Comparison of MR-PWI quantitative and semi-quantitative parameters for the evaluation of liver fibrosis

Hepatic microcirculatory disturbance in liver diseases: intervention with traditional Chinese medicine

The liver, a complex parenchymal organ, possesses a distinctive microcirculatory system crucial for its physiological functions. An intricate interplay exists between hepatic microcirculatory disturbance and the manifestation of pathological features in diverse liver diseases. This review updates the main characteristics of hepatic microcirculatory disturbance, including hepatic sinusoidal capillarization, narrowing of sinusoidal space, portal hypertension, and pathological angiogenesis, as well as their formation mechanisms. It also summarized the detection methods for hepatic microcirculation. Simultaneously, we have also reviewed the characteristics of microcirculatory disturbance in diverse liver diseases such as acute liver failure, hepatic ischemia-reperfusion injury, viral hepatitis, non-alcoholic fatty liver disease, hepatic fibrosis, hepatic cirrhosis, and hepatocellular carcinoma. Finally, this review also summarizes the advancement in hepatic microcirculation attributed to traditional Chinese medicine (TCM) and its active metabolites, providing novel insights into the application of TCM in treating liver diseases.

Neuronal Apoptosis in Patients with Liver Cirrhosis and Neuronal Epileptiform Discharge Model Based upon Multi-Modal Fusion Deep Learning

Neurons refer to nerve cells. Each neuron is connected with thousands of other neurons to form a corresponding functional area and carry out complex communication with other functional areas. Its importance to the human body is self-evident. There are also many scholars studying the mechanism of apoptosis. This paper proposes a study of neuronal apoptosis in patients with liver cirrhosis and neuronal epileptiform discharge models based on multi-modal fusion deep learning, aiming to study the influencing factors of abnormal neuronal discharge in the brain. The method in this paper is to study multi-modal information fusion methods, perform Bayesian inference, and analyze multi-modal medical data. The function of these research methods is to obtain the relationship between the independence of information and the intersection of information among modalities. In the neuronal epileptiform discharge model, the mRNA expression level of the necroptotic signaling pathway related protein was detected, and the mechanism of neuronal necrosis in patients with liver cirrhosis was explored. Experiments show that the neuron recognition rate has been increased from 67.2% to 84.5%, and the time has been reduced, proving the effectiveness of deep learning.