The Brain Oxylipin Profile Is Resistant to Modulation by Dietary n‐6 and n‐3 Polyunsaturated Fatty Acids in Male and Female Rats
Bibliographic record
Abstract
Oxylipins are bioactive lipids formed by the monooxygenation of polyunsaturated fatty acids (PUFA). Eicosanoids derived from arachidonic acid (ARA) are the most well-studied class of oxylipins that influence brain functions in normal health and in disease. However, comprehensive profiling of brain oxylipins from other PUFA with differing functions, and the examination of the effects of dietary PUFA and sex differences in oxylipins are warranted. Therefore, female and male Sprague-Dawley rats were provided standard rodent diets that provided additional levels of the individual n-3 PUFA α-linolenic acid (ALA), eicosapentaenoic acid (EPA) or docosahexaenoic acid (DHA), or the n-6 PUFA linoleic acid (LNA) alone or with ALA (LNA + ALA) compared to essential fatty acid-sufficient control diets. Oxylipins and PUFA were quantified in whole brains using HPLC-MS/MS and GC, respectively. Eighty-seven oxylipins were present at quantifiable levels: 51% and 17% of these were derived from ARA and DHA, respectively. At the mass level, ARA and DHA oxylipins comprised 81-90% and 6-12% of total oxylipins, while phospholipid ARA and DHA represented 25-35% and 49-62% of PUFA mass, respectively. Increasing dietary n-3 PUFA resulted in higher levels of oxylipins derived from their precursor PUFA; otherwise, the brain oxylipin profile was largely resistant to modulation by diet. Approximately 25% of oxylipins were higher in males, and this was largely unaffected by diet, further revealing a tight regulation of brain oxylipin levels. These fundamental data on brain oxylipin composition, diet effects, and sex differences will help guide future studies examining the functions of oxylipins in the brain.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".