Exploring the role of the Ser9Gly (rs6280) Dopamine D3 receptor polymorphism in nicotine reinforcement and cue-elicited craving
Bibliographic record
Abstract
Preclinical studies show that the dopamine D3 receptor (D3R) is involved in the reinstatement of drug seeking and motivation for drugs of abuse. A D3R gene variant, Ser9Gly (rs6280) has been linked to nicotine dependence, yet the mechanisms underlying its involvement in nicotine dependence is unclear. This study investigated the relationship between the Ser9Gly variant and measures of both nicotine reinforcement and cue-elicited craving. Phenotypes of smoking behaviors were assessed in genetically grouped (Glycine vs. No Glycine carriers) current smokers (n = 104, ≥ 10 cigarettes per day). Laboratory measures included a forced choice session (to measure reinforcement of nicotine containing vs. denicotinized cigarettes), and a cue-reactivity session (to measure smoking cues vs. neutral cues elicited craving). The forced choice procedure revealed that subjective ratings were significantly higher in response to nicotinized compared to denicotinized cigarettes; however the Ser9Gly variant did not influence this effect. By comparison, smoking cues elicited greater craving over time compared to neutral cues, and Glycine carriers of the Ser9Gly D3R variant seem to experience a significant blunted cue-elicited craving effect. Results support D3R involvement in nicotine cue reactivity. However, more research is needed to reveal how this gene variant modulates various aspects of nicotine dependence.
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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".