The information regarding the effect of hepatitis B virus (HBV) infection on gut microbiota and the relationship between gut microbiota dysbiosis and hepatitis B virus-induced chronic liver disease (HBVCLD) is limited. In this study, we aimed at characterizing the gut microbiota composition in the three different stages of hepatitis B virus-induced chronic liver disease patients and healthy individuals. Faecal samples and clinical data were collected from HBVCLD patients and healthy individuals.The 16S rDNA gene amplification products were sequenced. Bioinformatic analysis including alpha diversity and PICRUSt was performed. A total of 19 phyla, 43 classes, 72 orders, 126 families and 225 genera were detected. The beta-diversity showed a separate clustering of healthy controls and HBVCLD patients covering chronic hepatitis (CHB), liver cirrhosis (LC) and hepatocellular carcinoma (HCC); and gut microbiota of healthy controls was more consistent, whereas those of CHB, LC and HCC varied substantially. The abundance of Firmicutes was lower, and Bacteroidetes was higher in patients with CHB, LC and HCC than in healthy controls. Predicted metagenomics of microbial communities showed an increase in glycan biosynthesis and metabolism-related genes and lipid metabolism-related genes in HBVCLD than in healthy individuals. Our study suggested that HBVCLD is associated with gut dysbiosis, with characteristics including, a gain in potential bacteria and a loss in potential beneficial bacteria or genes. Further study of CHB, LC and HCC based on microbiota may provide a novel insight into the pathogenesis of HBVCLD as well as a novel treatment strategy. K E Y W O R D S16S rDNA, dysbiosis, Gut Microbiota, hepatitis B virus, progression

Correlation analysis of red blood cell distribution width (RDW) and C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), tumor necrosis factor α (TNF-α), interleukin (IL)-6, and IL-10 in rheumatoid arthritis (RA) to investigate whether RDW can serve as a potential parameter for indicating inflammation in RA patients. A total of 670 RA patients from October 2014 to April 2016 were enrolled in our study. The white blood cell (WBC), red blood cell (RBC), platelet (PLT), hemoglobin (HGB), RDW, CRP, and ESR in peripheral blood of patients with RA were retrospectively analyzed. The relative expression of TNF-α, IL-6, and IL-10 was detected by RT-qPCR. Correlation analysis between RDW and CRP, ESR, TNF-α, IL-6, and IL-10 in RA was conducted by Microsoft Excel. RDW level was significantly increased in RA patients compared to osteoarthritis (OA) patients (P < 0.001) and healthy donors (HDs) (P < 0.001), and RDW was positively associated with inflammatory markers, such as CRP and ESR. In ROC curve analysis, the area under the curve (AUC) of RDW for the identification of RA was 0.881, with a 95% confidence interval (CI) from 0.864 to 0.898. Moreover, correlation analysis showed that RDW level was positively associated with TNF-α and IL-6, however negatively associated with IL-10. RDW was increased in patients with RA which was associated with inflammation in RA, suggesting that RDW may be a potential auxiliary marker for indicating inflammation process in RA conveniently.

Background. Circulating long noncoding RNAs (lncRNAs) have been demonstrated to serve as diagnostic biomarkers for various cancers. We aimed to elucidate the diagnostic efficacy of eight serum lncRNAs HULC, MALAT1, Linc00152, PTENP1, PTTG3P, SPRY4-IT1, UBE2CP3, and UCA1 and their combinations for the diagnosis of hepatocellular carcinoma (HCC). Methods. A total of 129 patients with HCC, 49 patients with liver cirrhosis, 27 patients with chronic hepatitis B, and 93 healthy controls were enrolled in this study. The levels of serum lncRNAs were assessed by quantitative real-time polymerase chain reaction. The correlations between serum lncRNAs and clinicopathological characteristics were further analyzed. The receiver operating characteristic (ROC) curve and area under curve (AUC) were utilized to estimate the diagnostic capacity of serum lncRNAs and their combination with AFP for HCC. A logistic regression model was performed to establish a multiple-lncRNA panel. Results. The levels of serum HULC, MALAT1, Linc00152, PTTG3P, SPRY4-IT1, UBE2CP3, and UCA1 were significantly higher in HCC patients than in patients with benign liver diseases and healthy controls, whereas serum PTENP1 was significantly decreased in HCC patients compared with healthy participants. Positive correlations between serum Linc00152 and GGT, serum PTTG3P and GGT, and serum SPRY4-IT1 and ALT were noted in HCC patients. ROC analysis revealed that all these lncRNAs had a significantly predictive value for HCC except for PTENP1. The best performance of single lncRNA was obtained by Linc00152 with an AUC of 0.877. When combined with AFP, the combination of Linc00152 and AFP gained the highest accuracy, yielding an AUC of 0.906. Through logistic regression analysis, the panel consisting of serum linc00152, UCA1, and AFP provided the greatest predictive ability, obtaining an AUC of 0.912 with 82.9% sensitivity and 88.2% specificity. Conclusion. The panel of serum Linc00152, UCA1, and AFP demonstrates a novel and noninvasive biomarker with relatively high sensitivity and specificity for HCC diagnosis.

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