Development of a Polyester Coating Combining Antithrombogenic and Cell Adhesive Properties: Influence of Sequence and Surface Density of Adhesion Peptides
Bibliographic record
Abstract
Biofunctionalization strategies have been developed to improve small-diameter vascular grafts. However, a fully successful coating featuring antithrombogenic properties while allowing for endothelialization has not been achieved yet. In this report, we explored the combination of low-fouling polyethylene glycol (PEG) and adhesion peptides, namely, RGD, YIGSR, and REDV, grafted on top of polyvinylamine (PVAm)-coated polyester. The peptides were grafted over a wide range of density (ca. 20-2000 pmol/cm(2)) on top of a dense PEG underlayer. The coating performances were assessed through HUVEC adhesion, platelet attachment, and protein adsorption, which were all drastically diminished on PEG-coated samples. RGD exhibited the expected high adhesive properties, toward both HUVEC and platelets. REDV had no effect neither on platelet attachment, as expected, nor on HUVEC adhesion, in contrast with previous reports. YIGSR was the most promising sequence even though its combination with other agents should be explored to further decrease thrombogenicity for vascular graft applications.
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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) | 0.001 | 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) | 0.000 | 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".