<p>Depressed mood induction in early cigarette withdrawal is unaffected by acute monoamine precursor supplementation</p>
Bibliographic record
Abstract
BACKGROUND: Cigarette smoking is the leading preventable cause of death; however, quitting is difficult and early relapse is common. Dysphoric mood during early cigarette withdrawal is associated with relapse, and with the exception of bupropion and nortriptyline, few interventions have been developed to prevent this. During early cigarette withdrawal there is an elevation in the levels of monoamine oxidase-A (MAO-A), which removes monoamines excessively and induces oxidative stress and is implicated in creating sad mood. Hence, we conducted a randomized, placebo-controlled, double-blind crossover trial of a dietary supplement designed to counter the effects of elevated MAO-A levels on vulnerability to depressed mood. METHODS: Twenty-one otherwise healthy cigarette smokers completed the protocol, receiving either active dietary supplement followed by washout and placebo or the same in reverse order. The dietary supplement was composed of monoamine precursors (2 g tryptophan, 10 g tyrosine) and blueberry antioxidants (blueberry juice with blueberry extract). Vulnerability to depressed mood was measured by the change in scores of depressed mood on the visual analog scale (VAS) following the sad mood induction paradigm (MIP). RESULTS: There was a significant increase in VAS depressed mood scores after the sad MIP during supplement and placebo, but no difference between active and placebo conditions. There was also a significant increase in urge-to-smoke scores after sad MIP during supplement and placebo but no difference between active and placebo conditions. Reliability of the increase in VAS after MIP was very good. CONCLUSION: The dietary supplement had negligible effect on depressed mood, but sad MIP is a very reliable method that can be applied in future studies to assess other interventions for preventing dysphoric mood during early cigarette withdrawal.
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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 | 0.001 |
| 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 | 0.001 |
| 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".