Kidney transplantation is an effective way to improve the condition of patients with end-stage renal disease. However, maintaining long-term graft function and improving patient survival remain a key challenge after kidney transplantation. Dysbiosis of intestinal flora has been reported to be associated with complications in renal transplant recipients. The commensal microbiota plays an important role in the immunomodulation of the transplant recipient responses. However, several processes, such as the use of perioperative antibiotics and high-dose immunosuppressants in renal transplant recipients, can lead to gut dysbiosis and disrupt the interaction between the microbiota and the host immune responses, which in turn can lead to complications such as infection and rejection in organ recipients. In this review, we summarize and discuss the changes in intestinal flora and their influencing factors in patients after renal transplantation as well as the evidence related to the impact of intestinal dysbiosis on the prognosis of renal transplantation from in vivo and clinical studies, and conclude with a discussion of the use of microbial therapy in the transplant population. Hopefully, a deeper understanding of the function and composition of the microbiota in patients after renal transplantation may assist in the development of clinical strategies to restore a normal microbiota and facilitate the clinical management of grafts in the future.

Background: This study aimed to assess the diagnostic accuracy of combining donor-derived cell-free DNA (dd-cfDNA) fraction and absolute quantification in detecting kidney allograft rejection. Methods: A prospective study was conducted from December 2019 to April 2021 at the First Affiliated Hospital of Sun Yat-sen University. Kidney transplant recipients who underwent biopsy, including cases of T-cell-mediated rejection (TCMR), antibody-mediated rejection (ABMR), and borderline rejection, were included. dd-cfDNA fraction and absolute concentrations were measured, and diagnostic efficacy was evaluated using receiver operating characteristic (ROC) analysis. The double-positive and double-negative methods were applied to assess performance. Results: A total of 50 kidney transplant recipients were included. The dd-cfDNA fraction cutoff of 1.08% achieved 93.33% sensitivity and 91.43% specificity (AUC = 0.95), with an NPV of 96.97% and a PPV of 82.35%. The absolute dd-cfDNA threshold of 32 cp/mL yielded 80.00% sensitivity and 71.43% specificity (AUC = 0.78), with an NPV of 89.29% and a PPV of 54.55%. The double-positive method provided superior accuracy, with a PPV of 91.67% and an NPV of 89.47%, demonstrating 73.33% sensitivity and 97.14% specificity. The double-negative method achieved 100% NPV and 100% sensitivity. Conclusions: Combining dd-cfDNA fraction and absolute quantification improves diagnostic accuracy for kidney transplant rejection, especially ABMR. The double-positive and double-negative approaches show high predictive value, offering potential clinical value for monitoring kidney transplant recipients.

Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related death worldwide. Currently, recent risk stratification has only focused on liver function and tumor characteristics. Thus, the purpose of this study was to develop a prognostic model based on genes involved in aerobic respiration. Matched tumor and normal tissues from TCGA and ICGC cohorts were analyzed to identify 15 overlapping differential expressed genes. Cox univariate analysis of the 15 genes in the TCGA cohort revealed they were all associated with disease-specific survival (DSS) in HCC patients. Using LASSO estimation and the optimal value for penalization coefficient lambda 12 genes were selected for the prognostic model, and then HCC patients in the TCGA cohort were dichotomized into low-risk and high-risk groups. Univariate and multivariate Cox analysis demonstrated patients in low-risk group had better survival. Validation of the risk score model with the ICGC cohort produces results consistent with those of the TCGA cohort. In conclusion, this study developed and validated a prognostic model of HCC through a comprehensive analysis of genes involved in aerobic respiration. This model may help develop personalized treatments for patients with HCC.

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