Isomer-Specific Transplacental Efficiencies of Perfluoroalkyl Substances in Human Whole Blood
Bibliographic record
Abstract
Data on isomer-specific transplacental transfer of perfluoroalkyl substances (PFASs) are very scarce. This study investigates transplacental transfer of 23 PFASs, including isomers of perfluorooctanoate (PFOA) and perfluorooctanesulfonate (PFOS), by analyzing 63 paired maternal and cord whole blood samples collected in Hubei, China. Significant correlations ( r = 0.311–0.888; p ≤ 0.013) were observed between the concentrations in maternal and cord blood for most PFASs, indicating that PFASs could be efficiently transported from mother to fetus. For perfluorocarboxylates, a U-shaped trend of transplacental transfer efficiencies (TTEs) with increasing carbon chain lengths was confirmed. For PFOA and PFOS branched isomers, TTEs generally increased as the branching point moved closer to the carboxyl or sulfonate moiety, and branched isomers transferred more efficiently than their linear isomers did. This is the first report of the TTEs of PFAS isomers based on human whole blood samples and the first calculation of the TTEs of perfluorooctane sulfonamide. For almost all PFASs, the TTEs we reported are lower than those from previous studies based on serum or plasma. Whole blood is recommended for risk assessment of PFAS placental transfer considering that PFASs exhibit different partitioning behaviors between blood matrices. More accurate parameters for the health risks of PFASs during prenatal exposure are provided here.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".