A healthy gut consists of commensal flora,epithelial layer and gut-associated lymphoid tissue (GALT). GALT is hyporesponsive to commensal flora and dietary antigens,but can recognize and at-tack pathogens. Accumulating evidence suggests that dendritic cells (DCs) play a crucial role in managing this paradoxical situation and maintaining the complex homeostasis in gut. Influenced by intestinal epithelial cells (IECs) and commensal flora,intestinal DCs possess unique properties that enable them to regulate T-helper 2 (Th2) cells,regulatory T cells (Tregs) and immunoglobulin A (IgA)-producing cells in a steady state. During infection,intestinal DCs are involved in the induction of effector lymphocytes, although they are also responsible for initiating pathogenic responses in inflammatory bowel diseases (IBDs). Therefore, intestinal DCs are associated with not only the maintenance of immune tolerance to commensal flora,but also the induction of protective immune responses against pathogens. This review outlines the roles of commensal flora, epithelial layer, and GALT in mucosal homeostasis and inflammation and summarizes recent progress in DCs-mediated intestinal immune homeostasis.

【Objective】 To construct an easy-to-use individual survival prognostic tool based on competing risk analyses to predict the risk of 1-, 2- and 3- year recurrence for patients with non-muscle invasive bladder cancer (NMIBC). 【Methods】 The follow-up data of 419 NMIBC patients were obtained. The patients were randomly divided into training cohort (n=293) and validation cohort (n=126). The variables included age at diagnosis, sex, history of smoking, tumor number, tumor size, histolo-gic grade, pathological stage, and bladder perfusion drug. The cumulative incidence function (CIF) of recurrence was estimated using all variables in the training cohort and potential prognostic variables were determined with Gray’s test. The Fine-Gray subdistribution proportional hazard approach was used as a multivariate competitive risk analysis to identify independent pro-gnostic variables. A competing risk nomogram was developed to predict the recurrence. The performance of the competing risk model was evaluated with the area under the receiver operating characteristic curve (AUC), calibration curve, and Brier score. 【Results】 Five independent prognostic factors including age, number of tumors, tumor size, histologic grade and pathological stage were used to construct the competing risk model. In the validation cohort, the AUC of 1-, 2- and 3- year recurrence were 0.895 (95%CI: 0.831-0.959), 0.861(95%CI: 0.774-0.948) and 0.827(95%CI: 0.721-0.934), respectively, indicating that the model had a high predictive performance. 【Conclusion】 We successfully constructed a competing risk model to predict the risk of 1-, 2- and 3-year recurrence for NMIBC patients. It may help clinicians to improve the postoperative management of patients.