Effects of olive oil and its minor constituents on serum lipids, oxidative stress, and energy metabolism in cardiac muscle
Bibliographic record
Abstract
Recent lines of evidence suggest that the beneficial effects of olive oil are not only related to its high content of oleic acid, but also to the antioxidant potential of its polyphenols. The aim of this work was determine the effects of olive oil and its components, oleic acid and the polyphenol dihydroxyphenylethanol (DPE), on serum lipids, oxidative stress, and energy metabolism on cardiac tissue. Twenty four male Wistar rats, 200 g, were divided into the following 4 groups (n = 6): control (C), OO group that received extra-virgin olive oil (7.5 mL/kg), OA group was treated with oleic acid (3.45 mL/kg), and the DPE group that received the polyphenol DPE (7.5 mg/kg). These components were administered by gavage over 30 days, twice a week. All animals were provided with food and water ad libitum. The results show that olive oil was more effective than its isolated components in improving lipid profile, elevating high-density lipoprotein, and diminishing low-density lipoprotein cholesterol concentrations. Olive oil induced decreased antioxidant Mn-superoxide dismutase activity and diminished protein carbonyl concentration, indicating that olive oil may exert direct antioxidant effect on myocardium. DPE, considered as potential antioxidant, induced elevated aerobic metabolism, triacylglycerols, and lipid hydroperoxides concentrations in cardiac muscle, indicating that long-term intake of this polyphenol may induce its undesirable pro-oxidant activity on myocardium.
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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 | 0.000 | 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) | 0.001 | 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".