Effects of perfluoroalkyl substances (PFAS) and benzo[a]pyrene (BaP) co-exposure on phase I biotransformation in rainbow trout (Oncorhynchus mykiss)
Bibliographic record
Abstract
Abstract The presence of perfluoroalkyl substances (PFAS) in the environment, especially in aquatic ecosystems, continues to be a significant concern for human and environmental health. Previous studies have suggested that several PFAS do not undergo biotransformation due to their chemical stability, yet perfluorooctanesulfonic acid (PFOS)- and perfluorooctanoic acid (PFOA)-exposed organisms have presented altered activity of important biotransformation pathways. Given the fundamental role of biotransformation in biological organisms and the significant distribution of PFAS in aquatic environments, the present study investigated the influence of PFOA and PFOS on phase I biotransformation enzymes in vitro using the rainbow trout liver RTL-W1 cell line and in vivo using juvenile rainbow trout. Cells and fish were exposed and co-exposed to environmentally relevant concentrations of PFOA, PFOS, and benzo[a]pyrene (BaP), for 72 h and 10 days, respectively, prior to measurements of cytotoxicity and biotransformation ability through measurements of CYP1A1-, CYP1A2- and CYP3A4-like activities. Our results indicate that exposure to PFAS-BaP binary mixtures altered CYP1A-like activity in vivo; however, those alterations were not observed in vitro. Similarly, while BaP did not significantly induce CYP3A4, exposure to the PFAS led to significantly lower enzymatic activity relative to basal levels. These observations may have implications for organisms simultaneously exposed to PFAS and other environmental pollutants for which biotransformation is necessary, especially in detoxification mechanisms. Furthermore, the interference with biotransformation pathways could potentially increase adverse outcomes, compromising the stability of fish populations inhabiting PFOA- and PFOS-polluted environments.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.001 | 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".