Dietary n‐3 fatty acids alter lipid profile in allograft heart tissues in rats
Bibliographic record
Abstract
This study investigated the influence of dietary n‐3 polyunsaturated fatty acids on lipid metabolism in native and allograft hearts. Cardiac allografts were produced through abdominal heterotopic cardiac transplantation in rats by using male Fischer and Lewis rats being donors and recipients, respectively. After surgery animals were randomly assigned into one of the 3 groups fed a PicoLab rat chow supplemented with safflower oil (control, 5% w/w), flaxseed oil (5% w/w) or fish oil (2%, w/w) and received cyclosporine (1.5 mg/kg/d). Native and graft hearts were collected for lipid analysis after 12 weeks. Graft hearts showed significant increases in the levels of TG (p<0.0001) and MG (p<0.05), but decrease in FFA, Chol, and PL in comparison to native hearts. The increase of TG and MG was much higher in graft hearts from rats fed the fish oil diet. The incorporation of dietary PUFA into PL was significantly lower in graft hearts compared to native hearts. Animals fed fish oil diet significantly increased 22:6n‐3 levels, in both native and graft heart in PL in comparison to rats fed the control and flax diet. These results show that abnormal lipid metabolism occurs in heart after heart transplantation. Dietary n‐3 fatty acids influence the lipid profile and fatty acid compositions in graft hearts implying therapeutic strategies for post‐transplantation care. (supported by NSERC & HSF).
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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".