Non-Invasive Biomonitoring of Pesticides

描述（由申请人提供）：本研究项目将建立一种非侵入性生物监测能力，利用灵敏、非侵入性、微量分析仪器对唾液中暴露和反应的生物标志物进行实时分析，以评估有机磷（OP）杀虫剂的暴露情况。该项目将创建一个小型化的纳米生物电子生物传感器，对目标分析物具有高度选择性和灵敏度。此外，将修改OP杀虫剂毒死蜱的生理药代动力学和药效学模型（PBPK/PD），以纳入唾液腺隔室，用于定量预测血液毒死蜱浓度和唾液胆碱酯酶（ChE）抑制，以估计基于唾液标本的暴露量。利用唾液进行生物监测，再加上实时监测和建模是一种新的方法，具有广泛的应用评估职业暴露于杀虫剂。基于抗原诱导形成纳米颗粒-免疫复合物纳米结构的生物传感新原理，研制了OP传感器。一个胆碱酯酶传感器也将开发的基础上的胆碱酯酶水解反应产物胆碱和过氧化氢的电检测。随后，传感器将被转换为“芯片实验室”，生物芯片的性能将被表征、优化和验证。为了验证这种方法的药代动力学毒死蜱排泄和胆碱酯酶抑制在唾液中的各种生理条件和剂量水平下进行评估，以确保这些终点是准确的预测内部剂量。结合预测药代动力学模型的实时唾液分析的发展代表了当前生物监测策略的重大进步。一旦这个模型系统已经得到充分验证，它可以很容易地用来评估工人暴露于杀虫剂在广泛的职业情况下。

DESCRIPTION (provided by applicant): This research project will establish a non-invasive biomonitoring capability to evaluate exposure to organophosphorus (OP) insecticides utilizing a sensitive, non-invasive, micro-analytical instrument for realtime analysis of biomarkers of exposure and response in saliva. This project will create a miniaturized nanobioelectronic biosensor that is highly selective and sensitive for the target analyte(s). In addition, a physiologically based pharmacokinetic and pharmacodynamic model (PBPK/PD) for the OP insecticide chlorpyrifos will be modified to incorporate a salivary gland compartment that will be used to quantitatively predict blood chlorpyrifos concentration and saliva cholinesterase (ChE) inhibition to estimate exposure based on a saliva specimen. The utilization of saliva for biomonitoring, coupled to real-time monitoring and modeling is a novel approach with broad application for evaluating occupational exposures to insecticides. An OP sensor will be developed based on a new biosensing principle of antigen-induced formation of nanoparticle-immuno complex nanostructure. A ChE sensor will also be developed based on the electrodetection of the ChE hydrolyzed reaction products choline and hydrogen peroxide. Subsequently, the sensors will be transformed to a "lab-on-a-chip", and the biochip performance will be characterized, optimized and validated. To validate this approach the pharmacokinetics of chlorpyrifos excretion and ChE inhibition in saliva under various physiological conditions and dose levels will be assessed to ensure that these endpoints are accurate predictors of internal dose. The development of a real-time saliva analysis coupled to a predictive pharmacokinetic model represents a significant advancement over current biomonitoring strategies. Once this model system has been adequately validated it can readily be employed to assess worker exposure to insecticides under a wide range of occupational situations.