Biotransformation of 6PPD-quinone <i>In Vitro</i> Using RTL-W1 Cell Line
Bibliographic record
Abstract
Urban stormwater runoff contains the tire-derived transformation product N -(1,3-dimethylbutyl)- N ′-phenyl- p -phenylenediamine-quinone (6PPD-quinone), which poses significant environmental risks due to its high toxicity toward certain salmonids. 6PPD-quinone biotransformation has been investigated to explain some of the stark interspecies differences in sensitivity across different fishes; however, the primary mechanisms of 6PPD-quinone biotransformation remain unclear. This work aimed to explore the toxicokinetics of 6PPD-quinone in immortalized rainbow trout ( Oncorhynchus mykiss ) liver cells (RTL-W1) to identify transformation products, using coexposure with different enzyme inhibitors and inducers. Using high-resolution mass spectrometry, we identified three phase I 6PPD-quinone transformation products, with phenyl ring hydroxylation dominating, followed by hydroxylation of the alkyl side chain, and an unknown transformation product after 4 h of exposure. Co-exposing RTL-W1 cells with α-naphthoflavone and quercetin greatly inhibited the biotransformation of 6PPD-quinone, revealing that CYP1A is primarily involved in phase I biotransformation. Hepatic clearance predicted from in vitro results was further verified based on isolated perfused trout liver experiments. Further studies are necessary on the biotransformation and kinetics of 6PPD-quinone and the detoxification pathways involved in a wide phylogenetic space in fishes.
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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 | 0.000 |
| 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) | 0.001 | 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".