Engineering DNA aptamers and DNA enzymes with fluorescence-signaling properties
Bibliographic record
Abstract
Abstract Single-stranded DNA molecules with ligand-binding ability and catalytic function, referred to as DNA aptamers and DNA enzymes, respectively, are special DNA sequences isolated from random-sequence DNA libraries by “in vitro selection”. These two new classes of artificial DNA molecules have the potential of being used as molecular tools in a variety of innovative applications ranging from biosensing to gene regulation. Our laboratory is interested in engineering fluorescence-signaling DNA aptamers and DNA enzymes that can be widely exploited for detection-directed applications. In this article, we will first discuss our recent efforts on the rational design of a new class of signaling aptamers denoted “structure- switching signaling aptamers”, which report target binding by switching structures from DNA/DNA duplex to DNA/target complex. We will then describe the in vitro selection of fluorescence-signaling DNA enzymes that exhibit a synchronized catalysis-signaling capability by cleaving a chimeric RNA/DNA substrate at the lone RNA linkage surrounded by closely spaced fluorophore-quencher pair. Potential utilities of these signaling DNA molecules will also be discussed.
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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".