Objective To elucidate the relationship between preoperative immunotherapy，the abundance of tertiary lymphoid structures（TLS）in hepatocellular carcinoma（HCC）tissues，and to evaluate patient prognosis following liver transplantation. Methods The clinical data of 149 liver transplant patients with liver cancer at Huashan Hospital Affiliated to Fudan University from January 2018 to December 2023 were retrospectively analyzed. Pathological slides of each patient were scored for TLS. Patients were categorized into four groups based on downstaging treatment outcomes ：those initially meeting the Milan criteria（n ＝ 35），those exceeding the Milan criteria without downstaging treatment（n ＝ 38），successful downstaging cases（n ＝ 33），and unsuccessful downstaging cases （n ＝ 43）. Kaplan-Meier analysis and the log-rank test were employed for survival analysis. The correlation betweenimmunotherapy and TLS abundance was assessed using non-parametric statistical methods. Results Survival analysis of the overall cohort revealed that patients with high intratumoral TLS abundance had significantly higher recurrence-free survival（RFS）than those with low TLS abundance（P ＜ 0.05）. Among patients receiving downstaging treatment，the recurrence risk in the successful downstaging group was significantly lower than in the unsuccessful group（P ＜ 0.05）. Non-parametric testing of the successful downstaging group demonstrated that preoperative immunotherapy significantly increased intratumoral TLS abundance（P ＜ 0.05）. Similarly，nonparametric testing of all patients receiving immunotherapy showed a statistically significant increase in intratumoral TLS abundance in the successful downstaging group（P ＜ 0.05）. Conclusion Successful downstaging withpreoperative immunotherapy improves the prognosis of HCC patients undergoing liver transplantation，potentially by enhancing intratumoral TLS abundance. 

Objective Establish model of abdominal heterotopic heart transplantation in mice and summarize the experience to provide animal model support for further study of organ transplantation immunology. Methods Inbred BALB/c（n ＝ 30）and C57BL/6（n ＝ 30）mice were selected as donors，and inbred BALB/c（n ＝ 60）mice were used as recipients. The ascending aorta of the donor was anastomosed to the abdominal aorta of the recipient，and the pulmonary artery of the donor was anastomosed to the inferior vena cava of the recipient respectively to establish the heterotopic heart transplantation model. The survival time and the rejection of grafts were observed postoperatively. Results The successful rate of transplantation was 85%（51/60）. The donoroperation time was（7.0±1.0）min，and the recipient operation time was（60±10）min. The vascular anastomosis time was（25±3.0）min. After the transplantation，no immunosuppressive agent was used，and the survival time of the graft was（7.6±0.9）d. The graft on the fifth day，the seventh day showed typical rejection by histopathology. Conclusion Skilled microsurgical techniques and timely management of surgical complications are key to the successful establishment of abdominal heterotopic heart transplantation in mice. 

Objective To explore the physiological and psychological factors affecting pulmonary infection in kidney transplant recipients and to construct a risk prediction model. Methods The clinical and follow-updata of 327 recipients undergoing kidney transplantation in Shandong Provincial Qianfoshan Hospital from January2019 to January 2024 were retrospectively analyzed. The recipients were divided into pulmonary infection group（102 cases）and non-pulmonary infection group（225 cases）according to whether pulmonary infection occurred after kidney transplantation. The data of the two groups of recipients was analyzed with multivariate regression analyze，theprediction model of pulmonary infection of kidney transplant recipients was constructed，and the receiver operatingcharacteristic（ROC）curve was used to verify the predictive value. Results The rate of pulmonary infection within 1 years after kidney transplantation was 31.19%. Age，blood glucose，insomnia severe index，use of cyclosporine and mycophenolate mofetil were independent risk factors for pulmonary infection. While white blood cell count on postoperative day 5 and positive psychological capital were independent protective factors（P ＜ 0.05）.The areaunder curve（AUC）of the constructed model equation for predicting the risk of pulmonary infection was 88.7% with a Kappa value of 0.66（P ＜ 0.05）. Conclusion The prediction model of pulmonary infection in kidney transplant recipients constructed based on physiological and psychological factors has a good predictive value. 

Objective Post-renal transplantation anemia（PTA）occurs frequently in kidney transplant recipients，significantly impacting their quality of life and graft loss. Currently，effective methods to predictthe risk of persistent PTA early post-transplantation are lacking. This study aimed to develop a nomogram prediction model for early persistent PTA specifically tailored to kidney transplant recipients. Methods Using the electronic medical record system of Southern Hospital of Southern Medical University，patient data from January 1，2020 to December 31，2022 were obtained，and 245 subjects were ultimately selected as the research subjects. Among these，85% were randomly selected as the training set for model development，and the remaining 15% constituted the testing set. Using the Least Absolute Shrinkage and Selection Operator（Lasso）regression model，variables potentially affecting early persistent PTA were screened to identify predictive factors.A logistic regression analysis was employed to establish the prediction model. Model performance was assessed using Receiver operating characteristic（ROC）curves，area under the curve（AUC），Calibration plots，and decision Curve Analysis（DCA）. Results Identified predictive factors after screening included recipient's preoperative body mass index，preoperative serum albumin level，preoperative hemoglobin level，preoperative mean corpuscular volume，perioperative use of angiotensin-converting enzyme inhibitors or angiotensin receptor blockers，exogenous iron supplementation，and exogenous erythropoietin supplementation. The model demonstrated good discriminativeability with an AUC of 0.87 for the training set and 0.75 for the testing set，indicating robust predictive performance. Calibration and DCA further confirmed the accuracy and clinical utility of the model. Conclusion This nomogram prediction model utilizes early recipient information，including demographic characteristics，laboratory data，and medication regimens，to accurately predict individualized risk of early persistent PTA in kidney transplant recipients. This provides a basis for early clinical intervention，potentially improving patient prognosis and quality of life.