The effect of methoxsalen on nicotine and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) metabolism in vivo
Bibliographic record
Abstract
Nicotine is metabolized to the inactive metabolite cotinine by cytochrome P450 2A6. NNK, or 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone, is a potent procarcinogen shown to be activated to a reactive mutagenic metabolite by the enzyme CYP2A6. We studied the effect of inhibiting CYP2A6 on smoking behavior and metabolism of the procarcinogen NNK. In study 1, abstinent smokers (n=7) received methoxsalen (a potent CYP2A6 inhibitor), 30-50 mg orally, one-half hour before three subcutaneous nicotine injections (31 microg/kg) were given at hourly intervals. Methoxsalen increased mean plasma nicotine by 47% (p<.01) and mean nicotine area under the curve (AUC) by 63% (p<.0001); and decreased nicotine clearance by 39% (p<.0001), relative to placebo. In study 2, smokers (n=11) were told to maintain their same number of cigarettes smoked while receiving methoxsalen, 10 mg orally three times daily for 3 days. On day 3 of methoxsalen treatment, a 29% increase in plasma nicotine/expired-air CO (an index of smoke exposure) (p=0.03) was observed. Urinary levels of trans 3'-hydroxycotinine (metabolized by CYP2A6 from cotinine) also were decreased (p<.0001), and significantly more NNK was metabolized to the inactive NNAL-glucuronide (1.04+/-0.54 pmol/mg on day 1 to 1.37+/-0.74 pmol/mg on day 4, p<.01) relative to placebo. Thus, treatment with the CYP2A6 inhibitor methoxsalen in vivo increases the routing of NNK to the inactive NNAL-glucuronide and decreases smoking. CYP2A6 inhibition may have potential as an exposure reduction or cessation strategy in tobacco dependence.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".