Developing a predictive toxicity model for metallic anions in plants

开发植物中金属阴离子的预测毒性模型

• 批准号: IN190100044
• 负责人: Dr Dane Lamb
• 金额: $ 34.82万
• 依托单位: RMIT University
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Indigenous
• 财政年份: 2019
• 资助国家: 澳大利亚
• 起止时间: 2019-05-16 至 2023-05-15
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/IN190100044
• 关键词: Developing; predictive; toxicity; model; metallic

This project aims to develop competitive anionic toxicity models for antimony, arsenic, molybdenum and selenium supported by detailed speciation information. Available ecotoxicological models for inorganic toxicants have exclusively focused on cations such as zinc, and ignored anionic toxicants such as arsenic and antimony. For available models on cations to be applicable to contaminated environments, it is essential for equivalent anionic toxicity models be developed. This project will develop the first such model, which will provide new insights on ecotoxicological modelling for inorganic anionic toxicants. The project will transform ecotoxicological modelling approaches for metals and metalloids in terrestrial systems and directly improve our ability to assess risks associated with environmental contamination.

该项目旨在开发有详细形态信息支持的Sb、As、Mo和Se的竞争性阴离子毒性模型。现有的无机毒物生态毒理学模型只关注锌等阳离子毒物，而忽略了砷和锑等阴离子毒物。为了使现有的阳离子模型适用于污染环境，建立等效的阴离子毒性模型是必不可少的。该项目将开发第一个这样的模型，这将为无机阴离子毒物的生态毒理学建模提供新的见解。该项目将改变陆地系统中金属和类金属的生态毒理学建模方法，并直接提高我们评估与环境污染有关的风险的能力。