Superior Photophysical and Photosensitizing Properties of Nanoaggregates of Weakly Emissive Dyes for Use in Bioimaging and Photodynamic Therapy
Bibliographic record
Abstract
The development of luminescent dyes based on 1,1,4,4-tetracyanobuta-1,3-dienes (TCBDs) is an active research area, and a quantum yield (Φ F ) of 7.8% has been achieved so far in cyclohexane by appending a fluorophore. Our novel method radically refines weakly emissive 2,3-disubstituted TCBD (phenyl-TCBD 1 ) (Φ F = 2.3% in CH 3 CN) into a water-soluble, biocompatible nanoformulation as highly emissive aggregates 1NPs ⊂ PF-127 with Φ F = 7.9% in H 2 O and without fluorophore conjugation. Characterization of 1NPs ⊂ PF-127 was carried out using various spectroscopic techniques, and its predominant size was found to be 80–100 nm according to transmission electron microscopy and dynamic light scattering techniques. Spectroscopic studies including Fourier transform infrared spectroscopy revealed that aggregated phenyl-TCBD particles were encapsulated in a nonluminescent triblock copolymer (PF-127)-based nanomicelles with the TCBD entrapment efficiency of 77%. With increasing water fraction, the phenyl-TCBD nanoaggregates exhibited a 3-fold higher quantum yield, a greater lifetime, and a red shift (155 nm). This remarkable enhancement in red emissivity enabled them to be used as a bioprobe for bioimaging applications and in photodynamic therapy to selectively target cancer cell lines with singlet oxygen generation capability (Φ Δ = 0.25). According to the MTT assay, compared to the native molecular form (1229 nM), the aggregated 1NPs ⊂ PF-127 (13.51 nM) exhibited dose-dependent cell death when exposed to light with 91-fold increased activity. The histoarchitectures of various vital organs (liver, kidneys, heart, lungs, and spleen) were intact when tested for in vivo biocompatibility. This study has significant implications for developing nonplanar push–pull chromophore-based dyes as biosensors and with potential applications beyond bioimaging.
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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 | 0.000 |
| 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 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".