Oxylipin profiles and levels vary by skeletal muscle type, dietary fat and sex in young rats
Bibliographic record
Abstract
Polyunsaturated fatty acids (PUFA)-derived bioactive lipid mediators called oxylipins have been shown to influence muscle growth, inflammation and repair in select muscles. Since individual oxylipins have varying effects and potencies, broad profiling in differing muscle types is required to further understand their overall effects. In addition, diet and sex are key determinants of oxylipin levels. Therefore, to provide comprehensive data on oxylipin profiles in rat soleus (SO), red gastrocnemius (RG), and white gastrocnemius (WG) muscles, female and male weanling Sprague–Dawley rats were provided control or experimental diets enriched in n-3 (ω-3) or n-6 (ω-6) PUFA for 6 weeks. Free oxylipin analysis by HPLC/MS/MS revealed that SO muscle had 25% more oxylipins and 4–13 times greater oxylipin mass than WG muscle. Dietary n-3 PUFA (α-linolenic acid, eicosapentaenoic acid, and docosahexaenoic acid) each increased n-3 oxylipins derived directly from their precursors and several that were not direct precursors, while reducing arachidonic acid derived oxylipins. Dietary linoleic acid had few effects on oxylipins. Oxylipins with a sex effect were higher in females in SO and RG. Oxylipins generally reflected the effects of diet and sex on PUFA, but there were exceptions. These fundamental oxylipin profile data provide groundwork knowledge and context for future research on muscle oxylipin functions. Novelty: Rat SO compared with RG and WG muscles have a higher number and greater mass of oxylipins. Oxylipins generally reflect diet effects on PUFA in all muscles, but there are notable exceptions. Oxylipins in SO and RG are higher in females.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".