BACKGROUND & AIMS:Acute-on-chronic liver failure (ACLF) is characterised by multiorgan failure and high short-term mortality in hospitalised patients with acute decompensation of cirrhosis. Although the EASL-CLIF criteria are widely used for diagnosis and prognostication, evolving definitions of organ dysfunction and emerging therapies require updated, tailored criteria to improve diagnostic accuracy, treatment assessment, and applicability in clinical trials. We aimed to develop and validate the A-TANGO organ failure (OF) score to refine ACLF diagnosis and enhance its utility for treatment response evaluation and risk stratification. METHODS:We performed a retrospective analysis of prospective observational cohorts. The derivation cohort comprised three EF-CLIF consortium studies conducted in Europe and Latin America (CANONIC, PREDICT, ACLARA; n = 3,896). Validation cohorts included one study from India (Ambi-spective study n = 2,055) and one from China (CATCH-LIFE; n = 2,568). Patients were enrolled between 2011 and 2023, with follow-up completed in 2023. The primary objective was to redefine thresholds for organ dysfunction and failure using three subscores per organ, with subscore 3 corresponding to ≥15% 28-day mortality and defining organ failure. RESULTS:Compared with the CLIF-C OF score, the A-TANGO OF score introduced revised thresholds for organ failure and added an ACLF grade 4 to address the wide mortality variation within CLIF-C OF grade 3. A-TANGO identified more organ failures, increasing ACLF diagnosis from 24% to 36% and improving the net reclassification index by 16%, while maintaining similar predictive accuracy for 28- and 90-day mortality. Two additional prognostic models (A-TANGO ACLF-WBC and A-TANGO ACLF-CRP) demonstrated strong associations with 28- and 90-day mortality and improved prognostic performance. Findings were confirmed in external validation cohorts. CONCLUSIONS:The A-TANGO OF score is a reproducible and comprehensive tool for ACLF diagnosis with preserved prognostic performance, validated across large international cohorts. It provides a robust framework for clinical trials by enabling more accurate diagnosis, reducing required sample sizes, and offering clinically meaningful endpoints such as ACLF resolution for treatment response assessment. IMPACT AND IMPLICATIONS:The A-TANGO organ failure (OF) score provides a scientifically justified advancement in ACLF research by refining organ-specific dysfunction thresholds and introducing a new grade 4, thereby addressing limitations in current EASL-CLIF criteria and improving identification of high-risk patients. These findings are important for clinicians, researchers, and healthcare systems globally, as they increase detection of organ failure, enhance risk stratification, and enable more accurate prediction of short-term mortality in hospitalized patients with cirrhosis. The A-TANGO OF score and its associated prognostic scores (ACLF-WBC and ACLF-CRP) can be applied in clinical practice to guide treatment decisions, and serve as reliable, measurable endpoints in clinical trials evaluating emerging therapies. Although limitations such as missing data, cohort-specific recruitment differences, and historical classification criteria exist, the consistent and robust performance of the A-TANGO scores across large, multinational cohorts highlights their potential applicability and utility on a global scale.

BACKGROUND AND AIMS:To establish an early and quick model for diagnosing infections in patients with acute-on-chronic liver disease (AoCLD). APPROACH:This study analysed 3949 patients from two multicenter prospective cohorts of the Chinese Acute-on-Chronic Liver Failure (CATCH-LIFE) study. The dataset was randomly divided into training and validation cohorts in a 7:3 ratio. In the training cohort, logistic regression and least absolute shrinkage and selection operator regression analyses were used to identify predictive risk factors for infection in patients with AoCLD, and a simple nomogram was established. Two different cutoff values were determined to stratify infection risk in AoCLD patients. RESULTS:The developed diagnostic model included six variables: cirrhosis, ascites, neutrophil count (N), total bilirubin, C-reactive protein (CRP) and blood sodium levels. The area under the receiver operating characteristic curve for the training and validation cohorts was 0.818 and 0.809, respectively, significantly higher than using CRP, procalcitonin or N alone. Additionally, in the training cohort, we set a low cutoff value of 0.2028, resulting in a sensitivity of 80.15%, specificity of 68.25% and a negative predictive value of 92.7% for rule-out diagnosis. A high cutoff value of 0.4045 results in a specificity of 90.1%, sensitivity of 52.7% and a positive predictive value of 64% for rule-in diagnosis. These cutoff values were validated in the validation cohort. CONCLUSIONS:We established a nomogram model to assist clinicians in diagnosing infections in patients with AoCLD, effectively improving the accuracy and timeliness of diagnosis.

Background and Aims:Bacterial infection is a key cause of mortality in patients with acute-on-chronic liver failure (ACLF). In this study, we aimed to identify metabolite biomarkers and develop a novel machine learning model for early identification of bacterial infection in ACLF. Methods:Based on a prospective multicenter cohort from 14 centers, 1,314 patients with acute-on-chronic liver disease were enrolled, including those with ACLF and non-ACLF. Plasma samples at admission were collected for metabolomics profiling. Patients were randomly divided into discovery (n = 921) and validation (n = 393) sets. Machine learning was used to develop diagnostic models. The win ratio method was employed to assess the risk stratification capability of the models. Results:Bacterial infection occurred in 198 of the 451 ACLF patients and 132 of the 863 non-ACLF patients. Infection altered the plasma metabolome, especially in lipid, amino acid, and xenobiotic metabolic pathways. Models for bacterial infection in ACLF (five metabolites) and non-ACLF (six metabolites) demonstrated superior discrimination in the discovery (AUCs: 0.881 and 0.935, respectively) and validation sets (AUCs: 0.835 and 0.889, respectively) compared with C-reactive protein, white blood cell count, procalcitonin, and the best composite clinical model. Metabolic risk stratification based on the models effectively predicted 90-day outcomes (all-cause death, organ failure, sepsis, new-onset acute decompensation, and systemic inflammatory response syndrome). Conclusions:Our models based on novel metabolic biomarkers enable identification of patients at high risk of bacterial infection and support risk stratification of 90-day outcomes.

Background and Aims:Acute-on-chronic liver failure (ACLF) lacks a universally accepted definition, and recent efforts have proposed consensus organ failure criteria. In this study, we aimed to compare the clinical validity of a recently proposed consensus ACLF framework with the outcome-calibrated A-TANGO classification. Methods:We performed a multinational cohort study including 2,398 patients from the TIH cohort (India) and 2,568 from the CATCH-LIFE cohort (China) who were hospitalized with acute decompensation of cirrhosis. ACLF was defined using A-TANGO and an operationalized version of the 2025 consensus framework. Outcomes were 28- and 90-day mortality. Analyses assessed case capture, overlap, mortality risk, sensitivity, specificity, and net reclassification improvement (NRI). Results:ACLF prevalence differed substantially by definition. In TIH, A-TANGO classified 79.2% as ACLF versus 42.3% by the consensus definition; in CATCH-LIFE, the corresponding values were 31.4% versus 5.8%, respectively. Most consensus ACLF cases were captured by A-TANGO, which additionally classified 26%-37% of patients as having ACLF. These patients had substantial mortality (28-day: 18.1%-26.9%; 90-day: 33.2%-37.9%), significantly higher than those negative by both frameworks and comparable to established ACLF risk thresholds. A-TANGO showed higher sensitivity for 28-day mortality (TIH: 94.1% vs. 67.8%; CATCH-LIFE: 76.1% vs. 25.6%), whereas consensus criteria were more specific. Reclassification analyses showed improved discrimination with A-TANGO (NRI: 17.1% in TIH; 27.4% in CATCH-LIFE). Within the consensus non-ACLF group, A-TANGO further stratified patients into distinct risk groups with stepwise increase in mortality. Conclusions:In conclusion, the two frameworks identify fundamentally different populations. The consensus definition significantly reduces sensitivity and under-recognizes high-risk patients. Compared with consensus definitions, the outcome-calibrated framework better supports diagnosis, clinical decision-making, risk stratification, and trial design in ACLF.

Abstract Background/Aims Acute-on-chronic liver failure (ACLF) is one of the deadliest complications of chronic liver disease yet treatment options are sparse. In Asia, HBV-reactivation (HBVr) is one of the most common triggers. Recently, HBV-associated ACLF was associated with distinct changes in the metabolome. Here, metabolic impacts of HBVr were analysed in-depth in non-ACLF, pre-ACLF and ACLF. Methods Clinical and metabolic data of 1024 Chinese patients (CATCH-LIFE studies) with chronic HBV mono-infection were analyzed. ACLF was diagnosed according to COSSH criteria. Metabolites in plasma were quantified using LC-MS, compared to non-ACLF and subjected to enrichment and pathway analyses using the database SMPDB via MetaboAnalyst v6. Results In 1024 patients (611: non-ACLF, 72: pre-ACLF, 341: ACLF), HBVr was present in 20.2% (ACLF) or 33.3% (pre-ACLF) of patients. HBVr increased 28-day mortality in pre-ACLF patients (2.1% in HBVnr vs. 25% in HBVr). Energy metabolism generating reactive oxygen species (ROS) was highly induced in the absence of ROS-detoxifying pathways in pre-ACLF. Urea cycle, thus nitric oxide (NO) build-up, the polyamine metabolism and related pathways were highly increased in both HBVr pre-ACLF and ACLF, shifting pre-ACLF close to mature ACLF. Specific metabolites could be identified as putative markers and key-regulators herein. Conclusion HBV reactivation induces inflammation, hepatic injury and mortality especially in pre-ACLF patients. Metabolic disruption in the ROS/NO/polyamine axis favors stress and hinders liver regeneration. Findings help identifying and alleviating HBVr-driven progression towards ACLF via pharmacological or biopharmaceutical intervention. Trial registration Analyses were based on the CATCH-LIFE studies. The CATCH-LIFE studies were registered at Clinical.trials.gov (Clinical Trial Number: NCT02457637, first registered 2015-01-31 and NCT03641872, first registered 2018-08-14).

Mycoplasma pneumoniae infections resurged globally in 2023-2024 following a significant decline during the coronavirus disease 2019 (COVID-19) pandemic. To understand the genomic epidemiology of this resurgence in China, a nationwide 1-year genomic surveillance identified 9907 patients infected with M. pneumoniae, resulting in an overall positive rate of 10.05%. We developed a hybrid capture-based targeted next-generation sequencing (hc-tNGS) assay, obtaining 271 high-quality genomes directly from clinical samples. Phylogenetic analysis of a global collection of 562 M. pneumoniae genomes identified six distinct lineages, including three newly emerged main Chinese clades (MCCs) that co-circulated across various regions of China. Among these MCCs, one clade, comprising P1-1, ST17, and L4, was localized in Taiwan, while two others-P1-1, ST3, and L6 clade, and P1-2, ST14 and L2 clade-co-circulated in different regions of China during the 2023-2024 epidemic season. Notably, 96.31% of the isolates identified in this study exhibited a point mutation, primarily A2063G (95.94%). This study offers a comprehensive genomic characterization of the post-pandemic M. pneumoniae resurgence in China, highlighting the emergence and spread of resistant clades. These findings emphasize the importance of adopting a One Health approach to address the potential global public health threats posed by this resurgent pathogen.

Hepatitis E virus (HEV) represents a leading cause of acute viral hepatitis in China, yet large-scale studies characterizing its dynamic epidemiology and enabling early prediction of adverse outcomes remain scarce. We performed a retrospective cohort study comprising 816 patients hospitalized with acute HEV infection (2019–2024). Predictors were identified through multivariable logistic regression, with Firth's penalized likelihood method applied to address potential small-sample bias, and bootstrap resampling (BCa 95

ObjectiveHepatitis B surface antigen (HBsAg) clearance is a key milestone for functional (clinical) cure of chronic hepatitis B virus (HBV) infection. However, data on the efficacy and safety of pegylated interferon alpha (Peg-IFNα) for HBsAg clearance in postpartum women with chronic HBV infection remain scarce. This study aimed to prospectively evaluate the efficacy and safety of Peg-IFNα in promoting HBsAg clearance in this specific population.MethodsA total of 263 HBV-infected postpartum women with a baseline HBsAg levels ≤3000 IU/mL were enrolled. Based on patient preference, they were assigned to either the Peg-IFNα group (n=62, receiving Peg-IFNα monotherapy or combination therapy with nucleos(t)ide analogs [NAs]) or the control group (n=201, receiving NAs or follow-up only). The duration of Peg-IFNα treatment was ≥48 weeks. Propensity score matching (PSM) was performed to balance baseline characteristics. The primary endpoints were both HBsAg clearance rate and the magnitude of HBsAg decline.ResultsAt week 48, the Peg-IFNα group had significantly higher HBsAg clearance (29.03% [18/62]) and seroconversion rates (27.42% [17/62]) than the control group (both 0%, P < 0.001). Post-PSM, the Peg-IFNα group still had a significantly higher HBsAg clearance/seroconversion rate (30.43% [14/46]) versus the control group (0%, P < 0.001). Subgroup analysis showed that patients with baseline HBsAg < 1000 IU/mL had higher clearance rates (pre-PSM: 39.02% [16/41]; post-PSM: 40.00% [12/30]). Receiver operating characteristic (ROC) curve analysis identified a ≥ 99.2% HBsAg reduction from baseline to week 12 as a strong predictor of week 48 HBsAg clearance (AUC ≥0.9; sensitivity =0.818; specificity= 1.000).ConclusionPeg-IFNα treatment can achieve high rates of HBsAg clearance and seroconversion in postpartum women with chronic HBV infection. The postpartum period represents a unique and favorable immune window for interferon-based intervention, and patients with baseline HBsAg <1000 IU/mL derive particular benefit from this strategy.

BACKGROUND AND OBJECTIVES:Early differentiation between infectious and non-infectious systemic inflammatory response syndrome (SIRS) in patients with acute-on-chronic liver disease (AoCLD) remains challenging. This study aimed to develop and validate an early diagnostic model to accurately identify infection status in AoCLD patients with SIRS, thereby guiding targeted anti-infective therapy and improving clinical management. METHODS:Based on two multicenter prospective cohorts from the Chinese Acute-on-Chronic Liver Failure (CATCH-LIFE) study, 515 AoCLD patients with SIRS were randomly divided into a training cohort (n = 361) and a validation cohort (n = 154). In the training cohort, predictive factors for infection were screened using logistic regression, least absolute shrinkage and selection operator (LASSO) regression, multicollinearity analysis, and stepwise regression. Restricted cubic splines (RCS) were employed to explore nonlinear relationships and interaction effects. A nomogram model was subsequently constructed. The model's performance was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA), with internal validation via bootstrap method. RESULTS:The final model incorporated five clinical indicators: jaundice, ascites, neutrophil count (N), albumin (ALB), and C-reactive protein (CRP). CRP exhibited a significant nonlinear relationship with infection risk (P < 0.001) and was included as a spline term, while an interaction term between ALB and jaundice was incorporated. The model demonstrated excellent discrimination, with area under the ROC curve (AUC) of 0.840 (95 % CI: 0.788-0.888) in the training cohort and 0.865 (95 % CI: 0.803-0.927) in the validation cohort, significantly outperforming single biomarkers. Calibration curves showed high consistency between predicted and observed probabilities. DCA indicated substantial clinical net benefit across threshold probabilities. A clinical decision pathway was developed based on the nomogram's risk prediction and optimal DCA threshold. CONCLUSION:The early diagnostic model developed in this study effectively differentiates between infectious and non-infectious SIRS in AoCLD patients, potentially reducing unnecessary antimicrobial exposure and improving clinical outcomes.

Exhaustion of the immune system’s ability to adapt to novelty suggests that the changes it undergoes might be a consequence of an evolutionary unpredictable antigenic exposure over a lifetime. Thus, we raise the question of whether a naive immune system can manage new antigens better than an educated immune system. Here, by employing the naive immune system of germ-free (GF) mice without a history of microbial exposure, we compared their adaptive immune responses with those of the conventional (Conv) mice upon new viral infection. Interestingly, the naive GF immune system showed robust T-cell responses, with more potent memory T cells established for long-term protection, even in the condition of primary lower T-cell levels for naive GF mice. Furthermore, we found that the ABX-treated Conv mice showed impaired T-cell responses, compared with the untreated Conv ones. With the microbiota eliminated, the ABX mice still have a history of microbial exposure and education for their immune system. In summary, commensal bacteria education history calibrates the naivety and the activation threshold of the adaptive antiviral immune system.

Aims Increased serum creatinine (sCR) is associated with increased mortality in cirrhotic patients, while there remains a lack of evidence-based sCR cutoffs for indicating disease deterioration and predicting 90-day liver transplantation (LT)-free mortality in the cirrhotic Chinese population. We aimed to investigate the quantitative relationship between sCR on admission and 90-day mortality in hospitalized patients with cirrhosis in the Chinese population. Methods Data were prospectively collected from two multicenter cohorts, which enrolled hospitalized patients with chronic liver disease. After screening, 2582 patients with cirrhosis from January 2015 to December 2016 and from July 2018 to January 2019 were included in the primary analysis. Creatinine values were collected on admission. Patients were regularly followed up at the end of 90 days. The univariate and multivariate Cox proportional hazard model was conducted to explore the relationship between sCR and 90-day LT-free mortality. A generalized additive model and second derivative (acceleration) were used to plot "creatinine-mortality correlation curves", adjusting for potential confounders. Results Among 2582 hospitalized patients with cirrhosis, 428 (16.6%) experienced deaths at the end of 90 days. sCR levels on admission were significantly associated with 90-day LT-free mortality in both univariate and multivariate analyses (hazard ratio [HR], 1.77, p < 0.001; HR, 1.22, p = 0.003). sCR of 1.1 mg/dL was identified as the starting point (stage 1a) of disease deterioration of acute kidney injury (AKI) in hospitalized patients with cirrhosis. Patients with 1.1 mg/dL< sCR <= 1.8 mg/dL had significantly higher 90-day mortality compared to those with sCR <= 1.1 mg/dL (HR, 1.90, p < 0.001). The corresponding 28-day and 90-day LT-free mortality to sCR 1.1 mg/dL were 11% and 18%, respectively. Conclusions sCR was an independent risk factor for 90-day LT-free mortality in hospitalized cirrhotic patients. sCR of 1.1 mg/dL is the starting point of disease deterioration and serves as an important supplement for the diagnostic threshold of AKI stage 1a in the Chinese cirrhotic population without baseline sCR.

PurposeThis study aimed to comprehensively analyze the global landscape, trends, and research focus of nanopore sequencing technology in the field of pathogenic microorganism diagnosis using bibliometric analysis.MethodsLiterature published between January 2014, and December 2024, was retrieved from the Web of Science Core Collection. A cross-sectional bibliometric analysis was conducted using VOSviewer, CiteSpace, Origin 2024, and R software to extract and evaluate metrics. Publications were categorized by country, institution, author, journal, highly cited papers, and keywords. Variables were compared based on publication output and academic impact, which included citation counts, citation impact, H-index, journal impact factor, total link strength, major pathogens, and research directions.ResultsInitial searches identified 2,098 articles related to nanopore sequencing and pathogenic microorganisms, of which 729 were ultimately included in the analysis. Among the 104 participating countries, the United Kingdom, the United States, and China have led in publication output, citations, and academic influence. The most versatile institution was the University of Oxford, followed by Zhejiang University. The most productive scholars and journals were Crook, Derrick W., and Frontiers in Microbiology, respectively. Keyword analysis revealed that the primary advantages of nanopore sequencing include portability, long-read capabilities, and real-time analysis. Current research hotspots focus on real-time pathogen identification, viral genomic surveillance, and antimicrobial resistance profiling.ConclusionPresently, nanopore sequencing is rapidly transitioning from laboratory research to on-site sequencing and public health emergency scenarios. To our knowledge, this study is the first bibliometric analysis to comprehensively delineate the latest developments in nanopore sequencing in pathogenic microorganism diagnosis. It provides researchers with an understanding of the current situation, identifies knowledge gaps, and points out future research directions.

Acute exacerbation (AE) is common for patients with chronic hepatitis B (CHB). The aim of the study is to investigate the values of hepatitis B core antibody (anti-HBc) IgM in CHB-AE. Patients were screened from a prospective sub-cohort, 419 CHB patients with AE were enrolled and divided into groups according to antiviral treatment history, treatment naïve, withdrawal above or within 6 months, and on-treatment. The prevalence, clinical characteristics of anti-HBc IgM, and its relationship with the outcomes of CHB were assessed. A total of 157 patients (37.5%) were tested positive for anti-HBc IgM, of which patients with antiviral-withdrawal more than 6 months had the highest prevalence (49.3%). Anti-HBc IgM was significantly associated with HBV DNA and ALT, regarding to its prevalence and serum level. Furthermore, serum anti-HBc IgM values varied in different phases of CHB, of which immune active and HBeAg-negative chronic hepatitis phases were significantly higher than that in inactive carriers (p = 0.017 and p = 0.0097, respectively). Anti-HBc IgM could distinguish hepatitis from inactive infection phases in HBeAg-negative patients (AUC 0.841). Anti-HBc IgM levels were significantly higher in subgroup who developed ACLF (p < 0.05), but had no relationship with short-term mortality. Finally, anti-HBc IgM seropositivity was the only predictor of HBeAg seroclearance (OR 3.18, 95% CI 1.30-7.73) and all patients who achieved HBsAg seroclearance within 1-year had a markedly elevated anti-HBc IgM level. In conclusion, our study shows anti-HBc IgM is highly prevalent in CHB patients with AE and would be a new predictor of HBeAg and HBsAg loss in this population.