De Oro-Carretero Paloma, Sanz-Landaluze Jon
Department of Analytical Chemistry, Faculty of Chemical Science, Complutense University of Madrid, Avenida Complutense s/n, 28040 Madrid, Spain.
J Xenobiot. 2025 Jun 16;15(3):93. doi: 10.3390/jox15030093.
The development of alternative methods that link cellular and predictive toxicity to high-level toxicity is a key focus of current research within the framework of the 3Rs in animal experimentation. In this context, this study aimed to evaluate the previously developed in vitro approach using the zebrafish liver cell line (ZFL) for assessing bioaccumulation and biotransformation of the compound BDE-47, which is more hydrophobic than phenanthrene, and is the compound used in the previous study. For this purpose, experimentally, the internal concentrations in the cells (C) and the exposure medium of both BDE-47 and its main metabolites were quantified at different exposure times by GC-MS. Additionally, the free bioavailable concentration (C) was determined with a solid-phase microextraction (SPME) experiment. With the aim of refine models, C and C were also estimated using a predictive chemical distribution model (MBM). Bioconcentration factors (BCFs) were determined by relating all these values, as well as by toxicokinetic fitting and by in vitro-in vivo extrapolation modelling (IVIVE). The results showed a high concordance with the values obtained in vivo. Moreover, the study highlighted the importance of experimentally determining C and C, as the predicted values can vary depending on the chemical, thereby influencing the BCF outcome. This variation occurs because models do not account for the absorption and biotransformation kinetics of the compounds. The data presented may contribute to refining predictive models.
开发将细胞毒性和预测毒性与高级毒性联系起来的替代方法，是当前动物实验3R框架内研究的关键重点。在此背景下，本研究旨在评估先前开发的使用斑马鱼肝细胞系（ZFL）的体外方法，以评估化合物BDE-47的生物累积和生物转化，BDE-47比菲更疏水，是先前研究中使用的化合物。为此，通过实验，在不同暴露时间用气相色谱-质谱法（GC-MS）对细胞内BDE-47及其主要代谢物的浓度（C）和暴露介质中的浓度进行了定量。此外，通过固相微萃取（SPME）实验测定了游离生物可利用浓度（C）。为了完善模型，还使用预测性化学分布模型（MBM）估算了C和C。通过关联所有这些值、毒代动力学拟合以及体外-体内外推建模（IVIVE）来确定生物浓缩因子（BCF）。结果与体内获得的值高度一致。此外，该研究强调了通过实验确定C和C的重要性，因为预测值可能因化学物质而异，从而影响BCF结果。这种变化的发生是因为模型没有考虑化合物的吸收和生物转化动力学。所呈现的数据可能有助于完善预测模型。
