Self-Healing Dyes—Keeping the Promise?
Bibliographic record
Abstract
Self-healing dyes have emerged as a new promising class of fluorescent labels. They consist of two units, a fluorescent dye and a photostabilizer. The latter heals whenever the fluorescent dye is in danger of taking a reaction pathway toward photobleaching. We describe the underlying concepts and summarize the developmental history and state-of-the-art, including latest applications in high-resolution microscopy, live-cell, and single-molecule imaging. We further discuss remaining limitations, which are (i) lower photostabilization of most self-healing dyes when compared to solution additives, (ii) limited mechanistic understanding on the influence of the biochemical environment and molecular oxygen on self-healing, and (iii) the lack of cheap and facile bioconjugation strategies. Finally, we provide ideas on how to further advance self-healing dyes, show new data on redox blinking caused by double-stranded DNA, and highlight forthcoming work on intramolecular photostabilization of fluorescent proteins.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.018 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 0.005 |
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".