Machine Learning-Based Models for Advanced Fibrosis and Cirrhosis Diagnosis in Chronic Hepatitis B Patients With Hepatic Steatosis.

BACKGROUND AND AIMS: The global rise of chronic hepatitis B (CHB) superimposed on hepatic steatosis (HS) warrants noninvasive, precise tools for assessing fibrosis progression. This study leveraged machine learning (ML) to develop diagnostic models for advanced fibrosis and cirrhosis in this patient population. METHODS: Treatment-naive CHB patients with concurrent HS who underwent liver biopsy in 10 medical centers were enrolled as a training cohort and an independent external validation cohort (NCT05766449). Six ML models were implemented to predict advanced fibrosis and cirrhosis. The final models, derived from SHAP (Shapley Additive exPlanations), were compared with Fibrosis-4 Index, nonalcoholic fatty liver disease Fibrosis Score, and aspartate aminotransferase-to-platelet ratio index using the area under receiver-operating characteristic curve (AUROC) and decision curve analysis (DCA). RESULTS: Of 1,198 eligible patients, the random forest model achieved AUROCs of 0.778 (95% confidence interval [CI], 0.749-0.807) for diagnosing advanced fibrosis (random forest advanced fibrosis model) and 0.777 (95% CI, 0.748-0.806) for diagnosing cirrhosis (random forest cirrhosis model) in the training cohort, and maintained high AUROCs in the validation cohort. In the training cohort, the random forest advanced fibrosis model obtained an AUROC of 0.825 (95% CI, 0.787-0.862) in patients with hepatitis B virus DNA ≥105 IU/mL, and the random forest cirrhosis model had an AUROC of 0.828 (95% CI, 0.774-0.883) in female patients. The 2 models outperformed Fibrosis-4 Index, nonalcoholic fatty liver disease Fibrosis Score, and aspartate aminotransferase-to-platelet ratio index in the training cohort, and also performed well in the validation cohort. CONCLUSIONS: The random forest models provide reliable, noninvasive tools for identifying advanced fibrosis and cirrhosis in CHB patients with concurrent HS, offering a significant advancement in the comanagement of the 2 diseases. CLINICALTRIALS: gov, Number: NCT05766449.

Deciphering lung granulomas in HIV & TB co-infection: unveiling macrophages aggregation with IL6R/STAT3 activation.

Tuberculosis (TB) remains a leading cause of mortality among individuals coinfected with HIV, characterized by progressive pulmonary inflammation. Despite TB's hallmark being focal granulomatous lung lesions, our understanding of the histopathological features and regulation of inflammation in HIV & TB coinfection remains incomplete. In this study, we aimed to elucidate these histopathological features through an immunohistochemistry analysis of HIV & TB co-infected and TB patients, revealing marked differences. Notably, HIV & TB granulomas exhibited aggregation of CD68 + macrophage (Mφ), while TB lesions predominantly featured aggregation of CD20+ B cells, highlighting distinct immune responses in coinfection. Spatial transcriptome profiling further elucidated CD68+ Mφ aggregation in HIV & TB, accompanied by activation of IL6 pathway, potentially exacerbating inflammation. Through multiplex immunostaining, we validated two granuloma types in HIV & TB versus three in TB, distinguished by cell architecture. Remarkably, in the two types of HIV & TB granulomas, CD68 + Mφ highly co-expressed IL6R/pSTAT3, contrasting TB granulomas' high IFNGRA/SOCS3 expression, indicating different signaling pathways at play. Thus, activation of IL6 pathway may intensify inflammation in HIV & TB-lungs, while SOCS3-enriched immune microenvironment suppresses IL6-induced over-inflammation in TB. These findings provide crucial insights into HIV & TB granuloma formation, shedding light on potential therapeutic targets, particularly for granulomatous pulmonary under HIV & TB co-infection. Our study emphasizes the importance of a comprehensive understanding of the immunopathogenesis of HIV & TB coinfection and suggests potential avenues for targeting IL6 signaling with SOCS3 activators or anti-IL6R agents to mitigate lung inflammation in HIV & TB coinfected individuals.

Histological features of chronic hepatitis B patients with normal alanine aminotransferase according to different criteria.

BACKGROUND: The upper limits of normal (ULNs) for alanine aminotransferase (ALT) are different among international guidelines for chronic hepatitis B (CHB). We aimed to investigate the proportion of significant histological disease in Asian patients with CHB with detectable hepatitis B virus (HBV) DNA under diverse ALT ULNs. METHODS: Consecutive patients with CHB and detectable HBV DNA who underwent liver biopsy were retrospectively included from four tertiary hospitals. Above grade 2 inflammation and stage 2 fibrosis were defined as significant inflammation and significant fibrosis, respectively. Significant histological disease was defined as above grade 2 inflammation or stage 2 fibrosis. RESULTS: Among the 414 patients with detectable HBV DNA and normal ALT, the proportion of those with significant histological disease was lower (59.7%) according to the ULN for ALT at 30/19 U/L (male/female), while the corresponding proportions were 66.7% and 62.3% according to the ULNs of 40 U/L and 35/25 U/L (male/female), respectively. In patients with detectable HBV DNA and normal ALT levels without significant fibrosis, the proportions of significant inflammation were comparable among different ULNs of ALT at 40 U/L (30.7%), 35/25 U/L (27.3%) and 30/19 U/L (25.0%). The proportion of significant histological disease was significantly lower in patients with normal ALT for 2 determinations at least 6 months apart compared to patients with normal ALT once. CONCLUSIONS: Although a more stringent ALT ULN may reduce the risk of the presence of significant histological disease in patients with detectable HBV DNA, the rates of significant histological disease remain high. Persistently normal ALT levels are more important for excluding patients with CHB with a high probability of significant histological disease.

Development of a machine learning-based model to predict hepatic inflammation in chronic hepatitis B patients with concurrent hepatic steatosis: a cohort study.

Background: With increasingly prevalent coexistence of chronic hepatitis B (CHB) and hepatic steatosis (HS), simple, non-invasive diagnostic methods to accurately assess the severity of hepatic inflammation are needed. We aimed to build a machine learning (ML) based model to detect hepatic inflammation in patients with CHB and concurrent HS. Methods: We conducted a multicenter, retrospective cohort study in China. Treatment-naive CHB patients with biopsy-proven HS between April 2004 and September 2022 were included. The optimal features for model development were selected by SHapley Additive explanations, and an ML algorithm with the best accuracy to diagnose moderate to severe hepatic inflammation (Scheuer's system ≥ G3) was determined and assessed by decision curve analysis (DCA) and calibration curve. This study is registered with ClinicalTrials.gov (NCT05766449). Findings: From a pool of 1,787 treatment-naive patients with CHB and HS across eleven hospitals, 689 patients from nine of these hospitals were chosen for the development of the diagnostic model. The remaining two hospitals contributed to two independent external validation cohorts, comprising 509 patients in validation cohort 1 and 589 in validation cohort 2. Eleven features regarding inflammation, hepatic and metabolic functions were identified. The gradient boosting classifier (GBC) model showed the best performance in predicting moderate to severe hepatic inflammation, with an area under the receiver operating characteristic curve (AUROC) of 0.86 (95% CI 0.83-0.88) in the training cohort, and 0.89 (95% CI 0.86-0.92), 0.76 (95% CI 0.73-0.80) in the first and second external validation cohorts, respectively. A publicly accessible web tool was generated for the model. Interpretation: Using simple parameters, the GBC model predicted hepatic inflammation in CHB patients with concurrent HS. It holds promise for guiding clinical management and improving patient outcomes. Funding: This research was supported by the National Natural Science Foundation of China (No. 82170609, 81970545), Natural Science Foundation of Shandong Province (Major Project) (No. ZR2020KH006), Natural Science Foundation of Jiangsu Province (No.BK20231118), Tianjin Key Medical Discipline (Specialty), Construction Project, TJYXZDXK-059B, Tianjin Health Science and Technology Project key discipline special, TJWJ2022XK034, and Research project of Chinese traditional medicine and Chinese traditional medicine combined with Western medicine of Tianjin municipal health and Family Planning Commission (2021022).

Liver inflammation activity in patients with autoimmune hepatitis with normal alanine aminotransferase and immunoglobulin G levels.

Background and aims: Normal serum transaminases and immunoglobulin G (IgG) levels are surrogate markers for hepatic histologic disease activity in autoimmune hepatitis (AIH). This study aimed to evaluate liver inflammation in patients with AIH with normal serum alanine aminotransferase (ALT) and IgG levels. Methods: Two hundred and five AIH patients who underwent liver biopsy in four medical centers were included. Logistic regression analysis was used to identify risk factors associated with advanced inflammation. Results: One hundred and thirty-one (63.9 %) AIH patients had advanced liver inflammation, and 108 (52.7 %) patients had advanced liver fibrosis. 60.0 % of patients with normal ALT and 51.7 % of patients with normal ALT and IgG had advanced inflammation. However, 76.7 % and 35.0 % of patients with or without advanced fibrosis with normal ALT had advanced inflammation, while the corresponding proportions of advanced inflammation were 78.6 % and 26.7 % in patients with normal ALT and IgG, respectively. Moreover, 81.0 % and 44.8 % of patients with and without cirrhosis with normal ALT had advanced inflammation, while the corresponding proportions were 83.3 % and 29.4 % in patients with normal ALT and IgG, respectively. Red cell distribution width (OR = 1.325, 95%CI 1.045-1.681, P = 0.020) and PT (OR = 1.514, 95%CI 1.138-2.014, P = 0.004) were independent factors associated with advanced inflammation. Conclusions: High proportion of advanced inflammation was found in AIH patients with normal ALT and IgG levels despite without advanced fibrosis. Although using non-invasive methods may contribute to rule out liver fibrosis in AIH patients with normal ALT and IgG levels, liver biopsy is encouraged to assess liver inflammation.

NAFLD is associated with less severe liver fibrosis in chronic hepatitis B: A multi-center, retrospective study.

INTRODUCTION AND OBJECTIVES: Chronic hepatitis B (CHB) may progress to more serious liver diseases and it is often accompanied by non-alcoholic fatty liver disease (NAFLD). NAFLD and CHB share risk factors for liver fibrosis and cirrhosis, but the influence of NAFLD on fibrosis progression is controversial. This retrospective study evaluated the prevalence of NAFLD in patients with CHB and investigated associations between NAFLD and liver fibrosis in a large multi-center cohort of hepatitis B patients submitted to liver biopsy. PATIENTS AND METHODS: Treatment-naïve patients with CHB who underwent liver biopsy were analyzed. Propensity score matching (PSM) was performed to adjust the confounders between patients with and without NAFLD. RESULTS: A total of 1496 CHB patients were included. Two hundred and ninety (19.4%) patients were diagnosed with NAFLD by liver biopsy. The proportions of significant liver fibrosis (52.8% vs. 63.9%, P<0.001), advanced liver fibrosis (27.2% vs. 36.5%, P=0.003), and cirrhosis (13.4% vs. 19.7%, P=0.013) was considerably lower in CHB patients with NAFLD compared to those without NAFLD. 273 patients were included in each group after PSM adjusted for age, sex, hepatitis B envelope antigen status, and hepatitis B virus DNA. Liver fibrosis remained less severe in CHB patients with NAFLD than those without NAFLD (P<0.05) after PSM. The presence of NAFLD was considered an independent negative factor of significant liver fibrosis (odds ratio (OR) 0.692, P=0.013) and advanced liver fibrosis (OR 0.533, P = 0.002) in CHB patients. CONCLUSIONS: NAFLD is not uncommon in CHB patients with the prevalence of 19.4%. The presence of NAFLD is associated with less severe liver fibrosis in CHB patients. OF THE STUDY/TRIAL: NCT03097952.

Noninvasive diagnosis of significant liver inflammation in patients with chronic hepatitis B in the indeterminate phase.

The presence of significant liver inflammation is an important indication for antiviral treatment in patients with chronic hepatitis B (CHB) in the indeterminate phase. We aimed to establish a non-invasive nomogram to predict significant liver inflammation in these patients. A total of 195 CHB patients in the indeterminate phase were randomly split into training and validation sets. The least absolute shrinkage and selection operator and logistic regression were applied to identify risk factors and establish a predictive model. A calibration curve, decision curve analysis (DCA), and receiver operating characteristic (ROC) curve were applied to assess the performance of the nomogram. The median age was 42.0 y and 59.5% of the patients were male. Alkaline phosphatase, γ-glutamyl transpeptidase, and prothrombin time were independent predictors for significant liver inflammation and selected to establish the AGP-nomogram. The calibration plot demonstrated that the predicted results matched the actual values. The DCA showed a high net benefit when the threshold probability was 25-83% in the training set and 31-100% in the validation set. The areas under ROC curves of AGP-nomogram in predicting significant inflammation were significantly higher than ALT in the training set (0.744 vs. 0.642, P = 0.049) and validation set (0.766 vs. 0.660, P = 0.047). The ability of AGP-nomogram in predicting advanced inflammation was also superior to ALT. The AGP-nomogram can accurately identify significant inflammation in CHB patients in the indeterminate phase, and its application may reduce the need for liver biopsy and help identify candidates for antiviral treatment.Abbreviations: AASLD: American Association for the Study of Liver Diseases; ALB: albumin; ALP: alkaline phosphatase; ALT: alanine aminotransferase; APRI: aspartate aminotransferase-to-platelet ratio index; AST: aspartate aminotransferase; AUROC: area under the receiver operating characteristic curve; CHB: chronic hepatitis B; CI: confidence interval; DCA: decision curve analysis; FIB-4: fibrosis index based on the four factors; GLB: globulin; GGT: γ-glutamyl transpeptidase; HBcAb: hepatitis B core antibody; HBeAg: hepatitis B e antigen; HBsAg: hepatitis B surface antigen; HBV: hepatitis B virus; HCC: hepatocellular carcinoma; HIV: human immunodeficiency virus; INR: international-normalized ratio; IQR: interquartile range; LASSO: least absolute shrinkage and selection operator; LB: liver biopsy; LR: Likelihood ratio; NAFLD: non-alcoholic fatty liver disease; NPV: negative predictive value; PLT: platelets; PPV: positive predictive value; PT: prothrombin time; ROC: receiver operating characteristic; TB: total bilirubin; TE: transient elastography; ULN: upper limit of normal.

A novel web-based online nomogram to predict advanced liver fibrosis in patients with autoimmune hepatitis-primary biliary cholangitis overlap syndrome.

Background: Patients with autoimmune hepatitis-primary biliary cholangitis (AIH-PBC) overlap syndrome have a worse prognosis compared to AIH or PBC alone and accurately predicting the severity and dynamically monitoring the progression of disease are therefore essential. We aimed to develop a nomogram-based model to predict advanced liver fibrosis in patients with AIH-PBC overlap syndrome. Methods: A total of 121 patients with AIH-PBC overlap syndrome were retrospectively included and randomly assigned to a development set and a validation set. Backward stepwise regression's best model with the lowest AIC was employed to create a nomogram. Diagnose accuracy was evaluated using the area under the receiver operator characteristic curve (AUROC), calibration analysis, and decision curve analysis (DCA) and was compared with aspartate aminotransferase-to-platelet ratio (APRI) and fibrosis index based on four factors-4 (FIB-4) score. Results: The median age of patients was 53.0 years (IQR: 46.0-63.0), and female patients accounted for 95.0 %. Platelets, globulin, total bilirubin, and prothrombin time were associated with advanced fibrosis (≥S3) and used to construct an AIH-PBC overlap syndrome fibrosis (APOSF)-nomogram (available online at https://ndth-zzy.shinyapps.io/APOSF-nomogram/). The AUROCs of APOSF-nomogram were 0.845 (95 % CI: 0.754-0.936) and 0.843 (95 % CI: 0.705-0.982) in development set and validation set respectively, which was significantly better than APRI and FIB-4. Calibration revealed that the estimated risk fits well with biopsy-proven observation. DCA outperformed APRI and FIB4 in terms of net benefit, demonstrating clinical utility. Conclusion: This novel non-invasive web-based online APOSF-nomogram provided a convenient tool for identifying advanced fibrosis in patients with AIH-PBC overlap syndrome. Further prospective, multicenter studies with large sample size are necessary to validate the applicability of APOSF-nomogram.

Corrigendum: Novel molecular therapeutics targeting signaling pathway to control hepatitis B viral infection.

[This corrects the article DOI: 10.3389/fcimb.2022.847539.].

Development and Validation of a Nomogram to Predict Significant Liver Inflammation in Patients with Chronic Hepatitis B.

Background: Noninvasive diagnosis of liver inflammation is important for patients with chronic hepatitis B (CHB). This study aimed to develop a nomogram to predict significant liver inflammation for CHB patients. Methods: CHB patients who underwent liver biopsy were retrospectively collected and randomly divided into a development set and a validation set. The least absolute shrinkage and selection operator regression and logistic regression analysis were used to select independent predictors of significant liver inflammation, and a nomogram was developed. The performance of nomogram was assessed by receiver operating characteristic (ROC) curves, calibration curves and decision curve analysis (DCA). Results: A total of 1019 CHB patients with a median age of 39.0 years were included. Alanine aminotransaminase (ALT, P = 0.018), gamma-glutamyl transpeptidase (P = 0.013), prothrombin time (P < 0.001), and HBV DNA level (P = 0.030) were identified as independent predictors of significant liver inflammation in the development set. A model namely AGPD-nomogram was developed based on the above parameters. The area under the ROC curve in predicting significant inflammation was 0.765 (95% CI: 0.727-0.803) and 0.766 (95% CI: 0.711-0.821) in the development and validation sets, which were significantly higher than other indexes. The AGPD-nomogram had a high predictive value in patients with normal ALT. Moreover, the nomogram was proven to be clinically useful by DCA. Conclusion: A visualized AGPD-nomogram which incorporated routine clinical parameters was proposed to facilitate the prediction of significant liver inflammation in CHB patients. This nomogram had high accuracy in the identification of significant liver inflammation and would be a useful tool for the better management of CHB patients, especially for those with normal ALT.

Develop and validate a novel online AIHI-nomogram to predict severe liver inflammation in patients with autoimmune hepatitis.

INTRODUCTION AND OBJECTIVES: Assessment of liver inflammation plays a vital role in the management of patients with autoimmune hepatitis (AIH). We aimed to establish and validate a nomogram to predict severe liver inflammation in AIH patients. PATIENTS AND METHODS: AIH patients who underwent liver biopsy were included and randomly divided into a training set and a validation set. Independent predictors of severe liver inflammation were selected by the least absolute shrinkage and selection operator regression from the training set and used to conduct a nomogram. Receiver characteristic curves (ROC), calibration curves, and decision curve analysis (DCA) were adopted to evaluate the performance of nomogram. RESULTS: Of the 213 patients, female patients accounted for 83.1% and the median age was 53.0 years. The albumin, gamma-glutamyl transpeptidase, total bilirubin, red cell distribution width, prothrombin time, and platelets were independent predictors of severe inflammation. An online AIHI-nomogram was established and was available at https://ndth-zzy.shinyapps.io/AIHI-nomogram/. The calibration curve revealed that the AIHI-nomogram had a good agreement with actual observation in the training and validation sets. The area under the ROCs of AIHI-nomogram were 0.795 in the training set and 0.759 in the validation set, showing significantly better performance than alanine aminotransferase and immunoglobulin G in the training and validation sets, as well in AIH patients with normal ALT in the training set. DCA indicated that the AIHI-nomogram was clinically useful. CONCLUSIONS: This novel AIHI-nomogram provided an excellent prediction of severe liver inflammation in AIH patients and could be used for the better management of AIH.

Antithrombin III activity is associated with prognosis, infection, and inflammation in patients with hepatitis B virus-related acute-on-chronic liver failure.

OBJECTIVE: Patients with hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) are characterized by severe liver function impairment, coagulation disorder, and multiple organ function impairment. The aim of this study was to explore the predictive value of antithrombin Ⅲ activity to the prognosis of HBV-ACLF patients. METHODS: A total of 186 HBV-ACLF patients were included in the analysis, and the baseline clinical data of patients were recorded to analyze the risk factors affecting the 30-day survival outcome of patients. Bacterial infection, sepsis, and hepatic encephalopathy were observed in ACLF patients. Antithrombin Ⅲ activity and serum cytokine levels were determined. RESULTS: The antithrombin Ⅲ activity of ACLF patients in the death group was significantly lower than that in the survival group, and antithrombin Ⅲ activity was independent factors affecting the 30-day outcome. The areas under the receiver operation characteristic (ROC) curve of antithrombin Ⅲ activity to predict the 30-day mortality of ACLF was 0.799. Survival analysis showed that the mortality of patients with antithrombin Ⅲ activity less than 13% was significantly increased. Patients with bacterial infection and sepsis had lower antithrombin Ⅲ activity than those without infection. Antithrombin Ⅲ activity was positively correlated with platelet count, fibrinogen, interferon (IFN)-γ, interleukin (IL)-13, IL-1ß, IL-4, IL-6, tumor necrosis factor-α, IL-23, IL-27, and IFN-α, but negatively correlated with C-reactive protein, D dimer, total bilirubin, and creatinine levels. CONCLUSION: As a natural anticoagulant, antithrombin Ⅲ can be regarded as a marker of inflammation and infection in patients with HBV-ACLF, and as a predictor of survival outcome in patients with ACLF.

Effect of Chinese Medicines combined with transarterial chemoembolization on primary hepatic carcinoma: A systematic review and meta-analysis.

BACKGROUND: To systematically evaluate the survival rate and postoperative adverse reactions of patients with hepatocellular carcinoma treated with traditional Chinese medicine combined with TACE by meta-analysis. METHODS: Four major literature databases (Cochrane Library, Embase, PubMed, and Web of Science) were retrieved to collect published English articles since 2009. After determining the random effect model or fixed utility model based on a heterogeneity test, odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. RESULTS: This meta-analysis included 8 prospective studies published between 2009 and 2019. Due to moderate heterogeneity (P < .05, I2 = 54.8%), Therefore, the random effect model is used to analyze the data, so as to explore the relationship between CMs combined with TACE treatment and survival rate and postoperative adverse reactions. All the comprehensive test results show that there is a statistical significance between CMs combined with TACE treatment and survival rate. (OR = 1.88, 95% CI 1.34-2.64, P = .03). Then subgroup analysis and sensitivity analysis were carried out. The results indicated that the overall results ranged from 1.12(95% CI = 1.03-1.11) to 1.21(95% CI = 1.22-1.33). CONCLUSIONS: The 1-year survival rate of patients treated with traditional Chinese medicine TACE is a protective factor, and the quality score included in the study affects the evaluation of the effective dose. At the same time, traditional Chinese medicine combined with TACE has nothing to do with the reduction of postoperative complications.

An easy-to-use AIHF-nomogram to predict advanced liver fibrosis in patients with autoimmune hepatitis.

Background: The evaluation of liver fibrosis is essential in the management of patients with autoimmune hepatitis (AIH). We aimed to establish and validate an easy-to-use nomogram to identify AIH patients with advanced liver fibrosis. Methods: AIH patients who underwent liver biopsies were included and randomly divided into a training set and a validation set. The least absolute shrinkage and selection operator (LASSO) regression was used to select independent predictors of advanced liver fibrosis from the training set, which were utilized to establish a nomogram. The performance of the nomogram was evaluated using the receiver characteristic curve (ROC), calibration curve, and decision curve analysis (DCA). Results: The median age of 235 patients with AIH was 54 years old, with 83.0% of them being female. Six independent factors associated with advanced fibrosis, including sex, age, red cell distribution width, platelets, alkaline phosphatase, and prothrombin time, were combined to construct a predictive AIH fibrosis (AIHF)-nomogram. The AIHF-nomogram showed good agreement with real observations in the training and validation sets, according to the calibration curve. The AIHF-nomogram performed significantly better than the fibrosis-4 and aminotransferase-to-platelet ratio scores in the training and validation sets, with an area under the ROCs for predicting advanced fibrosis of 0.804 in the training set and 0.781 in the validation set. DCA indicated that the AIHFI-nomogram was clinically useful. The nomogram will be available at http://ndth-zzy.shinyapps.io/AIHF-nomogram/as a web-based calculator. Conclusions: The novel, easy-to-use web-based AIHF-nomogram model provides an insightful and applicable tool to identify AIH patients with advanced liver fibrosis.

A novel non-invasive model for the prediction of advanced liver fibrosis in chronic hepatitis B patients with NAFLD.

There are still lack of non-invasive models to evaluate liver fibrosis in chronic hepatitis B (CHB) patients with nonalcoholic fatty liver disease (NAFLD). We aimed to establish a predictive model for advanced fibrosis in these patients. A total of 504 treatment-naive CHB patients with NAFLD who underwent liver biopsy were enrolled and randomly divided into a training set (n = 336) and a validation set (n = 168). Receiver operating characteristic (ROC) curve was used to compare predicting accuracy for the different models. One hundred fifty-six patients (31.0%) had advanced fibrosis. In the training set, platelet, prothrombin time, type 2 diabetes, HBeAg positivity and globulin were significantly associated with advanced fibrosis by multivariable analysis. A predictive model namely PPDHG for advanced fibrosis was developed based on these parameters. The areas under the ROC curve (AUROC) of PPDHG with an optimal cut-off value of -0.980 in predicting advanced fibrosis was 0.817 (95% confidence interval 0.772 to 0.862), with a sensitivity of 81.82% and a specificity of 66.81%. The predicting accuracy of PPDHG for advanced fibrosis was significantly superior to AST to platelet ratio index (APRI), fibrosis-4 score (FIB-4) and NAFLD fibrosis score (NFS). Further analysis revealed that the AUROC of PPDHG remained significantly higher than FIB-4 and NFS indexes, while it was comparable with APRI for predicting advanced fibrosis in the validation set. PPDHG had a better predicting performance than established models for advanced fibrosis in CHB patients with NAFLD. The application of PPDHG can reduce the necessary for liver biopsy in these patients.

Significant histological disease of patients with chronic hepatitis B virus infection in the grey zone.

BACKGROUND: Many patients with chronic hepatitis B (CHB) do not meet the definitions of the traditional natural phases and are classified as being in the grey zone (GZ). AIMS: To investigate liver histology, and to establish a management strategy for patients with CHB in the GZ. METHODS: This study included 1043 patients with CHB who underwent liver biopsy. Phases of natural history were determined according to the AASLD 2018 hepatitis B guidance. CHB patients in the GZ were divided into HBeAg-positive, normal ALT and HBV DNA ≤106  IU/ml (GZ-A); HBeAg-positive, elevated ALT and HBV DNA ≤2 × 104  IU/ml (GZ-B); HBeAg-negative, normal ALT and HBV DNA ≥2 × 103  IU/ml (GZ-C) and HBeAg-negative, elevated ALT and HBV DNA ≤2 × 103  IU/ml (GZ-D). Significant histological disease was defined as liver inflammation ≥G2 and/or liver fibrosis ≥S2. RESULTS: Two hundred and forty two (23.2%) patients were in the GZ. Approximately 72.7% had significant histological disease. HBeAg-positive GZ CHB patients had a higher proportion of significant histological disease than HBeAg-negative GZ patients (91.1% vs. 68.5%, p = 0.002). GZ-D (42.6%) was the dominant category, followed by GZ-C (38.8%), GZ-A (10.3%) and GZ-B (8.3%). The highest proportion of significant histological disease was observed patients in GZ-B (100.0%), followed by GZ-A (84.0%), GZ-D (69.9%) and GZ-C (67.0%). Prothrombin time (PT) was an independent risk factor of significant histological disease in the HBeAg-negative GZ. CONCLUSIONS: Over 70% of GZ CHB patients had significant histological disease. We recommend antiviral treatment for HBeAg-positive and HBeAg-negative GZ CHB patients with high PT.

Novel Molecular Therapeutics Targeting Signaling Pathway to Control Hepatitis B Viral Infection.

Numerous canonical cellular signaling pathways modulate hepatitis B virus (HBV) replication. HBV genome products are known to play a significant role in regulating these cellular pathways for the liver's viral-related pathology and physiology and have been identified as the main factor in hepatocarcinogenesis. Signaling changes during viral replication ultimately affect cellular persistence, multiplication, migration, genome instability, and genome damage, leading to proliferation, evasion of apoptosis, block of differentiation, and immortality. Recent studies have documented that numerous signaling pathway agonists or inhibitors play an important role in reducing HBV replication in vitro and in vivo, and some have been used in phase I or phase II clinical trials. These optional agents as molecular therapeutics target cellular pathways that could limit the replication and transcription of HBV or inhibit the secretion of the small surface antigen of HBV in a signaling-independent manner. As principle-based available information, a combined strategy including antiviral therapy and immunomodulation will be needed to control HBV infection effectively. In this review, we summarize recent findings on interventions of molecular regulators in viral replication and the interactions of HBV proteins with the components of the various targeting cellular pathways, which may assist in designing novel agents to modulate signaling pathways to prevent HBV replication or carcinogenesis.

Umbilical cord blood-derived mesenchymal stem cells in treating a critically ill COVID-19 patient.

INTRODUCTION: The coronavirus disease 2019 (COVID-19) pandemic is spreading rapidly. Critically ill cases of COVID-19 can rapidly progress to acute respiratory distress syndrome and multiple organ failures. However, no effective drugs have been available till now, leading to more than 300,000 deaths up to 29 April 2020. Here, we present a critically ill case utilizing umbilical cord blood-derived mesenchymal stem cells (UCB-MSCs). CASE PRESENTATION: A 72-year-old man was admitted, with the diagnosis of COVID-19, ARDS, type-2 diabetes, diabetic nephropathy, renal insufficiency, and hypertension. His clinical condition continually developed to be life-threatening even receiving various treatment options including antiviral therapy and extracorporeal membrane oxygenation. Between 28 February and 8 March 2020, the patient was given 5-time intravenous infusions of UCB-MSCs. His hematological and biochemical indexes, including lymphocytes and renal function improved. Pulmonary static compliance increased significantly and PaO2/FiO2 ratio maintained stable. On March 10, he received lung transplantation. CONCLUSIONS: Our current findings suggested that UCB-MSCs therapy may show some positive effect in treating critical COVID-19 to some extent, for its delaying deterioration of the disease and efficacy in respiratory and renal function, though limited.

Excessive Neutrophils and Neutrophil Extracellular Traps in COVID-19.

Background: Cases of excessive neutrophil counts in the blood in severe coronavirus disease (COVID-19) patients have drawn significant attention. Neutrophil infiltration was also noted on the pathological findings from autopsies. It is urgent to clarify the pathogenesis of neutrophils leading to severe pneumonia in COVID-19. Methods: A retrospective analysis was performed on 55 COVID-19 patients classified as mild (n = 22), moderate (n = 25), and severe (n = 8) according to the Guidelines released by the National Health Commission of China. Trends relating leukocyte counts and lungs examined by chest CT scan were quantified by Bayesian inference. Transcriptional signatures of host immune cells of four COVID19 patients were analyzed by RNA sequencing of lung specimens and BALF. Results: Neutrophilia occurred in 6 of 8 severe patients at 7-19 days after symptom onset, coinciding with lesion progression. Increasing neutrophil counts paralleled lesion CT values (slope: 0.8 and 0.3-1.2), reflecting neutrophilia-induced lung injury in severe patients. Transcriptome analysis revealed that neutrophil activation was correlated with 17 neutrophil extracellular trap (NET)-associated genes in COVID-19 patients, which was related to innate immunity and interacted with T/NK/B cells, as supported by a protein-protein interaction network analysis. Conclusion: Excessive neutrophils and associated NETs could explain the pathogenesis of lung injury in COVID-19 pneumonia.