Modulation of plasma N-acylethanolamine levels and physiological parameters by dietary fatty acid composition in humans
Bibliographic record
Abstract
N-Acylethanolamines (NAEs) are endogenous lipid-signaling molecules involved in satiety and energetics; however, how diet impacts circulating NAE concentrations and their downstream metabolic actions in humans remains unknown. Objectives were to examine effects of diets enriched with high-oleic canola oil (HOCO) or HOCO blended with flaxseed oil (FXCO), compared with a Western diet (WD), on plasma NAE levels and the association with energy expenditure and substrate oxidation. Using a randomized controlled crossover design, 36 hypercholesterolemic participants consumed three isoenergetic diets for 28 days, each containing 36% energy from fat, of which 70% was HOCO, FXCO, or WD. Ultra-performance liquid chromatography-MS/MS was used to measure plasma NAE levels and indirect calorimetry to assess energy expenditure and substrate oxidation. After 28 days, compared with WD, plasma oleoylethanolamide (OEA) and alpha-linolenoyl ethanolamide (ALEA) levels were significantly increased in response to HOCO and FXCO (P = 0.002, P < 0.001), respectively. Correlation analysis demonstrated an inverse association between plasma OEA levels and percent body fat (r = -0.21, P = 0.04), and a positive association was observed between the plasma arachidonoyl ethanolamide (AEA)/OEA ratio and android:gynoid fat (r = 0.23, P = 0.02), respectively. Results suggest that plasma NAE levels are upregulated via their dietary lipid substrates and may modulate regional and total fat mass through lipid-signaling mechanisms.
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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 | 0.000 |
| 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".