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Objective:To explore the feature of FOS expression in oxytocin-and vasopressin-positive neurons in the hypothalamic paraventricular nucleus(PVN)under different status of diabetes mellitus(DM).Methods:Intraperito-neal injection of vehicle or STZ in mice was conducted to establish control or diabetes model.Mechanical sensitivity was evaluated by von Frey filament tests to distinguish diabetic neuropathic pain(DNP)from without-pain group(DWP).The expression of FOS,oxytocin(OXT)-and vasopressin(VP)-positive neurons,as well as their double labeling was detected by immunohistochemical and immunofluorescent staining.Cell counting and comparison were made in groups.Results:FOS expression was easily detected in the PVN in the three groups(Control group,DNP group and DWP group)at 7 days,while that in DWP and DNP groups at 28 days was hardly detectable,with the number being signifi-cantly different from the 7 days group(P＜0.05 or 0.001).Likewise,compared with the control group,immunofluo-rescent signals for VP and OXT staining in the DNP and DWP groups also showed a trend of weakening as the modeling time increased(P＜0.05).The cell counting after double staining for VP or OXT with FOS showed that,in the DWP group at 7 days,the number of VP and FOS double-labeled neurons was 74.33±22.10,accounting for(56.64± 7.52)％of VP-positive cells,whereas the double labeling rate for OXT and FOS was only(10.44±3.14)％.In the DNP group at 7 days,the number of OXT and FOS double-labeled neurons was 51.00±31.80,accounting for(18.50 ±9.51)％of OXT-positive neurons,whereas the double labeling rate for VP and FOS was only(9.34±3.27)％.In contrast to these changes in 7 days group,the expression of FOS decreased sharply in the group of 28 days,thereby al-most no double-labeled neurons.Conclusion:The plasticity changes of oxytocin-and vasopressin-positive neurons in the PVN are different depending on the status of pain and non-pain,and the stage of disease progression.Understanding the changes is of great significance for unravelling the neural mechanism of diabetes and its complications.
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【Objective】 To make bioinformatics analysis of inflammatory cardiomyopathy so as to screen out hub genes related to etiology and therapeutic targets. 【Methods】 Differential expression analysis of inflammatory cardiomyopathy gene chip data from Gene Expression Omnibus （GEO） Database was carried out via GEO2R tool. Protein-protein interaction（PPI）network and hub genes identification were realized by String database and CytoHubba. GO and KEGG enrichment analysis for functional annotation and pathway analysis of hub genes were conducted by R language. Web-based enrichment analysis platform Enrichr and Drug Signatures database were applied to screen out candidate drugs targeting hub genes for inflammatory cardiomyopathy. 【Results】 The 149 DEGs were statistically significant， among which 44 were upregulated and 105 were downregulated. To identify hub genes， PPI network consisting of 37 nodes and 116 edges was constructed， and 16 hub genes were NDUFB7， POLR2L， NDUFS7， UQCR11， NDUFA13， NDUFA2， PHPT1， NDUFB10， UBA52， ATP5D， NDUFA3， COX6B1， POLR2J， COX4I2， AURKAIP1 and MRPL41. Hub genes were enriched to 113 different GO terms， and the most significant terms were mitochondrial ATP synthesis coupled electron transport， respiratory electron transport chain， oxidative phosphorylation， respiratory chain， mitochondrial inner membrane， NADH dehydrogenase activity and oxidoreductase activity. DEGs were enriched to 13 different signal pathways， including oxidative phosphorylation， non-alcoholic fatty liver disease， diabetic cardiomyopathy， and cardiac muscle contraction. We screened out candidate drugs targeting hub genes， namely， metformin hydrochloride， clindamycin， and hydralazine. 【Conclusion】 Hub genes screened out by decoding the expression profiles are convolved in the etiology and mechanism of inflammatory cardiomyopathy， which might serve as latent therapeutic targets and benefit patients with inflammatory cardiomyopathy.
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Objective To investigate podocyte number, the expression of nephrin and transforming growth factor-β1(TGF-β1) in adriamycin-induced-nephropathy rat model and its significance. Methods The rat adriamycin nephrosis model was constructed to detect blood and urine biochemical indicators and observe the pathological changes of renal tissues by light microscope and electron microscope. The expression levels of nephrin and TGF-β1 as well as the podocyte number were examined at different time points by immunohistochemistry. Results The pathological changes of the renal tissues were obvious. Nephrin presented a weak signal at the end of the first week (P<0.05). TGF-β1 started to increase (P<0.05) while the podocyte number started to decrease at the end of the eighth week (P<0.05). Expression of nephrin was negatively correlated with the P<0.05) and serum creatinine (r=-0.71, P<0.05). Expression of TGF-β1 was blood urea nitrogen (r=0.62, P<0.05) and serum creatinine (r=0.59, urinary protein (r=-0.63, P<0.05), blood urea nitrogen (r=-0.72, P<0.05) and serum creatinine (r=-0.76, P<0.05); it was positively correlated with nephrin (r=0.78, P<0.01) but negatively correlated with TGF-β1 (r=-0.64, P<0.05). Conclusion The acute and chronic adriamycin nephrosis models were twice every two weeks. The genesis and development of proteinuria are closely related to the abnormal expression of nephrin. Focal segmental glomerulosclerosis occurs when the podocyte number decreases and TGF-β1 accelerates it.
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Objective To investigate podocyte number,the expression of nephrin and transforming growth factor-?1(TGF-?1) in adriamycin-induced-nephropathy rat model and its significance.Methods The rat adriamycin nephrosis model was constructed to detect blood and urine biochemical indicators and observe the pathological changes of renal tissues by light microscope and electron microscope.The expression levels of nephrin and TGF-?1 as well as the podocyte number were examined at different time points by immunohistochemistry.Results The pathological changes of the renal tissues were obvious.Nephrin presented a weak signal at the end of the first week(P