Host response biomarkers can accurately distinguish between influenza and bacterial infection. However, published biomarkers require the measurement of many genes, thereby making it difficult to implement them in clinical practice. This study aims to identify a single-gene biomarker with a high diagnostic accuracy equivalent to multi-gene biomarkers.In this study, we combined an integrated genomic analysis of 1071 individuals with experiments using well-established infection models.We identified a single-gene biomarker,, which had a high prediction accuracy (91%) equivalent to that obtained by multi-gene biomarkers. studies showed that was upregulated by TLR7 in plasmacytoid dendritic cells, antigen-presenting cells that responded to influenza virus rather than bacteria. studies confirmed that was expressed in influenza patients but not in bacterial infection, as demonstrated in multiple patient cohorts (n=521). In a large prospective study (n=439) of patients presented with undifferentiated respiratory illness (aetiologies included viral, bacterial and non-infectious conditions), displayed 88% diagnostic accuracy (AUC) and 90% specificity in discriminating between influenza and bacterial infections. represents a significant step forward in overcoming a translational barrier in applying genomic assay in clinical setting; its implementation may improve the diagnosis and management of respiratory infection.

We examined whether the hepatitis B virus (HBV) pregenomic RNA (pgRNA) status after nucleos(t)ide (NA) treatment can predict the long‐time prognoses of chronic hepatitis B patients. Patients with chronic hepatitis B (98) who were treatment‐naïve and had begun a 7‐year NA therapy regimen were enrolled in this study. Biochemical indicators and serological markers of HBV infection were performed during therapy. HBV pgRNA was quantified by real‐time quantitative PCR with specific primers. During treatment, HBV DNA undetectable rates increased. The aminotransferase (ALT) normalization (ALT < 50 IU/L) and HBeAg‐negative rates also increased. After 48 weeks’ NA treatment, 48.28% (28/58) of HBV DNA undetectable patients still had HBV pgRNA‐positive. After 7 years of treatment, more HBV pgRNA‐negative patients (n = 35) achieved HBeAg clearance than the patients who were HBV pgRNA‐positive (n = 63) (19/23 vs 19/56, P < .00). HBV pgRNA‐positive patients also had an increased risk of failing to achieve HBeAg clearance (OR = 9.25, 95% CI: 2.75‐31.08). The median time to HBeAg clearance in the HBV pgRNA‐positive patients was longer than that of the HBV pgRNA‐negative patients (152 weeks vs 72 weeks). The HBV pgRNA‐positive patients also required more time to achieve HBV DNA undetectable (124 weeks, 95% CI: 103.33‐144.67 vs 48 weeks, 95% CI: 34.80‐61.20). The HBV pgRNA status after NA treatment can predict the long‐term prognoses of patients with chronic HBV. Patients who remain HBV pgRNA‐positive after 48 weeks of NA treatment have an increased risk of not achieving HBeAg clearance, need more time to achieve HBeAg clearance and undetectable HBV DNA load.

BACKGROUNDCharacteristics of alterations of serum hepatitis B virus (HBV) RNA in different chronic hepatitis B (CHB) patients still cannot be fully explained. Whether HBV RNA can predict HBeAg seroconversion is still controversial.AIMTo investigate whether HBV RNA can predict virological response or HBeAg seroconversion during entecavir (ETV) treatment when HBV DNA is undetectable.METHODSThe present study evaluated 61 individuals who were diagnosed and treated with long-term ETV monotherapy at the Department of Infectious Diseases of Peking University First Hospital (China) from September 2006 to December 2007. Finally, 30 treatment-naive individuals were included. Serum HBV RNA were extracted from 140 μL serum samples at two time points. Then they were reverse transcribed to cDNA with the HBV-specific primer. The product was quantified by real-time quantitative PCR (RT-PCR) using TAMARA probes. Statistical analyses were performed with IBM SPSS 20.0.RESULTSLevel of serum HBV RNA at baseline was 4.15 ± 0.90 log10 copies/mL. HBV RNA levels showed no significant difference between the virological response (VR) and partial VR (PVR) groups at baseline (P = 0.940). Serum HBV RNA significantly decreased among patients who achieved a VR during ETV therapy (P < 0.001). The levels of HBV RNA in both HBeAg-positive patients with seroconversion group and those with no seroconversion increased after 24 wk of treatment. Overall, HBV RNA significantly but mildly correlated to HBsAg (r = 0.265, P = 0.041), and HBV RNA was not correlated to HBV DNA (r = 0.242, P = 0.062). Furthermore, serum HBV RNA was an independent indicator for predicting HBeAg seroconversion and virological response. HBeAg seroconversion was more likely in CHB patients with HBV RNA levels below 4.12 log10 copies/mL before treatment.CONLUSIONThe level of serum HBV RNA could predict HBeAg seroconversion and PVR during treatment. In the PVR group, the level of serum HBV RNA tends to be increasing.

BackgroundReactivation of hepatitis B virus (HBV) is a fatal complication of chemotherapy. Occult HBV infection might be reactivated in patients undergoing chemotherapy or immunosuppression. However, the mechanism of HBV reactivation induced by chemotherapy or immunosuppression remains unclear.Material/MethodsHepG2.2.15 cells were treated with an autophagy inducer (rapamycin), an inhibitor (3-methyladenine, 3-MA), and dexamethasone. Autophagosomes were observed by a transmission electron microscope (TEM). LC3-I, LC3-II, and P62 were analyzed by western blot. HBV replicative intermediates were detected by southern blot. HBV DNA expression was quantitated with real-time polymerase chain reaction (PCR). The level of HBV surface antigen (HBsAg) in culture medium was examined by ELISA.ResultsIn this study, we find that dexamethasone stimulates HBV replication and protein expression by inducing autophagy in HepG2.2.15 cells. In contrast, autophagy inhibitor (3-MA) abrogates HBsAg secretion stimulated by dexamethasone.ConclusionsOur results suggest that dexamethasone stimulates HBV replication through autophagy. This might provide a novel insight into the mechanism of glucocorticoid-mediated HBV reactivation through autophagy, which might be a new therapeutic target.

BackgroundHepatocellular carcinoma is a common cause of death in middle-aged patients. We aimed to construct a new nomogram to predict cancer-specific survival (CSS) in middle-aged patients with hepatocellular carcinoma at an early stage.MethodWe collected clinicopathological information on early middle-aged patients with hepatocellular carcinoma from the SEER database. Univariate and multivariate Cox regression models were used to screen the independent risk factors for prognosis. These risk factors were used to construct predictions of CSS in patients with hepatocellular carcinoma. Consistency index (C- index), calibration curve, area under the receiver operating curve (AUC) were used. A decision analysis curve (DCA) was used to evaluate the clinical utility of the predictive model.ResultsA total of 6,286 patients with hepatocellular carcinoma in early middle age were enrolled. Univariate and multivariate Cox regression analysis showed that sex, marriage, race, histological tumor grade, T stage, surgery, chemotherapy, AFP, and tumor size were independent risk factors for prognosis. All independent risk factors were included in the nomogram to predict CSS at 1-, 3-, and 5-years in early middle age patients with hepatocellular carcinoma. In the training cohort and validation cohort, the C-index of the prediction model was 0.728 (95%CI: 0.716–0.740) and 0.733 (95%CI: 0.715–0.751), respectively. The calibration curve showed that the predicted value of the prediction model is highly consistent with the observed value. AUC also suggested that the model has good discrimination. DCA suggested that the nomogram had better predictive power than T staging.ConclusionWe constructed a new nomogram to predict CSS in middle-aged patients with early-stage hepatocellular carcinoma. This prediction model has good accuracy and reliability, which can help patients and doctors to judge prognosis and make clinical decisions.

Aim. The success of direct-acting antivirals (DAAs) against hepatitis C virus is a major breakthrough in hepatology. Previous studies have shown that chitinase 3-like protein 1 (CHI3L1) was a marker for staging of liver fibrosis caused by HCV. In this investigation, we used CHI3L1 as a surrogate marker to compare dynamic hepatic fibrosis variations following the elimination of HCV among cases receiving sofosbuvir (SOF)-based regimens and pegylated interferon/ribavirin (PR) treatments. Methods. The study enrolled 105 patients, including 46 SOF-based regimens treated patients, 34 PR-experienced patients, and 25 untreated patients. Serum samples and clinical data were obtained at the baseline, the end of treatment, and at weeks 24 and 48 after treatments. Results. First, we found that serum level of CHI3L1 correlated moderately but significantly with LSM (r=0.615, P<0.001) at the baseline, and diagnosed liver cirrhosis at baseline with high accuracy (AUC=0.939) by ROC analysis. So we explored CHI3L1 as a sensitive biomarker to monitor the regression of liver fibrosis after HCV eradication. We found that the serum CHI3L1 level of CHC cases receiving SOF-based regimen treatments was markedly reduced immediately after treatment compared with that at the baseline (123.79 (118.55) vs. 118.20 (103.68), P=0.001). For cases undergoing PR treatment, the serum CHI3L1 decreased significantly at week 24 posttreatment compared with that at the baseline (69.98 (51.44) vs 89.15 (110.59), P=0.016). For the untreated cirrhotic patients, CHI3L1 levels increased at week 96 follow-up compared with that at the baseline (194.73 (172.46) vs. 89.50 (242.97), P=0.048), reflecting continued worsening of liver fibrosis. Conclusion. CHI3L1 is suggested to be the sensitive marker to monitor fibrosis variations in weeks during treatments and after achieving SVR. It has the potential to allow the identification of early treatment failure for a timely switch to alternative treatment and to allow monitoring progression of fibrosis as a risk factor for liver cirrhosis.

Background Lipid profiles are declined in patients with viral liver cirrhosis and correlated with severity of liver disease. Hepatitis B virus (HBV) is the leading cause of liver cirrhosis in China. Our primary aim was to investigate whether serum lipids and lipoproteins associate with survival in patients with HBV-related cirrhosis and acute gastrointestinal bleeding, and develop a 6-week mortality risk score that incorporates it. Methods From January 2008 to December 2015, consecutive cirrhotic patients with acute gastrointestinal bleeding admitted to our hospital were evaluated and randomly divided into the derivation (n = 629) and validation (n = 314) cohorts. A logistic regression model was established to confirm the association between lipoprotein cholesterol and mortality. Accuracy to predict mortality were assessed by area under the receiver operating characteristic curves (AUROCs) and compared using the Hanley and McNeil test. Results Among study subjects, the 6-week mortality rate was 10.6%. High-density lipoprotein cholesterol (HDL-C) level was found to correlate most strongly with prognostic scores. On ROC analysis, HDL-C showed excellent diagnostic accuracy for 6-week mortality. Logistic regression analysis provided a simple algorithm based on the combined use of 4 variables (total bilirubin (TBIL), HDL-C, International normalized ratio, and hemoglobin), allowing accurate discrimination of 3 distinct prognostic subgroups with 1.7% (low risk), 12.3% (intermediate risk), and 56.9% (high risk) mortality. Its accuracy was significantly better than that of Child–Pugh, model of end-stage liver disease, albumin-bilirubin score, D’Amico model, Augustin model, AIMS65 score and Glasgow-Blatchford score. Baseline HDL-C values ≤ 0.54 mmol/L were associated with markedly lower 6-week survival. Comparable results were found in the validation set. Conclusion HDL-C is a potential indicator for the prognosis of patients with cirrhosis and acute gastrointestinal bleeding. The new algorithm based on HDL-C allowed an accurate predictive assessment of 6-week mortality after bleeding attack.

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