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.

As new evidence emerges, treatment strategies toward the functional cure of chronic hepatitis B are evolving. In 2019, a panel of national hepatologists published a Consensus Statement on the functional cure of chronic hepatitis B. Currently, an international group of hepatologists has been assembled to evaluate research since the publication of the original consensus, and to collaboratively develop the updated statements. The 2.0 Consensus was aimed to update the original consensus with the latest available studies, and provide a comprehensive overview of the current relevant scientific literatures regarding functional cure of hepatitis B, with a particular focus on issues that are not yet fully clarified. These cover the definition of functional cure of hepatitis B, its mechanisms and barriers, the effective strategies and treatment roadmap to achieve this endpoint, in particular new surrogate biomarkers used to measure efficacy or to predict response, and the appropriate approach to pursuing a functional cure in special populations, the development of emerging antivirals and immunomodulators with potential for curing hepatitis B. The statements are primarily intended to offer international guidance for clinicians in their practice to enhance the functional cure rate of chronic hepatitis B.

As new evidence emerges, treatment strategies toward the functional cure of chronic hepatitis B are evolving. In 2019, a panel of national hepatologists published a Consensus Statement on the functional cure of chronic hepatitis B. Currently, an international group of hepatologists has been assembled to evaluate research since the publication of the original consensus, and to collaboratively develop the updated statements. The 2.0 Consensus was aimed to update the original consensus with the latest available studies, and provide a comprehensive overview of the current relevant scientific literatures regarding functional cure of hepatitis B, with a particular focus on issues that are not yet fully clarified. These cover the definition of functional cure of hepatitis B, its mechanisms and barriers, the effective strategies and treatment roadmap to achieve this endpoint, in particular new surrogate biomarkers used to measure efficacy or to predict response, and the appropriate approach to pursuing a functional cure in special populations, the development of emerging antivirals and immunomodulators with potential for curing hepatitis B. The statements are primarily intended to offer international guidance for clinicians in their practice to enhance the functional cure rate of chronic hepatitis B.

As new evidence emerges, treatment strategies toward the functional cure of chronic hepatitis B are evolving. In 2019, a panel of national hepatologists published a Consensus Statement on the functional cure of chronic hepatitis B. Currently, an international group of hepatologists has been assembled to evaluate research since the publication of the original consensus, and to collaboratively develop the updated statements. The 2.0 Consensus was aimed to update the original consensus with the latest available studies, and provide a comprehensive overview of the current relevant scientific literatures regarding functional cure of hepatitis B, with a particular focus on issues that are not yet fully clarified. These cover the definition of functional cure of hepatitis B, its mechanisms and barriers, the effective strategies and treatment roadmap to achieve this endpoint, in particular new surrogate biomarkers used to measure efficacy or to predict response, and the appropriate approach to pursuing a functional cure in special populations, the development of emerging antivirals and immunomodulators with potential for curing hepatitis B. The statements are primarily intended to offer international guidance for clinicians in their practice to enhance the functional cure rate of chronic hepatitis B.

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.

Objective To study the effect of nano-ceria on doxorubicin-induced cardiotoxic injury and its effect on P53 gene expression,and to explore the mechanism of nano-ceria on doxorubicin-induced cardiotoxic injury.Methods H9C2 myocardial cells were cultured and randomly divided into five groups:control group,model group(1μmol/L adriamycin),nano-cerium oxide group(10μg/ml nano-cerium oxide),experimental group(1μmol/L adriamycin +10μg/ml nano-cerium oxide),and positive control group(1μmol/L adriamycin+10μmol/L dexperimine).The adriamycin induced cardiotoxicity model was established,and the viability of myocardial cells was measured by CCK-8 method.The contents of lactate dehydrogenase(LDH)and malondialdehyde(MDA)in myocardial cells were detected by biochemical method.The levels of reactive oxygen(ROS)and the apoptosis rate in myocardial cells were detected by flow cytometry.The expressions of Bax,Bcl-2 and P53 proteins in myocardial cells were detected by Western blot.Results Compared with the control group,the cell viability was decreased in the model group,the cell LDH and MDA contents were increased,the intracellular ROS level and apoptosis rate were increased,the expressions of Bax and P53 proteins were increased,and the expression of Bcl-2 protein was decreased,and the ratio of Bcl-2/Bax was decreased(all P<0.001).Compared with the model group,the experimental group showed increased cell viability,decreased cell LDH and MDA contents,decreased cell ROS content and apoptosis rate,decreased Bax and P53 protein expressions,and increased Bcl-2 protein expression,and the Bcl-2/Bax ratio was increased(all P<0.001).Conclusion Ceria nanoparticles can effectively prevent adriamycin-induced cardiotoxic injury,and its effect may be related to the down-regulation of P53 gene to inhibit cardiomyocyte apoptosis.

Objective To evaluate the effect of coagulation function changes on the incidence of acute kidney injury (AKI) after liver transplantation. Methods Clinical data of 245 liver transplant recipients who met the inclusion and exclusion criteria were retrospectively analyzed. According to the incidence of AKI after liver transplantation, all recipients were divided into the AKI group (n=99) and non-AKI group (n=146). The incidence of AKI after liver transplantation was summarized. Perioperative parameters of the recipients were collected. The risk factors of AKI after liver transplantation were assessed by univariate and multivariate analysis. Results Among 245 recipients undergoing liver transplantation, 99 cases developed AKI after operation with an incidence rate of 40.4%. Preoperative serum creatinine levels of the recipients and the in-hospital fatality were relatively high in the AKI group (all P < 0.05). Compared with the recipients in the non-AKI group, those in the AKI group presented with significantly higher liver function parameters within postoperative 24 h, significantly decreased levels of stage Ⅱ coagulation parameters including coagulation factorsⅤ, Ⅶ, Ⅸ, Ⅹ, Ⅻ and protein S, protein C and antithrombin Ⅲ, evidently elevated prothrombin time international normalized ratio (PT-INR), remarkably increased stage Ⅲ coagulation parameters including D-dimer and fibrin degradation product (FDP) levels and considerably decreased fibrinogen (FIB) level (all P < 0.05). Thrombelastogram showed that the R value was increased, the α angle was decreased and the coagulation time was prolonged in the AKI group (all P < 0.05). Logistic regression analysis demonstrated that the increased R value of postoperative thrombelastogram [odd ratio (OR) 1.116, 95% confidence interval (CI) 1.018-1.223, P=0.019], and decreased levels of antithrombin Ⅲ (OR 0.974, 95%CI 0.955-0.993, P=0.007) were the independent risk factors of incidence of AKI after liver transplantation. Conclusions The incidence of AKI after liver transplantation is high, which is associated with the coagulation function changes of the recipients. Decreased coagulation factor activity (increased R value) and declined antithrombin Ⅲ level are the independent risk factors of AKI in liver transplantat recipients.

Objective:To investigate the effect of lncRNA UCA1 on the radiosensitivity of in vitro cultured glioma cell lines SHG-44, U87 and U251 by regulating the miR-873-5p expression. Methods:The survival of glioma cells SHG-44, U87 and U251 treated with different radiation intensities (0, 2, 4, 6 and 8 Gy) was detected by colony formation assay. The expression levels of UCA1 in glioma cells SHG-44, U87 and U251 were measured by qRT-PCR. The radiation-resistant glioma cells U87 and U251 were selected for subsequent study. After silencing UCA1 expression and/or over-expressing miR-873-5p, the cell survival rate was detected by colony formation assay, and the cell apoptosis rate was determined by flow cytometry. The dual luciferase reporter gene assay and qRT-PCR were employed to verify the targeting relationship between UCA1 and miR-873-5p.Results:UCA1 was up-regulated in the radiation-resistant U87 and U251 cells. Silencing UCA1 or over-expressing miR-873-5p inhibited the survival of U87 and U251 cells, and promoted the cell apoptosis induced by radiation exposure. miR-873-5p was a target gene of UCA1, and UCA1 negatively regulated the expression of miR-873-5p. The inhibition of miR-873-5p could reverse the effect of silencing UCA1 on the radiosensitivity of glioma cells. Silencing UCA1 increased the inhibitory effect of radiation on the glioma cell U251 xenografts.Conclusion:Silencing UCA1 inhibits the survival of glioma cells and promotes the cell apoptosis by up-regulating the expression of miR-873-5p, thereby increasing the radiosensitivity of glioma cells.

ObjectiveTo explore the relationship between schizotypal personality traits and creativity in college students and the mediating role of cognitive flexibility. MethodsSchizotypal Personality Questionnaire （SPQ）， Cognitive Flexibility Inventory （CFI） and Williams Creative Aptitude Test （WCAT） were used to assess 471 college students. Thereafter， Spearman correlation analysis was used to explore the relationship among the variables and the Bootstrap methodology was used to estimate the mediating role of cognitive flexibility. ResultsThe total SPQ， positive and disorganized schizotypal traits scores， and CFI score were all positively correlated with WCAT score （r=0.241~0.313， P<0.01）. The total SPQ， positive and disorganized schizotypal traits scores were also positively correlated with CFI score （r=0.111~0.128， P<0.05）. Cognitive flexibility mediated the relationship between positive schizotypal traits and creativity ［indirect effect=0.052 （95% CI： 0.016~0.112， P<0.01）， accounting for 11.93% of the total effect］. Cognitive flexibility mediated the relationship between disorganized schizotypal traits and creativity ［indirect effect=0.075 （95% CI： 0.020~0.161， P<0.01）， accounting for 11.50% of the total effect］. ConclusionSchizotypal personality has a direct impact on the creativity of medical students and also cause an indirect impact on their creativity through the mediating role of cognitive flexibility.

Objective: To analyze the clinical characteristics of chronic pancreatitis (CP) and evaluate its impact on growth of children. Methods: A retrospective study was conducted in 94 children (male 49 cases, female 45 cases) who were diagnosed with CP in the Department of Pediatrics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine from August 2008 to July 2015. Clinical characteristics, such as features of abdominal pain, etiologies, image data, levels of serum amylase and lipase, and physical development data were extracted from electronic medical records. The comparison between groups based on etiology or with normal control was performed with student′s t test. Results: The age of first episode was (8.2±3.7) years. There were 61 (65%) children diagnosed with idiopathic CP, and 25 (27%) with anatomic abnormalities. The age of onset in the group with anatomic abnormalities was lower than that in the idiopathic CP group ((6.3±3.5) vs. (8.9±3.4) years, t=3.211, P=0.002). There were 51 (54%) patients with serum amylase elevation, 41(44%) patients with lipase elevation, and 35 (37%) with elevation in both. The questionnaire showed that 28 out of 30 children had moderate to severe abdominal pain. The patients′ weight standard score (SDS) was significantly lower than the overall average in normal control (-0.4±1.1 vs. 0, t=-3.308, P=0.001). Meanwhile, the mean level of insulin like growth factor-1 (IGF-1) SDS of 35 children was significantly decreased (-1.8±1.8 vs. 0, t=-6.136, P<0.01). There were 69% (37/54) patients diagnosed by magnetic resonance cholangiopancreatography (MRCP) combined with magnetic resonance imaging (MRI), higher than that diagnosed by abdominal ultrasound (29%, 27/94). Conclusions Idiopathic CP and anatomic abnormalities were the two main etiologies. Normal level of serum amylase and lipase or negative finding of ultrasound cannot exclude CP, while MRCP and MRI should be considered to improve CP diagnostic rate. It is noteworthy that growth delay would happen in children with CP history.