis-related complications by 1.033-fold. The risk of hepatorenal syndrome showed the highest increase, with an adjusted hazard ratio of 1.149, followed by hepatic encephalopathy and ascites. Conclusions The MELD3.0 demonstrated robust prognostic performance in predicting mortality in patients with cirrhosis. Moreover, the MELD3.0 score was linked to cirrhosis-related complications, particularly those involving kidney function, such as hepatorenal syndrome and ascites.

Objective: To evaluate the effects of Catalpa bignonioides fruit extract on the promotion of muscle growth and muscular capacity in vitro and in vivo. Methods: Cell viability was measured using the 3-(4,5-dimethylthiazol- 2-yl)-2,5-diphenyltetrazolium bromide assay. Cell proliferation was assessed using a 5-bromo-2’-deoxyuridine (BrdU) assay kit. Western blot analysis was performed to determine the protein expressions of related factors. The effects of Catalpa bignonioides extract were investigated in mice using the treadmill exhaustion test and whole-limb grip strength assay. Chemical composition analysis was performed using high-performance liquid chromatography (HPLC). Results: Catalpa bignonioides extract increased the proliferation of C2C12 mouse myoblasts by activating the Akt/mTOR signaling pathway. It also induced metabolic changes, increasing the number of mitochondria and glucose metabolism by phosphorylating adenosine monophosphate-activated protein kinase. In an in vivo study, the extract-treated mice showed improved motor abilities, such as muscular endurance and grip strength. Additionally, HPLC analysis showed that vanillic acid may be the main component of the Catalpa bignonioides extract that enhanced muscle strength. Conclusions: Catalpa bignonioides improves exercise performance through regulation of growth and metabolism in skeletal muscles, suggesting its potential as an effective natural agent for improving muscular strength.

Purpose: Unnecessary prostate biopsies for detecting prostate cancer (PCa) should be minimized. Therefore, this study developed a machine learning (ML) model to predict PCa in Korean men and evaluated its usability. Materials and Methods: We retrospectively analyzed clinical data from 928 patients who underwent prostate biopsies at Kangwon National University Hospital between May 2013 and May 2023. Of these, 377 (41.6%) were diagnosed with PCa, and 551 (59.4%) did not have cancer. For external validation, clinical data from 385 patients aged 48–89 years who underwent prostate biopsies from September 2005 to September 2023 at Wonju Severance Christian Hospital were also included. Twenty-two clinical features were used to develop an ML model to predict PCa. Features were selected based on their contributions to model performance, leading to the inclusion of 15 features. A meta-learner was constructed using logistic regression to predict the probability of PCa, and the classifier was trained and validated on randomly extracted training and test sets at an 8:2 ratio. Results: The prostate health index, prostate volume, age, nodule on digital rectal examination, and prostate-specific antigen were the top 5 features for predicting PCa. The area under the receiver operating characteristic curve (AUC) of the meta-learner logistic regression model was 0.89, and the accuracy, sensitivity, and specificity were 0.828, 0.711, and 0.909, respectively. Our model also showed excellent prediction performance for high-grade PCa, with a Gleason score of 7 or higher and an AUC of 0.903. Furthermore, we evaluated the performance of the model using external cohort clinical data and achieved an AUC of 0.863. Conclusions Our ML model excelled in predicting PCa, specifically clinically significant PCa. Although extensive cross-validation in other clinical cohorts is needed, this ML model is a promising option for future diagnostics.

Purpose: Unnecessary prostate biopsies for detecting prostate cancer (PCa) should be minimized. Therefore, this study developed a machine learning (ML) model to predict PCa in Korean men and evaluated its usability. Materials and Methods: We retrospectively analyzed clinical data from 928 patients who underwent prostate biopsies at Kangwon National University Hospital between May 2013 and May 2023. Of these, 377 (41.6%) were diagnosed with PCa, and 551 (59.4%) did not have cancer. For external validation, clinical data from 385 patients aged 48–89 years who underwent prostate biopsies from September 2005 to September 2023 at Wonju Severance Christian Hospital were also included. Twenty-two clinical features were used to develop an ML model to predict PCa. Features were selected based on their contributions to model performance, leading to the inclusion of 15 features. A meta-learner was constructed using logistic regression to predict the probability of PCa, and the classifier was trained and validated on randomly extracted training and test sets at an 8:2 ratio. Results: The prostate health index, prostate volume, age, nodule on digital rectal examination, and prostate-specific antigen were the top 5 features for predicting PCa. The area under the receiver operating characteristic curve (AUC) of the meta-learner logistic regression model was 0.89, and the accuracy, sensitivity, and specificity were 0.828, 0.711, and 0.909, respectively. Our model also showed excellent prediction performance for high-grade PCa, with a Gleason score of 7 or higher and an AUC of 0.903. Furthermore, we evaluated the performance of the model using external cohort clinical data and achieved an AUC of 0.863. Conclusions Our ML model excelled in predicting PCa, specifically clinically significant PCa. Although extensive cross-validation in other clinical cohorts is needed, this ML model is a promising option for future diagnostics.