Determining optimal ALT cut-off values for predicting significant hepatic histological changes in patients with normal ALT in the grey zone of chronic hepatitis B virus infection.

BACKGROUND AND AIMS: We aimed to define gender-specific, optimal alanine aminotransferase (ALT) cut-off values for the prediction of significant liver histological changes (SLHC) in Chinese patients with grey zone (GZ) chronic hepatitis B (CHB) and normal ALT. METHODS: In a retrospective study, we included 1101 consecutive patients with GZ CHB and normal ALT assigned to training or internal validation cohorts. We included an independent cohort of 842 patients for external validation. We performed receiver operating characteristic (ROC) curve, smoothed curve fitting, and threshold effect analyses to determine optimal ALT cut-off values. Area under the curve (AUC) values were calculated to assess their predictive performance. RESULTS: A proportion of 79.3% of patients with GZ CHB and normal ALT (≤40 U/L) had SLHC. ROC curve analysis initially identified optimal ALT cut-off values of 29 U/L (male) and 22 U/L (female). After smoothed curve fitting and threshold effect analyses, new optimal cut-off values were 27 U/L for males and 24 U/L for females. AUCs for these values were 0.836 (male) and 0.833 (female) in the internal validation cohort, and 0.849 (male) and 0.844 (female) in the external validation cohort. The accuracy and discriminative ability of the newly defined ALT cut-off values were greater than those of the current recommendations. CONCLUSION: This study established novel optimal ALT cut-off values for more precise prediction of SLHC among Chinese patients with GZ CHB and normal ALT levels. This may help identify individuals who will benefit from timely antiviral therapy.

Hepatitis B Virus Envelope Antigen and Hepatitis B Virus Surface Antigen Both Contribute to the Innate Immune Response During Persistent Hepatitis B Virus Infection.

This study aimed to investigate the changes of toll-like receptor 4 (TLR4), proinflammatory cytokine expression, hepatitis B virus surface antigen (HBsAg), and hepatitis B virus envelope antigen (HBeAg) expression as well as innate immune cell percentages in a mouse model of persistent hepatitis B virus (HBV) infection to better understand the innate immune response. Mouse models of persistent HBV infection, HBsAg expression, and HBeAg expression were developed using high-pressure tail-vein injection of recombinant adeno-associated viruses. Enzyme-linked immunosorbent assays (ELISAs) were used to determine the serum proinflammatory cytokine levels. Immunohistochemistry and western blot assays were used to detect TLR4 expression. Flow cytometric analysis was used to assess the percentage of innate immune cells in the whole blood. Persistent HBV infection, HBsAg expression, and HBeAg expression each significantly decreased the expression of TLR4. Persistent HBV infection significantly increased the percentages of T cells and monocytes, whereas it decreased the percentage of natural killer (NK) cells. Persistent HBeAg expression also decreased the percentage of NK cells, whereas persistent HBsAg expression increased the percentage of NK cells. Both persistent HBsAg and HBeAg expression increased the percentage of monocytes. However, both persistent HBsAg and HBeAg expression decreased the percentage of T cells. HBV as well as HBsAg and HBeAg showed similar effects on the expression of TLR4 and proinflammatory cytokines as well as the percentage of monocytes. Persistent HBV infection increased the percentage of T cells and decreased the percentage of NK cells, whereas only persistent HBeAg expression contributed to a decreased percentage of NK cells.

Development a novel nomogram model for predicting significant hepatic histological changes in chronic hepatitis B virus carriers.

A proportion of chronic hepatitis B virus (HBV) carriers with normal alanine transaminase (ALT) present with significant liver histological changes (SLHC). To construct a noninvasive nomogram model to identify SLHC in chronic HBV carriers with different upper limits of normal (ULNs) for ALT. The training cohort consisted of 732 chronic HBV carriers who were stratified into four sets according to different ULNs for ALT: chronic HBV carriers I, II, III, and IV. The external validation cohort comprised 277 chronic HBV carriers. Logistic regression and least absolute shrinkage and selection operator analyses were applied to develop a nomogram model to predict SLHC. A nomogram model-HBGP (based on hepatitis B surface antigen, gamma-glutamyl transpeptidase, and platelet count) demonstrated good performance in diagnosing SLHC with area under the curve (AUCs) of 0.866 (95% confidence interval [CI]: 0.839-0.892) and 0.885 (95% CI: 0.845-0.925) in the training and validation cohorts, respectively. Furthermore, HBGP displayed high diagnostic values for SLHC with AUCs of 0.866 (95% CI: 0.839-0.892), 0.868 (95% CI: 0.838-0.898), 0.865 (95% CI: 0.828-0.901), and 0.853 (95% CI: 0.798-0.908) in chronic HBV carriers I, II, III, and IV, respectively. Additionally, HBGP showed greater ability in predicting SLHC compared with the existing predictors. HBGP has shown high predictive performance for SLHC, and thus may lead to an informed decision on the initiation of antiviral treatment.

Advantages of a Novel Model for Predicting Hepatic Fibrosis in Chronic Hepatitis B Virus Carriers Compared with APRI and FIB-4 Scores.

Background and Aims: Aspartate aminotransferase-to-platelet ratio index (APRI) and fibrosis-4 index (FIB-4) are widely used to assess liver fibrosis in chronic hepatitis B virus (HBV) infection. Currently, the definition of normal alanine aminotransferase (ALT) is controversial. We aimed to examine the diagnostic value of APRI and FIB-4 in chronic HBV carriers with different upper limits of normal (ULNs) for ALT. Methods: 581 chronic HBV carriers were divided into the following four groups based on different ULNs for ALT: chronic HBV carriers I, II, III, and IV. Furthermore, 106 chronic HBV carriers formed an external validation group. Predictive values of APRI and FIB-4 were elucidated using the area under the curve (AUC). A liver fibrosis-predictive model-GPSA (named for its measure of gamma glutamyl transpeptidase, platelet count, HBsAg and albumin) was developed using multivariate logistic regression analysis. Results: In chronic HBV carriers I, the AUCs of APRI and FIB-4 were 0.680 and 0.609 for significant fibrosis and 0.678 and 0.661 for cirrhosis, respectively. The AUCs of GPSA for significant fibrosis in the training group, internal group, and external validation group were 0.877, 0.837, and 0.871, respectively. The diagnostic value of GPSA differed among chronic HBV carriers I, II, III, and IV, with AUCs for significant fibrosis being 0.857, 0.853, 0.868, and 0.905 and AUCs for cirrhosis being 0.901, 0.905, 0.886, and 0.913, respectively. GPSA showed a higher diagnostic value than APRI and FIB-4 for predicting significant fibrosis in the four groups. Conclusions: The GPSA model allows for accurate diagnosis of liver fibrosis in chronic HBV carriers with different ULN for ALT.

The dynamics of a dominant dinoflagellate, Noctiluca scintillans, in the subtropical coastal waters of the Matsu archipelago.

Bioluminescent seas caused by blooms of the dinoflagellate Noctiluca scintillans are a famous scenic attraction in the Matsu archipelago near the Chinese coast in the northern part of the Taiwan Strait. The relationship between the abundance of N. scintillans and various environmental factors was examined in the subtropical coastal waters of these islands from April to December, 2016. N. scintillans disappeared after June 20th, when the sea water temperature exceeded 27°C. A strong inverse correlation between N. scintillans and diatoms in PCA analysis indicated that diatoms suffer high grazing pressure from N. scintillans. N. scintillans appeared most abundantly during the flood season, when diatoms are most abundant. Strong inverse correlations between N. scintillans and the wind speed and wind direction in PCA further point to the effect of wind on the accumulation of cells.