Non-Invasive Biomonitoring of Pesticides

描述（由申请人提供）：本研究项目将建立一个非侵入性生物监测能力，以评估有机磷（OP）杀虫剂的暴露，利用一个敏感的、非侵入性的微分析仪器，实时分析唾液中暴露和反应的生物标志物。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敏感性。此外，将修改基于生理学的毒死蜱杀虫剂药代动力学和药效学模型（PBPK/PD），纳入唾液腺室，用于定量预测血液毒死蜱浓度和唾液胆碱酯酶（ChE）抑制，以估计基于唾液样本的暴露。利用唾液进行生物监测，结合实时监测和建模，是一种具有广泛应用前景的职业杀虫剂暴露评估新方法。基于抗原诱导形成纳米粒子-免疫复合物纳米结构这一新的生物传感原理，将开发一种OP传感器。基于电检测ChE水解反应产物胆碱和过氧化氢的ChE传感器也将被开发。随后，传感器将转化为“芯片实验室”，并对生物芯片的性能进行表征、优化和验证。为了验证这一方法，将评估不同生理条件和剂量水平下毒死蜱排泄和唾液中ChE抑制的药代动力学，以确保这些终点是内剂量的准确预测指标。与预测药代动力学模型相结合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。一旦该模型系统得到充分验证，就可以很容易地用于评估工人在各种职业情况下接触杀虫剂的情况。

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.