Role of specific cytochrome P450 enzymes in the N-oxidation of the antiarrhythmic agent mexiletine
Bibliographic record
Abstract
1. Mexiletine is extensively metabolized in man by C- and N-oxidation and the aim of the present study was to characterize major cytochrome P450 enzyme(s) involved in the formation of N-hydroxymexiletine. 2. Incubations with genetically engineered microsomes indicated that the formation rate of N-hydroxymexiletine was highest in the presence of microsomes expressing high levels of either CYP1A2 or CYP2E1 and the formation of N-hydroxymexiletine by human liver microsomes was inhibited about 40% by antibodies directed against CYP1A1/1A2 or CYP2E1. Additional incubations demonstrated that formation of N-hydroxymexiletine was decreased 47 and 51% by furafylline, 40 microm and 120 microm, respectively, and decreased 55 and 67% by alpha-naphthoflavone, 1 microm and 3 microm, respectively (all p < 0.05 versus control). 3. The formation rate of N-hydroxymexiletine in human liver microsomes was highly correlated with CYP2B6 (RS-mexiletine, r = 0.7827; R-(-)-enantiomer, r = 0.7034; S-(+)-enantiomer, r = 0.7495), CYP2E1 (S-(+)-enantiomer, r = 0.7057) and CYP1A2 (RS-mexiletine, r = 0.5334; S-(+)-enantiomer, r = 0.6035). 4. In conclusion, we have demonstrated that CYP1A2 is a major human cytochrome P450 enzyme involved in the formation of N-hydroxymexiletine. However, other cytochrome P450 enzymes (CYP2E1 and CYP2B6) also appear to play a role in the N-oxidation of this drug.
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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".