Objective:To analyze the prognostic factors of patients with liver cirrhosis and portal vein thrombosis (PVT), and to construct a prognostic prediction model based on machine learning methods.Methods:The clinical data of 388 patients with liver cirrhosis and PVT admitted to the Fifth Medical Center of PLA General Hospital from January 2022 to April 2024 were retrospectively collected and analyzed, including 243 males and 145 females, aged (56.9±10.9) years. A total of 388 patients were randomly divided into the training set ( n=310) and the testing set ( n=78) in a 4∶1 ratio. The Boruta algorithm was used to screen the key features in the training set, and then four machine learning algorithms, including random forest, support vector machine, generalized linear model and Bayesian, were used to establish a survival prediction model. Model performance was evaluated by the receiver operating characteristic (ROC) curves of the test set and the training set. The patients were followed up for 1 year for survival. Sort the importance of features based on the SHAP value. Results:There were 250 patients (80.6%) who survived and 60 (19.4%) who died. The model for end-stage liver disease score, total bilirubin, serum creatinine, prothrombin time, international normalized ratio, D-dimer, white blood cell count, severe ascites ratio, and Child-Pugh grade C ratio of liver function in the death group were higher than those in the survival group, and the red blood cell count and hematocrit were lower than those in the survival group, and the differences were statistically significant (all P<0.05). The areas under the ROC curve for predicting survival by random forest, support vector machine, generalized linear model and Bayesian model were 0.92, 0.78, 0.81 and 0.71 in the training set, and the area under the ROC curve in the testing set were 0.81, 0.72, 0.67 and 0.68, respectively. Random forest had the best prediction performance, with an accuracy of 81.7%, a sensitivity of 84.6%, and a specificity of 76.9% in the testing set. In the analysis of the importance of characteristic parameters of the random forest model, total bilirubin, red blood cells, hematocrit, serum creatinine, ascites classification, etc. had a relatively high contribution to the model. Conclusion:In the survival prediction model of patients with liver cirrhosis and PVT based on machine learning algorithm, the random forest model had high prediction performance, and total bilirubin may be the most important factor affecting the survival prognosis of patients.

Galectin-9 (Gal-9), a member of the β-galactoside-binding lectin family, is widely expressed in various tissues and cells. It can specifically bind to multiple glycoprotein receptors, including the receptors of Tim-3, CD44, 4-1BB/CD137, and Dectin-1, thereby regulating the activity of immune cells and participating in crucial physiological and pathological processes such as immune regulation and tumor development. Given its role in immunomodulation, Gal-9 is considered a potential target for immunotherapy, showing promising prospects in the treatment of various diseases, including autoimmune disorders, transplantation rejection, pregnancy complications, inflammation, infection, and cancer. This review summarizes the biological effects mediated by Gal-9 upon binding to its receptors, which may help to explore the potential application value of Gal-9 in clinical diagnosis and therapy.

Objective:To investigate the effects of ascites grading and the application of non-selective beta-blockers (NSBBs) on the 1-year prognosis of acute-on-chronic liver failure (ACLF).Methods:1 386 ascitic cases with ACLF were graded and followed up for one year. The 1-year prognostic effect of ascites grade and NSBBs was analyzed on ACLF by the Kaplan Meier Log-rank test, Cox stepwise regression, and multivariate regression.The t-test, Mann-Whitney U, or Kruskal-Wallis test were used for intergroup comparison of measurement data. The χ2 test was used for intergroup comparison of numerical data. Results:The incidence rate of ascites at admission was 77.56% in 1 386 ACLF cases. The Log-rank (Mantel-Cox) of the 1-year survival curve test for 1 386 ACLF patients with ascites grade was 21.384, P<0.01. Multivariate regression and Cox stepwise regression analysis showed that ascites grade, age, gastrointestinal bleeding, pulmonary infection, acute kidney injury, prothrombin activity (PTA), urea, MELD-Na score, and the use of NSBBs were closely related to the 1-year prognosis of ACLF. The log rank (Mantel-Cox) of NSBBs treatment in the grade 2/3 ascites group was 6.113, P=0.013, and the difference was statistically significant, suggesting that NSBBs treatment can help improve the 1-year survival rate in ACLF patients with grade 2 and 3 ascites. Conclusions:Ascites grading and the use of NSBBs affect the prognostic factor of ACLF at one year. NSBBs may be beneficial for the long-term prognosis of ACLF, and treatment can be continued in patients who have already received NSBBs prior to the onset of ACLF.

Objective:To analyze the prognostic factors of patients with liver cirrhosis and portal vein thrombosis (PVT), and to construct a prognostic prediction model based on machine learning methods.Methods:The clinical data of 388 patients with liver cirrhosis and PVT admitted to the Fifth Medical Center of PLA General Hospital from January 2022 to April 2024 were retrospectively collected and analyzed, including 243 males and 145 females, aged (56.9±10.9) years. A total of 388 patients were randomly divided into the training set ( n=310) and the testing set ( n=78) in a 4∶1 ratio. The Boruta algorithm was used to screen the key features in the training set, and then four machine learning algorithms, including random forest, support vector machine, generalized linear model and Bayesian, were used to establish a survival prediction model. Model performance was evaluated by the receiver operating characteristic (ROC) curves of the test set and the training set. The patients were followed up for 1 year for survival. Sort the importance of features based on the SHAP value. Results:There were 250 patients (80.6%) who survived and 60 (19.4%) who died. The model for end-stage liver disease score, total bilirubin, serum creatinine, prothrombin time, international normalized ratio, D-dimer, white blood cell count, severe ascites ratio, and Child-Pugh grade C ratio of liver function in the death group were higher than those in the survival group, and the red blood cell count and hematocrit were lower than those in the survival group, and the differences were statistically significant (all P<0.05). The areas under the ROC curve for predicting survival by random forest, support vector machine, generalized linear model and Bayesian model were 0.92, 0.78, 0.81 and 0.71 in the training set, and the area under the ROC curve in the testing set were 0.81, 0.72, 0.67 and 0.68, respectively. Random forest had the best prediction performance, with an accuracy of 81.7%, a sensitivity of 84.6%, and a specificity of 76.9% in the testing set. In the analysis of the importance of characteristic parameters of the random forest model, total bilirubin, red blood cells, hematocrit, serum creatinine, ascites classification, etc. had a relatively high contribution to the model. Conclusion:In the survival prediction model of patients with liver cirrhosis and PVT based on machine learning algorithm, the random forest model had high prediction performance, and total bilirubin may be the most important factor affecting the survival prognosis of patients.

Galectin-9 (Gal-9), a member of the β-galactoside-binding lectin family, is widely expressed in various tissues and cells. It can specifically bind to multiple glycoprotein receptors, including the receptors of Tim-3, CD44, 4-1BB/CD137, and Dectin-1, thereby regulating the activity of immune cells and participating in crucial physiological and pathological processes such as immune regulation and tumor development. Given its role in immunomodulation, Gal-9 is considered a potential target for immunotherapy, showing promising prospects in the treatment of various diseases, including autoimmune disorders, transplantation rejection, pregnancy complications, inflammation, infection, and cancer. This review summarizes the biological effects mediated by Gal-9 upon binding to its receptors, which may help to explore the potential application value of Gal-9 in clinical diagnosis and therapy.

Objective:To investigate the effects of ascites grading and the application of non-selective beta-blockers (NSBBs) on the 1-year prognosis of acute-on-chronic liver failure (ACLF).Methods:1 386 ascitic cases with ACLF were graded and followed up for one year. The 1-year prognostic effect of ascites grade and NSBBs was analyzed on ACLF by the Kaplan Meier Log-rank test, Cox stepwise regression, and multivariate regression.The t-test, Mann-Whitney U, or Kruskal-Wallis test were used for intergroup comparison of measurement data. The χ2 test was used for intergroup comparison of numerical data. Results:The incidence rate of ascites at admission was 77.56% in 1 386 ACLF cases. The Log-rank (Mantel-Cox) of the 1-year survival curve test for 1 386 ACLF patients with ascites grade was 21.384, P<0.01. Multivariate regression and Cox stepwise regression analysis showed that ascites grade, age, gastrointestinal bleeding, pulmonary infection, acute kidney injury, prothrombin activity (PTA), urea, MELD-Na score, and the use of NSBBs were closely related to the 1-year prognosis of ACLF. The log rank (Mantel-Cox) of NSBBs treatment in the grade 2/3 ascites group was 6.113, P=0.013, and the difference was statistically significant, suggesting that NSBBs treatment can help improve the 1-year survival rate in ACLF patients with grade 2 and 3 ascites. Conclusions:Ascites grading and the use of NSBBs affect the prognostic factor of ACLF at one year. NSBBs may be beneficial for the long-term prognosis of ACLF, and treatment can be continued in patients who have already received NSBBs prior to the onset of ACLF.

Galectin-9 （Gal-9） is a member of the galectin family that can specifically recognize and bind to galactosides. Recent studies have shown that Gal-9 is highly expressed in the liver and can help to maintain intrahepatic immune homeostasis and perform biological functions in various liver diseases. This article reviews the immunomodulatory functions of Gal-9 and its role in different liver diseases. Studies have shown that Gal-9 has important biological functions in different liver diseases through multiple pathways. Research on the specific immunomodulatory mechanisms and functions of Gal-9 may help to discover the therapeutic role of Gal-9 in liver diseases.

ObjectiveTo investigate the efficacy and safety of N-acetylcysteine （NAC） in the treatment of severe alcoholic hepatitis （SAH）， and to provide a basis for clinical medication for SAH. MethodsA prospective randomized controlled trial was conducted among 172 SAH patients with a Maddrey discriminant function score of >32 points who were recruited by The Fifth Medical Center of Chinese PLA General Hospital from June 2015 to June 2018， and these patients were divided into NAC group with 84 patients and control group with 86 patients. NAC （8 g/day， 28 days） was assessed in terms of its safety in SAH patients， its impact on 28-day biochemical parameters， and its role in improving 28- and 180-day survival rates. A further analysis was performed to investigate the effect of NAC on the 28- and 180-day survival rates of SAH patients with acute-on-chronic liver failure （ACLF-SAH patients） and those without acute-on-chronic liver failure （non-ACLF-SAH patients）. The independent-samples t test was used for comparison of normally distributed continuous data between two groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups. The Kaplan-Meier method was used to plot survival curves， and the Log-rank test was used for comparison of survival curves. Univariate and multivariate Cox proportional-hazards regression model analyses were used to investigate independent influencing factors. ResultsNo serious adverse events were observed during NAC treatment， suggesting that NAC had a good safety profile. Compared with the control group， NAC did not significantly improve the 28-day biochemical parameters （all P>0.05） and survival rate of SAH patients （P=0.081）， but it could improve the 180-day survival rate of SAH patients （67.4% vs 81.0%， χ²=4.280， P=0.039）. NAC did not improve the 28- and 180-day survival rates of ACLF-SAH patients （both P>0.05）； NAC did not improve the 28-day survival rate of non-ACLF-SAH patients （P>0.05）， but it could improve the 180-day survival rate of these patients （68.4% vs 88.9%， χ²=4.883， P=0.027）. The multivariate Cox regression survival analysis showed that NAC treatment （hazard ratio ［HR］=2.530， 95% confidence interval ［CI］： 1.334‍ ‍— 4.796， P=0.004，）， Maddrey discriminant function score （HR=3.852， 95%CI： 2.032 — 7.304， P<0.001）， and serum sodium level （HR=1.948， 95%CI： 1.079‍ ‍—‍ ‍3.517， P=0.027） were independent influencing factors for 180-day survival rate in SAH patients. ConclusionNAC has a good safety profile in the treatment of SAH and can improve the 180-day survival rate of SAH patients， and in particular， non-ACLF-SAH patients can benefit from NAC treatment in terms of middle- and long-term survival rates.

Serum cholinesterase(ChE)level is important for the diagnosis and prognostic evaluation of various diseases such as liver diseases and toxic diseases,and butyrylcholinesterase(BuChE)is an important component of ChE.Mutations in the BCHE gene can cause a significant reduction in the level of BuChE,with extensive reports in European and American populations and relatively few reports in Eastern countries,particularly China.This study describes a male patient,aged 35 years,who was misdiagnosed with organophosphorus pesticide poisoning due to an extreme reduction in ChE level and was given detoxification therapy,but such diagnosis was excluded by various biochemical examinations.Finally whole-exome sequencing and Sanger sequencing revealed the complex heterozygous mutations of c.1027dup and c.401dup at exon 2 of the BCHE gene,and hereditary BuChE deficiency due to these mutations is the cause of the extreme reduction in ChE level.