Dietary flax oil reduces renal injury, oxidized LDL content, and tissue n−6/n−3 FA ratio in experimental polycystic kidney disease
Bibliographic record
Abstract
As whole flaxseed is beneficial in the treatment of experimental renal disease, we undertook a study to determine whether previously documented benefits of whole flaxseed could be reproduced with dietary low-lignan flax oil (FO), a rich source of alpha-linolenic acid, in experimental polycystic kidney disease. Male offspring of Han:SPRD-cy heterozygous rats were fed a synthetic diet containing FO or corn oil (CO) for 8 wk from the time of weaning. Renal inflammation, fibrosis, proliferation, cystic change, and oxidized-LDL were assessed morphometrically. Hepatic and renal lipid composition was assessed using GC. FO feeding produced hepatic and renal enrichment of n-3 PUFA and an increase in C18:>C18 PUFA ratios (18-carbon PUFA compared to longer-chain PUFA), with a reduction in proportion of hepatic long-chain PUFA. The FO-based diet was associated with lower mean cystic change by 29.7% (P = 0.018), fibrosis by 21.7% (P = 0.017), macrophage infiltration by 31.5% (P < 0.0001), epithelial proliferation by 18.7% (P = 0.0035), and ox-LDL detection by 31.4% (P < 0.0001) in Han:SPRD-cy heterozygotes. Serum creatinine was significantly lower in FO-fed diseased animals. A small hypocholesterolemic effect was noted in all animals fed FO. FO feeding moderates renal injury, modifies the profile of substrates available for elongation to eicosanoid precursors, and inhibits the elongation of C18 PUFA in this model. The consumption of FO-based products may prove a more practical way of obtaining health benefit than attempts to increase dietary content of unrefined seed.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".