Non-Additive Ah Receptor Ligand Interactions

尽管人类接触毒物是一种复杂的混合物，但风险评估通常基于 在啮齿动物模型中进行的单一化学研究。与当前方法相关的限制有 由于潜在的重大健康、社会和经济问题而日益受到质疑 后果。为了改进对慢性和亚慢性接触的风险进行量化评估 合成和天然化学品及其复杂混合物，从来源到结果的不确定性 在整个有机体及其基因组的背景下，必须最小化连续体。在这份提案中， 2，3，7，8-四氯二苯并对二恶英(TCDD)、3，3‘，4，4’，5-五氯联苯(PCB126)和2，2‘，4，4’，5，5‘- 六氯联苯(PCB153)以及反映这些物质环境水平的重组混合物 将对污染物进行系统的研究，以阐明添加剂、拮抗剂的作用机理。 以及在分子和生理水平上发生的协同作用。光线设计和建模 方法将被用来最小化完全析因研究，以调查混合的假设 在与环境有关的水平上，TCDD、PCB126和PCB153会引起非加性的肝毒性效应。 剂量和时间依赖的肝脏基因表达和脂肪肝效应将在小鼠身上进行评估 富含二恶英反应基因的基因芯片和互补的组织病理学方法。 微阵列数据将通过计算与组织病理学和临床化学相结合，以识别 基因表达变化与生理/毒性结果之间的关联 阐明二恶英介导的脂肪肝毒性的作用机制。然后，混合物将被 被检查以检测和表征影响 使用与脂肪肝相关的基因的响应面模型进行脂肪肝反应。这项提议将 不仅制定创新和可信的统计战略，严格评估由 含有使用共同作用机制的化学品的混合物，但也将进一步阐明 TCDD诱导的脂肪的毒性机制。

Although human exposure to toxicants occurs as a complex mixture, risk assessments are typically based on single chemical studies conducted in rodent models. Limitations associated with current approaches are increasingly being questioned due to the potential for significant health, societal and economic consequences. In order to improve the quantitative risk assessment of chronic and subchronic exposure to synthetic and natural chemicals and their complex mixtures, uncertainties within the source-to-outcome continuum must be minimized in the context of the whole organisms, and its genome. In this proposal, 2,3,7,8-tetrachlrodibenzo-p-dioxin (TCDD), 3,3',4,4',5-pentachlorobiphenyl (PCB126), and 2,2',4,4',5,5'- hexachlorobiphenyl (PCB153) as well as a reconstituted mixture that reflects environmental levels of these contaminants will be systematically examined to elucidate the mechanisms of action of additive, antagonistic and synergistic interactions that occur at molecular and physiological levels. Ray designs and modeling approaches will be used to minimize full factorial studies in order to investigate the hypothesis that a mixture of TCDD, PCB126 and PCB153 at environmentally relevant levels elicit non-additive hepatotoxic effects. Dose- and time-dependent hepatic gene expression and fatty liver effects will be assessed using a mouse cDNA array enriched with dioxin responsive genes and complementary histopathology approaches. Microarray data will be computationally integrated with histopathology and clinical chemistry to identify associations between changes in gene expression and physiological/toxic outcomes that facilitates the elucidation the mechanisms of action of dioxin-mediated fatty liver toxicity. The mixture will then be examined to detect and characterize the additive, synergistic and antagonistic interactions that affect the fatty liver response using response surface models for genes associated with fatty liver. This proposal will not only develop innovative and credible statistical strategies to rigorously assess interactions induced by mixtures containing chemicals that use a common mechanism of action, but will also further elucidate mechanisms of toxicity associated with TCDD-induced fatty.