Stroke is the leading cause of death and disability among adults in China， and its common complications include digestive system abnormalities， cognitive impairment， depression， stroke-associated pneumonia， and hemiplegia. The combination of traditional Chinese and Western medicine has great potential in treating post-stroke complications. Xinglou Chengqitang （XLCQT） is a representative prescription of alleviating the disease in the upper part by treating the lower part. It has definite therapeutic effect and high safety. Clinically， XLCQT is often used to treat stroke and its complications. However， the quantity and quality of clinical trials of XLCQT in treating post-stroke complications need to be improved. Additionally， since the basic research is weak， the material basis and multi-target mechanism for the efficacy of this prescription are unknown. This article reviews XLCQT in terms of the pharmacodynamic basis， medicinal properties， safety evaluation， and progress in clinical research and mechanisms in treating post-stroke complications. This article summarizes 22 key active ingredients of XLCQT in treating acute stroke complicated with syndrome of phlegm heat and fu-organ excess. Among these key active ingredients， resveratrol， kaempferol， luteolin， chrysoeriol， apigenin， （+）-catechin， and adenosine have good pharmacokinetic properties and high bioavailability. The mechanisms of XLCQT in treating post-stroke complications are complex， including inflammatory response， brain-gut axis， hypothalamic-pituitary-adrenal （HPA） axis， intestinal flora， neurotrophic factors， autophagy， oxidative stress， and free radical damage. This review helps to deeply understand the pharmacodynamic basis and mechanisms of XLCQT in treating post-stroke complications and provides a theoretical basis for the clinical application of XLCQT against post-stroke complications and the development of drugs.

ObjectiveTo investigate the therapeutic effects and mechanisms of Qinlian Hongqutang （QLHQT） on nonalcoholic steatohepatitis （NASH）. MethodsC57BL/6J mice were randomly divided into normal and modeling groups. The NASH model was established by feeding a high-fat diet for 12 weeks. After successful modeling， mice were randomly assigned to the model group， low-， medium-， and high-dose QLHQT groups （0.51， 1.02， and 2.04 g·kg^-1）， and a positive control metformin group， with six mice in each group. The mice were treated for 8 weeks. Body weight was recorded before and after treatment. Serum levels of total cholesterol （TC）， triglycerides （TG）， and low-density lipoprotein cholesterol （LDL-C）， as well as hepatic TC， TG， and LDL-C contents， were determined by biochemical assays. Hematoxylin-eosin （HE） staining and oil red O staining were used to evaluate liver histopathology and lipid deposition， respectively. Flow cytometry， enzyme-linked immunosorbent assay （ELISA）， and Real-time polymerase chain reaction （Real-time PCR） were used to assess hepatic macrophage expression and related markers. Western blot and immunofluorescence were used to investigate the potential mechanisms of QLHQT in regulating macrophage polarization. ResultsCompared with the normal group， body weight and serum and hepatic levels of TC， TG， and LDL-C were significantly increased in the model group （P<0.01）. Liver histopathology showed unevenly distributed round lipid droplets in the hepatocyte cytoplasm， accompanied by inflammatory cell aggregation. Flow cytometry showed that the proportion of CD86-positive cells was significantly increased， whereas the proportion of CD206-positive cells was markedly decreased （P<0.05）. Hepatic inducible nitric oxide synthase （iNOS） levels and tumor necrosis factor-α （TNF-α） mRNA expression were significantly increased， while hepatic IL-10 levels and IL-4 mRNA expression were significantly decreased （P<0.01）. The protein expression levels of Toll-like receptor 4 （TLR4）， tumor necrosis factor receptor-associated factor 6 （TRAF6）， and myeloid differentiation factor 88 （MyD88） in the liver were significantly increased （P<0.01）. Compared with the model group， body weight was reduced in the high-， medium-， and low-dose QLHQT groups and in the metformin group. Serum and hepatic TC， TG， and LDL-C levels were significantly decreased （P<0.01）. Liver histopathology showed alleviated hepatic lipid deposition， with markedly reduced lipid droplets and inflammation. Immunofluorescence and flow cytometry showed that the proportions of CD86-positive cells were significantly decreased， whereas the proportions of CD206-positive cells were significantly increased in the high-， medium-， and low-dose QLHQT groups （P<0.05）. Hepatic iNOS levels and TNF-α mRNA expression were significantly decreased （P<0.01）， whereas hepatic IL-10 levels and IL-4 mRNA expression were significantly increased （P<0.01）. The hepatic protein expression levels of TLR4， TRAF6， and MyD88 were significantly decreased， while signal transducer and activator of transcription 6 （STAT6） phosphorylation was significantly increased （P<0.05， P<0.01）. There was no statistically significant difference in total STAT6 protein expression. ConclusionQLHQT effectively ameliorates hepatic inflammation in NASH mice， and the mechanism may involve STAT6- and TLR4-mediated signaling pathways driving polarization of M1 macrophages toward the M2 phenotype.

ObjectiveTo investigate the therapeutic effects and mechanisms of Qinlian Hongqutang （QLHQT） on nonalcoholic steatohepatitis （NASH）. MethodsC57BL/6J mice were randomly divided into normal and modeling groups. The NASH model was established by feeding a high-fat diet for 12 weeks. After successful modeling， mice were randomly assigned to the model group， low-， medium-， and high-dose QLHQT groups （0.51， 1.02， and 2.04 g·kg^-1）， and a positive control metformin group， with six mice in each group. The mice were treated for 8 weeks. Body weight was recorded before and after treatment. Serum levels of total cholesterol （TC）， triglycerides （TG）， and low-density lipoprotein cholesterol （LDL-C）， as well as hepatic TC， TG， and LDL-C contents， were determined by biochemical assays. Hematoxylin-eosin （HE） staining and oil red O staining were used to evaluate liver histopathology and lipid deposition， respectively. Flow cytometry， enzyme-linked immunosorbent assay （ELISA）， and Real-time polymerase chain reaction （Real-time PCR） were used to assess hepatic macrophage expression and related markers. Western blot and immunofluorescence were used to investigate the potential mechanisms of QLHQT in regulating macrophage polarization. ResultsCompared with the normal group， body weight and serum and hepatic levels of TC， TG， and LDL-C were significantly increased in the model group （P<0.01）. Liver histopathology showed unevenly distributed round lipid droplets in the hepatocyte cytoplasm， accompanied by inflammatory cell aggregation. Flow cytometry showed that the proportion of CD86-positive cells was significantly increased， whereas the proportion of CD206-positive cells was markedly decreased （P<0.05）. Hepatic inducible nitric oxide synthase （iNOS） levels and tumor necrosis factor-α （TNF-α） mRNA expression were significantly increased， while hepatic IL-10 levels and IL-4 mRNA expression were significantly decreased （P<0.01）. The protein expression levels of Toll-like receptor 4 （TLR4）， tumor necrosis factor receptor-associated factor 6 （TRAF6）， and myeloid differentiation factor 88 （MyD88） in the liver were significantly increased （P<0.01）. Compared with the model group， body weight was reduced in the high-， medium-， and low-dose QLHQT groups and in the metformin group. Serum and hepatic TC， TG， and LDL-C levels were significantly decreased （P<0.01）. Liver histopathology showed alleviated hepatic lipid deposition， with markedly reduced lipid droplets and inflammation. Immunofluorescence and flow cytometry showed that the proportions of CD86-positive cells were significantly decreased， whereas the proportions of CD206-positive cells were significantly increased in the high-， medium-， and low-dose QLHQT groups （P<0.05）. Hepatic iNOS levels and TNF-α mRNA expression were significantly decreased （P<0.01）， whereas hepatic IL-10 levels and IL-4 mRNA expression were significantly increased （P<0.01）. The hepatic protein expression levels of TLR4， TRAF6， and MyD88 were significantly decreased， while signal transducer and activator of transcription 6 （STAT6） phosphorylation was significantly increased （P<0.05， P<0.01）. There was no statistically significant difference in total STAT6 protein expression. ConclusionQLHQT effectively ameliorates hepatic inflammation in NASH mice， and the mechanism may involve STAT6- and TLR4-mediated signaling pathways driving polarization of M1 macrophages toward the M2 phenotype.

Objective: To explore the remodeling effect of a 12 week supervised exercise intervention on the relative proportion of body composition among junior and senior high school students with obesity using compositional data analysis (CoDA), to clarify the longitudinal association between body composition changes and the improvement of metabolic syndrome (MetS), and to identify the core body composition targets for ameliorating metabolic risk in adolescents. Methods: A randomized controlled trial design was employed in March 2025. Totally 182 obese adolescents aged 12-18 years from two junior and senior high schools in Tianjin were recruited and randomly assigned to an exercise intervention group ( n =92) and a health education control group ( n =90) at a 1∶1 ratio. The intervention group received a 12 week supervised aerobic combined with resistance exercise intervention (4 sessions/week, 60 min/session), while the control group only received routine health education concurrently. Body composition was determined using 3.0 T magnetic resonance imaging. With students sex specific MetS Z score as the core outcome, compositional data were processed via isometric log ratio transformation. Statistical tests were performed combining repeated measures MANOVA, multiple linear regression, and analysis of covariance. Results: After the intervention, the overall body composition of the intervention group changed significantly ( F =18.72, P <0.01), with the relative proportion of visceral fat decreasing the most (change the isometric logratio: -0.17), and the betweengroup difference was statistically significant ( P <0.01). The relative mass of visceral fat before and after the intervention was positively correlated with the MetS Z score (before intervention: β =1.02, 95% CI =0.06-1.98; after intervention: β =1.42, 95% CI =0.58-2.26, both P <0.05), and there was no statistically significant difference in the slopes and intercepts of the regression models between the two time points (both P >0.05). When the magnitude of weight loss was fixed, a greater relative reduction in visceral fat was associated with a more significant decrease in the MetS Z score. Conclusions The relative proportion of visceral fat is a core stable marker for MetS risk in obese junior and senior high school students. A 12 week supervised combined exercise intervention can effectively reduce the proportion of visceral fat and improve the risk of metabolic syndrome among junior and senior high school students.

Diabetes mellitus, primarily caused by insulin deficiency or insulin resistance, is a metabolic disorder characterized by hyperglycemia. It has become a global public health priority. In addressing the core issue of pancreatic dysfunction, the limitations of traditional treatments have become increasingly apparent, leading to a growing interest in novel strategies for islet function remodeling. With advancements in stem cell technology, stem cell therapy is emerging as a promising approach for islet function restoration. This review summarizes recent progress in stem cell therapy for islet function remodeling, with a particular focus on the application of stem cell technology to in vitro islet reconstruction, offering new insights for the development of efficient and safe therapeutic strategies for diabetes.

Objective To investigate the causal relationship between circulating white blood cells(WBC)and juvenile idiopathic arthritis(JIA)using a two-sample Mendelian randomization(MR)analysis,and to provide a reference for the treatment strategy of JIA.Methods Relevant data of WBC and JIA were extracted from the public data of genome-wide association studies.Then,bidirectional MR analysis was conducted using the inverse variance weighted method(IVW),MR-Egger regression method,mixed contamination method,and Bayesian weighted Mendelian randomization.A series of sensitivity analyses were used to verify the robustness of the results.Results After MR analysis,false discovery rate(FDR)correction and sensitivity verification,calculations using IVW as the main method showed that neutrophils could reduce the risk of JIA(OR=0.752,95%CI:0.622,0.908,P=0.003,PFDR=0.003),and that JIA could lead to increased monocyte counts(bete=0.015,95%CI:0.007,0.022,P=1.90E-04,PFDR=1.14E-03).Conclusion A bidirectional causal association is identified between WBC and the risk of JIA occurrence.

Objective:To explore the role of curcumin (Cur) in improving IgA nephropathy (IgAN) and its related mechanisms.Methods:Fifty 7-month-old miR-23b knockout (miR-23b -/-) mice weighing (25±5) g were used to establish an IgAN disease model, and were randomly divided into IgAN group, IgAN+Cur (150 mg/kg) group and IgAN+Cur (300 mg/kg) group using simple randomisation. Sixteen healthy 7-month-old weighing (25±3) g C57BL/6J wild-type mice served as the normal control group. IgAN+Cur (150 mg/kg) and IgAN+Cur (300 mg/kg) groups were respectively gavaged continuously with 150 mg/kg Cur and 300 mg/kg Cur for 8 weeks, and the normal control and IgAN groups were gavaged continuously with an equal dose of 0.9% sodium chloride solution for 8 weeks. The samples of urine, serum, intestinal fluid, intestinal tissues, kidney tissues and liver tissues were collected from each group. In vitro experiments, human cloned colon adenocarcinoma (Caco-2) cells were divided into blank control (Ctrl), Ctrl+Cur (10 μmol/L), Ctrl+ Cur (60 μmol/L), tumor necrosis factor-α（TNF-α), TNF-α+Cur (10 μmol/L) and TNF-α+Cur (60 μmol/L) groups. Enzyme-linked immunosorbent assay was used to detect serum alanine transaminase, aspartate transaminase, secretory IgA (sIgA), creatinine, blood urea nitrogen, 24 h urine microalbumin, as well as sIgA, TNF-α, interleukin（IL)-6 and IL-1β in the intestinal fluids. HE staining was used to observe the effect of Cur on liver tissues, the hyperplasia of glomerular mesangial zone in kidney tissues and the morphological and structural changes of intestinal epithelial barrier, and the histopathological damage scores were performed respectively. PAS staining was used to observe the changes of glomerular basement membrane and mesangial matrix. Immunofluorescence was used to observe the deposition of immune complexes in the glomerular mesangial zone. Real-time quantitative PCR was used to detect the mRNA expression levels of B-cell activating factor ( BAFF) and a proliferation inducing ligand ( APRIL). Western blotting was used to detect the protein expression levels of tight junction proteins zonula occluden-1 (ZO-1) and occludin in the mouse intestinal tissues. The potential targets of Cur in IgAN were predicted. Western blotting was used to detect the protein expression levels of tight junction proteins, as well as Toll-like receptor 9 (TLR9), myeloid differentiation primary response protein (MyD88), nuclear factor-κB p65 (NF-κB p65) and p-NF-κB p65. Results:Genetic identification results revealed that all IgAN model mice exhibited the miR-23b -/- genotype, confirming successful model establishment. Seven-month-old mice were subsequently selected for Cur treatment. Histopathological analysis demonstrated no significant differences in hepatic tissue morphology across groups, with comparable liver histopathological injury scores and unaltered liver function parameters, thereby validating the safety of Cur administration. Compared with the normal control group, IgAN mice displayed elevated levels of serum sIgA, serum creatinine, blood urea nitrogen and 24 h urine microalbumin (all P<0.05). Renal pathological results revealed severe mesangial hypercellularity in glomeruli, higher glomerular injury scores, and notable glomerular mesangial deposits of IgA, IgG and complement C3 in IgAN mice (all P<0.05). Additionally, intestinal pathological alterations were observed, including structural changes in intestinal epithelium and Peyer's patches, accompanied by significantly higher intestinal histopathological injury scores in IgAN mice ( P<0.05). Intestinal epithelial expression levels of ZO-1 and occludin were significantly reduced, while sIgA, TNF-α, IL-1β and IL-6 in intestinal fluid were elevated (all P<0.05). Serum FITC fluorescence intensity was markedly increased, and intestinal tissue exhibited upregulated mRNA expression of BAFF and APRIL (all P<0.05). Following Cur treatment, serum sIgA level and renal function indices in mice showed partial recovery (all P<0.05). Renal pathological improvements included alleviated mesangial hypercellularity, reduced glomerular injury scores, and diminished glomerular immune complex deposition (all P<0.05). Intestinal pathologies, including epithelial and Peyer's patch lesions, were mitigated, with decreased intestinal histopathological injury scores ( P<0.05). Additionally, intestinal tight junction protein expression levels were upregulated, intestinal fluid sIgA level was reduced, inflammatory markers were attenuated, serum FITC fluorescence intensity was declined, and intestinal BAFF and APRIL mRNA expression levels were downregulated (all P<0.05). In vitro experiments demonstrated that TNF-α exposure reduced tight junction protein expression in Caco-2 cells, whereas Cur treatment reversed the effect (all P<0.05). Target prediction analysis revealed that Cur effectively bound to TLR9 structural domain in IgAN. Experimental validation confirmed that Cur treatment suppressed the upregulated protein expression levels of TLR9, MyD88, NF-κB p65 and p-NF-κB p65 in intestinal tissues of IgAN mice (all P<0.05). Conclusion:Cur has a significant effect in the treatment of IgAN and can regulate intestinal mucosal immunity by inhibiting the TLR9/MyD88/NF-κB signaling pathway, thereby reducing renal injury and protecting the kidneys.

Objective:To investigate the protective effect and its mechanism of proscillaridin A (PSD-A) on podocyte injury in lupus nephritis (LN).Methods:Molecular docking and surface plasmon resonance techniques were used to analyze the binding status of PSD-A to signal transducer and activator of transcription 1 (STAT1). The immortalized human podocyte injury model in the lupus group was induced by the serum of systemic lupus erythematosus patients, and the control and PSD-A intervention (2 nmol/L, 4 nmol/L) groups were also set up. Six female 12-week-old C57BL/6 mice were designated as the control group, and 12 female 12-week-old MRL/lpr lupus mice were randomly divided into lupus group and PSD-A intervention group by random number table method. The PSD-A intervention group was intraperitoneally injected with 5 mg/kg PSD-A, once per week for 6 consecutive weeks. While the control group and the lupus group were intraperitoneally injected with the same volume of the solvent without PSD-A. Western blotting and real-time quantitative PCR were employed to detect the relative protein and mRNA expression levels of podocin, STAT1, and interferon-induced protein with tetratricopeptide repeat 1 (IFIT1) in podocytes of each group. Enzyme-linked immunosorbent assay was used to detect the levels of serum anti-double strand DNA antibody and interferon-α in mice. Coomassie brilliant blue was used to detect the urinary protein level. HE, PAS, Masson and PASM staining and transmission electron microscopy were used to observe the pathological changes of renal tissues. Immunohistochemistry was used to examine the protein expression of podocin, STAT1 and IFIT1 in renal tissues.Results:Molecular docking and surface plasmon resonance techniques proved that PSD-A could bind to STAT1 protein and they exhibited a robust binding affinity. The podocyte experiments showed that, compared with the lupus group, the relative expression levels of podocin protein and mRNA in the PSD-A intervention group were upregulated, while the relative expression levels of STAT1 and IFIT1 protein and mRNA were downregulated (all P<0.05). The animal experiments showed that, compared with the lupus group, the serum levels of anti-double strand DNA antibody, interferon-α, and urinary protein in PSD-A intervention group were decreased, the pathological damage of renal tissues was alleviated, and the injury of renal podocytes was reduced. Immunohistochemical staining showed that the relative protein expression levels of STAT1 and IFIT1 of renal tissues in the PSD-A intervention group were lower than those in the lupus group (all P<0.05). Conclusion:PSD-A can play a protective role in podocyte injury in LN, and its mechanism may be related to the inhibition of the STAT1 signaling pathway.

Objective To observe the value of contrast-enhanced ultrasound(CEUS)for diagnosing malignant adnexal tumors.Methods Totally 112 patients with single adnexal masse were retrospectively enrolled and divided into benign adnexal tumor group(benign group,n=73)and malignant adnexal tumor group(malignant group,n=39).Clinical data,laboratory indicators,ovarian-adnexal ultrasound reporting and data system(O-RADS)classification based on conventional ultrasound(US),CEUS manifestations and CEUS classification of benign and malignant tumors were compared between groups.Multivariable logistic regression analysis of clinical and laboratory indicators being statistically different between groups,as well as US O-RADS classification and CEUS classification was performed to screen the independent predictors of malignant adnexal tumors,and combined models were constructed using forward stepwise regression method.The efficacy of each independent predictor and combined model for diagnosing malignant adnexal tumors was analyzed.Results Statistical differences of carbohydrate antigen 125(CA125),US O-RADS classification,enhancement time and level of CEUS,as well as CEUS classification were found between groups(all P＜0.05).CA125,US O-RADS classification and CEUS classification were all independent predictors of malignant adnexal tumors(all P＜0.05).Combined model Ⅰ,Ⅱ and Ⅲ were constructed based on CA125+CEUS classification,US O-RADS classification+CEUS classification and CA125+US O-RADS classification+CEUS classification,respectively.The area under the curve(AUC)of single CA125 level,US O-RADS classification,CEUS classification and combined model Ⅰ,Ⅱ and Ⅲ for diagnosing malignant adnexal tumor was 0.708,0.809,0.908,0.918,0.945 and 0.954,respectively.AUC of combined model Ⅲ was higher than that of combined model Ⅰ(Z=-2.142,P=0.032),while no significant difference of AUC was found between combined model Ⅱ and Ⅰ nor Ⅱ and Ⅲ(both P＞0.05).Conclusion CEUS could be used to effectively diagnose malignant adnexal tumor.Combining with CA125 level and US O-RADS classification could significantly improve its diagnostic efficacy.

Objective:To investigate the prognostic factors for esophageal cancer after radical resection and the application value of machine learning prediction model.Methods:The retrospective cohort study was conducted. The clinicopatholigical data of 406 esophageal cancer patients who were admitted to Qilu Hospital of Shandong University from January 2018 to March 2022 were collected. There were 357 males and 49 females, aged (64±8)years. All patients underwent radical resection of esophageal cancer. The 406 patients were randomly divided into a training set of 285 cases and a validation set of 121 cases at a 7∶3 ratio based on a random number table. The training set was used to construct prediction model, and the validation set was used to validate prediction model. Patients were divided into high-risk group and low-risk group based on risk scores. Observation indicators: (1) follow-up of patients and analysis of influencing factors for prognosis; (2) construction and validation of machine learning prediction models. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. Comparison of ordinal data between groups was conducted using the rank sum test. The Kaplan-Meier method was used to calculate survival rate and plot survival curve, and the Log-rank test was used for survival analysis. The Cox proportional hazard regression model was used for univariate and multivariate analyses. Independent influencing factors were included, and data processing, machine learning model construction, and visualization were performed using R packages including random survival forest (RSF), gradient boosting machine (GBM), least absolute shrinkage and selection operator Cox regression (LASSO-Cox), Cox proportional hazards model boosting (CoxBoost), survival support vector machine (survivalsvm), extreme gradient boosting (XGBoost), supervised principal component analysis (SuperPC), and Cox partial least squares regression (plsRcox). Receiver operating characteristic (ROC) curves were drawn, and sensitivity, specificity, and area under the curve (AUC) were calculated. The Delong test was used to assess the differences in AUC among different models in the training set, and the time-dependent ROC was used to compare the predictive performance of different models. Calibration curves were used to evaluate model accuracy, and decision curve analysis (DCA) was used to evaluate overall net benefit. Results:(1) Follow-up of patients and analysis of influencing factors for prognosis. All 406 patients were followed up postoperatively for 28(range, 6-36)months, with 1- and 3-year overall survival rate of 86.5% and 40.9%, respectively. The 285 patients in the training set were followed up postoperatively for 30(range, 6-36)months, with 1- and 3-year overall survival rate of 85.1% and 35.5%, respectively. The 121 patients in the validation set were followed up postoperatively for 25(range, 6-36)months, with 1- and 3-year overall survival rate of 87.0% and 43.2%, respectively. There was no significant difference in postoperative overall survival rate between the training set and the validation set ( χ2=3.20, P>0.05). Results of multivariate analysis showed that left thoracic surgical approach, preopera-tive neutrophil count, vascular invasion, perineural invasion, pathological T2-4 stage, pathological N2-3 stage, and postoperative pneumonia were independent risk factors affecting postoperative survival of 285 patients in the training set ( hazard ratio=1.466, 1.037, 1.482, 1.549, 5.268, 7.727, 22.202, 2.539, 2.686, 1.425, 95% confidence interval as 1.026-2.096, 1.003-1.073, 1.008-2.179, 1.105-2.170, 1.201-23.099, 1.833-32.576, 4.734-104.128, 1.577-4.087, 1.631-4.422, 1.018-1.994, P<0.05). (2) Construction and validation of machine learning prediction models. Independent risk factors affecting postoperative survival were included to construct RSF, GBM, LASSO-Cox, CoxBoost, survivalsvm, XGBoost, SuperPC, and plsRcox machine learning prediction models. Results of Delong test showed that there were significant differences in the AUC of RSF and GBM from the other six models ( P<0.05). Results of time-dependent ROC curve showed that all 8 machine learning predic-tion models had good discriminative ability in the training cohort, among which the RSF machine learning prediction model had the best predictive performance. Results of calibration curve showed that the RSF machine learning prediction model fitted well for predicting postoperative 1-, 2-, and 3-year overall survival in the training cohort, with high consistency with actual results. Results of decision curve analysis showed that within a threshold range of 0-0.80, the RSF machine learning prediction model provided a better overall net benefit. Further analysis showed that in the validation set, the AUC of RSF machine learning prediction model for postoperative 1-, 2-, and 3-year survival prediction were 0.786 (95% confidence interval as 0.609-0.962), 0.774 (95% confidence interval as 0.676-0.873), and 0.750 (95% confidence interval as 0.652-0.848), respectively. Results of calibration curve showed that the RSF machine learning prediction model fitted well for predicting postopera-tive 1-, 2-, and 3-year overall survival in the validation set, with high consistency with actual results. In the training set, the optimal cutoff value of the RSF machine learning prediction model risk score was 11.7. Patients with risk score ≥11.7 were classified as the high-risk group, and those with risk score <11.7 as the low-risk group. The median survival times of the two groups were 18.0 months and >36.0 months, respectively, showing a significant difference between them ( χ2=73.30, P<0.05). In the validation set, the optimal cutoff value of the RSF machine learning prediction model risk score was 11.7. Patients with risk score ≥11.7 were classified as the high-risk group, and those with risk score<11.7 as the low-risk group. The median survival times of the two groups were 17.0 months and>36.0 months for the high-risk and low-risk groups, respectively, showing a significant difference between them ( χ2=35.20, P<0.05). Conclusions:Left thoracic surgical approach, preoperative neutrophil count, vascular invasion, perineural invasion, pathological T2-4 stage, pathological N2-3 stage, and postoperative pneumonia are independent risk factors affecting survival of esophageal cancer patients after radical resection. The RSF machine learning prediction model constructed based on these factors can effectively distinguish the survival prognosis of high-risk and low-risk patients.