Optical Detection of DNA and Proteins with Cationic Polythiophenes
Bibliographic record
Abstract
In recent years, intense research has been carried out worldwide with the goal of developing simple, sensitive, and specific detection tools for biomedical applications. Along these lines, we reported in 2002 on cationic polythiophene derivatives able to provide ultrasensitive detection levels and the capability to distinguish perfect matches from oligonucleotides having as little as a single base mismatch. It was shown that the intrinsic fluorescence of the random-coil polymers quenches as a result of the planar, highly conjugated conformation adopted by the polymers when complexed with a single-strand DNA (ssDNA) capture probe but increases again after hybridization with the perfectly matched complementary strand. This change in fluorescence intensity is mainly due to a modification in the delocalization of pi electrons along the carbon chain backbone that occurs when switching between the two conformations. Thus, by monitoring, via the change in fluorescence intensity, the hybridization of the complementary ssDNA target with the "duplex", one could detect as little as 220 complementary target molecules in a 150 microL sample volume (0.36 zmol) in less than 1 hour. Building on this initial concept, we then reported that tagging the DNA probe with a suitable fluorophore dramatically increases the detection sensitivity. This novel molecular system involves the self-assembly of aggregates of duplexes in solution, prior to the introduction of the target, which allows a highly efficient resonance energy transfer (RET) between a "donor" (being the complex formed of the DNA double helix and the polymer chain wrapped around it) and a large number of neighboring "acceptors" (the fluorophores attached to the DNA probes). The massive intrinsic signal amplification (fluorescence chain reaction or FCR) provided by this novel integrated molecular system allows the specific detection of as little as five dsDNA copies in a 3 mL sample volume in only 5 minutes, without the need for prior amplification of the target. Clearly, direct and reliable detection of DNA hybridization without prior PCR amplification or chemical tagging of the genetic target is now possible with this methodology. We have also shown that proteins can be detected following a similar strategy. Impressive results have also been reported by direct and specific staining of targeted proteins. All these features have recently allowed the development of responsive polymeric supports for the detection of DNA and proteins. All these assays that do not require any chemical manipulation of the biological targets or sophisticated experimental procedures should soon lead to major advances in genomics and proteomics.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".