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Objective To identify M1 macrophage-related genes in rejection after kidney transplantation and construct a risk prediction model for renal allograft survival. Methods GSE36059 and GSE21374 datasets after kidney transplantation were downloaded from Gene Expression Omnibus (GEO) database. GSE36059 dataset included the samples from the recipients with rejection and stable allografts. Using this dataset, weighted gene co-expression network analysis (WGCNA) and differential analysis were conducted to screen the M1 macrophage-related differentially expressed gene (M1-DEG). Then, GSE21374 dataset (including the follow-up data of graft loss) was divided into the training set and validation set according to a ratio of 7∶3. In the training set, a multivariate Cox’s model was constructed using the variables screened by least absolute shrinkage and selection operator (LASSO), and the ability of this model to predict allograft survival was evaluated. CIBERSORT was employed to analyze the differences of infiltrated immune cells between the high-risk group and low-risk group, and the distribution of human leukocyte antigen (HLA)-related genes was analyzed between two groups. Gene set enrichment analysis (GSEA) was used to further clarify the biological process and pathway enrichment in the high-risk group. Finally, the database was employed to predict the microRNA (miRNA) interacting with the prognostic genes. Results In the GSE36059 dataset, 14 M1-DEG were screened. In the GSE21374 dataset, Toll-like receptor 8 (TLR8), Fc gamma receptor 1B (FCGR1B), BCL2 related protein A1 (BCL2A1), cathepsin S (CTSS), guanylate binding protein 2(GBP2) and caspase recruitment domain family member 16 (CARD16) were screened by LASSO-Cox regression analysis, and a multivariate Cox’s model was constructed based on these 6 M1-DEG. The area under curve (AUC) of receiver operating characteristic of this model for predicting the 1- and 3-year graft survival was 0.918 and 0.877 in the training set, and 0.765 and 0.736 in the validation set, respectively. Immune cell infiltration analysis showed that the infiltration of rest and activated CD4+ memory T cells, γδT cells and M1 macrophages were increased in the high-risk group (all P<0.05). The expression level of HLA I gene was up-regulated in the high-risk group. GSEA analysis suggested that immune response and graft rejection were enriched in the high-risk group. CTSS interacted with 8 miRNA, BCL2A1 and GBP2 interacted with 3 miRNA, and FCGR1B interacted with 1 miRNA. Conclusions The prognostic risk model based on 6 M1-DEG has high performance in predicting graft survival, which may provide evidence for early interventions for high-risk recipients. [ABSTRACT FROM AUTHOR]

Objective To analyze the prediction efficiency of scoring models at home and abroad on delayed graft function (DGF) after renal transplantation in China. Methods The clinical data of 112 donors and 220 recipients undergoing renal transplantation were prospectively analyzed. The DGF predicted by KDRI model, Jeldres model, and model of our center was compared with actual DGF incidence of renal transplant recipients. The prediction efficiency of each model was analyzed. The predictive accuracy was compared by the area under curve (AUC) of receiver operating characteristic (ROC) curve. Results The DGF incidence of 220 renal transplant recipients was 14.1% (31/220). DGF prediction using KDRI model showed that 41 cases were high risk donors, the AUC was 0.57, the sensitivity was 0.37, the specificity was 0.66, and the positive predictive value was 22%. DGF prediction using Jedres model showed that 22 cases were high risk recipients, the AUC was 0.56, the sensitivity was 0.13, the specificity was 0.92 and the positive predictive value was 20%. DGF prediction using the model of our center showed that 25 cases were high risk donors, the AUC was 0.80, the sensitivity was 0.53, the specificity was 0.84, the positive predictive value was 40%. Conclusions Compared with the KDRI and Jedres models, the prediction model of our center has higher AUC and sensitivity with a better prediction efficiency on DGF. Therefore, it is a suitable evaluation system of donors from donation after citizen s death in Chinese. [ABSTRACT FROM AUTHOR]

Objective To evaluate the effect of the preservation of the donor kidneys from donation after cardiac death (DCD) and expanded criteria donor (ECD) by donor kidney pulse perfusion storage transporter (LifePort) on the postoperative recovery of renal function in recipients undergoing renal transplantation. Methods Perioperative clinical data of 466 donors (DCD+ECD) and 882 recipients undergoing renal transplantation were retrospectively analyzed. According to different approaches of kidney preservation, bilateral kidneys of 309 DCD donors were randomly divided into the LifePort group (DCD-LP, n=309) and DCD cold storage group (n=309). All the bilateral kidneys of 132 ECD donors were stored and transported by LifePort and assigned into the ECD-LP group (n=264). The postoperative overall condition, early postoperative renal function indexes and postoperative complications of the recipients were observed among three groups. The pathological findings of renal puncture before renal transplantation were observed in donor kidneys. The LifePort perfusion parameters of the donor kidney were compared between the recipients with and without delayed graft function (DGF) after renal transplantation. Results Compared with the DCD cold storage group, the length of hospital stay was significantly shorter in the DCD-LP and ECD-LP groups (both P<0.05). The survival rate of the recipients was 100% in three groups. The survival rate of the donor kidney was 99.7%, 100% and 99.2% in the DCD cold storage, DCD-LP and ECD-LP groups, respectively. No statistical difference was observed among three groups (all P>0.05). Compared with the DCD cold storage group, the incidence of DGF was significantly lower in the DCD-LP and ECD-LP groups (both P<0.05). Early postoperative renal function, the incidence of acute rejection, infection and surgical complications did not significantly differ among three groups (all P>0.05). Pathological examination demonstrated that usage of LifePort perfusion could significantly mitigate the edema, degeneration and necrosis of renal tubules. In the recipients with DGF, the LifePort perfusion resistance index of donor kidney was significantly higher, whereas the LifePort perfusion volume of donor kidney was considerably lower than those without DGF (both P<0.05). Conclusions LifePort can effectively improve the quality of the donor kidney from DCD and ECD in vitro, reduce the incidence of postoperative DGF, promote the recovery of transplanted kidney function and predict the postoperative recovery during the maintenance and evaluation of the isolated kidney. [ABSTRACT FROM AUTHOR]

Objective To evaluate short-term clinical efficacy of renal transplantation from the donation of pediatric donors. Methods Clinical data of 15 pediatric donors and 28 recipients (including 2 cases of bilateral renal transplantation) undergoing renal transplantation in the Department of Renal Transplantation of the First Affiliated Hospital of Xi'an Jiaotong University from November 2013 to December 2015 were retrospectively analyzed. Results Renal transplantation was successfully performed in 28 recipients. The median warm ischemia time of transplant kidney was 1 2.5 min (range:0-1 7.0 min) and 4.3 h (range:1 .5-7.7 h) for the median cold ischemia time. After operation, 4 cases developed with delayed graft function (DGF), 1 required dialysis, 2 died from pulmonary infection, 2 underwent renal resection due to renal anastomosis stenosis and renal thrombosis. Postoperative follow-up lasted for 1 -24 months. Twenty-six (93%) recipients survived after renal transplantation and 24 (86%) recipients survived with restored normal renal function. Conclusions Unilateral and bilateral renal transplantation from pediatric donors has relatively favorable short-term clinical efficacy. [ABSTRACT FROM AUTHOR]