Making DNA Hybridization Assays in Capillary Electrophoresis Quantitative
Bibliographic record
Abstract
A single-stranded DNA-binding protein (SSB) has been recently proven to facilitate highly efficient separation of the excess hybridization probe from the probe-target hybrid in gel-free capillary electrophoresis. SSB added to the electrophoresis run buffer binds the single-stranded DNA probe but does not bind the double stranded DNA-DNA or DNA-RNA hybrid. As a result, SSB changes the electrophoretic mobility of the probe but does not affect the mobility of the hybrid. If the probe is labeled fluorescently, real-time sensitive detection can be facilitated. While the concept of SSB-mediated hybridization analysis has been proven in principle, the question of how to make such analysis quantitative without building a calibration curve remains open. Here, we propose a general approach for making SSB-mediated analysis quantitative. This approach takes into account such phenomena as (i) the potential influence of the probe-target hybridization and probe-SSB binding on the quantum yield of the fluorescent label and (ii) the potential dissociation of the hybrid by SSB. The proposed approach was used to study the quenching and the dissociation phenomena experimentally. We proved for the first time that SSB does not detectably dissociate the probe-target hybrid, which significantly simplifies the analysis.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".