DNAzyme motor systems and logic gates facilitated by toehold exchange translators
Bibliographic record
Abstract
DNAzyme motor systems using gold nanoparticles (AuNPs) as scaffolds are useful for biosensing and in situ amplification because these systems are free of protein enzymes, isothermal, homogeneous, and sensitive. However, detecting different targets using the available DNAzyme motor techniques requires redesigns of the DNAzyme motor. We report here a toehold-exchange translator and the translator-mediated DNAzyme motor systems, which enable sensitive responses to various nucleic acid targets using the same DNAzyme motor without requiring redesign. The translator is able to efficiently convert different nucleic acid targets into a specific output DNA that further activates the pre-silenced DNAzyme motor and consequently initiates the autonomous walking of the DNAzyme motor. Simply adjusting the target-binding region of the translator enables the same DNAzyme motor system to respond to various nucleic acid targets. The translator-mediated DNAzyme motor system is able to detect as low as 2.5 pM microRNA-10b and microRNA-21 under room temperature without the need of separation or washing. We further demonstrate the versatility of the translator and the DNAzyme motor by successful construction and operation of four logic gates, including OR, AND, NOR, and NAND logic gates. These logic gates use two microRNA targets as inputs and generate amplified fluorescence signals from the operation of the same DNAzyme motor. Incorporation of the toehold-exchange translator into the DNAzyme motor technology improves the biosensing applications of DNA motors to diverse nucleic acid targets.
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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 | 0.000 | 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 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".