Fluorescence Analysis of the Properties of Structure-Switching DNA Aptamers Entrapped in Sol–Gel-Derived Silica Materials
Bibliographic record
Abstract
The entrapment of structure-switching, fluorescence-signaling DNA aptamers into sol–gel-derived materials has recently been reported as a promising platform for solid-phase aptamer-based biosensors. However, there has not yet been a detailed study of the properties of such functional nucleic acids within different sol–gel-based materials. In this work, we utilized a range of fluorescence-based assays, which were previously used to assess the properties of entrapped proteins, to evaluate the factors that affect the function of structure-switching DNA aptamers upon entrapment within polar and nonpolar sol–gel-derived materials using both bipartite and tripartite constructs of fluorescein-labeled, ATP-binding structure-switching aptamers as model systems. The steady-state and time-resolved aptamer dynamics, thermal and long-term stability, accessibility of entrapped aptamers to quenchers, degree of aptamer leaching, and overall target-binding and signaling capabilities of these entrapped aptamers were assessed relative to solution. These studies demonstrate that the ability of the aptamer complex to remain fully hybridized to its complementary dabcyl-labeled quencher strand ( Q -DNA) upon entrapment is the most important factor in terms of signaling capability. It was also observed that more polar (anionic) materials derived from sodium silicate are optimal for DNA aptamers, since these allow the entrapped aptamer to remain hybridized to its complementary strands and retain the dynamic motion needed to undergo structure switching while providing a minimum degree of leaching. Furthermore, such materials improve both the thermal melting temperature of the Q -DNA strand and the long-term stability of entrapped DNA aptamers.
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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".