Adsorption of Fibrinogen and Lysozyme on Silicon Grafted with Poly(2-methacryloyloxyethyl Phosphorylcholine) via Surface-Initiated Atom Transfer Radical Polymerization
Bibliographic record
Abstract
Surfaces based on grafted poly(2-methacryloyloxyethyl phosphorylcholine) (poly(MPC)) "brushes" with a constant graft density of 0.39 chain/nm2 and chain length from 5 to 200 monomer units were prepared by surface-initiated atom transfer radical polymerization (ATRP) on silicon wafers. The chain length and layer thickness of the poly(MPC) grafts were varied via the ratio of MPC to sacrificial initiator. The surfaces were characterized by water contact angle, XPS, and AFM. The effect of poly(MPC) chain length on fibrinogen and lysozyme adsorption was studied in TBS buffer at pH 7.4. The adsorption of both proteins on the poly(MPC)-grafted surfaces was greatly reduced compared to the unmodified silicon. Adsorption decreased with increasing chain length of the poly(MPC) grafts. Grafts of chain length 200 (MW 59 000) gave adsorption levels of 7 and 2 ng/cm2, respectively, for fibrinogen and lysozyme at 1 mg/mL protein concentration, corresponding to reductions of greater than 98% compared to the unmodified silicon. Adsorption experiments using mixtures of the two proteins showed that the suppression of protein adsorption on the poly(MPC)-grafted surfaces was not strongly dependent on protein size or charge.
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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".