Stabilizing Structure-Switching Signaling RNA Aptamers by Entrapment in Sol–Gel Derived Materials for Solid-Phase Assays
Bibliographic record
Abstract
Structure-switching, fluorescence-signaling DNA and RNA aptamers have been reported as highly versatile molecular recognition elements for biosensor development. While structure-switching DNA aptamers have been utilized for solid-phase sensing, equivalent RNA aptamers have yet to be successfully utilized in solid-phase sensors due to their lack of chemical stability and susceptibility to nuclease attack. In this study, we examined entrapment into sol-gel derived organic-inorganic composite materials as a platform for immobilization of structure-switching fluorescence-signaling RNA aptamer reporters, using both the synthetic theophylline- and naturally occurring thiamine pyrophosphate-binding RNA aptamers as test cases. Structure-switching versions of both aptamers were entrapped into a series of sol-gel derived composites, ranging from highly polar silica to hydrophobic methylsilsesquioxane-based materials, and the target-binding and signaling capabilities of these immobilized aptamers were assessed relative to solution. Both immobilized aptamers demonstrated sensitivity and selectivity similar to that of free aptamers when entrapped in a composite material derived from 40% (v/v) methyltrimethoxysilane/tetramethoxysilane. Importantly, this material also conferred protection from nuclease degradation and imparted long-term chemical stability to the RNA reporter systems. Given the versatility of sol-gel entrapment for development of biosensors, microarrays, bioaffinity columns, and other devices, this entrapment method should provide a useful platform for numerous solid-phase RNA aptamer-based devices.
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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) | 0.000 | 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".