Influence of Methylphenidate on Eating in Obese Men
Bibliographic record
Abstract
OBJECTIVE: Rapid synaptic dopamine transport or reduced brain dopamine receptor signaling may influence energy intake. Methylphenidate, a dopamine reuptake inhibitor, increases brain synaptic dopamine and produces anorexia, suggesting that it may reduce energy intake. We investigated the effects of two doses of short-acting methylphenidate on energy intake over one meal in obese adult males. RESEARCH METHODS AND PROCEDURES: Nine obese males (>85th BMI percentile) ingested a placebo or a moderate dose (0.5 mg/kg) or a high dose (1.0 mg/kg) of methylphenidate in a within-subject double-blind acute laboratory study. One hour after ingestion, pizza consumption was measured in a naturalistic laboratory setting. RESULTS: Participants reduced energy intake by 23% for the moderate dose vs. the placebo (p < 0.02), but there was no significant difference for the high dose vs. the moderate dose (p > 0.05). Participants consumed 34% fewer kilocalories after ingesting the lowest effective dose of methylphenidate compared with placebo (725.7 +/- 404.5 vs.1095 +/- 271.1 kcal, p < 0.01). Seven of nine subjects responded to the moderate dose. The increase in perceived drug effect above placebo was correlated with the reduction in energy intake for both the moderate (r = -0.85, p = 0.004) and the high (r = -0.75 p = 0.021) doses. Hunger scores were not different across drug doses or placebo before drug administration. DISCUSSION: Methylphenidate reduced energy intake of a highly palatable food over one meal by one-third in obese adult males. Dopamine transport inhibition may be an effective component of a comprehensive treatment for obesity.
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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) | 0.000 | 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) | 0.002 | 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".