Toxicokinetics of perfluorocarboxylate isomers in rainbow trout
Bibliographic record
Abstract
Perfluorooctanoate (PFOA) and other perfluorocarboxylates (PFCAs) are widely dispersed in the environment. Current and/or historical production of PFOA and fluorochemical precursors was conducted by telomerization and electrochemical fluorination (ECF). Telomer products typically contain linear chains of perfluorocarbons, and ECF products are a mixture of linear and branched isomers. The objective of the present study was to examine the role of toxicokinetics on PFCA isomer profiles in fish since monitoring studies have revealed a predominance of n-isomers of PFCAs in biota. Using dietary exposure, rainbow trout were administered technical ECF PFOA isomers (6.9 microg/kg/d), linear perfluorononanoate (1.4 microg/kg/d n-PFNA), and isopropyl PFNA (1.1 microg/kg/d iso-PFNA) for 36 d and then switched to a 40-d clean diet. Throughout exposure and depuration phases, blood and tissue sampling ensued. The accumulation ratio (AR) revealed similar accumulation propensity of n-PFOA and two minor branched PFOA isomers; however, the majority of branched isomers had lower AR values than n-PFOA. Enrichment of n-PFOA and n-PFNA relative to most branched isomers was consistent in all tissues. First-order elimination (k(d)) and half-life (t1/2) values were calculated. The largest t1/2 corresponded to n-PFNA followed by iso-PFNA. In ECF PFOA isomers, both n-PFOA and one minor branched isomer had the largest t1/2, suggesting that this minor isomer could be diagnostic of ECF exposure using environmental PFOA isomer patterns. Results of lower-dose ECF PFOA exposure showed similar results to the high-dose study; it is possible that both scenarios resulted in saturation of processes involved in PFCA transport. As such, the toxicokinetics of PFCA isomers at environmentally realistic levels may deviate from the results of the present study.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".