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Background Minimal hepatic encephalopathy has atypical clinical symptoms but mild neuropsychiatric deficits, which are easily neglected by patients and their family members as a specific type of hepatic encephalopathy. The degree centrality (DC) analysis method based on resting-state blood oxygenation level-dependent functional magnetic resonance imaging (BOLD-fMRI) is a data analysis method derived from graph-theoretic approach reflecting whole-brain network connectivity, which can provide a more complete, faster and better representation of brain function. Objective To explore the effects of abnormal changes in the brain functional network connectivity properties and functional brain regions on cognitive function in patients with minimal hepatic encephalopathy and their neuroimaging mechanisms. Methods A total of 65 patients with hepatitis B cirrhosis hospitalized in the department of infectious diseases in General Hospital of Ningxia Medical University from October 2020 to February 2022 and 40 healthy volunteers recruited during the same period were selected as the study subjects. Gender, age, education level, number connection test A (NCT-A) score, digit symbol test (DST) score and Montreal cognitive assessment (MoCA) score of the study subjects were collected. Finally, patients with hepatitis B cirrhosis were divided into cirrhosis group (n=30) and MHE group (n=28) according to NCT-A and DST scores, and the recruited healthy volunteers were considered as the healthy control group (n=34) . The DC values of brain regions in each group were calculate, the differences in DC values of brain image between MHE group and cirrhosis group, cirrhosis group and healthy control group, MHE group and healthy control group were compared, respectively. The correlations between the DC values of brain regions with the scores of NCT-A, DST and MoCA in MHE patients was analyzed by using person correlation analysis, the distribution of brain regions with DC values correlated with the scores of above scales and the corresponding scatter plots were drawn. Results The NCT-A score in the healthy control and cirrhotic group was lower than MHE group, DST score and MoCA score in the healthy control and cirrhotic group were higher than MHE group (P18, P18, P18, P

Sarmentosin (SA) and Quercetin (QC) are two active components of Sedum Sarmentosum Bunge, which is a traditional Chinese herbal medicine. This study aimed to investigate the role and regulatory mechanism of SA and QC in fatty liver of Genetic Improvement of Farmed Tilapia (GIFT) tilapia. GIFT tilapia were randomly divided into two groups with three replicates per treatment (30 fish in each replicate): normal diet group (average weight 3.51±0.31 g) and high-fat diet group (average weight 3.44±0.09 g). After 8 weeks feeding trial, growth index, lipid deposition, and biochemical indexes were measured. Lipid deposition, and lipid and inflammation-related gene expression were detected in a primary hepatocyte model of fatty liver of GIFT tilapia treated with SA or QC. Our results showed that high-fat diet caused lipid deposition and peroxidative damage in the liver of GIFT tilapia. The cell counting kit-8 assay results indicated that 10 μM SA and 10 μM of QC both had the least effect on hepatocyte proliferation. Moreover, both 10 μM of SA and 10 μM of QC showed lipolytic effects and inhibited the expression of lipid-related genes (FAS, Leptin, SREBP-1c, and SREBP2) in fatty liver cells. Interestingly, QC induced autophagosome-like subcellular structure and increased the expression of IL-8 in fatty liver cells. In conclusion, this study confirmed that SA and QC improved fatty liver caused by high-fat diet, providing a novel therapeutic approach for fatty liver of GIFT tilapia. [ABSTRACT FROM AUTHOR]

This paper proposes a hybrid control scheme that combines fractional-order sliding-mode control (FOSMC) with radial basis function neural network adaptive damping passivity-based control (RBFPBC) for modular multilevel converters (MMC) under non-ideal operating conditions. According to the passive control theory, we establish the Euler–Lagrange (EL) models of positive and negative sequences based on the unbalanced grid. A passivity-based controller that satisfies the energy dissipation law is designed. To enable rapid convergence of the system energy storage function, a radial basis function neural network (RBFNN) is introduced to adjust the injection damping adaptively. Additionally, a fractional-order sliding-mode controller (FOSMC) is designed. The fractional-order sliding mode surface used can improve tracking performance, and effectively suppressed the undesirable chattering phenomenon compared to the traditional sliding-mode control (SMC). Finally, combining the two control methods can effectively solve the issue of passivity-based control (PBC) being too dependent on parameters. The proposed hybrid control scheme enhances the ability of the system to resist disturbances, and improves its overall robustness. Simulation results demonstrate the feasibility and effectiveness of this control method. [ABSTRACT FROM AUTHOR]