Oral Docosapentaenoic Acid (22:5n‐3) Is Differentially Incorporated into Phospholipid Pools and Differentially Metabolized to Eicosapentaenoic Acid in Tissues from Young Rats
Bibliographic record
Abstract
The present study assessed the effect of oral supplementation with docosapentaenoic acid (DPA, 22:5n-3) on the levels of serum and tissue lipid classes and their fatty acid compositions including individual phospholipid types in rat liver, heart, and kidney. Sprague-Dawley rats received daily oral gavage over 10 days as corn oil without (controls) or with purified DPA in free fatty acid form (21.2 mg/day). The DPA group exhibited significantly lower serum lipid concentrations. The concentrations in μmol/100 g serum or μmol/g tissue of DPA in the total lipid (TL) were higher by 2.3-, 2.4-, 10.9-, and 5.1-fold in the DPA group of serum, liver, heart, and kidney, respectively, with the phospholipids (PL) being the major DPA reservoir (45.2-52.1% of the DPA in the TL). No significant differences in DHA (22:6n-3) amounts in TL appeared. The highest relative mol% values as DPA were in heart tissue (means of 11.1% in PL and 16.2% in phosphatidylinositol) and lowest in kidney. The EPA (20:5n-3) concentrations were markedly higher in the DPA group and most pronounced in the kidney (5.1 times higher in the TL as compared to controls) relative to liver and heart yielding an estimated apparent % conversion of DPA to EPA of 67% and EPA:DPA ratios reaching 5.74 in kidney phosphatidylethanolamine. The serum lipid-lowering potential of dietary DPA and its impact in the kidney with the derived EPA warrants investigation.
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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".