Pharmacology network was used to investigate the common key target and signaling pathway of Notoginseng Radix et Rhizoma in the protection against diabetic nephropathy(DN), diabetic encephalopathy(DE) and diabetic cardiomyopathy(DCM). The chemical components of Notoginseng Radix et Rhizoma were obtained through TCMSP database and literature mining, and SwissTargetPrediction database was used to predict potential targets of Notoginseng Radix et Rhizoma. The disease targets of DN, DE and DCM were obtained through OMIM and GeneCards databases. The overlapped targets of component targets and disease targets of DN, DE and DCM were obtained, and the network of "chemical component-target-disease" was established. The enriched GO and KEGG of the overlapped genes were investigated by using ClueGo plug-in with Cytoscape. At the same time, the PPI network was constructed through STRING database, and the common key targets for the treatment of three diseases by Notoginseng Radix et Rhizoma were obtained through topological parametric mathematical analysis by Cytoscape. A total of 166 chemical components and 835 component targets were screened out from Notoginseng Radix et Rhizoma. Briefly, 216, 194 and 230 disease targets of DN, DE and DCM were collected, respectively. And 54, 45 and 57 overlapped targets were identified when overlapping these disease targets with component targets of Notoginseng Radix et Rhizoma, respectively. Enrichment analysis indicated that the AGE-RAGE signaling pathway and FoxO signaling pathway were the common pathways in the protection of Notoginseng Radix et Rhizoma against DN, DE and DCM. Network analysis of the overlapped targets showed that TNF, STAT3, IL6, VEGFA, MAPK8, CASP3 and SIRT1 were identified as key targets of Notoginseng Radix et Rhizoma against DN, DE and DCM, the selected key targets were verified by literature review, and it was found that TNF, IL6, VEGFA, CASP3 and SIRT1 had been reported in the literature. In addition, there were the most compounds corresponding to the commom core target STAT3, indicating that more compounds in Notoginseng Radix et Rhizoma could regulate STAT3. This study indicated that Notoginseng Radix et Rhizoma potentially protected against DN, DE and DCM through regulating AGE-RAGE signaling pathway and FoxO signaling pathway and 7 common targets including TNF, STAT3, IL6, VEGFA, MAPK8, CASP3 and SIRT1. This study provided a reference for the research of "different diseases with same treatment" and also elucidated the potential mechanism of Notoginseng Radix et Rhizoma against DN, DE and DCM.
Brain Diseases ; Diabetes Mellitus ; Diabetic Cardiomyopathies/genetics* ; Diabetic Nephropathies/genetics* ; Humans ; Research Design ; Signal Transduction

Objective To screen out the key genes leading to diabetic cardiomyopathy by analyzing the mRNA array associated with diabetic cardiomyopathy in the GEO database. Methods The online tool GEO2R of GEO was used to mine the differentially expressed genes (DEG) in the datasets GSE4745 and GSE5606.R was used to draw the volcano map of the DEG,and the Venn diagram was established online to identify the common DEG shared by the two datasets.The clusterProfile package in R was used for gene ontology annotation and Kyoto encyclopedia of genes and genomes pathway enrichment of the DEG.GSEA was used for gene set enrichment analysis,and STRING for the construction of a protein-protein interaction network.The maximal clique centrality algorithm in the plug-in Cytohubba of Cytoscape was used to determine the top 10 key genes. The expression of key genes was studied in the primary cardiomyocytes of rats and compared between the normal control group and high glucose group. Results The expression of Pdk4,Ucp3,Hmgcs2,Asl6,and Slc2a4 was consistent with the array analysis results.The expression of Pdk4,Ucp3,and Hmgcs2 was up-regulated while that of Acsl6 and Slc2a4 was down-regulated in the cardiomyocytes stimulated by high glucose (25 mmol/L) for 72 h. Conclusion Pdk4,Ucp3,Hmgcs2,Asl6,and Slc2a4 may be associated with the occurrence and development of diabetic cardiomyopathy,and may serve as the potential biomarkers of diabetic cardiomyopathy.
Animals ; Computational Biology/methods* ; Diabetes Mellitus ; Diabetic Cardiomyopathies/genetics* ; Gene Expression Profiling ; Glucose ; Protein Interaction Maps/genetics* ; Rats

Objective: To identify the differentially expressed circular RNA (circRNA) in the myocardium of diabetic cardiomyopathy (DCM) mice, and analyze their possible biological functions and related regulatory network. Methods: C57BL/6 mice, aged 8 weeks, and weighing were 21-27 g. Eight mice were selected as the control group and 15 mice were selected as the experimental group. The diabetic mice model was established by intraperitoneal injection of streptozotocin in the experimental group. One week after injection, the fasting blood glucose level of mice was measured, and 12 diabetic mice were included in the final experimental group. All mice were fed for 12 weeks under the same laboratory conditions. The cardiac structure and function were detected by echocardiography. Diabetic mice with the left ventricular ejection fraction less than 60% and the E/A less than 1.6 were selected as DCM group (n=3). Mice in DCM group and control group were then sacrificed under deep anesthesia. RNA was extracted from myocardial tissue. High-throughput RNA sequencing technology was used to sequence and identify the RNA in the myocardial tissue of DCM group and normal control group, and the difference was analyzed by DeSeq2. The analysis results were verified at the tissue level by RT-qPCR, and the differential circRNA were analyzed by GO and KEGG pathway analysis. The differentially expressed circRNA-microRNA(miRNA) interaction was predicted by the miRNA target gene prediction software. Results: A total of 63 differentially expressed circRNAs were found in the myocardium of DCM mice. The results of RT-qPCR showed that the tissue level expression of 8 differentially expressed circRNAs was consistent with the sequencing results, of which 7 were up-regulated and 1 was down-regulated. KEGG pathway analysis showed that the up-regulated circRNAs was mainly related to AMPK signal pathway and intercellular adhesion junction pathway, and the down-regulated circRNA was mainly related to cardiomyopathy. Go analysis showed that the up-regulated circRNA was mainly related to the binding process of ions, proteins, kinases and other factors in terms of molecular function, and was involved in regulating the intracellular structure, especially the composition of organelles in terms of cell components. The functional analysis of molecular function and cell components showed that the up-regulated circRNA were related to the cell component origin, recruitment and tissue, and thus participated in the regulation of cell biological process. The down regulated circRNA was related to catalytic activity in terms of molecular function, protein kinase binding process, transferase and calmodulin activity, and was closely related to the components of contractile fibers and the composition of myofibrils. These differentially expressed circRNAs were also related to biological processes such as lysine peptide modification, sarcomere composition, myofibril assembly, morphological development of myocardial tissue, myocardial hypertrophy and so on. Conclusions: In this study, we detected the novel differentially expressed circRNAs in the myocardium of DCM mice, and bioinformatics analysis confirmed that these circRNAs are related to oxidative stress, fibrosis and death of cardiomyocytes, and finally participate in the pathophysiological process of DCM.
Animals ; Diabetes Mellitus, Experimental ; Diabetic Cardiomyopathies/genetics* ; Gene Expression Profiling/methods* ; Mice ; Mice, Inbred C57BL ; MicroRNAs/genetics* ; Myocardium ; RNA, Circular ; Stroke Volume ; Ventricular Function, Left

To observe the preventive effect of polydatin on diabetic myocardial hypertrophy in mice and discuss its and mechanism. The diabetic model was induced with low dose STZ (40 mg x kg(-1) x d(-1) x 5 d, ip) for five days in mice. The myocardial hypertrophy was determined by hypertrophy indexes (LVHI, left ventricular/right ventricle and septum), left ventricular/body weight (LV/BW), the histological examination and the mRNA expression of atrial natriuretic factor(ANF). The fast blood glucose(FBG), serum insulin and plasma hemoglobin A1c ( HbA1c) levels were detected, and then HOMA insulin resistance index ( HOMA. IR) was calculated. The mRNA and protein expressions were measured by qRT-PCR and western blotting, respectively. According to the results, the FBG of the model group exceeded 11.1 mmol x L(-1), with notable decrease in BW and significant increase in insulin, HbA1c and HOME. IR, suggesting the successful establishment and stability of the diabetic model. The increases in LVHI, LV/BW, cell surface and ANF mRNA indicated a myocardial hypertrophy in diabetic mice. Meanwhile, the model group showed decrease in mRNA and protein expressions of PPARβ and significant increase in NF-κB p65, COX-2 and iNOS expressions. After the preventation with PD (50, 100 mg x kg(-1) x d(-1)), diabetic mice showed increase in BW, reduction in the levels of FBG, insulin and HbA1 c, relief in insulin resistance and significant recovery in hypertrophy indexes, indicating PD has the protective effect in diabetic myocardial hypertrophy. Meanwhile, PD up-regulated the expression of PPARβ, inhibited the expressions of NF-κB p65, COX-2 and iNOS, demonstrating that PD's protective effect may be related to the activation of PPARβ and the inhibition of NF-κB, COX-2 and iNOS signaling pathways.
Animals ; Diabetes Mellitus, Experimental ; complications ; Diabetic Cardiomyopathies ; drug therapy ; genetics ; metabolism ; Drugs, Chinese Herbal ; administration & dosage ; Glucosides ; administration & dosage ; Humans ; Hypertrophy ; drug therapy ; genetics ; metabolism ; Insulin ; metabolism ; Male ; Mice ; NF-kappa B ; genetics ; metabolism ; Signal Transduction ; Stilbenes ; administration & dosage