Probing nucleobase mismatch variations by electrochemical techniques: exploring the effects of position and nature of the single-nucleotide mismatch
Bibliographic record
Abstract
Electrochemical impedance spectroscopy (EIS) has been used as an ultrasensitive tool for label-free detection of single-nucleotide mismatches in double-stranded DNA (ds-DNA) films. In this study, we have explored the effects of the position and of the type of single-nucleotide mismatch in ds-DNA on gold surfaces and were able to distinguish mismatch positions and mismatch pairs. The single-nucleotide mismatches A-C, A-A and A-G were introduced at three positions within the sequence in bottom, middle and top positions of ds-DNA, the films were studied by EIS, and the impedance results were interpreted with the help of equivalent circuits. The DeltaR(ct), the difference in charge transfer resistance before and after the addition of Zn(2+), was used to distinguish single-nucleotide mismatch within the DNA sequences. Importantly, the mismatch pair is easily distinguishable at the middle position. A purine-pyrimidine mismatch can be distinguished from purine-purine mismatch by its lower DeltaR(ct) value. In addition, all ds-DNA films were studied by scanning electrochemical microscopy in the absence and presence of Zn(2+), allowing us to distinguish a range of mismatched films from matched ds-DNA film.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".