Thieno[3,2-<i>b</i>]thiophene for the Construction of Far-Red Molecular Rotor Hemicyanines as High-Affinity DNA Aptamer Fluorogenic Reporters
Bibliographic record
Abstract
The construction of far-red fluorescent molecular rotors (FMRs) is an imperative task for developing nucleic acid stains that have superior compatibility with cellular systems and complex matrices. A typical strategy relies on the methine extension of asymmetric cyanines, which unfortunately fails to produce sensitive rotor character. To break free from this paradigm, we have synthesized far-red hemicyanines using a dimethylamino thieno[3,2- b ]thiophene donor. The resultant probes, designated as ATh 2 Ind and ATh 2 Btz, possess excitation maxima (λ max ) of >600 nm and have been rigorously characterized by NMR, electrochemistry, and computational methods. The dyes possess alternating charge patterns like indodicarbocyanine (Cy5), but with twisted intramolecular charge transfer (TICT) rotational barriers at 60°, akin to the classical FMR thiazole orange (TO1). ATh 2 Btz also displays cyanine characteristics, enhancing its response upon binding to nucleic acids and allowing for efficient staining of cellular nuclei. When binding to the DNA aptamer for quinine (MN4), ATh 2 Btz exhibits a K d of 17 nM, a 660-fold light-up response, brightness (Φ fl x ε max ) of ∼37,000 M –1 cm –1, and λ ex /λ em of 655/677 nm. The resulting far-red DNA-based MN4-ATh 2 Btz platform has been termed “pomegranate.”
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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 | 0.000 | 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 | 0.001 |
| 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".