Oat protein modulates cholesterol metabolism and improves cardiac systolic function in high fat, high sucrose fed rats
Bibliographic record
Abstract
Oats are recognized to provide many health benefits that are mainly associated with its dietary fibre, β-glucan. However, the protein derived from oats is largely understudied with respect to its ability to maintain health and attenuate risk factors of chronic diseases. The goal of the current study was to investigate the metabolic effects of oat protein consumption in lieu of casein as the protein source in high fat, high sucrose (HF/HS) fed Wistar rats. Four-week-old rats were divided into three groups and were fed three different experimental diets: a control diet with casein as the protein source, an HF/HS diet with casein, or an HF/HS diet with oat protein for 16 weeks. Heart structure and function were determined by echocardiography. Blood pressure measurements, an oral glucose tolerance test, and markers of cholesterol metabolism, oxidative stress, inflammation, and liver and kidney damage were also performed. Our study results show that incorporation of oat protein in the diet was effective in preserving systolic heart function in HF/HS fed rats. Oat protein significantly reduced serum total and low-density lipoprotein cholesterol levels. Furthermore, oat protein normalized liver HMG-CoAR activity, which, to our knowledge, is the first time this has been reported in the literature. Therefore, our research suggests that oat protein can provide hypocholesterolemic and cardioprotective benefits in a diet-induced model of metabolic syndrome.
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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".