Dual surface modification of polydimethylsiloxane (PDMS) with antithrombin-heparin complex (ATH) and tissue plasminogen activator (t-PA) for enhanced antithrombotic activity
Bibliographic record
Abstract
Medical devices used in contact with blood trigger coagulation and activate platelets leading to thrombotic complications. To prevent these effects, systemic anticoagulants and antiplatelet agents are typically prescribed, but these agents tend to increase the risk of bleeding. Modification of the surface of the blood-contacting material is an alternative approach to the inhibition of coagulation and thrombosis. In this work, the dual surface modification of polydimethylsiloxane (PDMS) with an antithrombin-heparin complex (ATH) to inhibit coagulation, and tissue plasminogen activator (t-PA) to lyse incipient clot, was investigated. Three different modification processes were used to immobilize ATH and t-PA: sequentially, with one component followed by the other; and with both components present simultaneously. Polydopamine (PDA) was used as a "bioglue" to enhance adhesion of the modifiers. The surface hydrophilicity and roughness were found to increase with increasing extent of modification. The surface density of the modifiers and their stability in plasma were significantly influenced by the modification process. The sequential method with t-PA first followed by ATH led to increased heparin activity. Data from plasma clotting time experiments showed that the combination of ATH and t-PA provides a synergistic effect, wherein both the anticoagulant activity of ATH and the clot lysis activity of t-PA on the surface are enhanced. This dual modification approach using both an anticoagulant and a thrombolytic agent shows promise to improve the blood compatibility of PDMS. The strategy can be applied to materials other than PDMS since the PDA coating is generic, thus providing a method for improving the performance of many blood-contacting devices.
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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".