(Invited) Designed DNA Nano-Switches As Sensitive Electrochemical Biosensors
Bibliographic record
Abstract
Functional nucleic acid receptors (aptamers) have emerged as effective and robust recognition elements for state-of-the-art biosensors. Analytical readouts from aptamer-based biosensors (whether optical, electrochemical, or otherwise) derive primarily from global-scale conformational changes induced in the aptamer domain by analyte binding. Herein, we describe a unique biosensor design principle that represents a distinct alternative to this paradigm; particularly we demonstrate the ready applicability of this design principle in the de novo creation of electrochemical sensors for a clinical analyte of current interest. The function of the class of biosensors we describe, termed “DNA nano-switches”, is designed to depend on the integrity of duplex DNA-mediated charge transfer between an electrode and a redox label. [1] Thomas, J. M.; Chakraborty, B.; Sen, D.; Yu, H.-Z. J. Am. Chem. Soc. 2012, 134, 13823–13833. [2] Tang, Y.; Ge, B.; Sen, D.; Yu, H.-Z. Chem. Soc. Rev. 2014, 43, 518–529 [3] Ma, F.; Qi, L.; Einarson, O.; Sen, D.; Yu, H.-Z. Anal. Chem. 2019, 91, 8244−8251. Figure 1
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.007 |
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".