eALT-F: A New Non-Invasive Staging Method to Identify Medium to High-Risk Patients with HCC from Ultra-High HBV Viral Load Population - China, 2010-2023.

Background: The objective of this study was to examine the clinical characteristics of individuals with ultra-high hepatitis B virus (HBV) viral load and develop a novel staging method for chronic hepatitis B (CHB) that can more effectively identify patients with medium to high hepatocellular carcinoma (HCC) risk. Methods: A total of 2,118 patients with HBV DNA >1×107 IU/mL who visited Peking University People's Hospital between January 2010 and March 2023 were enrolled retrospectively. Clinical data from the first visit were obtained and analyzed. The traditional phases and new 'eALT-F' stages were compared to evaluate the risk of HCC. Results: In the overall patients, more than one-third of the patients were under 30 years old. Additionally, a small proportion of older people (>60 years) also had ultra-high HBV viral load (4.3%). 9.1% and 6.7% of individuals with ultra-high HBV viral load showed FIB-4>3.25 and aMAP≥50, respectively. In the traditional stages of CHB, which are based on HBeAg and alanine aminotransferase (ALT) [the upper limit of normal (ULN) ALT level at 40 IU/L for both men and women], regardless of phase, a certain proportion of patients were at risk of developing HCC (4.1%, 6.4%, 25.0%, and 20.3%). However, in the new 'eALT-F' stages, which are based on HBeAg, ALT (the ULN of ALT level at 30 IU/L for men and 19 IU/L for women), and/or FIB-4 levels (>1.45), aMAP≥50 was only observed in chronic hepatitis patients with positive or negative HBeAg (6.4% and 22.1%, respectively). Conclusions: The 'eALT-F' staging method, based on HBeAg, ALT (males: the ULN of ALT was 30 IU/L, females: 19 IU/L) and/or FIB-4 levels, was more effective in identifying medium to high-risk patients with HCC from patients with ultra-high HBV viral load than the traditional staging methods.

The beneficial effects of Agaricus blazei Murrill on hepatic antioxidant enzymes and the pancreatic tissue recovery in streptozotocin-induced diabetic rats.

Agaricus blazei Murrill (ABM), is a medicinal mushroom, has beneficial effects on diabetes mellitus. In this study, ABM extracts (ethanol extract, EE and ethyl acetate extract, EA) were evaluated to explore the beneficial effect on hepatic antioxidant activity and recovery of the pancreatic tissue in streptozotocin-induced diabetic rats. The hepatic antioxidant activities of ABM extracts were analyzed by superoxide dismutase, catalase activity, glutathione, aspartate transaminase, and alanine transaminase. Moreover, the effects of ABM extracts on pancreatic tissue restoration were investigated by histopathological analysis. The results revealed that the EA showed a better protective effect on hepatic antioxidant activity and recovery of the impaired pancreatic tissues, compared to EE. The results suggested that ABM treatment could effectively reduce oxidative stress and contribute to pancreatic tissue recovery. Therefore, ABM could be used as a functional food to control diabetes. PRACTICAL APPLICATIONS: The research may contribute to the development of ABM as functional foods or dietary supplements for diabetes in the future.

Real-Time Curvature Detection of a Flexible Needle with a Bevel Tip.

As one of the major methods for the diagnosis and treatment of cancers in their early stages, the percutaneous puncture technique has bright prospect in biopsy, ablation, proximity radiotherapy, and drug delivery. Recent years, researchers found the flexible needle cannot realize feedback control during the puncture surgeries only by path planning. To solve this problem, the flexible needle is tried to achieve real-time detection in this paper. Compared with previous methods, the strain gauges glued on the needle surface rather than the medical imaging techniques is used to collect the information to reconstruct the needle curve, which is benefit to integrate the whole system and obtain a more simple and accurate closed-loop control. This paper presented the math model of curve fitting and analyzed the causes of curve fitting errors. To verify the feasibility of this method, an experiment setup was built. Results from the experiments validated the solution in this paper to be effective.