Inhibition of cytochrome P450 2A6 increases nicotine's oral bioavailability and decreases smoking
Bibliographic record
Abstract
BACKGROUND: Nicotine establishes and maintains tobacco dependence. Individuals with genetically deficient CYP2A6 nicotine metabolism are at lower risk to become smokers and, if dependent, will smoke fewer cigarettes. Hepatic CYP2A6 accounts for nicotine's low systemic bioavailability, precluding oral nicotine replacement to treat dependence. OBJECTIVE: We sought to determine whether CYP2A6 inhibition via oral methoxsalen decreases nicotine clearance, increases nicotine bioavailability, and decreases smoking. METHODS: Two within-subject designs in healthy tobacco-dependent volunteers were conducted: a singleblind kinetic study (n = 17) of methoxsalen 30, 10, or 3.5 mg or placebo given with nicotine 4 mg orally to abstinent smokers; and a double-blind randomized crossover study (n = 11) of methoxsalen 30 mg or placebo crossed with nicotine 4 mg given orally or placebo before 60 minutes' abstinence and 90 minutes' free smoking. RESULTS: Placebo plus nicotine 4 mg orally increased the mean 3-hour plasma nicotine level by 4 ng/mL over residual baseline nicotine level, whereas methoxsalen 10 or 30 mg plus nicotine increased it by 9 ng/mL (P<.01), demonstrating in vivo inhibition of CYP2A6 nicotine metabolism. Methoxsalen 30 mg plus nicotine 4 mg given orally decreased breath carbon monoxide concentration at the end of free smoking by 47% (4.6 versus 8.7 ppm; P<.01) and cigarettes smoked by 24% (3.1 versus 4.1, P<.01) compared with placebo plus placebo. CONCLUSIONS: Methoxsalen inhibits nicotine first-pass metabolism of orally administered nicotine, and the combination directly reduces smoking in a laboratory setting. CYP2A6 inhibitors may have an important role in smoking cessation and tobacco exposure reduction.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".