Computational Approach to Link Chemicals in Anthropogenic Smoke Particulate Matter with Toxicity.
Computational Approach to Link Chemicals in Anthropogenic Smoke Particulate Matter with Toxicity.
复制标题
将人为烟雾颗粒物中的化学物质与毒性联系起来的计算方法。
DOI：
10.1021/acs.chemrestox.2c00270
复制
发表时间：
2022
影响因子：
4.1
通讯作者：
Gilmour,MIan
中科院分区：
文献类型：
--
作者：
Kim,YongHo;Rager,JuliaE;Jaspers,Ilona;Gilmour,MIan
利用加权化学共表达网络分析(WCCNA)来识别与人为材料的不同燃烧共同调节的化学物质，并将化学物质与生物反应(肺毒性和致突变性)联系起来。多环芳烃(PAHs)与燃烧含塑料材料产生的燃烧烟雾颗粒物(PM)中浓度的增加共同调节，并显示出与中性粒细胞流入增加、细胞因子水平和诱变性显著相关。无机元素随着燃烧的胶合板和纸板烟雾PM中浓度的增加而共同调节，并显示出与蛋白质和白蛋白水平增加显著相关。这项研究显示了使用计算网络分析来识别复杂环境混合物中的危险化学成分并确定其优先顺序的可能性，并提供了干预研究所需的关键化学示踪剂的指导，以保护公众健康免受接触。
A weighted chemical coexpression network analysis (WCCNA) was utilized to identify chemicals co-modulated to variable burning of anthropogenic materials and to link chemicals to biological responses (lung toxicity and mutagenicity). Polyaromatic hydrocarbons (PAHs) were co-modulated with increased concentrations in flaming smoke particulate matter (PM) from the burning of plastic-containing materials and showed significant association with increased neutrophil influx, cytokine levels, and mutagenicity. Inorganic elements were co-modulated with increased concentrations in flaming plywood and cardboard smoke PM and showed significant association with increased protein and albumin levels. This study shows the potential for using a computational network analysis to identify and prioritize hazardous chemical components within complex environmental mixtures and provides guidance on key chemical tracers required for intervention research to protect public health from the exposure.