Reduced dopamine D1 receptor binding in the ventral striatum of cigarette smokers
Bibliographic record
Abstract
Several drugs of abuse, including nicotine, are thought to exert their reinforcing effects through actions on the mesolimbic dopamine system. Animal and human studies suggest that chronic administration of addictive drugs may lead to impaired dopamine neurotransmission in the nucleus accumbens. We measured D1 receptor density in 11 smokers and 18 nonsmokers using positron emission tomography and the D1 receptor ligand [11C]SCH 23390. Ten of the smokers were scanned twice, once after overnight abstinence from cigarettes, and once while smoking at their usual rate, to account for possible acute effects of cigarette smoking on D1 receptor binding. In addition, eight control subjects were scanned twice to assess the reproducibility of the method. We used compartmental modeling to measure [11C]SCH 23390 binding potential, a measure of D1 receptor density. There were no differences in binding between abstinent and nonabstinent scans in smokers or in the two scans in controls. However, there was a significant reduction in [11C]SCH 23390 binding potential in smokers compared to nonsmokers in the striatum, most prominently in the ventral striatum. This suggests that there is a reduction in dopamine D1 receptor density in the ventral striatum of human cigarette smokers relative to nonsmokers, which implies that the postsynaptic mesolimbic dopamine system may be chronically underactive in smokers, either as an antecedent or consequence of addiction to cigarettes. Such a hypodopaminergic state may play an important role in sustaining nicotine-seeking behavior. Alternatively, an inherited reduction in dopamine receptors in the striatum may be associated with an increased risk of addictive behavior.
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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) | 0.000 | 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".