QUANTIFYING NITROARENE GENOTOXICITY IN COMPLEX MIXTURES

硝化多环芳烃的生物活性 碳氢化合物(硝基芳烃)是广泛研究的对象 主要是因为它具有很强的致突变性和致癌性 一些硝基芳烃以及它们广泛存在于 环境，主要是不完全燃烧的结果 流程。然而，我们大多数人并不是主要接触到 单独的化合物，而是复杂的混合物 户外(汽车、发电厂等排放的废气)和 室内(香烟烟雾、暖气、炉子、烤箱等)。这个 本申请中提出的工作的目标是将 不同硝基芳烃类化合物的遗传毒性和致癌活性 排放的人工混合物和萃取物的活性 颗粒物，以便使用单一化学品的数据来评估 暴露在复杂混合物中的风险。拟议的项目， 它使用了计算机化和试验性的 方法论，将包括具有以下专业知识的专业人员 化学、生物化学、微生物学、人工智能和 风险评估，并具有丰富的研究经验 硝基芳烃。将使用两种计算机化技术。第一, 计算机自动结构评估(CASE)，一种人工 一个智能程序，它是为了预测 硝基芳烃的致突变性，将用于鉴定结构 致突变、遗传毒性和致癌性的决定因素。 二、致癌性预测与电池选型 (CPBS)方法将用于确定适当的电池 筛选单个硝基芳烃和混合物的短期试验 并预测潜在的致癌性，包括致癌性 威力。实验研究将针对评估 混合物中化合物的活性。人工合成的混合物 对硝基芳烃或相关化合物，以及 燃烧排放与个别化学品相结合，将是 检测其致突变性、代谢活性和失活 致突变性、哺乳动物遗传毒性和代谢 生物转化。将解决三个问题： 活动是累加的或受竞争的影响 酶激活，是否确定失活结构 通过案例代表替代的生物改造或竞争 以及复杂混合物的存在如何影响 个体的代谢、致突变性和遗传毒性 化学制品。解决关于外推法的几个问题 从单个组分到混合物将允许数据 与生物利用度、新陈代谢、 遗传毒性、解毒和排泄用于减少 年人体暴露风险评估中的不确定性 不完全燃烧产物和其他复杂混合物。

The biological activity of nitrated polycyclic aromatic hydrocarbons (nitroarenes) has ben the subject of extensive study primarily because of the potent mutagenicity and carcinogenicity of some nitroarenes as well as their widespread occurrence in the environment, principally as the result of incomplete combustion processes. However, most of us are not exposed primarily to individual compounds but rather to complex mixtures both outdoors (emissions from automobiles, power plants, etc.) and indoors (cigarette smoke, heaters, stoves, ovens etc). The objective of the work proposed in this application is to relate the genotoxic and carcinogenic activities of individual nitroarenes to activities of artificial mixtures and extracts of emission particulates in order to use data for single chemicals to evaluate the risk of exposure to complex mixtures. The proposed project, which employs both computerized and experimental methodologies, will involve professionals with expertise in chemistry, biochemistry, microbiology, artificial intelligence and risk assessment, and with extensive experience in the study of nitroarenes. Two computerized techniques will be used. First, Computer Automated Structure Evaluation (CASE), an artificial intelligence program which was developed to predict the mutagenicity of nitroarenes, will be used to identify structural determinants of mutagenicity, genotoxicity and carcinogenicity. Second, the Carcinogenicity Prediction and Battery Selection (CPBS) method will used to identify appropriate batteries of short-term tests for screening individual nitroarenes and mixtures and to predict potential carcinogenicity, including carcinogenic potency. Experimental studies will be directed towards assessing the activities of compounds in mixtures. Artificial mixtures of pairs of nitroarenes or related compounds, as well as extracts of combustion emissions combined with individual chemicals, will be tested for mutagenicity, metabolic activation and deactivation of mutagenicity, mammalian genotoxicity and metabolic biotransformation. Three issues will be addressed: whether activities are additive or are influenced by competition for enzymatic activation, whether inactivating structures identified by CASE represent alternative biotransformation or competition and how the presence of a complex mixture influences the metabolism, mutagenicity and genotoxicity of individual chemicals. Resolving these questions about the extrapolation from individual components to mixtures would allow data for individual chemicals concerning bioavailability, metabolism, genotoxicity, detoxification and excretion to be used to reduce uncertainty in the assessment of human risk from exposure in incomplete combustion products and other complex mixtures.