Structure and Toxicity Characterization of Alkyl Hydroxylated Metabolites of 6PPD-Q
Bibliographic record
Abstract
Distinct from other nontoxic PPD quinones, 6PPD-Q was recently discovered to be regioselectively metabolized to alkyl hydroxylated metabolites (alkyl-OH-6PPD-Q) in rainbow trout. It remains unknown whether the unique alkyl-OH-6PPD-Q might contribute to the toxicity of 6PPD-Q. To test this, we herein synthesized chemical standards of alkyl-OH-6PPD-Q isomers and investigated their metabolic formation mechanism and toxicity. The predominant alkyl-OH-6PPD-Q was confirmed to be hydroxylated on the C4 tertiary carbon (C4-OH-6PPD-Q). The formation of C4-OH-6PPD-Q was only observed in microsomal, but not cytosolic fractions of rainbow trout (O. mykiss) liver S9. A general CYP450 inhibitor fluoxetine inhibited the formation of hydroxylated metabolites of 6PPD-Q, supporting that CYP450 catalyzed the hydroxylation. This well-explained the compound- and regio-selective formation of C4-OH-6PPD-Q, due to the weak C-H bond on the C4 tertiary carbon. Surprisingly, while cytotoxicity was observed for 6PPD-Q and C3-OH-6PPD-Q in a coho salmon (O. kisutch) embryo (CSE-119) cell line, no toxicity was observed for C4-OH-6PPD-Q. To further confirm this under physiologically relevant conditions, we fractionated 6PPD-Q metabolites formed in the liver microsome of rainbow trout. Cytotoxicity was observed for the fraction of 6PPD-Q, but not the fraction of C4-OH-6PPD-Q. In summary, this study highlighted the C4 tertiary carbon as the key moiety for both metabolism and toxicity of 6PPD-Q, and confirmed that alkyl hydroxylation is a detoxification pathway for 6PPD-Q.
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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".