5‐Hydroxytryptamine is biotransformed by CYP2C9, 2C19 and 2B6 to hydroxylamine, which is converted into nitric oxide
Bibliographic record
Abstract
There is circumstantial evidence suggesting that 5-hydroxytryptamine (5-HT) could be biotransformed by enzymatic systems other than monoamino oxidase A, and that the isoforms of cytochrome P450 may be a source of nitric oxide. This study aimed to assess whether cytochrome P450 contributes to 5-HT biotransformation, and to provide evidence that 5-HT metabolism generates nitric oxide. Addition of 5-HT to cultured hepatocytes yielded 5-hydroxyindol acetic acid, a formation modulated by cytochrome P450 enzyme inducers and inhibitors. Recombinant human CYP2B6, 2C9 and 2C19 biotransformed 5-HT in 5-hydroxyindol acetic acid, but not CYP1A2, 2D6 or 3A4. Cultured hepatocytes with 5-HT generated nitric oxide, the amount of which was altered by cytochrome P450 enzyme inducers and inhibitors. In the presence of CYP2B6, 2C9 and 2C19, 5-HT relaxed precontracted isolated aortic rings, with or without endothelium, an effect prevented by the addition of methylene blue and an inhibitor of catalase, but not by myoglobin. In the absence of catalase, hydroxylamine was always assayed as a byproduct of 5-HT metabolism. In conclusion, CYP2B6, 2C9 and 2C19 biotransform 5-HT, yielding hydroxylamine, which is converted to nitric oxide in the presence of catalase. British Journal of Pharmacology (2004) 141, 407-414. doi:10.1038/sj.bjp.0705632
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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) | 0.002 | 0.001 |
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".