Effects of Nicotine Metabolic Rate on Withdrawal Symptoms and Response to Cigarette Smoking After Abstinence
Bibliographic record
Abstract
This study investigated the influence of the rate of nicotine metabolism, as indicated by the nicotine metabolite ratio (NMR), on tobacco dependence. We stratified 136 smokers on the basis of saliva NMR as fast (n = 65) and slow (n = 71) metabolizers. Two "loading cigarettes" were smoked after overnight, and a "reward cigarette" was smoked after 6 hours of daytime, abstinence. Blood nicotine concentrations, expired carbon monoxide, withdrawal/craving, and reward questionnaires were collected before/after smoking and during daytime abstinence. Compared with slow metabolizers, fast metabolizers had a shorter nicotine elimination half-life (P < 0.001), lower plasma nicotine concentrations (P < 0.001), and higher withdrawal/craving scores (P < 0.05) for most times during daytime abstinence, indicating that fast metabolizers are likely smoking more to relieve withdrawal symptoms (negative reinforcement). Reward/satisfaction scores were similar in fast and slow metabolizers, suggesting that faster nicotine metabolism, assessed by NMR, is not associated with greater positive reinforcement. CYP2A6 normal (n = 82) and reduced (n = 42) genotype predicted plasma nicotine concentrations but not withdrawal symptoms.
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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 | 0.001 | 0.003 |
| 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".