Binding Studies of Cationic Conjugated Polymers and DNA for Label-Free Fluorescent Biosensors
Bibliographic record
Abstract
Cationic conjugated polymers (CCPs), especially polythiophene, have been extensively used as probes for developing DNA and aptamer-based biosensors. Although many interesting applications have been achieved, a fundamental understanding of this system remains quite limited. In this work, we performed systematic binding assays to understand the interactions between poly(3-(3′- N, N, N -triethylamino-1′-propyloxy)-4-methyl-2,5-thiophene) (PMNT) and DNA. The fluorescence of PMNT at 530 nm initially decreased and then a peak at 580 nm emerged after binding with single-stranded DNA (ssDNA). The binding force between PMNT and DNA was dominated by electrostatic interactions at first and then DNA base-mediated interactions also became important. Since the bases in double-stranded DNA (dsDNA) were shielded, their fluorescence changes were quite different. To best differentiate ssDNA and dsDNA, the optimal pH was between 6 and 8, and the optimal NaCl concentration was around 0.3 M. Moreover, by changing the sequence and length of ssDNA, poly-T had the largest fluorescence shift and poly-A had the smallest change. Under the optimized conditions, the PMNT-based biosensor had a detection limit of 1 nM DNA, which was similar to the SYBR Green I-based assay.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".