Background: Despite the dominance of the Model for End-Stage Liver Disease (MELD) in liver transplantation (LTx) prognosis, its ability to predict early post-transplant survival remains debated. Furthermore, the current critical donor shortage has expanded the use of extended criteria donor (ECD) grafts, which still lack effective prognostic models. To address this, we developed an innovative series of albumin-bilirubin (ALBI)-based multivariable models (MVMs) for predicting perioperative mortality and identifying super high-risk patients. Methods: Among a total of 2,040 recipients included from multicenter, 1,310 recipients were enrolled in the training cohort to develop an MVM for predicting perioperative mortality using logistic regression. Model performance was assessed by receiver operating characteristic (ROC) curve, with the risk threshold defined by decision curve analysis (DCA). External validation was performed in a cohort of 730 patients. For subgroup analyses, the model's discriminatory power, quantified by the area under the ROC curve (AUC), was compared with that of the MELD score. Results: We developed and externally validated two ALBI-based models (ALBI-MVM and ALBI-MVM plus). The ALBI-MVM showed higher predictive power (AUCs: 0.736 and 0.714), identifying a very high-risk group (45.5% mortality; P<0.001) from the ALBI-defined medium/high-risk population. With added variables, performance improved sequentially (AUCs: 0.792 and 0.704), and the ALBI-MVM plus further isolated a super high-risk group (73.3% mortality; P<0.001). Notably, across ECD subgroups-including small-for-size, elderly, and ABO-incompatible (ABOi) grafts-both models showed significantly superior predictive performance over the MELD score. Conclusions: This large multicenter study established and validated ALBI-based MVMs that effectively predicted perioperative mortality and identified super high-risk patients. Especially in major ECD transplantation types, it demonstrated superior predictive performance over traditional systems.

Despite recent progresses in microbiome and infection, the role of multi-kingdom gut microbiome in kidney transplantation (KT) infection remains unexplored. Here we performed a longitudinal and integrative multi-omics analysis of the gut microbiome, fecal metabolome and plasma metabolome in 169 KT recipients across 5 different transplantation centers, comprising discovery and validation cohorts. We observed KT-specific four kingdom microbiome dysbiosis, including bacteria, fungi, archaea and viruses, with the most pronounced shifts in bacterial and fungal communities. Furthermore, we identified 6 infection-associated co-abundance groups (CAGs) composed of 23 bacterial and 3 fungal species, highlighting extensive bacterial-fungal interactions. Interestingly, infection-associated fecal metabolomic pattern F1, enriched in N-acetylputrescine and hydroxyproline, was positively correlated with Enterococcus-, Citrobacter- and Lactococcus-dominated CAGs, as well as the plasma metabolite signature, represented by phenylacetyl-l-glutamine, indoxyl sulfate and leukotriene. In contrast, cholesterol sulfate and menadione in plasma were aligned with fecal indoleacetic acid and stachyose, a metabolic signature more characteristic of non-infected recipients. Finally, the combinatorial biomarkers of fungal and bacterial species achieved powerful diagnosis ability of KT infection in an independent validation cohort (area under the receiver operating characteristic curve (AUROC) = 0.80) with the fecal metabolites achieving high accuracy (AUROC = 0.83). Collectively, our findings not only uncovered the postoperative infection-specific multi-kingdom microbial network dynamics, but also revealed the microbial and its metabolic biomarkers with powerful diagnostic ability for postoperative infection in kidney transplantation.

The liver executes essential metabolic functions including energy homeostasis, lipid biosynthesis, cholesterol regulation and xenobiotic detoxification. While hepatocyte metabolic activity forms the foundation of these processes, their precise regulation is achieved through chromatin remodelling mechanisms, with the SWI/SNF complex emerging as a central epigenetic orchestrator. Accumulating evidence positions this ATP-dependent chromatin remodeler as a critical regulator of hepatic development, homeostatic maintenance and pathological transformation. Through nucleosome repositioning and histone-DNA interaction modulation, the SWI/SNF complex governs transcriptional programs controlling cellular proliferation, differentiation and metabolic adaptation. This review synthesises current understanding of SWI/SNF-mediated epigenetic regulation in hepatic biology and explores its therapeutic potential for liver disorders.

Rapid and accurate assessment of senescence in aging marginal donor livers is critically important for liver transplantation, yet remains analytically challenging in clinical practice. Herein, we report CyC, a liver-targeted triple-modal molecular probe that integrates naked-eye colorimetric sensing with near-infrared fluorescence/photoacoustic (NIRF/PA) imaging for rapid evaluation of hepatic senescence. Upon activation by senescence-associated beta-galactosidase (beta-Gal), CyC produces a turn-on NIRF/PA response accompanied by a distinct blue-to-green color change visible to the naked eye. The probe exhibits high sensitivity and specificity for beta-Gal, efficient liver enrichment, and strong signal contrast in senescent cells and aged mouse liver tissues. When applied to small fragments of clinical human liver samples via simple ex vivo immersion, CyC readily detects beta-Gal activity. This platform integrates molecular imaging with visual sensing, offering a practical tool for rapid senescence assessment in aging marginal donor liver evaluation. By enabling immediate, instrument-free visual feedback alongside quantitative imaging, CyC has the potential to streamline intraoperative decision-making, reduce unnecessary graft discard, and ultimately expand the safe use of marginal donor livers in transplantation.

Obesity and related metabolic disorders, including metabolic dysfunction-associated steatohepatitis (MASLD), have reached epidemic proportions worldwide. We unveil a previously unknown moonlighting role for arginase 1 (Arg1) in facilitating hepatic lipogenesis. Male mice lacking hepatic Arg1 exhibit diminished lipid accumulation in both liver and adipocytes, an effect mirrored in genetically- or diet-induced obesity models following Arg1 inhibitor treatment. Mechanistically, Arg1 competes with RSK2 and Elk1 for binding to the substrate-binding pocket of extracellular signal-regulated kinase 2 (ERK2) via its S-shaped motif, thereby enhancing ERK2 ubiquitination and degradation and upregulating the AKT/mTOR/PPARγ and Elk1/c-Fos/PPARγ cascades, ultimately augmenting lipogenesis. Peptides designed to mimic the ERK2 substrate-binding pocket disrupt the Arg1-ERK2 interaction and improve metabolic profiles in obesity and MASLD models. Our findings implicate Arg1 regulates hepatic lipid metabolism via its physical interaction with ERK2, highlighting the Arg1-ERK2 interaction as a promising therapeutic target for obesity and related metabolic disorders in male mice.

Abstract Background: Methylation-based analysis of cell-free DNA (cfDNA) has emerged as a key technology for MCED. However, existing approaches rely on traditional machine learning algorithms, which inherently limit detection performance. With the rapid advancement of artificial intelligence (AI), we have developed Genie-ADLA, a deep learning algorithm designed specifically for MCED. By integrating state-of-the-art deep neural network architectures with the intrinsic patterns inherent in methylation data, Genie-ADLA significantly enhanced MCED performance. Methods: Genie-ADLA was trained and evaluated on a dataset of 4,781 participants aged 40-75 years, including 2,702 pathologically confirmed cancer cases across 16 cancer types and 2,079 non-cancer controls (NCT06217900). The training set comprised 3,217 samples (1,756 cancer cases and 1,461 non-cancer controls), and the model’s performance was evaluated on an independent test set of 1,564 samples (618 non-cancer controls and 946 cancer cases). To address challenges inherent to methylation data—high dimensionality, sparsity, and noise—we applied feature dimensionality reduction and embedding strategies, reducing computational burden, mitigating overfitting, and improving learning efficiency. An ensemble learning approach further strengthened robustness and generalization. Results: Across all stages of 16 cancer types, Genie-ADLA achieved an overall sensitivity of 63.43% (600/946, 95% CI: [60.26%, 66.50%]) at 99.3% (612/618, 95% CI: [97.90%, 99.64%]) specificity in the test cohort. Compared with the XGBoost model trained on the same dataset, Genie-ADLA demonstrated improved overall sensitivity in 11 of the 16 cancer types, with an average increase of 4.86%.For stage I-III cancer patients, the sensitivities at 99.3% specificity showed notable gains over XGBoost: colorectal cancer achieved 76.98% (97/126, 95% CI: [68.65%, 84.01%]), an improvement of 9.52% from 67.46%; esophageal cancer reached 80.95% (51/63, 95% CI: [69.09%, 89.75%]), up 6.35% from 74.60%; breast cancer reached 37.14% (26/70, 95% CI: [25.89%, 49.52%]), improving by 5.71% from 31.43%. Lung cancer was subdivided into adenocarcinoma and non-adenocarcinoma, with stage I-III sensitivities of 40.90% (27/66, 95% CI: [28.95%, 53.71%]) in adenocarcinoma, an increase of 10.6%, and 84.44% (38/45, 95% CI: [70.54%, 93.51%]) in non-adenocarcinoma, improving by 2.22%. Conclusions: Genie-ADLA, leveraging advanced deep neural network architectures and data processing strategies, substantially elevates the performance ceiling of methylation-based early cancer detection, offering a new paradigm for AI-driven cancer screening. Citation Format: Kezhong Chen, Ziyu Li, Xiaojian Wu, Jian Huang, Guoyue Lv, Weiping Wen, Dahong Zhang, Xiangyu Zhao, Danbo Wang, Zhihua Liu, Lixin Sun, Shu Wang, Xiangnan Li, Zhigang Li, Jiandong Tai, Jiayin Yang, Zhentong Wei, Ming Cai, Qiang Zhang, Songbing He, Shuhua Yi, Shenhong Qu, Wenhui Zhao, Xianjun Yu, Ruixia Guo, Jianhong Lian, Desong Yang, Huaiwu Lu, Xi Guo, Yan Zhang, Zhuowei Liu, Yingjiang Ye, Chang Lin, Jie Gao, Xuanhui Liu, Yushu Guo, Suying Ding, Guoqiang Zhao, Yanzhan Yang, Jiangyu Li, Shiqing Chen, Hui Yu, Fang Liu, Yang Wang, Min Li, Baoliang Zhu, Yonghui Li, Xiaohui Wu, Fan Yang, Jun Wang. Genie-ADLA: A deep learning algorithm for methylation-based multiple cancer early detection (MCED) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 5471.

Hepatic ischemia‒reperfusion injury (HIRI) represents a frequently occurring pathological condition during liver surgery, yet the mechanisms governing HIRI remain inadequately comprehended. Here, we investigate the role of B-cell translocation gene 2 (Btg2) in HIRI. Btg2 is upregulated following HIRI. A 70% HIRI model using hepatocyte-specific Btg2 transgenic and systemic Btg2 knockout mice reveals that Btg2 deteriorates hepatic inflammation and apoptosis. In primary hepatocytes, Btg2 knockdown reduces hypoxia/reoxygenation (H/R)-induced inflammation and mitochondrial stress. Metabolomics indicates that taurine metabolism is significantly affected in the livers of Btg2-/- mice. Mechanistically, Btg2 suppresses UFMylation of flavin-containing monooxygenase 1 (Fmo1), a key taurine synthesis enzyme, promoting its K48-linked ubiquitination and degradation. Virus-mediated Fmo1 overexpression inhibits ferroptosis, apoptosis, and HIRI significantly both in vivo and in vitro. Virtual screening of natural compounds indicates that Daturataturin A (DTA) inhibits Btg2, thereby attenuating ferroptosis and HIRI. These results suggest that Btg2 may constitute a promising therapeutic target for HIRI.

The prognosis for patients diagnosed with hepatocellular carcinoma with bile duct tumor thrombus (HCC-BDTT) remains dismal, and there are presently no universally accepted treatment guidelines to address this complex condition. Long-term outcomes of liver transplantation (LT) for HCC-BDTT patients are unclear, and whether LT is a proper therapeutic option for HCC-BDTT patients remains to be determined. Therefore, we design a clinical trial to evaluate whether LT can improve recurrence-free survival (RFS) and overall survival (OS) in HCC-BDTT patients. This is an open-labeled, single-arm, prospective, multicenter and real-world study aiming to assess the survival outcomes of HCC-BDTT patients in LT. Patients will be enrolled based on histological confirmation of HCC with BDTT. The study is planned to take 4 years, 2 years for enrollment and 2 years for follow-up. We anticipate that LT confers beneficial survival outcomes for HCC-BDTT patients, specifically in terms of the pivotal parameters, such as RFS and quality of life. Upon successful completion of the trial, we will extend our monitoring over a longer follow-up time to accurately estimate important indicators such as OS. We expect that this study provides substantial evidence to refine treatment guidelines through thorough data analysis, ultimately contributing to better patient outcomes and advancing our understanding of the disease.Trial Register: Trial registered at www.clinicaltrials.gov (NCT06928415)

Rapid and accurate assessment of senescence in aging marginal donor livers is critically important for liver transplantation, yet remains analytically challenging in clinical practice. Herein, we report CyC, a liver-targeted triple-modal molecular probe that integrates naked-eye colorimetric sensing with near-infrared fluorescence/photoacoustic (NIRF/PA) imaging for rapid evaluation of hepatic senescence. Upon activation by senescence-associated β-galactosidase (β-Gal), CyC produces a turn-on NIRF/PA response accompanied by a distinct blue-to-green color change visible to the naked eye. The probe exhibits high sensitivity and specificity for β-Gal, efficient liver enrichment, and strong signal contrast in senescent cells and aged mouse liver tissues. When applied to small fragments of clinical human liver samples via simple ex vivo immersion, CyC readily detects β-Gal activity. This platform integrates molecular imaging with visual sensing, offering a practical tool for rapid senescence assessment in aging marginal donor liver evaluation. By enabling immediate, instrument-free visual feedback alongside quantitative imaging, CyC has the potential to streamline intraoperative decision-making, reduce unnecessary graft discard, and ultimately expand the safe use of marginal donor livers in transplantation.

The optimal treatment (liver transplantation [LT] vs surgical resection [SR]) for early-stage hepatocellular carcinoma (HCC) remains controversial.A total of 209 SR patients and 129 LT patients were identified at our institution. After eliminating 27 patients with Child-Pugh C, the data from 209 SR patients and 102 LT patients were analyzed using a propensity score matching (PSM) model. Forty-six pairs were generated. A subgroup analysis was conducted based on the alpha-fetoprotein (AFP) level or platelet count (PLT). A survival analysis was performed using the Kaplan-Meier method.Gender, satellite lesions, and the treatment method were predictors of HCC recurrence. The Ishak score and treatment methods were associated with long-term survival after surgery. Before PSM, LT patients had a better prognosis than those treated by SR. Among HCC patients with childhood A/B cirrhosis, after PSM, SR achieved similar overall survival outcomes compared with LT. LT and SR resulted in comparable long-term survival for patients with or without thrombocytopenia. Patients with an AFP ≥ 400 ng/mL might achieve more survival benefits from LT.Our propensity score model provided evidence that, compared with transplantation, surgical resection could result in comparable long-term survival for resectable early-stage HCC patients, except for the AFP ≥ 400 ng/mL HCC subgroup. Surgical resection might not be a contraindication for early-stage HCC patients with thrombocytopenia due to their similar prognosis after transplantation.

Background and Objective:Liver transplantation (LT) is the most effective end-stage liver disease (ESLD) therapeutic intervention. However, in China, many liver transplant recipients lack a comprehensive management approach. This narrative review summarizes the current deficiencies in long-term post-transplant care and proposes a comprehensive model for Integrated Care Management (ICM) aimed at improving long-term outcomes after LT. Methods:An extensive electronic literature search was performed using PubMed database to identify relevant articles. The search included prospective clinical trials, observational trials, case-control studies, systematic reviews with or without meta-analysis. Articles were limited to English and Chinese language publications. The following Medical Subject Headings (MeSH) terms and free-text keywords were combined with Boolean operators: ("liver transplantation" OR "liver transplant*" OR "orthotopic liver transplantation" OR "OLT") AND ("postoperative management" OR "whole-course management" OR "perioperative care" OR "long-term follow-up") AND ("immunosuppress*" OR "tacrolimus" OR "cyclosporine" OR "mycophenolate" OR "infection prophylaxis" OR "graft function" OR "rejection" OR "biliary stricture" OR "hepatic artery thrombosis" OR "renal dysfunction" OR "hepatitis B recurrence" OR "hepatitis C recurrence"). Key Content and Findings:Research has shown the global number of LT recipients continues to rise, affecting millions of individuals and placing a substantial burden on healthcare systems worldwide. Despite considerable progress over the past three decades in surgical techniques, perioperative care, and immunosuppressive therapy, long-term post-transplant management has received comparatively limited attention from both the public and policy-makers. This neglect has contributed to suboptimal long-term outcomes, including increased mortality and reduced quality of life among recipients. Conclusions:A comprehensive model for ICM may be a new direction to improve the long-term outcomes after LT in the future.

Organ transplantation remains a life-saving intervention for end-stage organ failure. However, its long-term success has been constrained by a few critical challenges, including few noninvasive diagnostic technologies for graft assessment, a lack of effective organ preservation and rewarming techniques to mitigate ischemic damage, the issue of ischemia-reperfusion injury (IRI), the risk of immune-mediated rejection and the requirement of advanced postoperative management. Nanomedicine has been explored for overcoming these challenges for organ transplantation. A myriad of polymeric, inorganic and hybrid nanocarriers have been employed for nanomedicine. Targeting and stimuli-responsive nanomedicine has been developed to improve drug distribution and enhance its therapeutic/diagnostic efficacy. Nanomedicine has been applied for rewarming of large-sized organs, IRI mitigation, immunomodulation, and real-time monitoring. This review examines the mechanisms, elaborates design principles, and covers the application of nanomedicine in organ transplantation at stages of pre- to post-transplantation. The challenges in clinical translation of nanomedicine are discussed and future research directions are proposed. This review will provide a consolidated framework for the development and application of nanomedicine for organ transplantation, ultimately improving the quality of life of transplant recipients.

INTRODUCTION:The age-male-albumin-bilirubin-platelets (AMAP) score serves as a specific model for assessing liver fibrosis among individuals with chronic hepatitis B. However, there remains ambiguity regarding its ability to reliably predict the long-term outcomes for patients diagnosed with intrahepatic cholangiocarcinoma (ICC) after undergoing radical surgical interventions. METHODS:This retrospective multicenter investigation included 681 participants diagnosed with ICC who had undergone radical surgical procedures. The AMAP risk score was computed according to the following equation: (0.06 × age + 0.48 × ALBI - 0.01 × platelet + 7.4)/14.77 × 100. To assess the clinical significance of the AMAP score on survival outcomes, Kaplan-Meier methods, log-rank tests, and Cox proportional hazards regression models were utilized. In addition, a nomogram was created utilizing the outcomes of the multivariate analysis. RESULTS:The AMAP model demonstrated a significant correlation with the rates of disease-free survival (DFS) and overall survival (OS) in individuals diagnosed with ICC. Patients in the low-risk group exhibited significantly longer DFS (P = 0.002) and OS (P < 0.001) compared to those in the high-risk group. In addition, a nomogram was constructed to predict DFS, achieving a C-index of 0.705, and for OS, a C-index of 0.753. The nomogram based on AMAP demonstrates strong predictive performance. CONCLUSIONS:The AMAP score functions as a prospective prognostic indicator for individuals diagnosed with ICC. A nomogram incorporates the AMAP score proves valuable in recognizing patients with ICC who are at high risk and supports the creation of adjuvant treatment plans.

To analyze and compare the efficacy of two treatment strategies for biliary atresia (BA) sequential treatment of Kasai hepatoportoenterostomy-liver transplantation and primary liver transplantation. A retrospective analysis was conducted on the clinical data of 300 patients with BA who underwent LT in our center. Among these patients, 225 underwent Kasai hepatoportoenterostomy - liver transplantation sequential treatment (Kasai-LT group), while 75 received primary liver transplantation (pLT group). Data on demographic characteristics, perioperative conditions, postoperative recovery, and complications were collected to analyze the efficacy, complication rates, and survival outcomes of the two treatment approaches. After propensity score matching analysis, there were no differences in postoperative liver function recovery between two groups. However, the Kasai-LT group had lower APRI, lower γ-GT level, and lower PELD scores when liver transplantation. The Kasai-LT group had shorter operative time, shorter PICU stay, shorter hospital stay with lower hospitalization cost. The incidence of hepatic artery complications and thoracoabdominal infections after LT was significantly higher in the pLT group compared to the Kasai-LT group. The 5-year recipient cumulative survival rate was 94.40