Renal tubular cell death is the key factor of the pathogenesis of ischemia/reperfusion (I/R) kidney injury. Ferroptosis is a type of regulated cell death (RCD) found in various diseases. However, the underlying molecular mechanisms related to ferroptosis in renal I/R injury remain unclear. In the present study, we investigated the regulatory role of microRNAs on ferroptosis in I/R-induced renal injury. We established the I/R-induced renal injury model in rats, and H/R induced HK-2 cells injury in vitro. CCK-8 was used to measure cell viability. Fe²⁺ and ROS levels were assayed to evaluate the activation of ferroptosis. We performed RNA sequencing to profile the miRNAs expression in H/R-induced injury and ferroptosis. Western blot analysis was used to detect the protein expression. qRT-PCR was used to detect the mRNA and miRNA levels in cells and tissues. We further used luciferase reporter assay to verify the direct targeting effect of miRNA. We found that ischemia/reperfusion-induced ferroptosis in rat’s kidney. We identified that miR-182-5p and miR-378a-3p were upregulated in the ferroptosis and H/R-induced injury, and correlates reversely with glutathione peroxidases 4 (GPX4) and solute carrier family 7 member 11 (SLC7A11) expression in renal I/R injury tissues, respectively. In vitro studies showed that miR-182-5p and miR-378a-3p induced ferroptosis in cells. We further found that miR-182-5p and miR-378a-3p regulated the expression of GPX4 and SLC7A11 negatively by directly binding to the 3′UTR of GPX4 and SLC7A11 mRNA. In vivo study showed that silencing miR-182-5p and miR-378a-3p alleviated the I/R-induced renal injury in rats. In conclusion, we demonstrated that I/R induced upregulation of miR-182-5p and miR-378a-3p, leading to activation of ferroptosis in renal injury through downregulation of GPX4 and SLC7A11.

Chronic Kidney disease is a severe lifelong condition caused either by renal disease or by impaired functions of the kidneys. In the present area of research, Kidney cancer is one of the deadliest and crucial importance for the survival of the patients ’ diagnosis and classification. Early diagnosis and proper therapy can stop or delay the development of this chronic disease into the final stage where dialysis or renal transplantation is the only way of saving the life of the patient. The development of automated tools to accurately identify subtypes of kidney cancer is, therefore, an urgent challenge in the recent past. In this paper, to examine the ability of various deep learning methods an Adaptive hybridized Deep Convolutional Neural Network (AHDCNN) has been proposed for the early detection of Kidney disease efficiently and effectively. Classification technology efficiency depends on the role of the data set. To enhance the accuracy of the classification system by reducing the feature dimension an algorithm model has been developed using CNN. These high-level properties help to build a supervised tissue classifier that discriminates between the two types of tissue. The experimental process on the Internet of medical things platform (IoMT)concludes, with the aid of predictive analytics, that advances in machine learning which provides a promising framework for the recognition of intelligent solutions to prove their predictive capability beyond the field of kidney disease.

Tubular epithelial cells (TECs) represent the primary site of renal ischemia/reperfusion injury (RIRI). However, whether the damage of TECs could drive the initiation of inflammation was unclear. Here we investigated the role of the TECs and macrophages during RIRI. Increased expression of inflammation response and activated M1 macrophage were determined in the mice model of RIRI. Moreover, we demonstrated global miRNA expression profiling of renal exosomes, and miR-374b-5p was most upregulated in these exosomes in vivo. Inhibition of miR-374b-5p in the mice upon RIR operation would alleviate the kidney injury via decreasing the production of proinflammatory cytokines and suppressing the macrophage activation. Similar results were also identified in the hypoxia-induced cell model where exosomal miR-374b-5p was dramatically upregulated. Uptake of exosomes derived from the hypoxic TECs by macrophages would trigger M1 polarization via transferring miR-374b-5p. Besides, we confirmed that miR-374b-5p could directly bind to Socs1 using a dual-luciferase reporter assay. Notably, when we injected the miR-374b-5p-enriched exosomes into mice, a high-level inflammatory response and M1 macrophage activation were performed. Our studies demonstrated that exosomal miR-374b-5p played an essential role in the communication between injured TECs and macrophages, resulting in the M1 macrophage activation during RIRI. The blockage of the release of such exosomes may serve as a new therapeutic strategy for RIRI.

Background: Delayed graft function (DGF) is an important complication of kidney transplantation and can be diagnosed according to different definitions. DGF has been suggested to be associated with the long-term outcome of kidney transplantation surgery. However, the best DGF definition for predicting renal transplant outcomes in Chinese donations after cardiac death (DCDs) remains to be determined.Method: A total of 372 DCD kidney transplant recipients from June 2013 to July 2017 in the First Affiliated Hospital of Xi’an Jiaotong University were included in this retrospective study to compare 6 different DGF definitions. The relationships of the DGF definitions with transplant outcome were analyzed, including graft loss (GL) and death-censored graft loss (death-censored GL). Renal function indicators, including one-year estimated glomerular filtration rate (eGFR) and three-year eGFR, and were compared between different DGF groups.Results: The incidence of DGF varied from 4.19 to 35.22% according to the different DGF diagnoses. All DGF definitions were significantly associated with three-year GL as well as death-censored GL. DGF based on requirement of hemodialysis within the first week had the best predictive value for GL (AUC 0.77), and DGF based on sCr variation during the first 3 days post-transplant had the best predictive value for three-year death-censored GL (AUC 0.79). Combination of the 48-h sCr reduction ratio and classical DGF can improve the AUC for GL (AUC 0.85) as well as the predictive accuracy for death-censored GL (83.3%).Conclusion: DGF was an independent risk factor for poor transplant outcome. The combination of need for hemodialysis within the first week and the 48-h serum creatinine reduction rate has a better predictive value for patient and poor graft outcome.