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Identifying Chemicals and Mixtures of Potential Biological Concern Detected in Passive Samplers from Great Lakes Tributaries Using High-Throughput Data and Biological Pathways
Environmental Toxicology and Chemistry ( IF 4.1 ) Pub Date : 2021-05-18 , DOI: 10.1002/etc.5118
David A Alvarez 1 , Steven R Corsi 2 , Laura A De Cicco 2 , Daniel L Villeneuve 3 , Austin K Baldwin 4
Affiliation  

Waterborne contaminants were monitored in 69 tributaries of the Laurentian Great Lakes in 2010 and 2014 using semipermeable membrane devices (SPMDs) and polar organic chemical integrative samplers (POCIS). A risk-based screening approach was used to prioritize chemicals and chemical mixtures, identify sites at greatest risk for biological impacts, and identify potential hazards to monitor at those sites. Analyses included 185 chemicals (143 detected) including polycyclic aromatic hydrocarbons (PAHs), legacy and current-use pesticides, fire retardants, pharmaceuticals, and fragrances. Hazard quotients were calculated by dividing detected concentrations by biological effect concentrations reported in the ECOTOX Knowledgebase (toxicity quotients) or ToxCast database (exposure–activity ratios [EARs]). Mixture effects were estimated by summation of EAR values for chemicals that influence ToxCast assays with common gene targets. Nineteen chemicals—atrazine, N,N-diethyltoluamide, di(2-ethylhexyl)phthalate, dl-menthol, galaxolide, p-tert-octylphenol, 3 organochlorine pesticides, 3 PAHs, 4 pharmaceuticals, and 3 phosphate flame retardants—had toxicity quotients >0.1 or EARs for individual chemicals >10–3 at 10% or more of the sites monitored. An additional 4 chemicals (tributyl phosphate, triethyl citrate, benz[a]anthracene, and benzo[b]fluoranthene) were present in mixtures with EARs >10–3. To evaluate potential apical effects and biological endpoints to monitor in exposed wildlife, in vitro bioactivity data were compared to adverse outcome pathway gene ontology information. Endpoints and effects associated with endocrine disruption, alterations in xenobiotic metabolism, and potentially neuronal development would be relevant to monitor at the priority sites. The EAR threshold exceedance for many chemical classes was correlated with urban land cover and wastewater effluent influence, whereas herbicides and fire retardants were also correlated to agricultural land cover. Environ Toxicol Chem 2021;40:2165–2182. Published 2021. This article is a U.S. Government work and is in the public domain in the USA. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

中文翻译:

使用高通量数据和生物途径识别在五大湖支流的被动采样器中检测到的潜在生物问题的化学物质和混合物

2010 年和 2014 年,使用半透膜装置 (SPMD) 和极性有机化学综合采样器 (POCIS) 在劳伦森大湖的 69 个支流中监测了水性污染物。使用基于风险的筛选方法来确定化学品和化学混合物的优先级,确定生物影响风险最大的地点,并确定在这些地点监测的潜在危害。分析包括 185 种化学品(检测到 143 种),包括多环芳烃 (PAH)、传统和当前使用的杀虫剂、阻燃剂、药物和香料。通过将检测到的浓度除以 ECOTOX 知识库(毒性商)或 ToxCast 数据库(暴露-活动比 [EAR])中报告的生物效应浓度来计算危害商。通过将影响 ToxCast 检测与常见基因靶标的化学物质的 EAR 值相加来估计混合效应。十九种化学物质——阿特拉津,N,N-二乙基甲苯酰胺、邻苯二甲酸二(2-乙基己基)酯、dl-薄荷醇、佳乐清、对叔辛基苯酚、3 种有机氯农药、3 种 PAH、4 种药物和 3 种磷酸盐阻燃剂——毒性系数 >0.1 或 EAR在 10% 或更多的监测地点,单个化学品 >10 –3 。另外 4 种化学品(磷酸三丁酯、柠檬酸三乙酯、苯并[ a ]蒽和苯并[ b ]荧蒽)存在于 EAR >10 –3的混合物中. 为了评估在暴露的野生动物中监测的潜在顶端效应和生物学终点,将体外生物活性数据与不良结果通路基因本体信息进行了比较。与内分泌干扰、外源性代谢改变和潜在的神经元发育相关的终点和影响将与在优先站点进行监测有关。许多化学品类别的 EAR 阈值超标与城市土地覆盖和废水排放影响相关,而除草剂和阻燃剂也与农业土地覆盖相关。环境毒物化学2021;40:2165–2182。2021 年发布。本文是美国政府的作品,在美国属于公共领域。环境毒理学和化学由 Wiley Periodicals LLC 代表 SETAC 出版。
更新日期:2021-07-22
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