Parts-per-Million of Polyethylene Glycol as a Non-Interfering Blocking Agent for Homogeneous Biosensor Development
Bibliographic record
Abstract
Many homogeneous assays are complicated by the adsorption of probe molecules by the surface of reaction vessels, which are often made of polypropylene or polystyrene-based plastics. To solve this problem, many protein and surfactant-based blocking agents are used. However, these blockers may interfere with intended assays by sequestering transition-metal ions, inducing protein denaturing, generating air bubbles or making pores in membranes. Coating surfaces with polyethylene glycol (PEG) through covalent linkages has been proven to be an effective method to minimize protein adsorption. However, this method is more difficult to apply on plastic surfaces and is quite expensive. While unmodified PEG is often considered as a nonadsorbing polymer, in this Technical Note, we report that PEG at very low concentration (ppm level) can still effectively block plastic surfaces. This method works for DNA, protein, and liposome-based assays as long as the molecular weight of PEG is greater than 2000. PEG works because of multivalent hydrophobic interaction from its repeating methylene units. This Technical Note will not only facilitate biosensor development, but also enhance our understanding of the interaction between various molecules and plastic surfaces.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.006 |
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".