Rapid de-esterification and loss of eicosapentaenoic acid from rat brain phospholipids: an intracerebroventricular study
Bibliographic record
Abstract
Eicosapentaenoic acid (EPA, 20:5n-3) is being explored as a therapy in neurological diseases and disorders. Although it is known that palmitate is the most abundant fatty acid in the brain while EPA is one of the lowest, the mechanism by which the brain maintains this balance is unclear. Therefore, to trace the metabolism of these fatty acids in the brain, (14) C-palmitate or (14) C-EPA was administered via intracerebroventricular infusion to rats. From 4 to 128 days post-infusion, brains were collected after head-focused, high-energy microwave irradiation for biochemical analysis. At day 4 post-infusion, 57% (82 ± 26 nCi) of the total phospholipid radioactivity in (14) C-palmitate-infused brains was intact palmitate; whereas in (14) C-EPA-infused brains, 9% (2 ± 0.9 nCi) of the radioactivity was intact EPA. The half-life of esterified (14) C-palmitate and (14) C-EPA was 32 ± 4 (2% loss per day) and 5 ± 0.2 days (14% loss per day), respectively. Radioactivity was also detected in other saturates, monounsaturates, and cholesterol, suggesting that the infused radiolabeled fatty acids were β-oxidized. In conclusion, the low concentration of EPA in brain phospholipids may be the result of extensive metabolism of EPA, in part by β-oxidation, upon entry into the brain and upon de-esterification from phospholipids.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".