Surface properties of PEO–silicone composites: reducing protein adsorption
Bibliographic record
Abstract
Silicone-based polymers with reduced protein adsorption were successfully prepared by incorporating mono- or bifunctional poly(ethylene oxide) (PEO) derivatives, respectively, into PDMS during rubber formation using classic room temperature vulcanization chemistry. Characterization of the films by water contact-angle measurements and XPS showed that the PEO was present on the film surface, with greater amounts of PEO at the interface modified with monofunctional PEO. Scanning electron microscopy showed the PEO domains segregated into regular zigzag patterns on the PEO-modified surfaces. Significant reductions in the adsorption of fibrinogen, albumin and lysozyme were observed on both PEO-modified surfaces, although the monofunctional PEO surfaces performed much better in this regard. The reductions in protein adsorption were comparable for all three proteins on both surfaces, suggesting that molecular mass of the protein is not a significant factor in determining the magnitude of protein deposition. Western blot studies showed that the adsorption of proteins from plasma to the monofunctional PEO-modified surfaces was also significantly reduced and surprisingly selective, with very few bands noted relative to the control surfaces and those modified with bifunctional PEO.
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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".