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利用随机死亡和个体耐受模型对鱼类幼虫进行金属毒动学建模:模型假设、参数敏感性和预测性能的比较。

Toxicodynamic modeling of zebrafish larvae to metals using stochastic death and individual tolerance models: comparisons of model assumptions, parameter sensitivity and predictive performance.

机构信息

Key Laboratory of Pollution Process and Environmental Criteria of Ministry of Education and Tianjin Key Laboratory of Environmental Remediation and Pollution Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300071, China.

出版信息

Ecotoxicology. 2017 Apr;26(3):295-307. doi: 10.1007/s10646-017-1763-x. Epub 2017 Feb 3.

Abstract

Process-based toxicodynamic (TD) models are playing an increasing role in predicting chemical toxicity to aquatic organism. Stochastic death (SD) and individual tolerance distribution (IT) are two often used assumptions in TD models which could lead to different consequences for risk assessment of chemicals. Here, using the toxicity data of single (Cu, Zn, Cd, and Pb) and their binary metal mixtures on survival of zebrafish larvae, we assessed the parameter sensitivity and evaluated the predictive performance of SD and IT models. The sensitivity analysis indicated the parameters related to toxicodynamics such as k and threshold, had a great influence on the SD model's output and α had a great influence on the IT model's output. The predicted survival probability was highly sensitive to the assumptions of SD or IT models, and the SD model explained toxicity of single metal and binary metal mixtures better than IT model. Our results suggested that SD model is more suitable in assessing the metal toxicity to zebrafish larvae. Moreover, different combinations of laboratory metal-specific and species-specific experiments with SD and IT models need further study for better understanding and predicting toxic effects for different metals and organisms.

摘要

基于过程的毒代动力学(TD)模型在预测化学物质对水生生物的毒性方面发挥着越来越重要的作用。随机死亡(SD)和个体耐受分布(IT)是 TD 模型中常用的两个假设,这可能会对化学品风险评估产生不同的后果。在这里,我们使用单一(Cu、Zn、Cd 和 Pb)及其二元金属混合物对斑马鱼幼虫生存的毒性数据,评估了 SD 和 IT 模型的参数敏感性和预测性能。敏感性分析表明,与毒代动力学相关的参数,如 k 和阈值,对 SD 模型的输出有很大影响,而 α 对 IT 模型的输出有很大影响。预测的生存概率对 SD 或 IT 模型的假设高度敏感,SD 模型比 IT 模型更能解释单一金属和二元金属混合物的毒性。我们的结果表明,SD 模型更适合评估金属对斑马鱼幼虫的毒性。此外,还需要进一步研究基于 SD 和 IT 模型的实验室金属特异性和物种特异性实验的不同组合,以更好地理解和预测不同金属和生物的毒性效应。

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