A Label-Free, Mix-and-Detect ssDNA-Binding Assay Based on Cationic Conjugated Polymers
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Bibliographic record
Abstract
The accurate, simple, and efficient measurement of the concentration of single-stranded DNA (ssDNA) is important for many analytical applications, such as DNA adsorption, biosensor design, and disease diagnosis, but it is still a challenge. Herein, we studied a cationic conjugated polymer (CCP)-based ssDNA assay taking advantage of the obvious fluorescence change of CCPs upon binding ssDNA. Poly(3-(3′-N,N,N-triethylamino-1′-propyloxy)-4-methyl-2,5-thiophene hydrochloride) (PMNT) achieved an apparent dissociation constant (Kd) of 57 ± 4 nM for ssDNA, indicating a very high binding affinity between PMNT and ssDNA. This allowed us to develop a CCP-based ssDNA biosensor with a detection limit of 0.6 nM, similar to the fluorescence-dye-based method using SYBR Green I and SYBR Gold. Our CCP-based biosensor produced smaller differences among ssDNA samples with different base compositions. In addition, the existence of double-stranded DNA (dsDNA) at different concentrations did not interfere with the fluorescence of PMNT, indicating that our CCP-based biosensor was more suitable for the measurement of ssDNA. Compared with fluorescence-intensity-based quantification, our CCP system allowed ratiometric quantification, which made the calibration easier and more robust. We then applied our method to the quantification of ssDNA on AuNPs using both unmodified and thiolated ssDNA, and the accurate quantification of ssDNA was achieved without any fluorophore modification. This method provides an alternative approach for the measurement of ssDNA.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it