Significant association of nicotine reinforcement and cue reactivity: a translational study in humans and rats
Bibliographic record
Abstract
Relapse is common amongst smokers attempting to quit and tobacco cue-induced craving is an important relapse mechanism. Preclinical studies commonly use cue-induced reinstatement of nicotine seeking to investigate relapse neurobiology. Previous research suggests dependence severity and nicotine intake history affect smoking resumption and cue-induced reinstatement of nicotine seeking. However, behavioural data may be interpreted in terms of nicotine reinforcement. This translational study investigated if individual differences in objectively assessed nicotine reinforcement strength were associated with cue-reactivity in both rats and human smokers, which to our knowledge has not been investigated before. Rats (n = 16) were trained to self-administer nicotine and were tested on a progressive ratio schedule of nicotine reinforcement, to assess reinforcer strength, and on a test of cue-induced reinstatement of nicotine seeking. Nicotine reinforcement strength was assessed in human smokers (n = 104) using a forced choice task (nicotine containing vs. denicotinised cigarettes) and self-reported cue-induced craving was assessed following exposure to smoking and neutral cues. Responding for nicotine under progressive ratio was strongly positively correlated with cue-induced reinstatement of nicotine seeking in rats. Nicotine choices in human smokers were significantly associated with cue-induced craving controlling for dependence severity, years of smoking, and urge to smoke following neutral cues. Findings suggest nicotine reinforcement strength is associated with both types of cue-induced behaviour, implying some translational commonality between cue-induced craving in human smokers and cue-induced reinstatement of nicotine seeking in rats. Findings are discussed in relation to clinical implications and whether these laboratory tasks assess drug 'wanting'.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".