合成杀虫剂对家蝇混合毒性预测零模型的比较(双翅目:蝇科)。

Junho Yoon, Jun-Hyung Tak
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引用次数: 0

摘要

含有活性成分混合物的杀虫产品越来越普遍,这突出表明需要使用计算方法来预测特定剂量组合下的杀虫活性。已经提出了几种预测相互作用的模型,每个模型都基于对混合物毒性的不同假设。然而,对于采用哪种模型来测定杀虫活性缺乏共识,这阻碍了对混合物毒性的准确预测以及对增效或拮抗相互作用的识别。在本研究中,我们比较了14种合成杀虫剂在杀虫剂抗性行动委员会指定的3种行动组中的剂量反应。分析了剂量-反应参数的构效关系,重点分析了LD50和Hill slope值,它们在某些模型中起着关键作用。以家蝇(Musca domestica L.,双翅目:蝇科)为模式昆虫,对Bliss、Loewe、Highest Single Agent和Schindler 4种常用模型进行了混合毒性预测。Loewe和Bliss模型对91种二元混合物的可预测性分别为79.1%和76.9%。为了提高预测的准确性,设计了一个两步框架。根据其作用方式的相似性对组合进行分组,然后将模型选择性地应用于相应的组。这些发现有助于更好地了解混合型杀虫产品的开发和评价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison of null models predicting mixture toxicity of synthetic insecticides against Musca domestica L. (Diptera: Muscidae).

The increasing prevalence of insecticidal products containing mixtures of active ingredients has highlighted the need for computational approaches to predict the insecticidal activity at specific dose combinations. Several models predicting the interactions have been proposed, each based on different assumption regarding mixture toxicity. However, the lack of consensus on which model to adopt for insecticidal activity has hindered the accurate prediction of mixture toxicity and the identification of synergistic or antagonistic interactions. In the present study, we compared the dose-responses of 14 synthetic insecticides in 3 modes of action groups assigned by the Insecticide Resistance Action Committee. The structure-activity relationships of dose-response parameters were analyzed, with a particular focus on LD50 and Hill slope values, which play pivotal roles in some models. Four widely adopted models, Bliss, Loewe, Highest Single Agent, and Schindler, were evaluated to predict mixture toxicity using Musca domestica L. (Diptera: Muscidae) as the model insect. The Loewe and Bliss models demonstrated 79.1% and 76.9% predictability, respectively, for 91 binary mixtures. To improve predictive accuracy, a 2-step framework was devised. Combinations were grouped based on the similarity of their modes of action, and then the models were selectively applied to the corresponding group. These findings contribute to a better understanding of the development and assessment of mixture-based insecticidal products.

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