Poly(oligoethylene glycol methacrylate) Dip-Coating: Turning Cellulose Paper into a Protein-Repellent Platform for Biosensors
Bibliographic record
Abstract
The passivation of nonspecific protein adsorption to paper is a major barrier to the use of paper as a platform for microfluidic bioassays. Herein we describe a simple, scalable protocol based on adsorption and cross-linking of poly(oligoethylene glycol methacrylate) (POEGMA) derivatives that reduces nonspecific adsorption of a range of proteins to filter paper by at least 1 order of magnitude without significantly changing the fiber morphology or paper macroporosity. A lateral-flow test strip coated with POEGMA facilitates effective protein transport while also confining the colorimetric reporting signal for easier detection, giving improved performance relative to bovine serum albumin (BSA)-blocked paper. Enzyme-linked immunosorbent assays based on POEGMA-coated paper also achieve lower blank values, higher sensitivities, and lower detection limits relative to ones based on paper blocked with BSA or skim milk. We anticipate that POEGMA-coated paper can function as a platform for the design of portable, disposable, and low-cost paper-based biosensors.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".