Hemocompatible polyurethane surfaces
Bibliographic record
Abstract
With the aim of improving the hemocompatibility of blood‐contacting devices, antithrombotic or fibrinolytic biological molecules‐containing polyurethane (PU) materials have been developed. Cationic PU surfaces were prepared by grafting poly(dimethylaminoethyl methacrylate) and quaternizing the tertiary amino groups with iodomethane. The surfaces were characterized by water contact angles and X‐ray photoelectron spectroscopy. The materials (PU‐CH3I) were treated with antithrombotic or fibrinolytic drugs, such as hirudin or tissue plasminogen activator (tPA) in Tris‐buffered saline (pH 9.0) to yield hirudin‐loaded or tPA‐loaded PU surfaces. The hirudin and tPA quantity of the surfaces was observed using a radiolabeling method. The quantities of hirudin and tPA taken up by the cationic surfaces were significantly greater than those on the unmodified PU: approximately 200‐fold greater for hirudin and 10‐fold for tPA. The release of the bound hirudin and tPA from the materials in contact with plasma was slow, and at 48 h, ~78% of the initial hirudin and ~26% of the initial tPA remained bound. The activity of the bound hirudin and tPA, as measured by a plasma recalcification assay, was largely preserved. This approach may have potential for the development of surfaces having antithrombotic or fibrinolytic properties. Copyright © 2011 John Wiley & Sons, Ltd.
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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) | 0.004 | 0.001 |
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".