Electrochemical signature of mismatch in overhang DNA films: a scanning electrochemical microscopic study
Bibliographic record
Abstract
High throughput DNA basepair mismatch detection is an ultimate goal for earlier and point-of-care diagnostics. However, the size of a target sequence on single nucleotide mismatch detection will critically impact the design of sensors in future. To study the potential impact of target size, the probe and target strands of unequal size were hybridized in the absence and presence of single nucleotide mismatches along the sequence. After hybridization, the shorter target sequences form overhangs in the probe strand while longer target sequences form overhangs in the complementary strand. The resulting double stranded DNA hybrids were printed on gold surfaces and the electrochemical response of the films was studied by scanning electrochemical microscopy without signal amplification and label. The redox mediator, [Fe(CN)(6)](4-), experiences lower repulsion in the vicinity of mismatch containing ds-DNA films, which ultimately manifests into higher feedback current regardless of the size and hybridization position of the complementary strands. Kinetic rate constants monitored right above the ds-DNA films show k(0) = 4.5 ± 0.1 × 10(-5) cm s(-1) for the short sequence hybridized at the upper portion of the probe while k(0) = 4.1 ± 0.2 × 10(-5) cm s(-1) for longer complementary strands which has only top overhang. It suggests that hybridization position is important for mismatch detection in short complementary stands. However, in longer complementary strands, mismatches are easily detectable in the absence of bottom overhangs.
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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 | 0.001 | 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".