ArticleEnvironmental science & technology2024
Development of a Physiologically Based Pharmacokinetic (PBPK) Model for F-53B in Pregnant Mice and Its Extrapolation to Humans.
Article in Environmental science & technology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Assessing the health risks of rice cadmium content standards in China.Science advances · 2026Article
- Current approaches and advances in placental toxicology.Trends in endocrinology and metabolism: TEM · 2026Review
- Article
- Understanding Mechanisms of PFAS Absorption, Distribution, and Elimination Using a Physiologically Based Toxicokinetic Model.Environmental science & technology · 2025Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Chlorinated polyfluorinated ether sulfonic acid (F-53B), a commonly utilized alternative for perfluorooctane sulfonate, was detected in pregnant women and cord blood recently. However, the lack of detailed toxicokinetic information poses a significant challenge in assessing the human risk assessment for F-53B exposure. Our study aimed to develop a physiologically based pharmacokinetic (PBPK) model for pregnant mice, based on toxicokinetic experiments, and extrapolating it to humans. Pregnant mice were administered 80 μg/kg F-53B orally and intravenously on gestational day 13. F-53B concentrations in biological samples were analyzed via ultraperformance liquid chromatography-mass spectrometry. Results showed the highest F-53B accumulation in the brain, followed by the placenta, amniotic fluid, and liver in fetal mice. These toxicokinetic data were applied to F-53B PBPK model development and evaluation, and Monte Carlo simulations were used to characterize the variability and uncertainty in the human population. Most of the predictive values were within a 2-fold range of experimental data (>72%) and had a coefficient of determination (R
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