Protein‐resistant polyurethane by sequential grafting of poly(2‐hydroxyethyl methacrylate) and poly(oligo(ethylene glycol) methacrylate) via surface‐initiated ATRP
Bibliographic record
Abstract
Protein-resistant polyurethane (PU) surfaces were prepared by sequentially grafting poly(2-hydroxyethyl methacrylate) (poly(HEMA)) and poly(oligo(ethylene glycol) methacrylate) (poly(OEGMA)) via surface-initiated atom transfer radical polymerization (s-ATRP). The chain lengths of poly(HEMA) and poly(OEGMA) were regulated via the ratio of monomer to sacrificial initiator in solution. The surfaces were characterized by water contact angle and X-ray photoelectron spectroscopy (XPS). The protein resistant properties of the surfaces were assessed by single and binary adsorption experiments with fibrinogen (Fg), lysozyme (Lys), and lactalbumin (Lac). The adsorption of all three proteins on the sequentially grafted poly(HEMA)-poly(OEGMA) surfaces (PU/PH/PO) was greatly reduced compared with the unmodified PU. Adsorption decreased with increasing poly(OEGMA) chain length. On the PU/PH/PO surface with longest poly(OEGMA) chain length (∼100), the decrease in Lys adsorption was in the range of 95-98% and the decrease in Fg and Lac adsorption was >99% compared with the unmodified PU. Adsorption from binary protein solutions showed that the PU/PH/PO surfaces resisted these proteins more or less equally, that is, independent of protein size.
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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".