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.

Serum CXCL16: A new predictor of liver inflammation in patients with chronic hepatitis B.

The prompt initiation of antiviral therapy is essential in patients with chronic hepatitis B (CHB), especially when severe liver inflammation is detected. However, transcutaneous liver puncture, the gold standard for assessing liver inflammation, is invasive and its widespread application is limited. Therefore, there is an urgent need for more non-invasive markers to predict liver inflammation. In our retrospective cross-sectional study, which included 120 CHB patients and 31 healthy subjects, we observed a significant increase in serum chemokine C-X-C-motif ligand 16 (CXCL16) in CHB patients compared to healthy controls (p < .001). Notably, patients with severe inflammation (Scheuer's grade G ≥ 3, n = 26) exhibited a substantial increase in serum CXCL16 compared to those with non-severe inflammation (Scheuer's grade G < 3, n = 96) [(median, IQR), 0.42 (0.24-0.71) ng/mL vs. 1.01 (0.25-2.09) ng/mL, p < .001]. Furthermore, we developed a predictive model that combined CXCL16 with platelet count (PLT), alanine aminotransferase (ALT) and albumin (ALB) to accurately predict liver inflammation in CHB patients. This model was more effective than ALT alone in predicting liver inflammation (AUC, 0.92 vs. 0.81, p = .015). Additionally, using an HBV-transduced mouse model, we demonstrated that blocking CXCL16 led to a reduction in liver inflammation and impaired infiltration and function of natural killer T (NKT) and natural killer (NK) cells. These findings suggest that CXCL16 is a promising non-invasive biomarker of liver inflammation in CHB patients and may play a role in inducing liver inflammation via a NKT and NK cell pathway.

The presence of baseline HBsAb-Specific B cells can predict HBsAg or HBeAg seroconversion of chronic hepatitis B on treatment.

Indices for predicting HBsAg or HBeAg seroconversion in patients with chronic hepatitis B virus (HBV) infection during antiviral therapy remain elusive. We aimed to investigate if the presence of HBsAb-specific B cells at baseline can predict HBsAg or HBeAg seroconversion. In this study, 134 treatment-naive patients with chronic HBV were enrolled. A baseline HBsAb-specific B cell ELISpot assay was performed for all the patients that enrolled. Serum samples were collected at 12, 24, and 48 weeks for patients treated with Peg-IFN-α, or at 1 year, 3 years, and 5 years for patients treated with NAs. Laboratory testing of HBsAg, HBsAb, HBeAg, HBeAb, HBcAb, HBV DNA, ALT, and AST was done. We observed a significantly lower frequency of HBsAb-specific B cells in patients with chronic HBV than in healthy individuals . In the Peg-IFN-α-treated group, 41.2% of patients with baseline HBsAb-specific B cells achieved HBsAg seroconversion, while only 13.6% of patients without baseline HBsAb-specific B cells achieved HBsAg seroconversion (p = 0.006). By logistic regression analysis, patients with baseline HBsAb-specific B cells and HBsAg ≤ 1500 had higher HBsAg clearance at the end of treatment (p < 0.05). In the NA-treated group, 58.3% of patients with baseline HBsAb-specific B cells achieved HBeAg seroconversion, whereas only 30.0% of patients without baseline HBsAb-specific B cells achieved HBeAg seroconversion (p = 0.114). Our result revealed that baseline HBsAb-specific B cells by ELISpot assay might be a valuable predictive biomarker of HBsAg or HBeAg seroconversion in patients with chronic HBV on treatment.

A Reservoir Computing with Boosted Topology Model to Predict Encephalitis and Mortality for Patients with Severe Fever with Thrombocytopenia Syndrome: A Retrospective Multicenter Study.

INTRODUCTION: Severe fever with thrombocytopenia syndrome virus (SFTSV) is an emerging tick-borne virus associated with a high rate of mortality, as well as encephalitis. We aim to develop and validate a machine learning model to early predict the potential life-threatening conditions of SFTS. METHODS: The clinical presentation, demographic information, and laboratory parameters from 327 patients with SFTS at admission in three large tertiary hospitals in Jiangsu, China between 2010 to 2022 are retrieved. We establish a reservoir computing with boosted topology (RC-BT) algorithm to obtain the models' predictions of the encephalitis and mortality of patients with SFTS. The prediction performances of encephalitis and mortality are further tested and validated. Finally, we compare our RC-BT model with the other traditional machine learning algorithms including Lightgbm, support vector machine (SVM), Xgboost, Decision Tree, and Neural Network (NN). RESULTS: For the prediction of encephalitis among patients with SFTS, nine parameters are selected with equal weight, namely calcium, cholesterol, muscle soreness, dry cough, smoking history, temperature at admission, troponin T, potassium, and thermal peak. The accuracy for the validation cohort by the RC-BT model is 0.897 [95% confidence interval (CI) 0.873-0.921]. The sensitivity and negative predictive value (NPV) of the RC-BT model are 0.855 (95% CI 0.824-0.886) and 0.904 (95% CI 0.863-0.945), respectively. Area under curve of the RC-BT model for the validation cohort is 0.899 (95% CI 0.882-0.916). For the prediction of fatality among patients with SFTS, seven parameters are selected with equal weight, namely calcium, cholesterol, history of drinking, headache, field contact, potassium, and dyspnea. The accuracy of the RC-BT model is 0.903 (95% CI 0.881-0.925). The sensitivity and NPV of the RC-BT model are 0.913 (95% CI 0.902-0.924) and 0.946 (95% CI 0.917-0.975), respectively. The area under curve is 0.917 (95% CI 0.902-0.932). Importantly, the RC-BT models outperform the other artificial intelligence-based algorithms in both prediction tasks. CONCLUSIONS: Our two RC-BT models of SFTS encephalitis and fatality demonstrate high area under curves, specificity, and NPV, with nine and seven routine clinical parameters, respectively. Our models can not only greatly improve the early prognosis accuracy of SFTS, but can also be widely applied in underdeveloped areas with limited medical resources.

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.

A longitudinal study of humoral immune responses induced by a 3-dose inactivated COVID-19 vaccine in an observational, prospective cohort.

BACKGROUND: To determine the dynamic SARS-CoV-2 specific antibody levels induced by 3 doses of an inactivated COVID-19 vaccine, CoronaVac. An observational, prospective cohort study was performed with 93 healthy healthcare workers from a tertiary hospital in Nanjing, China. Serum SARS-CoV-2 specific IgM, IgG, and neutralizing antibodies (NAb) were measured at different time points among participants who received 3 doses of inactivated COVID-19 vaccine. RESULTS: 91.3% (85/93) and 100% (72/72) participants showed positive both for SARS-CoV-2 specific IgG and NAb after 2-dose CoronaVac and after 3-dose CoronaVac, respectively. Anti-SARS-CoV-2 IgG responses reached 91.21 (55.66-152.06) AU/mL, and surrogate NAb was 47.60 (25.96-100.81) IU/mL on day 14 after the second dose. Anti-SARS-CoV-2 IgG responses reached 218.29 (167.53-292.16) AU/mL and surrogate NAb was 445.54 (171.54-810.90) IU/mL on day 14 after the third dose. Additionally, SARS-CoV-2 specific surrogate neutralizing antibody titers were highly correlated with serum neutralization activities against Ancestral, Omicron, and Delta strains. Moreover, significantly higher SARS-CoV-2 IgG responses, but not NAb responses, were found in individuals with breakthrough infection when compared to that of 3-dose CoronaVac recipients. CONCLUSIONS: CoronaVac elicited robust SARS-CoV-2 specific humoral responses. Surrogate NAb assay might substitute for pseudovirus neutralization assay. Monitoring SARS-CoV-2 antibody responses induced by vaccination would provide important guidance for the optimization of COVID-19 vaccines.

The Third dose of CoronVac vaccination induces broad and potent adaptive immune responses that recognize SARS-CoV-2 Delta and Omicron variants.

The waning humoral immunity and emerging contagious severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants resulted in the necessity of the booster vaccination of coronavirus disease 2019 (COVID-19). The inactivated vaccine, CoronaVac, is the most widely supplied COVID-19 vaccine globally. Whether the CoronaVac booster elicited adaptive responses that cross-recognize SARS-CoV-2 variants of concern (VoCs) among 77 healthy subjects receiving the third dose of CoronaVac were explored. After the boost, remarkable elevated spike-specific IgG and IgA responses, as well as boosted neutralization activities, were observed, despite 3.0-fold and 5.9-fold reduced neutralization activities against Delta and Omicron strains compared to that of the ancestral strain. Furthermore, the booster dose induced potent B cells and memory B cells that cross-bound receptor-binding domain (RBD) proteins derived from VoCs, while Delta and Omicron RBD-specific memory B cell recognitions were reduced by 2.7-fold and 4.2-fold compared to that of ancestral strain, respectively. Consistently, spike-specific circulating follicular helper T cells (cTfh) significantly increased and remained stable after the boost, with a predominant expansion towards cTfh17 subpopulations. Moreover, SARS-CoV-2-specific CD4+ and CD8+ T cells peaked and sustained after the booster. Notably, CD4+ and CD8+ T cell recognition of VoC spike was largely preserved compared to the ancestral strain. Individuals without generating Delta or Omicron neutralization activities had comparable levels of CD4+ and CD8+ T cells responses as those with detectable neutralizing activities. Our study demonstrated that the CoronaVac booster induced broad and potent adaptive immune responses that could be effective in controlling SARS-CoV-2 Delta and Omicron variants.

Dynamic SARS-CoV-2-specific B-cell and T-cell responses following immunization with an inactivated COVID-19 vaccine.

OBJECTIVE: The dynamic adaptive immune responses elicited by the inactivated virus vaccine CoronaVac remain elusive. METHODS: In a prospective cohort of 100 healthcare professionals naïve for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) who received two doses of CoronaVac, we analysed SARS-CoV-2-specific humoral and cellular responses at four different timepoints, including before vaccination (T1), 2 weeks after the first dose (T2), 2 weeks after the booster dose (T3), and 8-10 weeks after the booster dose (T4). SARS-CoV-2-specific antibodies, serum neutralizing activities, peripheral B cells, CD4+ and CD8+ T cells and their memory subsets were simultaneously measured in this cohort. RESULTS: SARS-CoV-2 spike-specific IgG responses reached a peak (geometric mean titre (GMT) 54827, 30969-97065) after two doses and rapidly declined (GMT 502, 212-1190) at T4, whereas suboptimal IgA responses were detected (GMT 5, 2-9). Spike-specific circulating B cells (0.60%, 0.46-0.73% of total B cells) and memory B cells (1.18%, 0.92-1.44% of total memory B cells) were effectively induced at T3 and sustained over time (0.33%, 0.23-0.43%; 0.87%, 0.05-1.67%, respectively). SARS-CoV-2-specific circulating CD4+ T cells (0.57%, 0.47-0.66%) and CD8+ T cells (1.29%, 1.04-1.54%) were detected at T3. At T4, 0.78% (0.43-1.20%) of memory CD4+ T cells and 0.68% (0.29-1.30%) of memory CD8+ T cells were identified as SARS-CoV-2-specific, while 0.62% (0.51-0.75%) of CD4+ T cells and 0.47% (0.38-0.58%) of CD8+ T cells were SARS-CoV-2-specific terminally differentiated effector memory cells. Furthermore, age and interval between doses affected the magnitude of CoronaVac-induced immune responses. SARS-CoV-2 memory CD4+ T cells were strongly associated with both receptor binding domain (RBD)-specific memory B cells (r 0.87, p <0.0001) and SARS-CoV-2-specific memory CD8+ T cells (r 0.48, p <0.0001). CONCLUSIONS: CoronaVac induced robust circulating and memory B cell and T cell responses. Our study offers new insight into the underlying immunobiology of inactivated virus vaccines in humans and may have implications for vaccine strategies in the future.

miR-574-5p Targets FOXN3 to Regulate the Invasion of Nasopharyngeal Carcinoma Cells via Wnt/ß-Catenin Pathway.

MicroRNAs (miR) are a class of non-coding endogenous RNA molecules that suppress the translation of protein-coding genes by destabilizing target mRNAs. The MiR-574-5p has been reported to be involved in the several types of cancer. However, the expression of miR-574-5p and its mechanism in nasopharyngeal carcinoma (NPC) remain unclear. We found that the expression level of miR-574-5p was significantly increased in the NPC cell lines. We further demonstrated that Forkhead box N3 (FOXN3) was a target gene of miR-574-5p. FOXN3 overexpression and inhibition reversed the promoting or suppressing effect, respectively, of NPC cell proliferation, migration and invasion caused by miR-574-5p. Furthermore, miR-574-5p enhanced the ß-catenin and TCF4 protein expression by repressing FOXN3 expression, resulting in the activation of the Wnt/ß-catenin signaling pathway, but the activity of the Wnt/ß-catenin signaling pathway was inhibited by a miR-574-5p inhibitor or FOXN3 overexpression, which reversed the effect of miR-574-5p. Wound-healing and Transwell assays also showed that miR-574-5p promotes the cell migration and invasion of NPC cells, whereas the promoting effect of miR-574-5p was also reversed by a miR-574-5p inhibitor or FOXN3 overexpression. Collectively, these data suggested that miR-574-5p promotes NPC cell proliferation, migration, and invasion at least partly by targeting the FOXN3/Wnt/ß-Catenin signaling pathway.

The Bamboo Flowering Cycle Sheds Light on Flowering Diversity.

Bamboo is a perennial flowering plant with a distinctive life cycle: many bamboo species remain in the vegetative phase for decades, followed by mass synchronous flowering and subsequent death. The phenomenon of bamboo flowering is not fully understood, but its periodicity is a major research focus. Here, we collected information on bamboo flowering events by investigating historical documents and field studies at the Bamboo Research Institute of Nanjing Forestry University. We compiled information on more than 630 flowering events, 124 of which accurately recorded the flowering cycle time. We summarized the specific flowering cycles of 85 bamboo species, as well as four kinds of bamboo flowering habits in detail. We present a theory of the bamboo flowering cycle and discuss the reasons for the observed variations in bamboo flowering. This review also introduces two mechanisms by which bamboo forests are rejuvenated after flowering and explains the flowering phenomena of bamboo forests using the bamboo flowering cycle theory. Finally, we present suggestions for forest management strategies. Bamboo flowering is a normal physiological phenomenon, even though it has unique elements compared with flowering in other plants. The results presented here provide valuable reference material for understanding bamboo flowering and its periodicity.