Decreased Nicotinic Receptor Availability in Smokers with Slow Rates of Nicotine Metabolism
Bibliographic record
Abstract
UNLABELLED: The nicotine metabolite ratio (NMR), a stable measure of hepatic nicotine metabolism via the CYP2A6 pathway and total nicotine clearance, is a predictive biomarker of response to nicotine replacement therapy, with increased quit rates in slower metabolizers. Nicotine binds directly to nicotinic acetylcholine receptors (nAChRs) to exert its psychoactive effects. This study examined the relationship between NMR and nAChR (α4β2* subtype) availability using PET imaging of the radiotracer 2-(18)F-fluoro-3-(2(S)-azetidinylmethoxy)pyridine (2-(18)F-FA-85380, or 2-(18)F-FA). METHODS: Twenty-four smokers-12 slow metabolizers (NMR < 0.26) and 12 normal metabolizers (NMR ≥ 0.26)-underwent 2-(18)F-FA-PET brain imaging after overnight nicotine abstinence (18 h before scanning), using a validated bolus-plus-infusion protocol. Availability of nAChRs was compared between NMR groups in a priori volumes of interest, with total distribution volume (VT/fP) being the measure of nAChR availability. Cravings to smoke were assessed before and after the scans. RESULTS: Thalamic nAChR α4β2* availability was significantly reduced in slow nicotine metabolizers (P = 0.04). Slow metabolizers exhibited greater reductions in cravings after scanning than normal metabolizers; however, craving was unrelated to nAChR availability. CONCLUSION: The rate of nicotine metabolism is associated with thalamic nAChR availability. Additional studies could examine whether altered nAChR availability underlies the differences in treatment response between slow and normal metabolizers of nicotine.
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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 | 0.002 | 0.002 |
| 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".