Optimized Caveolin‐1 Scaffolding Domain‐derived peptides for increasing protective nitric oxide production in vascular diseases
Bibliographic record
Abstract
Protective vascular nitric oxide (NO), a critical regulator of vascular homeostasis, is produced by endothelial NO synthase (eNOS). Our goal is to promote therapeutic endothelial NO release as a therapeutic avenue for treatment of vascular diseases characterized by decreased NO bio‐availability, which is broadly associated with increased risk of cardiovascular events, such as atherosclerosis. Normally, association of eNOS to Caveolin‐1, the coat protein of caveolae, leads to eNOS inhibition. Using glutathione‐S‐transferase pull down, we identified 10 amino acids from the Cav‐1 Scaffolding Domain (CSD), the section responsible for eNOS inhibition, which binds eNOS. When converted into a cell permeable peptide, we find that the sequence was capable of increasing eNOS dependent NO release from endothelial cells while possessing improved effects on cell morphology compared to full length CSD peptides. In conclusion, we identified a peptide sequence that may serve as the basis for a novel pharmacophore for promoting NO release, providing a new target in cardiovascular diseases, as well as provide insight into caveolae signaling. We would like to thank CIHR, MSFHR and BC Heart and Stroke for funding support.
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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".