Enhanced Long-term Antithrombogenicity Instigated by Covalently-Attached Surface Modifier on Biomedical Polymers
Bibliographic record
Abstract
During a variety of medical procedures such as renal dialysis, bypass surgery, and lung transplantation patient blood is exposed to the surface of a number of polymeric materials such as polycarbonate (PC), poly (vinyl chloride) (PVC) and polysulfone (PS) for a period up to several days. Such exposure may result in undesirable protein-material interactions that can potentially trigger deleterious biological processes including thrombosis, which may be responsible for other complications such as cognitive disability. In order to address this issue, we have further examined the behavior of an ultrathin antifouling and antithrombogenic coating based on monoethylene glycol silane surface chemistry. Samples of polymeric substrates were exposed to blood flow at a shear rate of ~20 s-1 for time periods of 3 and 6 hours, as well as 3 days. No additional anticoagulant chemistry was applied in the experiments. For all time periods, platelet adhesion, aggregation, and thrombus formation on the coated surfaces was inhibited compared to bare substrates (coated PC performing the best, followed by PVC-, and then PS-coated), strongly supporting the results of previous research conducted over far shorter blood contact times.
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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".