BACKGROUND: APRI and FIB-4 scores are used to exclude clinically significant fibrosis (defined as stage ≥ F2) in patients with chronic viral hepatitis. However, the cut-offs for these scores (generated by Youden indices) vary between different patient cohorts. This study aimed to evaluate whether serum dithiothreitol-oxidizing capacity (DOC), i.e., a surrogate test of quiescin sulfhydryl oxidase-1, which is a matrix remodeling enzyme, could be used to non-invasively identify significant fibrosis in patients with various chronic liver diseases (CLDs).
METHODS: Diagnostic performance of DOC was compared with APRI and FIB-4 for identifying significant fibrosis. ROC curve analyses were undertaken in: a) two chronic hepatitis B (CHB) cohorts, independently established from hospitals in Wenzhou (n = 208) and Hefei (n = 120); b) a MASLD cohort from Wenzhou hospital (n = 122); and c) a cohort with multiple CLD etiologies (except CHB and MASLD; n = 102), which was identified from patients in both hospitals. Cut-offs were calculated using the Youden index. All CLD patients (n = 552) were then stratified by age for ROC curve analyses and cut-off calculations.
RESULTS: Stratified by CLD etiology or age, ROC curve analyses consistently showed that the DOC test was superior to APRI and FIB-4 for discriminating between clinically significant fibrosis and no fibrosis, when APRI and FIB-4 showed poor/modest diagnostic performance (P < 0.05, P < 0.01 and P < 0.001 in 3, 1 and 3 cohort comparisons, respectively). Conversely, the DOC test was equivalent to APRI and FIB-4 when all tests showed moderate/adequate diagnostic performances (P > 0.05 in 11 cohort comparisons). DOC had a significant advantage over APRI or FIB-4 scores for establishing a uniform cut-off independently of age and CLD etiology (coefficients of variation of DOC, APRI and FIB-4 cut-offs were 1.7%, 22.9% and 47.6% in cohorts stratified by CLD etiology, 2.0%, 26.7% and 29.5% in cohorts stratified by age, respectively). The uniform cut-off was 2.13, yielded from all patients examined. Surprisingly, the uniform cut-off was the same as the DOC upper limit of normal with a specificity of 99%, estimated from 275 healthy control individuals. Hence, the uniform cut-off should possess a high negative predictive value for excluding significant fibrosis in primary care settings. A high DOC cut-off with 97.5% specificity could be used for detecting significant fibrosis (≥ F2) with an acceptable positive predictive value (87.1%).
CONCLUSIONS: This proof-of-concept study suggests that the DOC test may efficiently rule out and rule in significant liver fibrosis, thereby reducing the numbers of unnecessary liver biopsies. Moreover, the DOC test may be helpful for clinicians to exclude significant liver fibrosis in the general population.

OBJECTIVE: To investigate the feasibility of developing a grading diagnostic model for schistosomiasis-induced liver fibrosis based on B-mode ultrasonographic images and clinical laboratory indicators.
METHODS: Ultrasound images and clinical laboratory testing data were captured from schistosomiasis patients admitted to the Second People\'s Hospital of Duchang County, Jiangxi Province from 2018 to 2022. Patients with grade I schistosomiasis-induced liver fibrosis were enrolled in Group 1, and patients with grade II and III schistosomiasis-induced liver fibrosis were enrolled in Group 2. The machine learning binary classification tasks were created based on patients\'radiomics and clinical laboratory data from 2018 to 2021 as the training set, and patients\'radiomics and clinical laboratory data in 2022 as the validation set. The features of ultrasonographic images were labeled with the ITK-SNAP software, and the features of ultrasonographic images were extracted using the Python 3.7 package and PyRadiomics toolkit. The difference in the features of ultrasonographic images was compared between groups with t test or Mann-Whitney U test, and the key imaging features were selected with the least absolute shrinkage and selection operator (LASSO) regression algorithm. Four machine learning models were created using the Scikit-learn repository, including the support vector machine (SVM), random forest (RF), linear regression (LR) and extreme gradient boosting (XGBoost). The optimal machine learning model was screened with the receiver operating characteristic curve (ROC), and features with the greatest contributions to the differentiation features of ultrasound images in machine learning models with the SHapley Additive exPlanations (SHAP) method.
RESULTS: The ultrasonographic imaging data and clinical laboratory testing data from 491 schistosomiasis patients from 2019 to 2022 were included in the study, and a total of 851 radiomics features and 54 clinical laboratory indicators were captured. Following statistical tests (t = -5.98 to 4.80, U = 6 550 to 20 994, all P values < 0.05) and screening of key features with LASSO regression, 44 features or indicators were included for the subsequent modeling. The areas under ROC curve (AUCs) were 0.763 and 0.611 for the training and validation sets of the SVM model based on clinical laboratory indicators, 0.951 and 0.892 for the training and validation sets of the SVM model based on radiomics, and 0.960 and 0.913 for the training and validation sets of the multimodal SVM model. The 10 greatest contributing features or indicators in machine learning models included 2 clinical laboratory indicators and 8 radiomics features.
CONCLUSIONS: The multimodal machine learning models created based on ultrasound-based radiomics and clinical laboratory indicators are feasible for intelligent identification of schistosomiasis-induced liver fibrosis, and are effective to improve the classification effect of one-class data models.
［摘要］ 目的 探索基于B型超声影像与临床实验室指标构建血吸虫病肝纤维化分级诊断模型的可行性。方法 收集 2018—2022年江西省都昌县第二人民医院血吸虫病患者超声影像及临床实验室数据。以血吸虫病肝纤维化I级病例 为第1组, II级和III级病例为第2组; 选取2018—2021年病例数据为训练集、2022年病例数据为验证集, 构建机器学习二 分类模型。采用ITK-SNAP软件标记影像特征, 采用Python 3.7编程语言和PyRadiomics工具包提取影像特征。采用t 检 验或Mann-Whitney U 检验比较两组样本间影像特征差异, 并采用套索算法 (least absolute shrinkage and selection operator, LASSO) 进行关键影像特征筛选。采用Scikit-learn机器学习库进行机器学习建模, 包括支持向量机 (support vector machine, SVM) 、随机森林 (random forest, RF) 、线性回归 (linear regression, LR) 和极端梯度提升 (extreme gradient boosting, XGBoost) 等4种模型。采用受试者工作特征曲线 (receiver operating characteristic curve, ROC) 进行最优机器学习模型筛 选, 并使用沙普利加和解释 (SHapley Additive exPlanations, SHAP) 评估对机器学习模型中超声影像鉴别特征贡献度最高 的特征。结果 2019—2022年, 累计将491例血吸虫病患者超声影像和临床实验室检查数据纳入研究。累计提取了851 项影像组学特征和54项临床实验室指标, 经统计学检验 (t = -5.98 ~ 4.80, U = 6 550 ~ 20 994, P 均< 0.05) 及LASSO回归 特征筛选, 纳入44项特征或指标进入下一步研究。临床实验室指标SVM机器学习模型训练集和验证集ROC曲线下面 积 (area under curve, AUC) 分别为0.763和0.611, 超声影像组学SVM机器学习模型训练集和验证集AUC分别为0.951和 0.892, 多模态SVM机器学习模型训练集和验证集AUC分别为0.960和0.913。机器学习模型中贡献度居前10位的特征 或指标包括2项临床实验室指标和8项影像组学特征。结论 超声影像组学和临床实验室指标相结合的多模态机器学 习模型可用于血吸虫病肝纤维化智能识别, 并可提升单类数据模型的分类效果。.

UNASSIGNED: This study aimed to assess the accuracy of Mac-2 binding protein glycosylation isomer (M2BPGi) in predicting the stage of liver fibrosis.
UNASSIGNED: Articles published until October 10, 2023, were searched in the PubMed, Embase, Web of Science, and Cochrane Library databases. Pooled sensitivity, specificity, diagnostic odds ratio (DOR), summary receiver-operator curves (SROC), and Spearman\'s rank correlation coefficient were used to examine the accuracy of M2BPGi in predicting the stage of liver fibrosis. A 95% confidence interval (CI) was provided for each estimate.
UNASSIGNED: Twenty-four studies were included in this meta-analysis, including 3,839 patients with liver fibrosis, 409 of whom progressed to stage 4 or above. The pooled sensitivity, specificity, and area under the ROC (AUC) for M2BPGi predicting liver fibrosis ≥F3 were 0.74 (95% CI [0.65-0.82]), 0.84 (95% CI [0.76-0.89]), and 14.99 (95% CI [9.28-24.21]), respectively. The pooled sensitivity, specificity, and AUC for ≥F4 were 0.80 (95% CI [0.70-0.88]), 0.80 (95% CI [0.73-0.86]), and 16.43 (95% CI [0.84-0.90]), respectively.
UNASSIGNED: Among different sample partitions, M2BPGi has the best diagnostic performance for liver fibrosis stage ≥4. Furthermore, the cutoff of 1-2 is more accurate than that of 0-1 or 2-3 for fibrosis ≥ F3 and ≥ F4.
UNASSIGNED: CRD42023483260.

UNASSIGNED: To use hepatic uptake index (HUI) of liver lobes on gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced magnetic resonance imaging (MRI) to discriminate between patients with hepatitis B-related cirrhosis in compensated and decompensated statuses.
UNASSIGNED: Forty-four consecutive patients with hepatitis B-related cirrhosis who underwent Gd-EOB-DTPA-enhanced MRI were divided into compensated and decompensated statuses based on clinical evaluation. Volume and signal intensity of individual lobes were retrospectively measured to calculate HUI of the right liver lobe (RHUI), medial (MHUI) and lateral (LHUI) left liver lobes, and caudate lobe (CHUI). Spearman\'s rank correlation analyses were performed to evaluate relationships of lobe-based HUI with Child-Pugh and model for end-stage liver disease (MELD) scoring system scores in compensated and decompensated statuses. The Mann-Whitney U-test was used to compare the lobe-based HUI between compensated and decompensated statuses. The performance of lobe-based HUI in distinguishing cirrhosis was evaluated using receiver operating characteristic (ROC) analysis, and the area under the ROC curve (AUC) was calculated as a measure of accuracy. Delong\'s method was used for statistical analysis to elucidate which HUI is optimal.
UNASSIGNED: Compensated and decompensated liver cirrhosis were confirmed in 25 (56.82%) and 19 (43.18%) patients, respectively. According to Spearman\'s rank correlation analysis, RHUI, MHUI, LHUI, and CHUI were all significantly associated with Child-Pugh and MELD scores (all P values <0.05). Receiver operating characteristic analysis demonstrated that among all lobe-based HUI parameters, RHUI could best perform the previous discrimination with a cut-off of 485.73 and obtain an AUC of 0.867. The AUC of RHUI improved and was significantly different from that of MHUI, LHUI, and CHUI (P = 0.03, P = 0.007, and P < 0.001, respectively, Delong\'s test).
UNASSIGNED: The RHUI could help quantitatively discriminate hepatitis B-related cirrhosis between compensated and decompensated statuses.

Metabolic dysfunction-associated fatty liver disease (MAFLD) is the most prevalent chronic liver condition worldwide. Current liver enzyme-based screening methods have limitations that may missed diagnoses and treatment delays. Regarding Chen et al, the risk of developing MAFLD remains elevated even when alanine aminotransferase levels fall within the normal range. Therefore, there is an urgent need for advanced diagnostic techniques and updated algorithms to enhance the accuracy of MAFLD diagnosis and enable early intervention. This paper proposes two potential screening methods for identifying individuals who may be at risk of developing MAFLD: Lowering these thresholds and promoting the use of noninvasive liver fibrosis scores.

UNASSIGNED: Biliary atresia (BA) is a devastating congenital disease characterized by inflammation and progressive liver fibrosis. Activation of hepatic stellate cells (HSCs) plays a central role in the pathogenesis of hepatic fibrosis. Our study aimed to investigate the pharmacological effect and potential mechanism of pirfenidone (PFD) and andrographolide (AGP) separately and together on liver fibrosis of BA.
UNASSIGNED: The bile ducts of male C57BL/6J mice were ligated or had the sham operation. The in vivo effects of PFD and/or AGP on liver fibrosis of BA were evaluated. Human hepatic stellate cells (LX-2) were also treated with PFD and/or AGP in vitro.
UNASSIGNED: PFD and/or AGP ameliorates liver fibrosis and inflammation in the mice model of BA, as evidenced by significant downregulated in the accumulation of collagen fibers, hepatic fibrosis markers (α-SMA, collagen I, and collagen IV), and inflammatory markers (IL-1β, IL-6, and TNF-α). Moreover, compared with monotherapy, these changes are more obvious in the combined treatment of PFD and AGP. Consistent with animal experiments, hepatic fibrosis markers (α-SMA, collagen I, and CTGF) and inflammatory markers (IL-1β, IL-6, and TNF-α) were significantly decreased in activated LX-2 cells after PFD and/or AGP treatment. In addition, PFD and/or AGP inhibited the activation of HSCs by blocking the TGF-β/Smad signaling pathway, and the combined treatment of PFD and AGP synergistically inhibited the phosphorylation of Smad2 and Smad3.
UNASSIGNED: The combined application of PFD and AGP exerted superior inhibitive effects on HSC activation and liver fibrosis by mediating the TGF-β/Smad signaling pathway as compared to monotherapy. Therefore, the combination of PFD and AGP may be a promising treatment strategy for liver fibrosis in BA.

Liver sinusoidal endothelial cells (LSECs) are highly specialized endothelial cells that represent the interface between blood cells on one side and hepatocytes on the other side. LSECs not only form a barrier within the hepatic sinus, but also play important physiological functions such as regulating hepatic vascular pressure, anti-inflammatory and anti-fibrotic. Pathologically, pathogenic factors can induce LSECs capillarization, that is, loss of fenestra and dysfunction, which are conducive to early steatosis, lay the foundation for the progression of metabolic dysfunction-associated fatty liver disease (MAFLD), and accelerate metabolic dysfunction-associated steatohepatitis (MASH) and liver fibrosis. The unique localization, phenotype, and function of LSECs make them potential candidates for reducing liver injury, inflammation, and preventing or reversing fibrosis in the future.

Liver fibrosis is characterized by the activation of perivascular hepatic stellate cells (HSCs), the release of fibrogenic nanosized extracellular vesicles (EVs), and increased HSC glycolysis. Nevertheless, how glycolysis in HSCs coordinates fibrosis amplification through tissue zone-specific pathways remains elusive. Here, we demonstrate that HSC-specific genetic inhibition of glycolysis reduced liver fibrosis. Moreover, spatial transcriptomics revealed a fibrosis-mediated up-regulation of EV-related pathways in the liver pericentral zone, which was abrogated by glycolysis genetic inhibition. Mechanistically, glycolysis in HSCs up-regulated the expression of EV-related genes such as Ras-related protein Rab-31 (RAB31) by enhancing histone 3 lysine 9 acetylation on the promoter region, which increased EV release. Functionally, these glycolysis-dependent EVs increased fibrotic gene expression in recipient HSC. Furthermore, EVs derived from glycolysis-deficient mice abrogated liver fibrosis amplification in contrast to glycolysis-competent mouse EVs. In summary, glycolysis in HSCs amplifies liver fibrosis by promoting fibrogenic EV release in the hepatic pericentral zone, which represents a potential therapeutic target.

The mortality rate related to variceal bleeding is high in patients with liver cirrhosis. Early detection and treatment of varices can reduce the risk of hemorrhage and thus decrease the mortality rate related to variceal bleeding. The study comprised 81 cirrhotic patients in training set, who were categorized into 2 groups: the patients with esophageal varices (EVs group) and the patients without esophageal varices (non-EVs group). The disparity in Cystatin C/albumin ratio (CAR) was assessed between these 2 groups. Subsequently, a regression model was constructed by generating a receiver operating characteristic (ROC) curve to calculate the area under the curve (AUC). Then an external validation was performed in 25 patients. Among patients with cirrhosis in training set, a statistically significant difference in CAR was observed between the EVs group and non-EVs group (P < .05). At the CAR cutoff value of 2.79*10-5, the AUC for diagnosing EVs were 0.666. Further, a multivariate logistic regression model was constructed, after adjusting the model, the AUC for EVs diagnosis were 0.855. And the external validation showed that the model could not be considered as a poor fit. CAR exhibits potential as an early detection marker for EVs in liver cirrhosis, and the regression model incorporating CAR demonstrates a strong capability for early EVs diagnosis.

This study aimed to assess the safety and efficacy of interventional embolization in cirrhotic patients with refractory hepatic encephalopathy (HE) associated with large spontaneous portosystemic shunts (SPSS). Inverse probability of treatment weighting (IPTW) was employed to minimize potential bias. A total of 123 patients were included in this study (34 in the embolization group and 89 in the control group). In the unadjusted cohort, the embolization group demonstrated significantly better liver function, a larger total area of SPSS, and a higher percentage of patients with serum ammonia levels > 60 µmol/L and the presence of hepatocellular carcinoma (HCC) (all P < 0.05). In the IPTW cohort, baseline characteristics were comparable between the two groups (all P > 0.05). Patients in the embolization group exhibited significantly longer HE-free survival compared to the control group in both the unadjusted and IPTW cohorts (both P < 0.05). Subsequent subgroup analyses indicated that patients with serum ammonia level > 60 μmol/L, hepatopetal flow within the portal trunk, the presence of solitary SPSS, a baseline HE grade of II, and the absence of HCC at baseline showed statistically significant benefit from embolization treatment (all P < 0.05). No early procedural complications were observed in the embolization group. The incidence of long-term postoperative complications was comparable to that in the control group (all P > 0.05). Hence, interventional embolization appears to be a safe and effective treatment modality for cirrhotic patients with refractory HE associated with large SPSS. However, the benefits of embolization were discernible only in a specific subset of patients.