ObjectiveTo summarize the relationship between Kupffer cells (KCs) and liver diseases.MethodsThe related literatures about the research progress of KCs in liver diseases in recent years were collected and analyzed.ResultsKCs were an important component of the monocyte-macrophage system. In a specific environment, activated KCs participated in a variety of inflammatory reactions, immune tolerance, and damage to hepatocytes by presenting antigens, secreting cytokines and chemokines, phagocytosis, and so on. KCs could not only be activated into M1 to promote inflammatory reaction and aggravate hepatocyte injury, but also could be activated to M2 to play an anti-inflammatory effect and improve liver injury. The role of KCs in liver diseases was very complex, but it also had potential research value.ConclusionKCs can affect the progression of liver diseases through many mechanisms and can provide new ideas for the prevention and treatment of liver diseases.
Objective To summarize the mechanism and research progress of Kruppel-like factor 2 (KLF2) in various liver diseases and related drug development, providing theoretical basis for further mechanism exploration and clinical application. Method The literatures on the mechanism of KLF2 in liver diseases at home and abroad were collected and summarized. Results KLF2 was widely distributed and had various functions in human body, mainly regulating the growth, differentiation and function of endothelial cells, inhibiting pro-inflammatory and pro-thrombotic gene expression, and participating in important physiological processes such as liver inflammation, oxidative stress and thrombosis, and affecting the occurrence and development of various liver diseases. The regulation of KLF2 expression by statins had been widely used in the treatment of liver diseases. Conclusion KLF2 regulates the expression of related molecules through a variety of pathways and affects the functions of various cells in the liver, which is the focus of research on improving liver injury.
【Abstract】ObjectiveBy using multidetector row spiral CT (MDCT) to investigate the CT imaging findings of gallbladder abnormalities caused by hepatic parenchymal diseases and those of inflammatory cholecystitis. MethodsCT and clinical data of 80 patients with gallbladder abnormalities were retrospectively reviewed. Fifty patients were in hepatic disease group, including 20 chronic hepatitis, 25 liver cirrhosis, and 5 cirrhosis with hepatocellular carcinoma. Thirty patients were in inflammatory group, including 19 chronic cholecystitis, 6 acute cholecystitis, 3 cholecystitis with acute pancreatitis, 1 gangrenous cholecystitis, and 1 xanthogranulomatous cholecystitis. All patients underwent MDCT plain scan and contrastenhanced dualphase scanning of upper abdomen. ResultsIn hepatic disease group, 48 cases had evenly thickened gallbladder wall (96%) with mean thickness of (3.67±0.49) mm; 38 cases had clear gallbladder outlines (76%); 38 cases had gallbladder wall enhancement of various degree (76%); 14 cases had gallbladder bed edema and localized nondependant pericholecystic fluid collection (28%). In inflammatory cholecystitis group, 28 cases had obscuring gallbladder outlines (93%) ; 26 cases had gallbladder wall evenly thickened (87%), 4 cases showed unevenly thicked wall (13%), the mean thickness being (4.54±1.14) mm; 30 cases had inhomogenous enhancement of the gallbladder wall (100%); 9 cases had highattenuation bile (30%); 4 cases had dependant pericholecystic fluid collection (13%); 5 cases had transient enhancement of adjacent hepatic bed in arterial phase (17%); microabscess and gas in the gallbladder wall was observed in 1 case respectively. ConclusionMDCT can offer imaging findings useful for differentiating abnormal gallbladder changes caused by hepatic parenchymal diseases from those due to inflammatory cholecystitis.
Features and interaction between features of liver disease is of great significance for the classification of liver disease. Based on least absolute shrinkage and selection operator (LASSO) and interaction LASSO, the generalized interaction LASSO model is proposed in this paper for liver disease classification and compared with other methods. Firstly, the generalized interaction logistic classification model was constructed and the LASSO penalty constraints were added to the interactive model parameters. Then the model parameters were solved by an efficient alternating directions method of multipliers (ADMM) algorithm. The solutions of model parameters were sparse. Finally, the test samples were fed to the model and the classification results were obtained by the largest statistical probability. The experimental results of liver disorder dataset and India liver dataset obtained by the proposed methods showed that the coefficients of interaction features of the model were not zero, indicating that interaction features were contributive to classification. The accuracy of the generalized interaction LASSO method is better than that of the interaction LASSO method, and it is also better than that of traditional pattern recognition methods. The generalized interaction LASSO method can also be popularized to other disease classification areas.
Objective To summarize the application and prospect of susceptibility weighted imaging （SWI） in diagnosis of hepatic disease. Methods The application of SWI in diagnosis of hepatic disease was analyzed retrospectively via reviewed the literatures home and abroad, and to look forward to the future of the clinical values of SWI. Results A number of hepatic diseases such as cirrhosis, hematochromatosis， and malignant tumors could induce iron overload in hepatic cell and Kuffper cell. Because of SWI is sensitive to vein， vascular abnormality, haemorrhage （including all kinds of metabolities after bleeding）， iron overload， calcification, and so on, so the use of SWI in hepatic disease is explored continually. Conclusions SWI may be a new method for diagnosis of hepatic disease, which can supply more valuable information for clinician.
ObjectiveTo summarize the epidemiology of nonalcoholic fatty liver disease (NAFLD) and the epidemiological and economic burdens of NAFLD, so as to provide a reference for hospital management decision-making. MethodThe domestic and foreign guidelines relevant to NAFLD and the literatures relevant to epidemiological investigation and disease burden researches were summarized and its research progress was reviewed. ResultsThe global prevalence of NAFLD was increasing over years. The incidence, mortality, and disability adjusted life years of liver cirrhosis and liver cancer caused by NAFLD had increased year by year. The patients relevant to NAFLD of inpatients and outpatients had increased obviously, and the overall medical expenses had also shown a rising trend. The possible reasons were health care awareness, new drug research, population aging, and excessive medical consumption. In addition, children and adolescents with NAFLD had a obviously increased risk of liver or extrahepatic diseases. ConclusionsBy understanding the epidemiological trend of NAFLD, it is a certain understanding of the disease burden of NAFLD and the related factors affecting the increase of its treatment cost. It is believed that it is necessary to further pay attention to and strengthen the genetic characteristics, pathogenesis, drug research and development, and early diagnosis of cirrhosis and liver cancer relevant to NAFLD in the future. At the same time, the NAFLD group of children and adolescents should not be ignored.
ObjectiveTo summarize the mechanism of endoplasmic reticulum stress (ERS) in liver diseases. MethodWe sorted out and summarized the studies related to ERS and liver diseases in recent years. ResultsEndoplasmic reticulum plays important roles in protein folding, calcium ion storage, and lipid synthesis in cells. ERS will be induced when the number of misfolded/unfolded proteins in the endoplasmic reticulum increases or the calcium ion homeostasis is unbalanced. The endoplasmic reticulum regulates the unfolded protein response through three transmembrane receptor proteins to initiate corresponding pathways for restoring endoplasmic reticulum homeostasis. Prolonged stress can lead to metabolic disorders. Mild ERS can promote the progression of hepatocellular carcinoma, and continuous ERS will induce cell apoptosis and play an anti-tumor effect; ERS can promote lipid accumulation in non-alcoholic fatty liver disease and aggravate the progression of the disease; in hepatic ischemia reperfusion injury, ERS activation will aggravate liver damage. Meanwhile, ERS activation plays an important pathogenic role in the pathogenesis of drug-induced liver injury. ConclusionERS plays a crucial regulatory role in the occurrence and development of liver-related diseases, providing a theoretical basis and new approach for targeted ERS therapy in liver diseases.
Objective To analyze and summarize the research progression of phenotypic markers of hepatic sinusoidal endothelial cell （HSEC） and its role in the development and progression of the liver diseases. Methods Databases such as PubMed， Wanfang， CNKI， etc were retrieved for the latest articles on research advance in HSEC using “hepatic sinus endothelial cell”， “liver regeneration”， and “liver disease” as key words. All of the publications about studies on relation between HSEC and liver disease were reviewed and summarized. Results HSEC with specific cytoarchitectures and phenotypic markers was initially received “the message of damage” in the process of liver regeneration， hepatic immunological tolerance， hepatic fibrosis， and liver damage. Additionally， HSEC as the first barrier not only enabled liver to be protected but also was regarded as the first alternation of liver damage. Therefore， HSEC played a great important role in the process of the onset and progression of the liver disease. Conclusions The function of HSEC is complex. How do play a role and its the mechanism is unclarified， it is needed to be further studied.
【Abstract】ObjectiveBy using multidetector row spiral CT (MDCT) to investigate the CT imaging findings of gallbladder abnormalities caused by hepatic parenchymal diseases and those of inflammatory cholecystitis. MethodsCT and clinical data of 80 patients with gallbladder abnormalities were retrospectively reviewed. Fifty patients were in hepatic disease group, including 20 chronic hepatitis, 25 liver cirrhosis, and 5 cirrhosis with hepatocellular carcinoma. Thirty patients were in inflammatory group, including 19 chronic cholecystitis, 6 acute cholecystitis, 3 cholecystitis with acute pancreatitis, 1 gangrenous cholecystitis, and 1 xanthogranulomatous cholecystitis. All patients underwent MDCT plain scan and contrastenhanced dualphase scanning of upper abdomen. ResultsIn hepatic disease group, 48 cases had evenly thickened gallbladder wall (96%) with mean thickness of (3.67±0.49) mm; 38 cases had clear gallbladder outlines (76%); 38 cases had gallbladder wall enhancement of various degree (76%); 14 cases had gallbladder bed edema and localized nondependant pericholecystic fluid collection (28%). In inflammatory cholecystitis group, 28 cases had obscuring gallbladder outlines (93%) ; 26 cases had gallbladder wall evenly thickened (87%), 4 cases showed unevenly thicked wall (13%), the mean thickness being (4.54±1.14) mm; 30 cases had inhomogenous enhancement of the gallbladder wall (100%); 9 cases had highattenuation bile (30%); 4 cases had dependant pericholecystic fluid collection (13%); 5 cases had transient enhancement of adjacent hepatic bed in arterial phase (17%); microabscess and gas in the gallbladder wall was observed in 1 case respectively. ConclusionMDCT can offer imaging findings useful for differentiating abnormal gallbladder changes caused by hepatic parenchymal diseases from those due to inflammatory cholecystitis.
Objective To summarize advances in the application of machine learning in the diagnosis and treatment of liver disease. Method The recent literatures on the progress of machine learning in the diagnosis, treatment and prognosis of liver diseases were reviewed. Results Machine learning could be used to diagnose and categorize substantial liver lesions, tumourous lesions and rare liver diseases at an early stage, which could facilitate clinicians to take timely and appropriate treatment measures. Machine learning was helpful in informing clinicians in choosing the best treatment decision, which was conducive to reducing medical risks. It could also help to determine the prognosis of patients in a comprehensive manner, and provide assistance in formulating early rehabilitation treatment plans, adjusting follow-up strategies and improving future prognosis. Conclusions Multiple types of machine learning algorithms have achieved positive results in the clinical application of liver diseases by constructing different prediction models, and have great potential and excellent prospects in multiple aspects such as diagnosis, treatment and prognosis of liver diseases.