Markers of lipid oxidation and inflammation in bronchial cells exposed to complete gasoline emissions and their organic extracts
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Road traffic emissions consist of gaseous components, particles of various sizes, and chemical compounds that are bound to them. Exposure to vehicle emissions is implicated in the etiology of inflammatory respiratory disorders. We investigated the inflammation-related markers in human bronchial epithelial cells (BEAS-2B) and a 3D model of the human airways (MucilAir™), after exposure to complete emissions and extractable organic matter (EOM) from particles generated by ordinary gasoline (E5), and a gasoline-ethanol blend (E20; ethanol content 20% v/v). The production of 22 lipid oxidation products (derivatives of linoleic and arachidonic acid, AA) and 45 inflammatory molecules (cytokines, chemokines, growth factors) was assessed after days 1 and 5 of exposure, using LC-MS/MS and a multiplex immunoassay, respectively. The response observed in MucilAir™ exposed to E5 gasoline emissions, characterized by elevated levels of pro-inflammatory AA metabolites (prostaglandins) and inflammatory markers, was the most pronounced. E20 EOM exposure was associated with increased levels of AA metabolites with anti-inflammatory effects in this cell model. The exposure of BEAS-2B cells to complete emissions reduced lipid oxidation, while E20 EOM tended to increase concentrations of AA metabolite and chemokine production; the impacts on other inflammatory markers were limited. In summary, complete E5 emission exposure of MucilAir™ induces the processes associated with the pro-inflammatory response. This observation highlights the potential negative health impacts of ordinary gasoline, while the effects of alternative fuel are relatively weak.
Keywords:Air-liquid interface; Chemokines; Cytokines; Growth factors; Polyunsaturated fatty acids derivatives; Road traffic emissions.
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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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