Nicotine Metabolite Ratio Predicts Smoking Topography and Carcinogen Biomarker Level
Bibliographic record
Abstract
BACKGROUND: Variability in smoking behavior is partly attributable to heritable individual differences in nicotine clearance rates. This can be assessed as the ratio of the metabolites cotinine and 3'-hydroxycotinine (referred to as the nicotine metabolism ratio; NMR). We hypothesized that faster NMR would be associated with greater cigarette puff volume and higher levels of total 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), a carcinogen biomarker. METHODS: Current smokers (n = 109) smoked one of their preferred brand cigarettes through a smoking topography device and provided specimens for NMR and total NNAL assays. RESULTS: Faster nicotine metabolizers (third and fourth quartiles versus first quartile) based on the NMR exhibited significantly greater total puff volume and total NNAL; the total puff volume by daily cigarette consumption interaction was a significant predictor of total NNAL level. CONCLUSION: A heritable biomarker of nicotine clearance predicts total cigarette puff volume and total NNAL. IMPACT: If validated, the NMR could contribute to smoking risk assessment in epidemiologic studies and potentially in clinical practice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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 | 0.000 |
| 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".