Smart Materials Based on DNA Aptamers: Taking Aptasensing to the Next Level
Bibliographic record
Abstract
"Smart" materials are an emerging category of multifunctional materials with physical or chemical properties that can be controllably altered in response to an external stimulus. By combining the standard properties of the advanced material with the unique ability to recognize and adapt in response to a change in their environment, these materials are finding applications in areas such as sensing and drug delivery. While the majority of these materials are responsive to physical or chemical changes, a particularly exciting area of research seeks to develop smart materials that are sensitive to specific molecular or biomolecular stimuli. These systems require the integration of a molecular recognition probe specific to the target molecule of interest. The ease of synthesis and labeling, low cost, and stability of DNA aptamers make them uniquely suited to effectively serve as molecular recognition probes in novel smart material systems. This review will highlight current work in the area of aptamer-based smart materials and prospects for their future applications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 teacher head, 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".