The effects of acute alcohol administration on circulating endocannabinoid levels in humans
Bibliographic record
Abstract
Several lines of evidence suggest that endocannabinoid signalling may influence alcohol consumption. Preclinical studies have found that pharmacological blockade of cannabinoid receptor 1 leads to reductions in alcohol intake. Furthermore, variations in endocannabinoid metabolism between individuals may be associated with the presence and severity of alcohol use disorder. However, little is known about the acute effects of alcohol on the endocannabinoid system in humans. In this study, we evaluated the effect of acute alcohol administration on circulating endocannabinoid levels by analysing data from two highly-controlled alcohol administration experiments. In the first within-subjects experiment, 47 healthy participants were randomized to receive alcohol and placebo in a counterbalanced order. Alcohol was administered using an intravenous clamping procedure such that each participant attained a nearly identical breath alcohol concentration of 0.05%, maintained over 3 h. In the second experiment, 23 healthy participants self-administered alcohol intravenously; participants had control over their exposure throughout the paradigm. In both experiments, circulating concentrations of two endocannabinoids, N-arachidonoylethanolamine (AEA) and 2-arachidonoylglycerol (2-AG), were measured at baseline and following alcohol exposure. During the intravenous clamping procedure, acute alcohol administration reduced circulating AEA but not 2-AG levels when compared to placebo. This finding was confirmed in the self-administration paradigm, where alcohol reduced AEA levels in an exposure-dependent manner. Future studies should seek to determine whether alcohol administration has similar effects on brain endocannabinoid signalling. An improved understanding of the bidirectional relationship between endocannabinoid signalling and alcohol intake may deepen our understanding of the aetiology and repercussions of alcohol use disorder.
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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) | 0.001 | 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".