Influence of Rose Bengal Dimerization on Photosensitization
Bibliographic record
Abstract
Abstract Protein crosslinking photosensitized by rose Bengal (RB 2− ) has multiple medical applications and understanding the photosensitization mechanism can improve treatment effectiveness. To this end, we investigated the photochemical efficiencies of monomeric RB 2− (RB M 2− ) and dimeric RB 2− (RB D 2− ) and the optimal pH for anaerobic RB 2− photosensitization in cornea. Absorption spectra and dynamic light scattering (DLS) measurements were used to estimate the fractions of RB M 2− and RB D 2− . RB 2− self‐photosensitized bleaching was used to evaluate the photoactivity of RB M 2− and RB D 2− . The pH dependence of anaerobic RB 2− photosensitization was evaluated in ex vivo rabbit corneas. The 549 nm/515 nm absorption ratio indicated that concentrations > 0.10 m m RB contained RB D 2− . Results from DLS gave estimated mean diameters for RB M 2− and RB D 2− of 0.70 ± 0.02 nm and 1.75 ± 0.13 nm, respectively, and indicated that 1 m m RB 2− contained equal fractions of RB M 2− and RB D 2− . Quantum yields for RB 2− bleaching were not influenced by RB D 2− in RB 2− solutions although accounting for RB 2− concentration effects on the reaction kinetics demonstrated that RB D 2− is not a photosensitizer. Optimal anaerobic photosensitization occurred at pH 8.5 for solutions containing 200 m m Arg. These results suggest potential approaches to optimizing RB M 2− ‐photosensitized protein crosslinking in tissues.
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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".