The effects of vitamin E and selenium intake on oxidative stress and plasma lipids in hamsters fed fish oil
Bibliographic record
Abstract
The aim of the present work was to test the effects of large-dose supplementation of vitamin E (Vit E) and selenium (Se), either singly or in combination, on fish oil (FO)-induced tissue lipid peroxidation and hyperlipidemia. The supplementation of Se has been shown to lower blood cholesterol and increase tissue concentrations of the antioxidant glutathione (GSH); however, the effects of Se supplementation, either alone or in combination with supplemental Vit E, on FO-induced oxidative stress and hyperlipidemia have not been studied. Male Syrian hamsters received FO-based diets that contained 14.3 wt% fat and 0.46 wt% cholesterol supplemented with Vit E (129 IU D-alpha-tocopheryl acetate/kg diet) and/or Se (3.4 ppm as sodium selenate) or that contained basal requirements of both nutrients. The cardiac tissue of hamsters fed supplemental Se showed increased concentrations of lipid hydroperoxides (LPO) but decreased oxidized glutathione (GSSG) concentrations. The higher concentrations of LPO in the hearts of Se-supplemented hamsters were not lowered with concurrent Vit E supplementation. In the liver, Se supplementation was associated with higher Se-dependent glutathione peroxidase activity and an increase in the GSH/GSSG ratio, whereas a lower hepatic non-Se-dependent glutathione peroxidase activity was seen with Vit E supplementation. Supplemental intake of Se was associated with lower plasma concentrations of total cholesterol and low density lipoprotein cholesterol plus very low density lipoprotein cholesterol. In view of the pro-oxidative effects of Se supplementation on cardiac tissue, a cautionary approach needs to be taken regarding the plasma lipid-lowering properties of supplemental Se.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".