脂肪变性
微粒
化学
环境化学
生物系统
钥匙(锁)
组分(热力学)
质谱法
鉴定(生物学)
数据集
集合(抽象数据类型)
人类健康
色谱法
环境科学
气相色谱-质谱法
转化(遗传学)
有机质
计算机科学
计算生物学
作者
Zhipeng Yan (7947353),Guohua Qin (386740),Xiaodi Shi (1542910),Xing Jiang (1661110),Zhen Cheng (195354),Yaru Zhang (484892),Nan Nan (589273),Fuyuan Cao (554940),Xinghua Qiu (1882321),Nan Sang (389836)
出处
期刊:
[Figshare (United Kingdom)]
日期:2024-06-05
标识
DOI:10.1021/acs.est.3c10012.s001
摘要
Hepatic steatosis is the first step in a series of events that drives hepatic disease and has been considerably associated with exposure to fine particulate matter (PM2.5). Although the chemical constituents of particles matter in the negative health effects, the specific components of PM2.5 that trigger hepatic steatosis remain unclear. New strategies prioritizing the identification of the key components with the highest potential to cause adverse effects among the numerous components of PM2.5 are needed. Herein, we established a high-resolution mass spectrometry (MS) data set comprising the hydrophobic organic components corresponding to 67 PM2.5 samples in total from Taiyuan and Guangzhou, two representative cities in North and South China, respectively. The lipid accumulation bioeffect profiles of the above samples were also obtained. Considerable hepatocyte lipid accumulation was observed in most PM2.5 extracts. Subsequently, 40 of 695 components were initially screened through machine learning-assisted data filtering based on an integrated bioassay with MS data. Next, nine compounds were further selected as candidates contributing to hepatocellular steatosis based on absorption, distribution, metabolism, and excretion evaluation and molecular dockingin silico. Finally, seven components were confirmed in vitro. This study provided a multilevel screening strategy for key active components in PM2.5 and provided insight into the hydrophobic PM2.5 components that induce hepatocellular steatosis.
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