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A Review on Per- and Polyfluoroalkyl Substances in Pregnant Women: Maternal Exposure, Placental Transfer, and Relevant Model Simulation.
Wu, Yuqing; Bao, Jia; Liu, Yang; Wang, Xin; Qu, Wene.
Afiliação
  • Wu Y; School of Environmental and Chemical Engineering, Shenyang University of Technology, Shenyang 110870, China.
  • Bao J; School of Environmental and Chemical Engineering, Shenyang University of Technology, Shenyang 110870, China.
  • Liu Y; School of Environmental and Chemical Engineering, Shenyang University of Technology, Shenyang 110870, China.
  • Wang X; School of Environmental and Chemical Engineering, Shenyang University of Technology, Shenyang 110870, China.
  • Qu W; School of Environmental and Chemical Engineering, Shenyang University of Technology, Shenyang 110870, China.
Toxics ; 11(5)2023 May 04.
Article em En | MEDLINE | ID: mdl-37235245
ABSTRACT
Per- and polyfluoroalkyl substances (PFASs) are important and ubiquitous environmental contaminants worldwide. These novel contaminants can enter human bodies via various pathways, subsequently posing risks to the ecosystem and human health. The exposure of pregnant women to PFASs might pose risks to the health of mothers and the growth and development of fetuses. However, little information is available about the placental transfer of PFASs from mothers to fetuses and the related mechanisms through model simulation. In the present study, based upon a review of previously published literature, we initially summarized the exposure pathways of PFASs in pregnant women, factors affecting the efficiency of placental transfer, and mechanisms associated with placental transfer; outlined simulation analysis approaches using molecular docking and machine learning to reveal the mechanisms of placental transfer; and finally highlighted future research emphases that need to be focused on. Consequently, it was notable that the binding of PFASs to proteins during placental transfer could be simulated by molecular docking and that the placental transfer efficiency of PFASs could also be predicted by machine learning. Therefore, future research on the maternal-fetal transfer mechanisms of PFASs with the benefit of simulation analysis approaches is warranted to provide a scientific basis for the health effects of PFASs on newborns.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Toxics Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Toxics Ano de publicação: 2023 Tipo de documento: Article