Background and aims:Hepatocellular carcinoma(HCC)is a tumor of high heterogeneity and complexity,which poses significant challenges to effective treatment and patient prognosis because of its immune evasion characteristics.To address these issues,single-cell technology and machine learning methods have emerged as a promising approach to identify genes associated with immune escape in HCC.This study aimed to develop a prognostic risk score model for HCC by identifying intrinsic immune-evasion genes(IIEGs)through single-cell technology and machine learning,providing insights into immune infiltration,enhancing predictive accuracy,and facilitating the development of more effective treatment strategies.Materials and methods:The study utilized data from The Cancer Genome Atlas database to analyze gene expression profiles and clinical data related to intrinsic immune evasion in patients with HCC.Various tools,including the Human Protein Atlas,cBioPortal,single-cell analysis,machine learning,and Kaplan-Meier plot,were used to analyze IIEGs.Functional enrichment analysis was conducted to explore po-tential mechanisms.In addition,the abundance of infiltrating cells in the tumor microenvironment was investigated using single-sample gene set enrichment analysis,CIBERSORT,xCELL,and tumor immu-nophenotype algorithms.The expression of glycosylphosphatidylinositol anchor attachment 1(GPAA1)was examined in the clinical sample of HCC by quantitative real-time polymerase chain reaction,Western blotting,and immunohistochemical staining.Results:Univariate Cox analysis identified 63 IIEGs associated with the prognosis of HCC.Using random forest,least absolute shrinkage and selection operator regression analysis,and support vector machine,a risk score model consisting of six IIEGs(carbamoyl-phosphate synthetase 2,aspartate transcarbamylase,and dihydroorotase(CAD),phosphatidylinositol glycan anchor biosynthesis class U(PIGU),endoplasmic reticulum membrane protein complex subunit 3(EMC3),centrosomal protein 55(CEP55),autophagy-related 10(ATG10),and GPAA1)developed,which was validated using 10 pairs of HCC and adjacent non-cancerous samples.Based on the calculated median risk score,HCC samples were categorized into high-and low-risk groups.The Kaplan-Meier curve analysis showed that the high-risk group had a worse prognosis compared with the low-risk group.Time-dependent receiver operating characteristic analysis demonstrated the accurate predictive capability of the risk score model for HCC prognosis.Furthermore,immune infiltration analysis showed a positive correlation between the risk score model and 40 immune checkpoint genes as well as Th2 cells.Conclusions:A prognostic risk score model was formulated by six IIEG signatures and showed promise in predicting the prognosis of patients diagnosed with HCC.The utilization of the IIEG risk score as a novel prognostic index,together with its significance as a valuable biomarker for immunotherapy in HCC,provides benefit for patients with HCC in determining therapeutic strategies for clinical application.

Objective To systematically evaluate the intervention effect of social psychological intervention on the health status of patients with bariatric surgery(BS).Methods 8 databases,including PubMed,PsycInfo,and Embase and Clinic Trials,were retrieved to recruit randomized controlled trials with computer from database establishing time to Sep.2022.Independent quality evaluation was conducted by 2 researchers,and Meta-analysis was performed by the RevMan5.3 software.Results Totally 23 RCTs were included.The meta-analysis showed that psychosocial interventions in BS patients improve emotional eating and binge eating behavior[SMD=-0.44,95％CI(-0.78,-0.09),P=0.010;MD=-5.88,95％CI(-8.65,-3.11),P＜0.001],promote better quality of life[SMD=0.30,95％CI(0.02,0.59),P=0.040]and physical mobility,alleviates anxiety and depression[SMD=-0.37,95％CI(-0.67,-0.08),P=0.010;SMD=-0.59,95％CI(-0.84,-0.33),P＜0.001].However,the effect on improving eating disorders[MD=-0.01,95％CI(-0.19,0.18),P=0.950]is not significant,and subgroup analysis results of different intervention measures and follow-up times showed that there was no statistically significant difference in weight changes between the social psychological intervention group and the control group.Conclusion Psychosocial intervention can effectively improve the mental state and eating behavior of the bariatric surgery patients,improve the quality of life and increase physical activity of patients.However,the effect of intervention on eating disorder and weight change is still unclear.More high-quality clinical studies need to be carried out for further verification.