Protein Binding Associated with Exposure to Fluorotelomer Alcohols (FTOHs) and Polyfluoroalkyl Phosphate Esters (PAPs) in Rats
Bibliographic record
Abstract
The biotransformation of fluorotelomer-based compounds such as fluorotelomer alcohols (FTOHs) and polyfluoroalkyl phosphate esters (PAPs) are sources of exposure to perfluorinated carboxylates (PFCAs), leading in part to the observation of significant concentrations of PFCAs in human blood. The biotransformation of FTOHs and PAPs yield intermediate metabolites that have been observed to covalently modify proteins. In the current investigation, the extent of covalent protein binding in Sprague-Dawley rats upon exposure to 8:2 FTOH and the 6:2 polyfluoroalkyl phosphate diester (6:2 diPAP) was quantified. The animals were administered a single dose of 8:2 FTOH or 6:2 diPAP at 100 mg/kg by oral gavage to monitor biotransformation and extent of protein binding within the liver, kidney, and plasma. In the 8:2 FTOH-dosed animals, perfluorooctanoate (PFOA) was produced as the primary PFCA, at 623.13 ± 59.3, 459.5 ± 171.8, and 397.3 ± 133.0 ng/g in the plasma, liver, and kidney, respectively. For the animals exposed to 6:2 diPAPs, perfluorohexanoate (PFHxA) was the primary PFCA produced, with maximum concentrations of 57.4 ± 6.5, 9.0 ± 1.2, and 25.3 ± 1.2 ng/g in the plasma, liver, and kidney, respectively. Protein binding was observed in the plasma, liver, and kidney after 8:2 FTOH and 6:2 diPAP exposure, with the most significant binding occurring in the liver (>100 nmol/g protein). This is the first study to link the exposure and in vivo biotransformation of fluorotelomer-based compounds to covalent protein binding.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".