Interim analysis of the PARADISE study: benefits of add-on peginterferon-α in NA-treated patients with CHB.

This study aimed to investigate whether peginterferon-α (IFN) add-on nucleos(t)ide analogs(NAs) can further reduce hepatocellular carcinoma(HCC) risk compared with NAs monotherapy in NA-treated patients with chronic hepatitis B(CHB). In this multi-center randomized controlled trial "PARADISE study" (NCT05671315), CHB patients with intermediate to high risk of HCC after more than 24-week NAs pretreatment were recruited, randomized to two groups at a ratio of 1:2 and followed up for 240 weeks. NAs group maintained NAs monotherapy, while IFN+NAs group received IFN add-on NAs therapy for 48 weeks, then switched to NAs monotherapy. Totally, 196 patients were included in interim analysis (NAs group 68, IFN+NAs group 128). The 96-week cumulative HCC incidence was lower in IFN+NAs group than NAs group (0% vs. 4.5%, p<0.05). Compared with NAs group, IFN+NAs group had significantly higher rates of HBsAg loss at week 48 and 96 (22.7% vs. 0%; 16.7% vs. 0%, both p<0.05). A new scoring system was established to predict HBsAg decline >2log10 IU/ml, HBsAg <10 IU/ml or HBsAg loss at the end of 48-week IFN treatment. The area under ROC curve was 0.914, 0.922 or 0.905 in the original cohort (n=128) and 0.896, 0.896 or 0.864 in the external validation cohort (n=162) for the aforementioned three outcomes, respectively. IFN add-on NAs therapy may suggest the dual benefits of reducing HCC development and facilitating HBsAg loss among NA-treated CHB patients with intermediate to high risk of HCC. The new scoring system helps to make the most of IFN treatment for a higher cost-effectiveness in healthcare.

Clinical outcomes of treatment-naïve HBeAg-negative patients with chronic hepatitis B virus infection with low serum HBsAg and undetectable HBV DNA.

Serum hepatitis B surface antigen (HBsAg) level < 100 IU/ml and undetectable hepatitis B virus (HBV) DNA have been recently proposed as an alternate endpoint of "partial cure" in chronic hepatitis B (CHB). We investigated clinical outcomes of hepatitis B e antigen (HBeAg)-negative CHB patients with HBsAg <100 IU/ml and undetectable HBV DNA. Treatment-naïve HBeAg-negative CHB patients with undetectable HBV DNA and normal alanine aminotransferase were retrospectively included from three institutions. Patients were classified into the low HBsAg group (<100 IU/ml) and the high HBsAg group (≥100 IU/ml). Liver fibrosis was evaluated by noninvasive tests (NITs). A total of 1218 patients were included and the median age was 41.5 years. Patients with low HBsAg were older (45.0 vs. 40.0 years, P < 0.001) than those in the high HBsAg group, while the NIT parameters were comparable between groups. During a median follow-up of 25.7 months, patients with low HBsAg achieved a higher HBsAg clearance rate (13.0% vs. 0%, P < 0.001) and a lower rate of significant fibrosis development (2.2% vs. 7.0%, P = 0.049) compared to patients with high HBsAg. No patient developed HCC in either group. HBsAg level was negatively associated with HBsAg clearance (HR 0.213, P < 0.001) and patients with HBsAg < 100 IU/ml had a low risk of significant fibrosis development (HR 0.010, P = 0.002). The optimal cutoff value of HBsAg for predicting HBsAg clearance was 1.1 Log10 IU/ml. Treatment-naïve HBeAg-negative CHB patients with HBsAg <100 IU/ml and undetectable HBV DNA had favourable outcomes with a high rate of HBsAg clearance and a low risk of fibrosis progression.

[Corrigendum] FKBP11 protects intestinal epithelial cells against inflammation­induced apoptosis via the JNK­caspase pathway in Crohn's disease.

Subsequently to the publication of the above article, the authors realized that Fig. 4 in their paper had been assembled containing two erroneously placed gel slices; essentially, the GAPDH bands featured in Fig. 4A had also been included in Fig. 5, and the data for the FKBP11 bands in Fig. 4A had also been included to show the GRP78 bands in Fig. 4. The authors were able to revisit their original data and to correct the data that had been featured incorrectly in Fig. 4. The corrected version of Fig. 4, now showing the true data for the GRP78 protein bands in Fig. 4C and the correct GAPDH protein bands for Fig. 4A, is shown on the next page. Note that these errors did not significantly affect the results or the conclusions reported in this paper. All the authors agree to the publication of this Corrigendum, and are grateful to the Editor of Molecular Medicine Reports for allowing them the opportunity to correct this error. Moreover, the authors apologize to the readership for any inconvenience caused. [Molecular Medicine Reports 18: 4428­4438, 2018; DOI: 10.3892/mmr.2018.9485].

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.

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.

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.

Animal models of hepatitis E infection: Advances and challenges.

Hepatitis E virus (HEV) is one of the leading causes of acute viral hepatitis worldwide. Although most of HEV infections are asymptomatic, some patients will develop the symptoms, especially pregnant women, the elderly, and patients with preexisting liver diseases, who often experience anorexia, nausea, vomiting, malaise, abdominal pain, and jaundice. HEV infection may become chronic in immunosuppressed individuals. In addition, HEV infection can also cause several extrahepatic manifestations. HEV exists in a wide range of hosts in nature and can be transmitted across species. Hence, animals susceptible to HEV can be used as models. The establishment of animal models is of great significance for studying HEV transmission, clinical symptoms, extrahepatic manifestations, and therapeutic strategies, which will help us understand the pathogenesis, prevention, and treatment of hepatitis E. This review summarized the animal models of HEV, including pigs, monkeys, rabbits, mice, rats, and other animals. For each animal species, we provided a concise summary of the HEV genotypes that they can be infected with, the cross-species transmission pathways, as well as their role in studying extrahepatic manifestations, prevention, and treatment of HEV infection. The advantages and disadvantages of these animal models were also emphasized. This review offers new perspectives to enhance the current understanding of the research landscape surrounding HEV animal models.

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.

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.

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.

Xihuang Pill-destabilized CD133/EGFR/Akt/mTOR cascade reduces stemness enrichment of glioblastoma via the down-regulation of SOX2.

BACKGROUND: Our previous study found that XHP could induce GBM cells to undergo apoptosis. A lot of evidence suggests that glioma stem-like cells (GSCs) are key factors that contribute to disease progression and poor prognosis of glioblastoma multiforme (GBM). Traditional Chinese medicine has been applied in clinical practice as a complementary and alternative therapy for glioma. PURPOSE: To evaluate the effect and the potential molecular mechanism of Xihuang pill (XHP) on GSCs. METHODS: UPLC-QTOF-MS analysis was used for constituent analysis of XHP. Using network pharmacology and bioinformatics methods, a molecular network targeting GSCs by the active ingredients in XHP was constructed. Cell viability, self-renewal ability, apoptosis, and GSC markers were detected by CCK-8 assay, tumor sphere formation assay and flow cytometry, respectively. The interrelationship between GSC markers (CD133 and SOX2) and key proteins of the EGFR/Akt/mTOR signaling pathway was evaluated using GEPIA and verified by western blot. A GBM cell line stably overexpressing Akt was constructed using lentivirus to evaluate the role of Akt signaling in the regulation of glioma stemness. The effect of XHP on glioma growth was analyzed by a subcutaneously transplanted glioma cell model in nude mice, hematoxylin-eosin staining was used to examine pathological changes, TUNEL staining was used to detect apoptosis in tumor tissues, and the expression of GSC markers in tumor tissues was identified by western blot and immunofluorescence. RESULTS: Bioinformatics analysis showed that 55 matched targets were related to XHP targets and glioma stem cell targets. In addition to causing apoptosis, XHP could diminish the number of GBM 3D spheroids, the proportion of CD133-positive cells and the expression level of GSC markers (CD133 and SOX2) in vitro. Furthermore, XHP could attenuate the expression of CD133, EGFR, p-Akt, p-mTOR and SOX2 in GBM spheres. Overexpression of Akt significantly increased the expression level of SOX2, which was prohibited in the presence of XHP. XHP reduced GSC markers including CD133 and SOX2, and impeded the development of glioma growth in xenograft mouse models in vivo. CONCLUSION: We demonstrate for the first time that XHP down-regulates stemness, restrains self-renewal and induces apoptosis in GSCs and impedes glioma growth by down-regulating SOX2 through destabilizing the CD133/EGFR/Akt/mTOR cascade.

Development and validation of a nomogram to predict failure of 14-day negative nucleic acid conversion in adults with non-severe COVID-19 during the Omicron surge: a retrospective multicenter study.

BACKGROUND: With the variability in emerging data, guidance on the isolation duration for patients with coronavirus disease 2019 (COVID-19) due to the Omicron variant is controversial. This study aimed to determine the predictors of prolonged viral RNA shedding in patients with non-severe COVID-19 and construct a nomogram to predict patients at risk of 14-day PCR conversion failure. METHODS: Adult patients with non-severe COVID-19 were enrolled from three hospitals of eastern China in Spring 2022. Viral shedding time (VST) was defined as either the day of the first positive test or the day of symptom onset, whichever was earlier, to the date of the first of two consecutively negative PCR tests. Patients from one hospital (Cohort I, n = 2033) were randomly grouped into training and internal validation sets. Predictors of 14-day PCR conversion failure were identified and a nomogram was developed by multivariable logistic regression using the training dataset. Two hospitals (Cohort II, n = 1596) were used as an external validation set to measure the performance of this nomogram. RESULTS: Of the 2033 patients from Cohort I, the median VST was 13.0 (interquartile range: 10.0‒16.0) days; 716 (35.2%) lasted > 14 days. In the training set, increased age [per 10 years, odds ratio (OR) = 1.29, 95% confidence interval (CI): 1.15‒1.45, P < 0.001] and high Charlson comorbidity index (OR = 1.25, 95% CI: 1.08‒1.46, P = 0.004) were independent risk factors for VST > 14 days, whereas full or boosted vaccination (OR = 0.63, 95% CI: 0.42‒0.95, P = 0.028) and antiviral therapy (OR = 0.56, 95% CI: 0.31‒0.96, P = 0.040) were protective factors. These predictors were used to develop a nomogram to predict VST > 14 days, with an area under the ROC curve (AUC) of 0.73 in the training set (AUC, 0.74 in internal validation set; 0.76 in external validation set). CONCLUSIONS: Older age, increasing comorbidities, incomplete vaccinations, and lack of antiviral therapy are risk factors for persistent infection with Omicron variant for > 14 days. A nomogram based on these predictors could be used as a prediction tool to guide treatment and isolation strategies.

The progress to establish optimal animal models for the study of acute-on-chronic liver failure.

Acute-on-chronic liver failure (ACLF) defines a complicated and multifaceted syndrome characterized by acute liver dysfunction following an acute insult on the basis of chronic liver diseases. It is usually concurrent with bacterial infection and multi-organ failure resulting in high short-term mortality. Based on the cohort studies in ACLF worldwide, the clinical course of ACLF was demonstrated to comprise three major stages including chronic liver injury, acute hepatic/extrahepatic insult, and systemic inflammatory response caused by over-reactive immune system especially bacterial infection. However, due to the lack of optimal experimental animal models for ACLF, the progress of basic study on ACLF is limping. Though several experimental ACLF models were established, none of them can recapitulate and simulate the whole pathological process of ACLF patients. Recently, we have developed a novel mouse model for ACLF combining chronic liver injury [injection of carbon tetrachloride (CCl4) for 8 weeks], acute hepatic insult (injection of a double dose CCl4), and bacterial infection (intraperitoneal injection of Klebsiella pneumoniae), which could recapitulate the major clinical features of patients with ACLF worsened by bacterial infection.

Ubiquitin E3 ligase ß-TrCP negatively regulates surface protein of hepatitis B virus.

Chronic hepatitis B (CHB) still cannot be cured currently, while the pursuit of a functional cure seems to be an accessible goal, in which the condition mainly depends on the serum hepatitis B surface antigen (HBsAg) levels. HBsAg may be downregulated by protein ubiquitination, which may facilitate finding a new potential intervention target for functional cure of CHB. We confirmed that ß-transducin repeat-containing protein (ß-TrCP) was the E3 ubiquitin ligase of HBsAg. ß-TrCP specifically downregulated the expression of Myc-HBsAg. The degradation of Myc-HBsAg occurred via the proteasome pathway. Knockdown of ß-TrCP increased Myc-HBsAg levels in HepG2 cells. The study further indicated that ß-TrCP could affect the K48-linked polyubiquitin chain by acting on Myc-HBsAg. The GS137 G motif of HBsAg protein is required for ß-TrCP-mediated degradation. Furthermore, we found that ß-TrCP could significantly inhibit both intracellular and extracellular HBsAg levels produced by pHBV-1.3. Our study demonstrated that the E3 ubiquitin ligase ß-TrCP induces K48-linked polyubiquitination of HBsAg, promotes the ubiquitination degradation of HBsAg, and downregulates intra- and extracellular HBsAg levels. Therefore, using the ubiquitination degradation pathway of HBsAg, it is possible to reduce HBsAg levels in CHB patients, which may be helpful in obtaining the goal of functional cure in the treatment of CHB patients.

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.