Regulation of inflammation by cannabinoids, the endocannabinoids 2-arachidonoyl-glycerol and arachidonoyl-ethanolamide, and their metabolites
Bibliographic record
Abstract
2-Arachidonoyl-glycerol (2-AG) and arachidonyl-ethanolamide (AEA) are endocannabinoids that have been implicated in many physiologic disorders, including obesity, metabolic syndromes, hepatic diseases, pain, neurologic disorders, and inflammation. Their immunomodulatory effects are numerous and are not always mediated by cannabinoid receptors, reflecting the presence of an arachidonic acid (AA) molecule in their structure, the latter being the precursor of numerous bioactive lipids that are pro- or anti-inflammatory. 2-AG and AEA can thus serve as a source of AA but can also be metabolized by most eicosanoid biosynthetic enzymes, yielding additional lipids. In this regard, enhancing endocannabinoid levels by using endocannabinoid hydrolysis inhibitors is likely to augment the levels of these lipids that could regulate inflammatory cell functions. This review summarizes the metabolic pathways involved in the biosynthesis and metabolism of AEA and 2-AG, as well as the biologic effects of the 2-AG and AEA lipidomes in the regulation of inflammation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".