Genetic algorithm-optimized backpropagation neural network establishes a diagnostic prediction model for diabetic nephropathy:Combined machine learning and experimental validation in mice

Background:Diabetic nephropathy(DN)is the most common complication of type 2 diabetes mellitus and the main cause of end-stage renal disease worldwide.Diagnostic biomarkers may allow early diagnosis and treatment of DN to reduce the prevalence and delay the development of DN.Kidney biopsy is the gold standard for diagnosing DN;however,its invasive character is its primary limitation.The machine learning approach provides a non-invasive and specific criterion for diagnosing DN,although traditional machine learning algorithms need to be improved to enhance diagnostic performance.Methods:We applied high-throughput RNA sequencing to obtain the genes related to DN tubular tissues and normal tubular tissues of mice.Then machine learning algorithms,random forest,LASSO logistic regression,and principal component analysis were used to identify key genes(CES1G,CYP4A14,NDUFA4,ABCC4,ACE).Then,the genetic algorithm-optimized backpropagation neural network(GA-BPNN)was used to improve the DN diagnostic model.Results:The AUC value of the GA-BPNN model in the training dataset was 0.83,and the AUC value of the model in the validation dataset was 0.81,while the AUC values of the SVM model in the training dataset and external validation dataset were 0.756 and 0.650,respectively.Thus,this GA-BPNN gave better values than the traditional SVM model.This diagnosis model may aim for personalized diagnosis and treatment of patients with DN.Immunohistochemical staining further confirmed that the tissue and cell expression of NADH dehydrogenase(ubiquinone)1 alpha subcomplex,4-like 2(NDUFA4L2)in tubular tissue in DN mice were decreased.Conclusion:The GA-BPNN model has better accuracy than the traditional SVM model and may provide an effective tool for diagnosing DN.

An integrated bioinformatics analysis and experimental study identified key biomarkers CD300A or CXCL1,pathways and immune infiltration in diabetic nephropathy mice

Diabetic nephropathy(DN)is a common microvascular complication that easily leads to end-stage renal disease.It is important to explore the key biomarkers andmolecular mechanisms relevant to diabetic nephropathy(DN).We used highthroughput RNA sequencing to obtain the genes related to DN glomerular tissues and healthy glomerular tissues of mice.Then we used LIMMA to analyze differentially expressed genes(DEGs)between DN and non-diabetic glomerular samples.And we performed KEGG,gene ontology functional(GO)enrichment,and gene set enrichment analysis to reveal the signaling pathway of the disease.The CIBERSORT algorithm based on support vector machine was used to determine the immune infiltration score.Random forest algorithm and Cytoscape obtained hub genes.Finally,we applied co-staining,immunohistochemical staining,RT-qPCR and western blotting to validate the protein and mRNA expression of both hub genes.We obtained 913 DEGs mainly related to inflammatory factors and immunity.GSEA results showed that differential genes were mainly enriched in IL-17 signaling pathway,lipid and atherosclerosis,rheumatoid arthritis,TNF signaling pathway,neutrophil extracellular trap formation,Staphylococcus aureus infection and other pathways.The intersection of the random forest algorithm and Cytoscape revealed both hub genes of CD300A and CXCL1.Experiments have shown that the both key genes of CD300A and CXCL1 shown increased expression in glomerular podocytes,and are related to the inflammation of diabetic nephropathy.And immunohistochemical staining and RT-qPCR further confirmed that the protein and mRNA expression level of CD300A or CXCL1 in glomeruli tissue in DN mice were increased.The expression levels of CD300A and CXCL1 increased significantly under HG(high glucose)stimulation,further confirming that diabetes can lead to increased levels of CD300A and CXCL1 at the cellular level.Through bioinformatics analysis,machine learning algorithms,and experimental research,CD300A and CXCL1 are confirmed as both potential biomarkers in diabetic nephropathy.And we further revealed the main pathways of differential genes and the differentially distributed immune infiltrating cells in diabetic nephropathy.

Dietary hypercholesterolemia aggravates contrast media-induced nephropathy

Background Contrast media adinistration can result in severe nephrotoxicity under pothological conditions such as diabetic nephropathy, congestive heart failure, dehydration, et al. The purpose of this study was to evaluate the effects of dietary hypercholesterolemia on contrast media-induced changes in renal function, blood flow, and histopathology.Methods Rats were fed either on a normal rodent diet (group N) or a high-cholesterol supplemented diet (group H; 4% cholesterol and 1% cholic acid) for 8 weeks. Half of the animals (n=6) from each diet group were then given a tail vein injection of 60% diatrizoate (6 ml/kg; group NC and group HC) and the other half were administered saline. Total serum cholesterol, triglyceride, serum creatinine, creatinine clearance rate, fractional excretion of sodium and potassium, and cortical nitric oxide production were determined one day following contrast media administration. Renal blood flow was determined by color Doppler flow imaging and pulsed-mode Doppler. Renal histopathology was observed by light microscopy.Results Total serum cholesterol and resistance indices of renal blood vessels increased significantly, while creatinine clearance rate and production of nitric oxide in the renal cortex decreased markedly in group HC and group H when compared to group N and group NC. The creatinine clearance rate decreased significantly in group HC compared to group H. Serum creatinine levels and fractional excretion of sodium and potassium in group HC were significantly higher than those in the other three groups. Severe tubular degeneration and necrosis, protein cast accumulation, and medullary congestion were found in group HC. Conclusion Hypercholesterolemia is a risk factor for contrast media-induced nephropathy. Hypercholesterolemia aggravates contrast media-induced nephrotoxicity through the reduced production of nitric oxide.