高效氯氟氰菊酯纳米农药健康风险及毒性机制研究

Nano-pesticide possesses great advantages in improving pesticide bioactivity, increasing pesticide efficacy, and reducing the usage. However，owing to the small size effect and high surface effect of nano particles, nano-pesticide can improve the efficiencies of pesticides as well as increase the risk of getting into human body. In this project, lambda-cyhalothrin nano-pesticide is selected as typical object to investigate the occupational exposure risk in different scenarios and dietary risk in crop harvest time. The main control factor on health risk of nano-pesticide will be clarified. Then, based on the determined exposure concentration, rats is used as model organism to simulation evaluate absorption, transformation, accumulation, and metabolism rules of nano-pesticide in human body through gavage, inhalation and cutaneous application. Finally, the health effect risk and toxicity mechanism of nano-pesticide would be evaluated and clarified based on metabolomics. This project will reveal the health risk of nano-pesticide from the view of exposure and toxicity and provide reference basis for accurate health risk assessment of nano-pesticide.

纳米农药在提高农药生物活性、增加农药持效性、减少农药使用量方面具有显著优势。但由于纳米颗粒的小尺寸效应和大比表面积效应使纳米农药在提高农药有效利用率的同时也大大增加了其进入人体的风险，给人类健康带来了潜在的威胁。本项目以高效氯氟氰菊酯纳米制剂为典型研究对象，开展纳米农药在不同施药场景下的职业暴露风险以及在农作物采收期的膳食风险研究，明确纳米农药的人体暴露量及其影响因素；以大鼠为模式生物，基于测定的纳米农药暴露量，通过灌胃、吸入、皮肤涂抹等暴露方式，系统模拟纳米农药在人体内吸收、迁移、富集、代谢规律，并结合代谢组学技术，阐明纳米农药的毒性机制。从暴露与毒性相结合的角度揭示纳米农药的健康风险，为纳米农药的准确健康风险评价提供借鉴。

纳米农药是纳米科技在农业领域的一项新兴应用，在增加靶标有效沉积、提高农药生物活性、减少农药用量等方面具有明显的优势。随着纳米农药研发技术的不断成熟以及推向市场的需求增加，纳米农药的安全问题已经受到越来越多的重视。本研究以高效氯氟氰菊酯为研究对象，系统研究了高效氯氟氰菊酯水乳剂、纳米颗粒剂、纳米微囊缓释剂在大鼠体内的代谢富集差异，在设施黄瓜种植体系中的残留规律差异以及对施药人员的健康风险差异。大鼠代谢结果表明，高效氯氟氰菊酯在心脏、肝脏、肾脏、脾脏、脑中快速代谢，而在脂肪、肌肉、卵巢和子宫中逐渐富集，在脂肪中的富集量最大。水乳剂和纳米颗粒剂在肺脏中也能快速代谢，而纳米微囊缓释剂在肺脏中显著沉积，在肺脏中浓度与其他两种剂型差异最高达100多倍，容易对肺脏造成毒性；水乳剂、纳米颗粒剂、纳米微囊缓释剂在黄瓜中的半衰期分别为2.0，4.2和5.1天，三种制剂在黄瓜上的最终残留量均远小于高效氯氟氰菊酯在黄瓜上的最大残留限量，按照推荐剂量施用高效氯氟氰菊酯纳米制剂不会产生膳食风险；在相同防护条件下，纳米颗粒剂的施药健康风险要高于水乳剂和纳米微囊缓释剂，同时在较差防护条件下，施用纳米颗粒剂其施药人员健康风险不可接受，建议在施用高效氯氟氰菊酯时穿长衣长裤并佩戴口罩。本研究结果为纳米农药的健康风险评价提供了重要的数据支撑。