DNA-Driven Focusing for Protein−DNA Binding Assays Using Capillary Electrophoresis
Bibliographic record
Abstract
A DNA-driven focusing technique is reported for protein-DNA binding assays using capillary electrophoresis. A fluorescent DNA aptamer of 84 nucleotides (RT12) was used to bind to a specific protein, human immunodeficiency virus type 1 reverse transcriptase. The aptamer-protein complexes were effectively focused, separated by capillary electrophoresis, and detected by laser-induced fluorescence (LIF). With this DNA-driven focusing, the separation efficiency of the aptamer-protein complex reached 5 million theoretical plates/m, and the sensitivity for the detection of this complex was improved by 70-120-fold. The DNA-driven focusing technique was further applied to protein-DNA binding assays and to enhance the detection of DNA adducts. DNA adducts present in short oligonucleotides or genomic DNA were recognized by and bound to specific antibodies, and the complexes were focused electrophoretically and detected by LIF. The results demonstrate that the DNA-driven focusing can improve separation, sensitivity, and speed of analysis. The focusing is tolerant to high-salt medium, which is usually necessary to support physiological protein-DNA binding. This technique may be applied to nucleic acid analysis, aptamer affinity analysis, immunoassays for DNA damage, and DNA/RNA based binding assays.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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".