A multifunctional endothelial-mimetic surface: Synergistically combating thrombus formation by releasing nitric oxide, promoting fibrinolysis, and enhancing endothelialization
Bibliographic record
Abstract
Thrombus formation often leads to the failure of intravascular implants. Natural endothelium provides multifaceted antithrombotic functions through nitric oxide/ prostacyclin secretion to inhibit platelet activation, glycosaminoglycan mediated anticoagulation, and tissue-type plasminogen activator driven fibrinolysis. Therefore, surfaces mimicking these multiple endothelial functions are expected to have enhanced antithrombotic properties. In this study, polyvinyl chloride surface was rendered porous through solvent/nonsolvent-induced phase separation and loaded with a metal-organic framework, CuBTTri to catalyze nitric oxide release from a precursor. Furthermore, using layer-by-layer self-assembly, multiple bilayers of a poly(lysine- co -oligo(ethylene glycol) methyl ether methacrylate) copolymer (fibrinolysis-promoting), and sodium heparin (endothelial cell growth-promoting), were deposited on the un-etched side of the polyvinyl chloride. This modified surface was shown to be capable of releasing nitric oxide, destroying nascent thrombus, inhibiting smooth muscle cell growth, and promoting endothelial cell adhesion. This study represents a novel approach to developing multifunctional blood-contacting surfaces that mimic multiple properties of the endothelium. • A porous structure was successfully constructed on the polyvinyl chloride surface. • A metal-organic framework was loaded on the surface to catalyze nitric oxide release. • A multifunctional surface was prepared using layer-by-layer self-assembly. • The surface promoted nitric oxide release, fibrinolysis, and endothelialization. • The multifunctional surface worked synergistically without interfering with each other.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 teacher head, 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".