Spent Hen Muscle Protein-Derived RAS Regulating Peptides Show Antioxidant Activity in Vascular Cells
Bibliographic record
Abstract
Spent hens are egg-laying hens reaching the end of their egg-laying cycles, being a major byproduct of the egg industry. Recent studies have been focusing on finding new value-added uses for spent hens. We have previously identified four bioactive peptides from spent hen muscle proteins, including three angiotensin-converting enzyme (ACE) inhibitory (ACEi) peptides (VRP, LKY, and VRY), and one ACE2 upregulating (ACE2u) peptide (VVHPKESF (V-F)). In the current study, we further assessed their antioxidant and cytoprotective activities in two vascular cell lines—vascular smooth muscle A7r5 cells (VSMCs) and endothelial EA.hy926 cells (ECs)—upon stimulation by tumor necrosis factor alpha (TNFα) and angiotensin (Ang) II, respectively. The results from our study revealed that all four peptides attenuated oxidative stress in both cells. None of the investigated peptides altered the expression of TNFα receptors in ECs; however, VRY and V-F downregulated Ang II type 1 receptor (AT1R), while V-F upregulated the Mas receptor (MasR) in VSMCs. Further, we found that the antioxidant effects of VRP, LKY, and VRY were likely through acting as direct radical scavengers, while that of V-F was at least partially ascribed to increased endogenous antioxidant enzymes (GPx4 and SOD2) in both cells. Besides, as an ACE2u peptide, V-F exerted antioxidant effect in a MasR-dependent manner, indicating a possible involvement of the upregulated ACE2-MasR axis underlying its antioxidant action. The antioxidant activities of VRP, LKY, VRY, and V-F in vascular cells indicated their multifunctional properties, in addition to their ACEi or ACE2u activity, which supports their potential use as functional food ingredients against hypertension.
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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".