Rapeseed protein-derived peptides, LY, RALP, and GHS, modulates key enzymes and intermediate products of renin–angiotensin system pathway in spontaneously hypertensive rat
Bibliographic record
Abstract
Rapeseed proteins are a rich source of bioactive peptides. LY, RALP and GHS were previously identified from rapeseed protein hydrolysates as potent ACE and renin inhibiting peptides. In this study, the rapeseed peptides were individually evaluated for their molecular mechanisms and regulatory effects on components of the renin-angiotensin system in spontaneously hypertensive rats (SHR), including the mRNA and/or protein levels of angiotensin-converting enzyme (ACE), renin, ACE2, angiotensin II and angiotensin-(1-7) in myocardial tissues. Oral administration of 30 mg peptides/kg body weight every 2 days for five weeks significantly decreased the systolic blood pressure and the myocardial mRNA and protein levels of ACE and renin in SHR. LY, RALP and GHS also increased the expression of ACE2, angiotensin-(1-7) and Mas receptor levels, which may have mediated their antihypertensive activity. Dipeptide LY also inhibited angiotensin II protein expression in the heart tissue. Taken together, the finding demonstrates the multi-target physiological effects of the rapeseed peptides, beyond ACE and renin inhibition, which enhances knowledge of the antihypertensive mechanisms of food protein-derived peptides.
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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 | 0.001 |
| 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".