Fatty acid ethanolamides modulate CD36-mRNA through dietary fatty acid manipulation in Syrian Golden hamsters
Bibliographic record
Abstract
Fatty acids convert to fatty acid ethanolamides which associate with lipid signalling, fat oxidation, and energy balance; however, the extent to which dietary fatty acids manipulation can impact such control processes through fatty acid ethanolamides-related mechanisms remains understudied. The objective was to examine the impact of diets containing 6% corn oil, high oleic canola oil, docosahexaenoic acid + high oleic canola oil, and fish oil on plasma and organ levels of fatty acid ethanolamides, peroxisome proliferator-activated receptor-α regulatory targets, and lipid metabolism in Syrian Golden hamsters. After 29 days, in plasma, animals that were fed fish oil showed greater (p < 0.05) oleoylethanolamide and lower (p < 0.05) arachidonoylethanolamide and palmitoylethanolamide levels compared with other groups, while animals fed canola oil showed higher (p < 0.05) oleoylethanolamide levels in proximal intestine and liver than groups that were fed coin oil and fish oil. The canola oil group showed elevated (p < 0.01) fat oxidation (%) and over 3.0-fold higher (p < 0.05) hepatic-CD36 expression compared with the corn oil group. Hepatic-lipogenesis was lower (p < 0.05) in hamsters that were fed DHA-canola oil compared with the corn oil group. To conclude, dietary fatty acids produced shifts in plasma and organ levels of arachidonoylethanolamide, oleoylethanolamide, and palmitoylethanolamid, which were accompanied by changes in gene expression, lipogenesis, and energy expenditure, suggesting mechanisms through which dietary fatty acids influence disease risk.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".