Photoactivated Rose Bengal Triggers Phospholipid Hydroperoxidation and Late Apoptosis in Colorectal Cancer Cells
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Rose Bengal (RB) is a promising photosensitizer (PS) for photodynamic therapy (PDT), but its application to colorectal carcinoma remains largely unexplored. Herein, we employ in vitro assays to demonstrate that incorporation of RB has substantial phototoxicity against Caco-2 cells, with more than 80% reduction in cell viability for 24 h incubation with 5 × 10 –6 mol/L RB followed by irradiation. In contrast, RB had minimal toxicity without irradiation. The mechanisms of RB action were further elucidated using confocal fluorescence microscopy, Langmuir monolayers as cell membrane models, and flow cytometry to determine the cell death pathways. Flow cytometry revealed that the primary mode of cell death was late apoptosis. RB incorporation affected Caco-2 plasma membrane morphology under light irradiation, and membrane interactions were confirmed using Langmuir monolayers of Caco-2 lipid extracts. Incorporation of RB into the monolayers shifted the pressure–area isotherms toward larger molecular areas, especially at low surface pressures and increasing RB concentrations (1, 10, and 25 × 10 –6 mol/L). RB adsorption also caused a decrease in the in-plane elasticity (Cs 1– ) of the Caco-2 monolayers, with a large increase in monolayer flexibility as RB concentration increased. According to polarization-modulated infrared reflection absorption spectroscopy (PM-IRRAS), the anionic RB interacted electrostatically with positively charged phospholipid groups. Moreover, the changes in surface area observed in the monolayers upon RB incorporation and irradiation could be attributed to hydroperoxidation reactions triggered by the generation of singlet oxygen ( 1 O 2 ). These findings indicate that RB may be used as a PS in the PDT of colorectal cancer, providing detailed insights into its mechanism of action and phototoxicity.
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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".