Nonbiofouling Polymer Brush with Latent Aldehyde Functionality as a Template for Protein Micropatterning
Bibliographic record
Abstract
A novel, nonfouling polymer brush, poly-N-[(2,3-dihydroxypropyl)acrylamide] (PDHPA), containing latent aldehyde groups, was synthesized by surface initiated atom transfer radical polymerization (SI-ATRP). The synthetic parameters were adjusted to produce brushes with varying graft densities and molecular weights. High-density PDHPA brushes successfully prevented the nonspecific protein adsorption from single protein solutions as well as from human platelet poor plasma. Patterns of nonfouling PDHPA and reactive PDHPA-aldehyde domains on the brush surface were created by a combination of photo and wet chemical lithography from a single homogeneous PDHPA brush. Successful micropatterning of single proteins and multiple proteins were achieved using this novel substrate. The high-density brush prevented the diffusion of large proteins into the brush, while a monolayer of covalently coupled proteins was formed on the PDHPA-aldehyde domains. Atomic force microscopy (AFM) force measurements using a biotin coupled AFM tip showed that covalently coupled streptavidin retained its activity, while PDHPA domains showed little nonspecific adsorption of streptavidin. The current study avoids tedious and complicated synthetic processes employed in conventional approaches by providing a novel approach to protein micropatterning from a single, multifunctional polymer brush.
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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".