Preparation of Functional Aptamer Films Using Layer-by-Layer Self-Assembly
Bibliographic record
Abstract
Advances in many aptamer-based applications will require a better understanding of how an aptamer's molecular recognition ability is affected by its incorporation into a suitable matrix. In this study, we investigated whether a model aptamer system, the sulforhodamine B aptamer, would retain its binding ability while embedded in a multilayer polyelectrolyte film. Thin films consisting of poly(diallyldimethylammonium chloride) as the polycation and both poly(sodium 4-styrene-sulfonate) and the aptamer as the polyanions were deposited by the layer-by-layer approach and were compared to films prepared using calf thymus DNA or a random single-stranded oligonucleotide. Data from UV-vis spectroscopy, quartz crystal microbalance studies, confocal microscopy, and time of flight secondary ion mass spectrometry confirm that the aptamer's recognition of its target is retained, with no loss of specificity and only a modest reduction of binding affinity, while it is incorporated within the thin film. These findings open up a raft of new opportunities for the development and application of aptamer-based functional thin films.
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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 | 0.000 |
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".