Effects of dietary n-3 or n-6 fatty acids on interleukin-1β-induced anxiety, stress, and inflammatory responses in rats
Bibliographic record
Abstract
The present study demonstrated that an omega (n)-3 fatty acid, ethyl-eicosapentaenoic acid (ethyl-EPA), supplemented diet significantly attenuated the stress/anxiety behavior of rats in the "open field" and elevated plus maze, which was induced by subchronic intracerebroventricular administration of proinflammatory cytokine interleukin (IL)-1beta. Ethyl-EPA also reduced the rise in serum corticosterone induced by IL-1. The n-6 fatty acid ethyl-gamma-linolenic acid (ethyl-GLA) had little effect on the IL-1-induced changes in behavior and the corticosterone concentration. Following IL-1beta administration, ethyl-EPA reduced the elevated prostaglandin (PG) E2 secretion and increased the secretion of antiinflammatory cytokine IL-10 from whole blood cells. Ethyl-GLA showed a similar antiinflammatory effect to ethyl-EPA. By contrast, n-6 fatty acid arachidonic acid (AA) had no effect on the behavior, immune, and endocrine changes induced by IL-1. AA alone enhanced the basal inflammatory response, raised serum corticosterone concentrations, and induced anxiety behavior in the elevated plus maze. The reduced growth rates of rats following the administration of IL-1 was attenuated by ethyl-EPA, and to a greater extent by ethyl-EPA plus ethyl-GLA, but not by AA alone or in combination with ethyl-EPA. Thus, ethyl-EPA would appear to antagonise the endocrine, immune, and behavioral effects of subchronic IL-1 administration. Ethyl-GLA only antagonised IL-1-induced inflammatory changes, whereas AA caused an increase in the secretion of corticosterone and PGE2, and induced anxiety-like behavior without enhancing the effects of IL-1.
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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 | 0.000 | 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".