Development of a Biocompatible Layer-by-Layer Film System Using Aptamer Technology for Smart Material Applications
Bibliographic record
Abstract
Aptamers are short, single-stranded nucleic acids that fold into well-defined three dimensional (3D) structures that allow for binding to a target molecule with affinities and specificities that can rival or in some cases exceed those of antibodies. The compatibility of aptamers with nanostructures such as thin films, in combination with their affinity, selectivity, and conformational changes upon target interaction, could set the foundation for the development of novel smart materials. In this study, the development of a biocompatible aptamer-polyelectrolyte film system was investigated using a layer-by-layer approach. Using fluorescence microscopy, we demonstrated the ability of the sulforhodamine B aptamer to bind its cognate target while sequestered in a chitosan-hyaluronan film matrix. Studies using Ultraviolet-visible (UV-Vis) spectrophotometry also suggest that deposition conditions such as rinsing time and volume play a strong role in the internal film interactions and growth mechanisms of chitosan-hyaluronan films. The continued study and development of aptamer-functionalized thin films provides endless new opportunities for novel smart materials and has the potential to revolutionize the field of controlled release.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".