Dietary (n-3) Fat and Cholesterol Alter Tissue Antioxidant Enzymes and Susceptibility to Oxidation in SHR and WKY Rats
Bibliographic record
Abstract
Previously, 8% fish oil blend diets, compared to butter and soybean oil blend diets, reduced specific antioxidant enzyme activities and tissue susceptibility to in vitro oxidative stress in spontaneously hypertensive (SHR) and Wistar Kyoto (WKY) rats. Moreover, high cholesterol (5.0 g/kg diet) diets protected against in vitro tissue lipid oxidation. In this study, we hypothesized that 160 g fat/kg diet as blends of (n-6) or (n-3) oils and cholesterol would alter antioxidant enzyme activities and thus increase tissue susceptibility to oxidation. The effects of diet blends of saturated (butter, B), (n-6) (soybean oil, SBO) or (n-3) (menhaden oil, MO) oils with cholesterol (0.5 or 5.0 g/kg) on systolic blood pressure (SBP), plasma lipids, antioxidant enzymes and susceptibility to oxidation were examined in SHR and WKY rats. SBP at 13 wk of age was greater (P ? 0.001) in SHR than in WKY rats, but was not affected by diets. Plasma cholesterol and triacylglycerols were decreased (P ? 0.001) by MO diets. Hepatic glutathione reductase activities were reduced (P ? 0.001) in SBO-fed SHR and enhanced in SBO- and MO-fed WKY rats. Glutathione levels were reduced (P ? 0.001) in RBC and enhanced (P ? 0.001) in livers of MO-fed rats. Lipid oxidation was enhanced (P ? 0.001) in red blood cells (RBC) from SBO groups, and hearts and livers of MO groups. High cholesterol diets reduced (P ? 0.001) susceptibility to lipid peroxidation in RBC and liver of SHR and WKY rats. Greater amounts of dietary (n-3) fat enhance tissue susceptibility to oxidation, which can be modulated by increased dietary cholesterol in SHR and WKY rats.
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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) | 0.000 | 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".