Measuring DNA Charge Transport on a Surface Using a Redox Modulated Fluorescence Intensity Strategy with DNA SAMs
Bibliographic record
Abstract
The double stranded DNA helix has drawn great attention across different research areas. Various types of platforms have been used to study DNA charge transfer (CT) system. Two types of DNA CT platforms are considered as the most effective: the photoinduced CT in solution with assembled donor and acceptor and electrochemistry on ground state CT in a DNA self-assembled monolayer (SAM)1. We will show a new approach for the study of DNA CT on gold surface by studying the redox modulated fluorescence signal of a co-deposited double-stranded DNA assemblies labeled with Methylene Blue (MB) or AlexaFluoro488 (AF488). We demonstrate a method that can optically distinguish between the two mechanisms of the MB redox on DNA-modified surface: namely either DNA CT mediated reduction or the direct reduction of MB by the gold surface2. Given the fact that the studies on DNA-mediated electrochemistry on surface has been mainly using electrochemical measurements and we still do not fully understand the full picture of the DNA CT, we believe that this study will provide a fresh opinion and facilitate understanding on the DNA CT mechanism on electrode surface. Reference: Arnold, A. R.; Grodick, M. A.; Barton, J. K. DNA Charge Transport: From Chemical Principles to the Cell. Cell Chem. Biol. 2016, 23 (1), 183–197. Pheeney, C. G.; Barton, J. K. DNA Electrochemistry with Tethered Methylene Blue. Langmuir 2012, 28 (17), 7063–7070. Muren, N. B.; Olmon, E. D.; Barton, J. K. Solution, Surface, and Single Molecule Platforms for the Study of DNA-Mediated Charge Transport. Chem. Chem. Phys. 2012, 14 (40), 13754–13771.
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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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".