Aberrant expression of proatherogenic cytokines and growth factors in human umbilical vein endothelial cells from newborns of type 2 diabetic women
Objectives: This study reports the levels of cytokines, chemokines, and growth factors previously identified as taking part in the pathology of atherosclerosis in human umbilical vein endothelial cells derived from mothers with type 2 diabetes and compares them with those in human umbilical vein endothelial cells derived from healthy mothers under normal glucose conditions. Methods: Cytokine analysis measures of human umbilical vein endothelial cell lysates were obtained using a multiple analyte profiling (xMAP) assay based on magnetic bead-based technology, using the MAGPIX instrument. The correlation between cytokines, chemokines, and growth factors was examined statistically in human umbilical vein endothelial cells derived from mothers with type 2 diabetes. Results: This study showed that the expression of proinflammatory cytokine interleukin-1 alpha was significantly greater in human umbilical vein endothelial cells derived from mothers with type 2 diabetes than those derived from healthy mothers. The protein level of granulocyte colony-stimulating factor was higher in human umbilical vein endothelial cells derived from mothers with type 2 diabetes than those derived from healthy mothers. A significant positive correlation was demonstrated between the protein expression of granulocyte colony-stimulating factor and granulocyte-macrophage colony-stimulating factor in human umbilical vein endothelial cells derived from mothers with type 2 diabetes. Conclusion: Diabetes evokes a persistent inflammatory phenotype in human umbilical vein endothelial cells, as indicated by the enhanced production of cytokines and growth factors under normal glucose conditions.Keywords: Proinflammatory cytokines; endothelial cells; growth factors; type 2 diabetes.
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基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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