Nanocaging Rose Bengal to Inhibit Aggregation and Enhance Photo‐induced Oxygen Consumption<sup>†</sup>
Bibliographic record
Abstract
Photosensitized crosslinking of proteins in tissues has many medical applications including sealing wounds, strengthening tissues, and beneficially altering tissue properties. Rose Bengal (RB) is used most frequently as the photosensitizer but is not as efficient as would be desired for broad utilization in medicine. Aggregation of RB, at the high concentrations used for medical treatments, decreases the yield of singlet oxygen, which mediates protein crosslinking. We hypothesized that nanocages that sequester RB would inhibit self-association, increasing photosensitization efficiency. We tested cucurbituril and cyclodextrin nanocages, demonstrating that hydroxypropyl-functionalized cyclodextrins are most effective in inhibiting RB aggregation. For these RB/cyclodextrin solutions, we investigated the effect of nanocaging on the photobleaching and oxygen consumption kinetics under 530 nm LED light in aqueous phosphate-buffered solutions. At 100 μm RB, the initial oxygen consumption rates increased by 58% and 80% compared with uncaged RB for the β and γ (2-hydroxypropyl) cyclodextrins, respectively. For 1 mm RB, the enhancement in these rates was much greater, about 200% and 300%, respectively. In addition, at 1 mm RB these two cyclodextrins increased the RB photobleaching rate by ~20% and ~75%. These results suggest that nanocages can minimize RB aggregation and may lead to higher-efficiency photo-medical therapies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".