A Method for Determining the Actual Rate of Orientation Switching of DNA Self-Assembled Monolayers Using Optical and Electrochemical Frequency Response Analysis
Bibliographic record
Abstract
Electrostatic control of the orientation of fluorophore-labeled DNA strands immobilized on an electrode surface has been shown to be an effective bioanalytical tool. Modulation techniques and later time-resolved measurements were used to evaluate the kinetics of the switching between lying and standing DNA conformations. These measurements, however, are the result of a convolution between the DNA "switching" response time and the other frequency limited responses in the measurement. In this work, a method for analyzing the response of a potential driven DNA sensor is presented by calculating the potential effectively dropped across the electrode interface (using electrochemical impedance spectroscopy) as opposed to the potential applied to the electrochemical cell. This effectively deconvolutes the effect of the charging time on the observed frequency response. The corrected response shows that DNA is able to switch conformation faster than previously reported using modulation techniques. This approach will ensure accurate measurements independent of the electrochemical system, removing the uncertainty in the analysis of the switching response, enabling comparison between samples and measurement systems.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".