Objective To improve the accuracy and clinical interpretability of recurrence prediction after liver transplantation in patients with hepatocellular carcinoma（HCC），and to explore the potential application of explainable machine learning models in integrating multimodal data. Methods This study included data from 138 liver transplant patients with liver cancer at the Third Medical Center of the Chinese People's Liberation Army General Hospital from December 2018 to December 2021. Preoperative contrast-enhanced CT radiomics features and clinical variables were extracted. Predictive models were developed using four machine learning methods ：LASSO regression，random forest，support vector machine（SVM），and neural network. Importance of variate was employed to identify key predictive factors. Model performance was evaluated using area under the receiver operating characteristiccurve（AUC），Brier score，and calibration curves. A nomogram was ultimately constructed based on important variables. Results The AUCs for the random forest model in predicting recurrence at 1，2，and 3 years were 0.881，0.906，and 0.915，respectively，significantly outperforming other models. The importance analysis identified five key imaging features，and the nomogram model combining these with clinical variables demonstrated good consistency and predictive capability. Conclusion Explainable machine learning models based on multimodal data can effectively improve the accuracy and transparency of recurrence prediction following liver transplantation in HCC patients. These models have strong clinical applicability and provide valuable support for individualized preoperative risk assessmentand treatment decision-making. 

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 To explore the molecular mechanisms and potential inflammation-related biomarkers of hepatic ischemia reperfusion injury（HIRI）process using bioinformatics techniques. Methods HIRI datasets GSE12720 and GSE14951 were obtained. Differential expressed genes（DEGs）were analyzed for functional enrichment and pathway enrichment. Hub genes were obtained using protein interactions analysis，and the correlationbetween Hub genes and inflammatory genes was calculated to finalize the key genes. The biological processes involved in these key genes were explored using GSEA analysis，and the expression of key genes was verified by mouse HIRI model. Finally，miRNAs of the key genes were predicted. Results Signaling pathways such as TNF，IL-17，MAPK and NF-κB were involved in inflammatory and immune processes during HIRI，and five key genes were closely related to inflammatory responses and their expressions are upregulated after HIRI. Conclusion This studyconfirms the central role of the inflammatory response in the process of HIRI and provides new perspectives for the discovery of the pathogenesis and potential therapeutic targets of HIRI. 

Objective To systematically summarize the long-term follow-up strategy for pediatric liver transplantation constructed by Tianjin First Central Hospital，analyze its application effects in ensuring patient survival，improving follow-up adherence，and accurately detecting complications，so as to provide a replicable practical reference for clinical follow-up management after pediatric liver transplantation. Methods A retrospective study was conducted，including 1 967 pediatric liver transplant patients in Tianjin First Central Hospital from 2013 to 2024. A long-term follow-up strategy of“standardized follow-up procedure + multidisciplinary team（MDT）+ information platform”was established. Kaplan-Meier method was used to calculate patient and graft survival rates，and Logistic regression analysis was performed to identify factors influencing follow-up status. Results The1-year，5-year and 10-year patient survival rates were 95.6%、94.1% and 93.8%，respectively，while the 1-year，5-year and 10-year graft survival rates were 94.4%，92.6% and 90.2%，respectively. The regular follow-up rate was91.68%，the pure loss to follow-up rate was 2.07%，and 96 .4% of patients from other provinces received standardized follow-up through the information platform. Multivariate Logistic regression analysis showed that only "postoperativefollow-up time" was an independent risk factor affecting follow-up status（OR＝1.433，95% CI＝1.208～1.700， P＜0.001）. Conclusion The long-term follow-up strategy of "standardized follow-up procedure + MDT + information platform" constructed by our center can effectively ensure long-term patient survival，improve follow-up adherence，and accurately identify late high-risk complications. It is particularly suitable for the clinical situation in China with a high proportion of remote patients，and has important clinical promotion value.

Objective To analyze the research hotspots and development trends of artificial intelligencein the field of organ transplantation. Methods Literatures on the application of artificial intelligence inthe field of organ transplantation from January 2004 to June 2024 were retrieved from the Web of ScienceCore Collection and China National Knowledge Infrastructure database. CiteSpace 6.2.R6 software was used for visual analysis. Results A total of 728 relevant literatures were retrieved，559 English literatures and 143 Chinese literatures were included after screening. The number of literatures published in the early stage was small，while the number of literatures published in recent years has increased significantly. The country with the largest number of articles was the United States，followed by China. The top three institutions in terms of foreignpublications were Mayo Clinic，University of Toronto and Harvard University. Zhejiang University，Peking UnionMedical College and the First Affiliated Hospital of Sun Yat-sen University were the most active institutions in China. The authors who have published the most articles in English were Cheungpasitporn Wisit and Thongprayoon Charat，and the author who has published the most articles in Chinese was Ren Bin. The main high-frequency keywords in English were machine learning，survival，artificial intelligence，liver transplantation，kidney transplantation，mortality，risk，model，outcome and deep learning. The main high-frequency keywords in Chinese were machine learning， liver transplantation， kidney transplantation， deep learning， artificial intelligence， hepatocellular carcinoma，radiomics，liver cancer，prognosis and tacrolimus. The first emergent keywords in English were artificial neural networks，data mining and survival analysis，and the most recent were predictive model and kidney transplant. The first emergent keywords in Chinese were neural networks，cyclosporine A，and blood concentration，and the most recent were deep learning and machine learning. Conclusion The application of artificial intelligence in thefield of organ transplantation is increasing significantly. The use of machine learning and deep learning to construct prediction models and to analyze the survival of various organ transplantation patients is a current research hotspots. In the future，exchanges and cooperation between countries and disciplines can be strengthened to promote the study and application of advanced AI technologies，so as to further promote the development of this field. 

Objective To evaluate the long-term efficacy and neurological outcomes of liver transplantation in patients with decompensated liver cirrhosis complicated by hepatic myelopathy. Methods This single-center retrospective case analysis included 9 patients with decompensated liver cirrhosis and hepatic myelopathy who underwent liver transplantation at Tianjin First Central Hospital between January 2014 and March 2025 and were followed up long-term. Baseline characteristics，surgical data，and follow-up information were collected. Neurological disability and activities of daily living were assessed using the modified rankin scale（MRS）and the Modified Barthel Index（MBI），respectively. The Wilcoxon signed-rank test was employed to compare score differences before and after surgery. Results All 9 male patients were followed up，with a mean age of（46 .8 ±7.8）years. At the final postoperative follow-up，the median MRS score was significantly lower than the preoperative score〔3 .0（2 .0，4.0）vs.4.0（4 .0～4.0），P＝0.034〕. The median MBI score was hig her than the preoperative level〔92 .0（85 .0～100.0） vs. 86.0（58 .0～87.0），P＝0.075〕；although this difference did not reach statistical significance，it indicated a clear trend towards improvement. Case analysis suggests that patients with a shorter disease course may benefitmore. Conclusion Liver transplantation can significantly improve neurological disability in patients with hepatic myelopathy and shows a trend towards enhancing their activities of daily living，proving to be an effective treatment for myelopathy and shows a trend towards enhancing their activities of daily living，proving to be an effective treatment for this condition. Early intervention with liver transplantation may lead to optimal neurological outcomes.

Objective To analyze the fluid management plan and early clinical outcomes of patients after heart transplantation. Methods The clinical data of 121 heart transplant recipients were retrospectively analyzed in Chinese Academy of Medical Sciences Fuwai Hospital. The data on early fluid usage of the patients were sorted out and analyzed. Meanwhile， the occurrence and clinical outcomes of the main early complications of heart transplant patients after surgery were summarized and described. Results The negative fluid balance on the day after surgery was （1729.5±861.8） ml. The negative fluid balance from the 1st to the 3rd day after surgery was （1138.6±805.2） ml，（696.7±779.2） ml， and （527.1±694.3） ml respectively. The amount of colloid used on the day after surgery was 826.4±503.0 ml， and the average venous pressure was （3.0±2.0） mmHg. A total of 4 patients died in the hospital. Postoperative blood transfusion accounted for 14.9%， postoperative application of CRRT accounted for 5.0%， and secondary thoracotomy exploration accounted for 5.8%. Conclusion For heart transplant patients after surgery， the early management was guided by central venous pressure， in addition to floating catheter parameters， and through multiparameter guided dynamic fluid management. The risk of in-hospital death and the incidence of major complications of hearttransplant patients after surgery were at a relatively low level. 

Objective Maintaining stable concentrations of anti-rejection drugs represents a critical facetof post-kidney transplantation patient care; however，achieving personalized and precise management for each patient remains challenging. This study leverages an artificial intelligence-based deep learning framework to develop a machine learning predictive model for tacrolimus concentration，with the objective of recommending optimal dosing regimens for individual kidney transplant recipients. Methods Fifty kidney transplant recipients who underwentsurgery at the Urology Department of Beijing Friendship Hospital，Capital Medical University，between January 2024 and April 2025，were enrolled in this study. Drawing on prior experience in tacrolimus dosing，we collected data on patients' gender，age，weight，comorbidities，CYP3A5 metabolic phenotypes，initial tacrolimus（Tac）doses，and FK506 levels measured on postoperative days 7，9，11，13，and 15，with subsequent dosage adjustments made according to each concentration measurement. A LightGBM regression model was employed to predict and optimize tacrolimus dosing regimens. Results Among the 50 kidney transplant recipients enrolled in this study，none developed severe complications，including delayed recovery of graft function，postoperative infections，or bleedingThe dataset was partitioned into training and validation sets using a five-fold cross-validation approach. The final model demonstrated robust predictive performance in the test set，with a mean absolute error（MAE）of 0.166，root mean square error（RMSE）of 0.227，mean absolute percentage error（MAPE）of 7.035%，P20 of 0.935，P30 of 0.97，and a coefficient of determination（R-squared）of 0.932. Conclusion The LightGBM regression model exhibited excellent performance，providing a novel and effective strategy for personalized tacrolimus dosage adjustment in kidney transplant recipients. 

Objective To investigate the role of ultrasound-based volume assessment in perioperative fluid management of liver transplant recipients. Methods A total of 106 end-stage liver disease patients who underwent liver transplantation at the Liver Transplantation Center， China-Japan Friendship Hospital， between September 2020 and April 2024 were enrolled. Using a historical control design， patients were divided into two groups based on whether postoperative ultrasonic volume indices were monitored. Cumulative intensive care unit （ICU） fluid balance and length of ICU stay were compared between the groups. Results Baseline characteristics （sex， age， BMI， etiology） were comparable. Pre-transplant MELD-Na scores （23 ± 10 vs. 22 ± 9，P ＝ 0.654） and APACHE II scores on ICU admission 〔19（5）vs. 19（3），P ＝ 0.525〕 were not statistically different. Patients in the ultrasound-monitored group （n ＝ 53）had longer operative times 〔10.0（3.1） h vs 9.4（2.3） h，P ＝ 0.016〕 and greater intraoperative fluid balance 〔（5341± 3447） ml vs.（1728 ± 2519） ml，P ＜ 0.001） than the non-monitored group. However， cumulative ICU fluid balance 〔-863（4600）ml vs. -48（2786）ml ，P ＝ 0.029〕 and daily fluid balance〔-276（1123）ml vs. -12（811）ml， P ＝ 0.017〕 were lower in the ultrasound-monitored group. Mechanical ventilation duration， ICU length of stay， and totalhospital stay did not differ between groups. Subgroup analyses showed no clear association in ultrasonic volume indices （lung ultrasound score， E-wave velocity， and renal venous congestion grading） for three consecutive days after the patients were transferred to the general ward and the incidence of AKI within 48 h post-operation was comparable（P ＞0.05）. Conclusion Ultrasound-assisted perioperative volume assessment in liver transplant recipients can mitigate fluid overload but does not shorten hospital stay. 

Objective To analyze the clinical efficacy，timing of transplantation，prognosis and comprehensive management strategies of liver transplantation for langerhans cell histiocytosis（LCH）in children. Methods A case of liver transplantation for langerhans cell histiocytosis in children was analyzed. Databases of CNKI，Wanfang，VIP，PubMed and Web of Science（as of August 31，2025）were retrieved to collect the case reports on liver transplantation for langerhans cell histiocytosis（LCH）in children，and the main clinical data of the patients were analyzed descriptively. Results In Shanghai Children’s Hospital，a male patient with multisystem involvement LCH received chemotherapy and liver transplantation，experiencing no complications and achieving complete remission for over six years. A comprehensive literature review encompassed 15 studies， involving 39 patients in total. The male-to-female ratio was 0.95：1. The median age at LCH diagnosis was 22（6～48）months，and the median age at liver transplantation was 50（14～204）months. All patients exhibited liver involvement，with the skin being the most commonly affected site（71 .8%）. Thirty-two patients had involvementof three or more organs. Pathological confirmation of LCH was obtained for all cases，with skin biopsy representing the most frequent diagnostic method（59 .0%）. The median follow-up duration was 20 months（9 d～88 months）. Among the 39 patients，recurrence was observed in 7 cases，death occurred in 4 cases，vascular complications were reported in 2 cases，and the most prevalent infection was cytomegalovirus infection（33 .3%）. Conclusion Liver transplantation is an effective treatment for end-stage liver disease related to Langerhans cell histiocytosis in children. To ensure sustained complete remission，this approach should be integrated with chemotherapy，targeted therapy， and meticulous follow-up protocols.

Objective To explore the expression of helper T cell 17（Th17）/regulatory T cell（Treg）levels in kidney transplant patients and their predictive value for the occurrence of pulmonary infections. Methods A total of 74 patients with kidney transplantation from January 2020 to December 2022 in People's Hospital ofXinjiang Uygur Autonomous Region were analysed in the study. The proportion of Th17 and Treg cells in peripheral blood was detected before and 2 months after surgery，and the Th17/Treg level was calculated. Patients werefollowed up for 1 year after surgery，and were divided into infected group and non infected group accordingto postoperative pulmonary infection. We focused on the ratio of Th17/Treg cells in renal transplant patients，and analyzed the predictive value of Th17/Treg ratio for postoperative pulmonary infection in renal transplant patients. Results There was a statistical significant difference in preoperative Th17/Treg ratio in kidney transplant patients with or without smoking history，diabetes，hypoproteinemia，and pulmonary infection history（P ＜ 0.05）. During the follow-up period of 74 kidney transplant patients，there were 21 cases of concurrent pulmonary infections，with an incidence rate of 28.38%（21/74）. The proportion of smoking history，diabetes，hypoproteinemia，and pulmonary infection history in the infected group was higher than that in the uninfected group，and the Tac blood concentration was higher than that in the uninfected group 2 months after surgery. The proportion of Treg cells in peripheral blood before and after surgery was lower than that in the non infected group，while the proportion of Th17 cells and Th17/Treg ratio were higher than those in the non infected group（P ＜ 0.05）. The results of plotting the receiver operating characteristic（ROC）curve showed that the AUC values of Th17，Treg cell ratio，and Th17/Treg level predicting postoperative pulmonary infection in kidney transplant patients were all ≥ 0.7 before surgery and 2 months after surgery，with a certain predictive value. Among them，the preoperative Th17/Treg ratio had a more ideal predictive value. Conclusion The elevated level ofTh17/Treg in renal transplant patients may participate in the process of pulmonary infection in renal transplant patients，and the high expression of Th17/Treg may be related to a history of smoking，diabetes and other risk factors for pulmonary infection；Preoperative examination of Th17/Treg ratio in patients can effectively predict the risk of postoperative pulmonary infection. 

Objective To explore the research status and hotspots of postoperative infection in lungtransplantation in the past decade. Methods The literature related to lung transplantation infection from 2014 to 2023 was searched based on the Web of Science core collection database，and CiteSpace6.2.R2 software was used to analyze the network of authors，countries，publishing institutions，as well as keyword co-occurrence，clustering，and emergence. Results A total of 1457 articles were included. The year of 2022 was the year with the highest number of publications. Husain Shahid’s team published the most papers. The United States was the country with the most papers，and the University of Toronto was the institution with the most papers. The keyword co-occurrence showed that the hotpots mainly focus on infection prevention and management，immune response and infection，assessment，treatment and research. Sixteen major sections were generated by keyword clustering with the value of the clustering module Q ＝ 0.76 and the average contour value of clustering S ＝ 0.89，and 26 keywords with citation explosion were obtained by keyword emergence. Conclusion At present，the research on lung transplantation infection is popular，and the research in Europe and the United States is in a leading position. The research hotspots mainly focuson the management of postoperative fungal and viral infections，immunity and rejection，and rapid diagnosis. Accurate assessment and rapid differentiation of immune rejection and infection，imaging-assisted diagnosis of infection，and management of viral infection in lung transplantation recipients are the research frontiers of lung transplantation infection.