A multifunctional surface for blood contact with fibrinolytic activity, ability to promote endothelial cell adhesion and inhibit smooth muscle cell adhesion
Bibliographic record
Abstract
Blood compatible materials are required for a wide variety of medical devices. Despite many years of intensive effort, however, the blood compatibility problem, in particular the ability to prevent thrombosis, remains unsolved. Based on the knowledge that the vascular endothelium, the ultimate blood contacting surface, draws on several mechanisms to maintain blood fluidity, it seems reasonable that analogous multifunctionality should be the goal for blood compatible biomaterials. In the present work, a polyurethane surface was modified with the terpolymer poly(2-hydroxyethyl methacrylate-co-6-amino-2-(2-methacylamido)-hexanoic acid-co-1-adamantan-1-ylmethyl methacrylate) (poly(HEMA-co-LysMA-co-AdaMA)), referred to as PU-PHLA. Poly(HEMA) and poly(LysMA) were intended to provide, respectively, resistance to non-specific protein adsorption and the ability to lyse incipient clots. The heparin-like moiety, sulfonated β-cyclodextrin was immobilized on the PU-PHLA via host-guest interactions with the poly(AdaMA). This component is expected to inhibit coagulation and smooth muscle cell proliferation and to promote endothelialization. The resulting materials were shown to have multifunctionalities including fibrinolytic activity, anticoagulant activity and the ability to promote endothelial cell adhesion and inhibit smooth muscle cell adhesion. This work provides a new strategy for the development of multifunctional, endothelial-mimicking, biomaterials for blood contacting 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) | 0.000 | 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".