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Updated: Jul 19, 2026

A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans
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进步生态毒性评估:利用预先训练的模型预测蜜蜂毒性和化合物降解性

Xinkang Li1, Feng Zhang2, Liangzhen Zheng3

  • 1Centre in Artificial Intelligence Driven Drug Discovery, Faculty of Applied Sciences, Macao Polytechnic University, 999078, Macao.

Journal of hazardous materials
|June 14, 2024
PubMed
概括

本研究引入了一种使用预训练和图形神经网络模型的新生态毒性评估模型. 该模型准确地预测了对蜜蜂的化学毒性和分子可降解性,提供了宝贵的见解.

关键词:
蜜蜂中毒是蜜蜂中毒的原因之一.生态毒性 生态毒性分子降解性 分子降解性.预训练模型,图形神经网络

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Toxicity Testing in Animals01:23

Toxicity Testing in Animals

Toxicity tests in animals are grounded on two main assumptions: first, the effects observed in laboratory animals can be extrapolated to humans, especially when adjusted for body surface area; second, high-dose exposure in animals is essential to identify potential human hazards from lower doses. This is based on the quantal dose-response concept, which faces the challenge of extrapolating results from relatively few test animals to much larger human populations. For example, a 0.01% incidence...