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Background and objective Precore (PC) variant (G1896A) and basal core promoter (BCP) variant (A1762T/G1764A) of HBV are associated with risk of hepatocellular carcinoma in HBV carriers. However, little is known about their impact on the adverse outcomes of hepatitis B e antigen (HBeAg)-negative hepatitis and liver cirrhosis. Methods 251 spontaneous HBeAg seroconverters who had genotype B or C infection and received a long-term follow-up were enrolled. PC and BCP mutants were determined qualitatively and quantitatively to correlate with these adverse outcomes. The findings were validated by an independent case–control study, which included 184 patients with biopsy-proven liver fibrosis stages. Results In the longitudinal cohort study, BCP mutant and possibly PC wild type were associated with cirrhosis development, but not HBeAg-negative hepatitis. Multivariable analysis showed that only BCP mutant was an independent risk factor for cirrhosis development. Using quantitative analysis of BCP mutant, a higher proportion of BCP mutant, defined as a continuous variable, a dichotomous variable or an ordinal variable, was associated with a higher risk of cirrhosis. If we chose 45% of BCP mutant as the cut-off, the risk of cirrhosis was higher in patients with BCP mutant ≥45% compared to <45% in the longitudinal cohort; this finding was validated by the case–control study (adjusted OR: 2.81, 95% CI 1.40 to 5.67). Conclusions A higher proportion of BCP mutant increases the risk of liver cirrhosis development in HBV carriers with genotype B or C infection.

Semantic communication allows the receiver to know the intention instead of the bit information itself, which is an emerging technique to support real-time human-machine and machine-to-machine interactions for future wireless communications. In semantic communications, both transmitter and receiver share some common knowledge, which can be used to extract small-size information at the transmitter and recover the original information at the receiver. Due to different design purposes, security issues in semantic communications have two unique features compared to standard bit-wise communications. First, an attacker in semantic communications considers not only the amount of stolen data but also the meanings of stolen data. Second, an attacker in semantic communication systems can attack not only semantic information transmission as done in standard communication systems but also attacks machine learning (ML) models used for semantic information extraction since most of semantic information is generated using ML based methods. Due to these unique features, in this paper, we present an overview on the fundamentals and key challenges in the design of secure semantic communication. We first provide various methods to define and extract semantic information. Then, we focus on secure semantic communication techniques in two areas: information security and semantic ML model security. For each area, we identify the main problems and challenges. Then, we will provide a comprehensive treatment of these problems. In a nutshell, this article provides a holistic set of guidelines on how to design secure semantic communication systems over real-world wireless communication networks.

SUMMARY BackgroundClearance of hepatitis B surface antigen (HBsAg) indicates clinical control of hepatitis B virus (HBV) infection. However, little is known about the impact of viral genomic variations on HBsAg loss.

In non-cirrhotic patients with chronic HBV infection, FIB-4 index <1.29 complements the existing clinical profile to define patients with the lowest HCC risk.

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Background: The connection between gut microbiota and metabolism and its role in the pathogenesis of diabetes are increasingly recognized. The objective of this study was to quantitatively measure Bifidobacterium and Lactobacillus species, members of commensal bacteria found in human gut, in type 2 diabetic patients (T2D) patients from Southern China.Methods: Fifty patients with T2D and thirty control individuals of similar body mass index (BMI) were recruited from Southern China. T2D and control subjects were confirmed with both oral glucose tolerance test (OGTT) and HbA1c measurements. Bifidobacterium and Lactobacillus species in feces were measured by real-time quantitative PCR. Data were analyzed with STATA 11.0 statistical software.Results: In comparison to control subjects T2D patients had significantly more total Lactobacillus (+18%), L. bugaricus (+13%), L. rhamnosum (+37%) and L. acidophilus (+48%) (P < 0.05). In contrast, T2D patients had less amounts of total Bifidobacteria (−7%) and B. adolescentis (−12%) (P < 0.05). Cluster analysis showed that gut microbiota pattern of T2D patients is characterized by greater numbers of L. rhamnosus and L. acidophillus, together with lesser numbers of B. adolescentis (P < 0.05).Conclusion: The gut microflora in T2D patients is characterized by greater numbers of Lactobacillus and lesser numbers of Bifidobacterium species.

Serum HBsAg level helps stratify HCC risk in patients with intermediate viral loads. Combining HBV DNA and HBsAg levels better predicts HCC risk.