@ucas.edu.cn
Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences
Scopus Publications
Ruili Xie, Yiping Xu, Mei Ma, and Zijian Wang
American Chemical Society (ACS)
High-throughput in vitro assays combined with in vitro-in vivo extrapolation (IVIVE) leverage in vitro responses to predict the corresponding in vivo exposures and thresholds of concern. The integrated approach is also expected to offer the potential for efficient tools to provide estimates of chemical toxicity to various wildlife species instead of animal testing. However, developing fish physiologically based toxicokinetic (PBTK) models for IVIVE in ecological applications is challenging, especially for plausible estimation of an internal effective dose, such as fish equivalent concentration (FEC). Here, a fish PBTK model linked with the IVIVE approach was established, with parameter optimization of chemical unbound fraction, pH-dependent ionization and hepatic clearance, and integration of temperature effect and growth dilution. The fish PBTK-IVIVE approach provides not only a more precise estimation of tissue-specific concentrations but also a reasonable approximation of FEC targeting the estrogenic potency of endocrine-disrupting chemicals. Both predictions were compared with in vivo data and were accurate for most indissociable/dissociable chemicals. Furthermore, the model can help determine cross-species variability and sensitivity among the five fish species. Using the available IVIVE-derived FEC with target pathways is helpful to develop predicted no-effect concentration for chemicals with similar mode of action and support screening-level ecological risk assessment.
Ruili Xie, Xiaodan Wang, Yiping Xu, Lei Zhang, Mei Ma, and Zijian Wang
Elsevier BV
Ruili Xie, Yiping Xu, Mei Ma, Xiaodan Wang, Lei Zhang, and Zijian Wang
Elsevier BV
Ruili Xie, Yiping Xu, Mei Ma, and Zijian Wang
Elsevier BV
Yiping Xu, Dahan Qing, Ruili Xie, Fenfen Zhu, Xiaozhong Gao, Kaifeng Rao, Mei Ma, and Zijian Wang
Elsevier BV
Ruili Xie, Gaofeng Zhao, Jianghua Yang, Zhihao Wang, Yiping Xu, Xiaowei Zhang, and Zijian Wang
Elsevier BV
Xiangjuan Yuan, Ruili Xie, Qi Zhang, Lei Sun, Xuejun Long, and Dongsheng Xia
Elsevier BV