Clinical Efficacy and Biological Regulations of ω–3 PUFA-Derived Endocannabinoids in Major Depressive Disorder
Bibliographic record
Abstract
BACKGROUND: Endocannabinoids (ECs) are one type of bioactive endogenous neuroinflammatory mediator derived from polyunsaturated fatty acids (PUFAs), which may regulate the emotional processes. Here, we assessed the effect of ω-3 PUFAs on EC levels, which may be the novel targets for the ω-3 PUFAs' antidepressive effects. METHODS: We conducted a 12-week double-blind, nonplacebo, randomized controlled trial. Eighty-eight major depressive disorder (MDD) participants were randomly assigned to receive eicosapentaenoic acid (EPA, 3.0 g/day), docosahexaenoic acid (DHA, 1.4 g/day), or a combination of EPA (1.5 g/d) and DHA (0.7 g/day). Eighty-five participants completed the trial, and their clinical remission and plasma PUFA-derived EC levels (pmol/mL) were measured. RESULTS: The cumulative rates of clinical remission were significantly higher in the EPA and EPA + DHA groups than the DHA group (51.85 and 53.84 vs. 34.37%; p =0.027 and p =0.024, respectively). EPA and EPA + DHA treatments increased the eicosapentaenoylethanolamide (EPEA) levels compared to DHA treatment (0.33 ± 0.18 and 0.35 ± 0.24 vs. 0.08 ± 0.12; p =0.002 and p =0.001, respectively), while EPA + DHA treatment increased the docosahexaenoylethanolamide levels more than EPA treatment (1.34 ± 2.09 vs. 0.01 ± 1.79; p =0.006). Plasma EPEA levels were positively correlated with rates of clinical remission (hazard ratio: 1.60, 95% confidence interval: 1.08-2.39). CONCLUSIONS: Treatments enriched with EPA increased plasma EPEA levels, which was positively associated with clinical remission. This finding may suggest that levels of plasma EPEA play a potential novel endogenous therapeutic target in MDD.
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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 | 0.001 | 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) | 0.001 | 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".