暴露的
生物监测
鉴定(生物学)
泌尿系统
计算生物学
赭曲霉毒素A
化学
内生
暴露评估
人类健康
生理学
医学
生物化学
致癌物
环境化学
富马西林
生物
生物流体
生物信息学
毒理
生物沉积
环境毒理学
口腔黏膜测试
职业暴露
环境卫生
尿
风险评估
作者
Xiaotu Liu,Xinyu Zhu,Shuyue Wang,Fengli Zhou,Ning Zhang,Ziliang Wang,Maohua Miao,Hong Liang,Meilin Yan,Xiangfei Sun,Da Chen
标识
DOI:10.1021/acs.est.5c07728
摘要
-methylphenylethylamine (MPEA) to label exogenous and endogenous molecules with phenolic hydroxyl, primary amine, and carboxyl groups and develops an integrated screening workflow based on diagnostic fragment ion filtering and machine learning-assisted retention time prediction and structure annotation. We applied the CLEAN strategy to screen for key environmental chemicals in pregnant women associated with small vulnerable newborns (SVN) in a nested case-control study of 80 SVN cases and 160 matched controls. Among 97 identified exogenous substances, 29 were detected in more than 70% samples. The BKMR analysis revealed a significant and positive association between mixed exposure and the SVN risk and identified 1-hydroxypyrene, monoisopropyl phthalate and pentabromophenol as the key exposure markers. Among the identified endogenous metabolites, four amino acids exhibited the strongest mediation effects on the environmental exposure-SVN associations. Collectively, our work demonstrates the ability of CLEAN to achieve high-throughput and accurate urinary exposome characterization, supporting large-scale human biomonitoring and epidemiological studies.
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