Exploitation of Long-Lived <sup>3</sup>IL Excited States for Metal–Organic Photodynamic Therapy: Verification in a Metastatic Melanoma Model
Bibliographic record
Abstract
Members of a family of Ru(II)-appended pyrenylethynylene dyads were synthesized, characterized according to their photophysical and photobiological properties, and evaluated for their collective potential as photosensitizers for metal-organic photodynamic therapy. The dyads in this series possess lowest-lying (3)IL-based excited states with lifetimes that can be tuned from 22 to 270 μs in fluid solution and from 44 to 3440 μs in glass at 77 K. To our knowledge, these excited-state lifetimes are the longest reported for Ru(II)-based dyads containing only one organic chromophore and lacking terminal diimine groups. These excited states proved to be extremely sensitive to trace amounts of oxygen, owing to their long lifetimes and very low radiative rates. Herein, we demonstrate that (3)IL states of this nature are potent photodynamic agents, exhibiting the largest photocytotoxicity indices reported to date with nanomolar light cytotoxicities at very short drug-to-light intervals. Importantly, these new agents are robust enough to maintain submicromolar PDT in pigmented metastatic melanoma cells, where the presence of melanin in combination with low oxygen tension is known to compromise PDT. This activity underscores the potential of metal-organic PDT as an alternate treatment strategy for challenging environments such as malignant melanoma.
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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) | 0.001 | 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".