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基于生理毒代动力学结合代谢(PBTK-MT)模型增强预测鱼类中酚类内分泌干扰化学物质及其代谢物的体内浓度。

Enhanced prediction of internal concentrations of phenolic endocrine disrupting chemicals and their metabolites in fish by a physiologically based toxicokinetic incorporating metabolism (PBTK-MT) model.

机构信息

SCNU Environmental Research Institute, Guangdong Provincial Key Laboratory of Chemical Pollution and Environmental Safety & MOE Key Laboratory of Theoretical Chemistry of Environment, South China Normal University, Guangzhou, 510006, People's Republic of China; School of Environment, South China Normal University, Guangzhou, 510006, People's Republic of China.

Guangdong Provincial Engineering Research Center for Hazard Identification and Risk Assessment of Solid Waste, Institute of Analysis, Guangdong Academy of Sciences (China National Analytical Center, Guangzhou), Guangzhou, 510070, People's Republic of China.

出版信息

Environ Pollut. 2022 Dec 1;314:120290. doi: 10.1016/j.envpol.2022.120290. Epub 2022 Sep 27.

Abstract

Bisphenol A (BPA), 4-nonylphenol (4-NP), and triclosan (TCS) are phenolic endocrine disrupting chemicals (EDCs), which are widely detected in aquatic environments and further bioaccumulated and metabolized in fish. Physiologically based toxicokinetic (PBTK) models have been used to describe the absorption, distribution, metabolism, and excretion (ADME) of parent compounds in fish, whereas the metabolites are less explored. In this study, a PBTK incorporating metabolism (PBTK-MT) model for BPA, 4-NP, and TCS was established to enhance the performance of the traditional PBTK model. The PBTK-MT model comprised 16 compartments, showing great accuracy in predicting the internal concentrations of three compounds and their glucuronidated and sulfated conjugates in fish. The impact of typical hepatic metabolism on the PBTK-MT model was successfully resolved by optimizing the mechanism for deriving the partition coefficients between the blood and liver. The PBTK-MT model exhibited a potential data gap-filling capacity for unknown parameters through a backward extrapolation approach of parameters. Model sensitivity analysis suggested that only five parameters were sensitive in at least two PBTK-MT models, while most parameters were insensitive. The PBTK-MT model will contribute to a well understanding of the environmental behavior and risks of pollutants in aquatic biota.

摘要

双酚 A(BPA)、4-壬基酚(4-NP)和三氯生(TCS)是酚类内分泌干扰物(EDCs),广泛存在于水环境中,并在鱼类中进一步生物累积和代谢。基于生理的毒代动力学(PBTK)模型已被用于描述鱼类中母体化合物的吸收、分布、代谢和排泄(ADME),而代谢物则较少被探索。在本研究中,建立了一个包含代谢的 PBTK(PBTK-MT)模型,用于 BPA、4-NP 和 TCS,以增强传统 PBTK 模型的性能。PBTK-MT 模型包含 16 个隔室,在预测三种化合物及其在鱼类中的葡萄糖醛酸化和硫酸化缀合物的内部浓度方面表现出很高的准确性。通过优化推导血液和肝脏之间分配系数的机制,成功解决了典型肝代谢对 PBTK-MT 模型的影响。PBTK-MT 模型通过参数的反向外推方法,具有填补未知参数的潜在数据填补能力。模型敏感性分析表明,至少在两个 PBTK-MT 模型中,只有五个参数是敏感的,而大多数参数是不敏感的。PBTK-MT 模型将有助于更好地了解污染物在水生生物群中的环境行为和风险。

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