Anti-obesity effects of Oleoylethanolamide: Modulation of mitochondrial bioenergetics, endocannabinoidome and gut microbiome
Bibliographic record
Abstract
The endocannabinoidome (eCBome) and gut microbiome play key roles in metabolism and obesity, and oleoylethanolamide (OEA), a lipid mediator within the eCBome, is known to reduce food intake and promote fat oxidation. This study investigated the effects of OEA administration on mice with diet-induced obesity, focusing on hepatic inflammation and mitochondrial function, the endocannabinoidome (eCBome), and the gut microbiome. Mice fed standard (STD) or high-fat (HFD) diets for 18 weeks were treated with either vehicle or OEA. Metabolic, inflammatory, oxidative stress and mitochondrial parameters were assessed, along with intestinal and hepatic levels of eCBome lipids and fecal microbiota and short chain fatty acid composition. In HFD-fed mice, OEA decreased body weight, food intake, and serum and liver inflammatory markers, limiting hepatic and body fat accumulation. OEA improved liver mitochondrial oxidative capacity, lipid metabolism and oxidative stress. It reduced intestinal levels of the endocannabinoid 2-arachidonoylglycerol. Effects on microbiota composition were mostly found in the STD-fed group. However, OEA increased the relative abundance of Akkermansia muciniphila more strongly in HFD-fed mice. These findings suggest that OEA may help counteract obesity-related metabolic dysfunction and inflammation, and gut microbiota unbalance, thus representing a promising candidate for future therapeutic strategies.
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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) | 0.000 | 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 | 0.001 |
| 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".