Preclinical studies of dual-photosensitizer PDT combined with optical clearing for treatment of cutaneous melanoma (Conference Presentation)
Bibliographic record
Abstract
Melanoma is the most aggressive type of skin cancer with high rates of recurrence, morbidly and mortality. Current standard treatment involves surgery, chemotherapy, immunotherapy and also radiation therapy but the response is limited to early-stage tumors. Photodynamic therapy (PDT) is already established as an effective therapeutic option for cutaneous pre-malignant lesions and non-melanoma skin cancer but has shown very limited efficacy for pigmented lesions as melanoma, where the high melanin absorption limits light penetration, preventing complete treatment. Optical clearing agents (OCA) are hyperosmotic agents that work by dehydrating tissue and matching the tissue refractive index, thereby reducing scattering and improving light penetration. here, OCA was used in combination with single and dual photosensitizer-based PDT, targeting the tumor cells and vasculature to improve treatment response in both melanotic and amelanotic melanoma models in vivo. Vascular-targeted PDT was more efficient for amelanotic tumors, independent of the use of OCA and could treat the whole tumor in a single treatment session. However, for the melanotic tumors, OCA significantly improved PDT response for the both vascular-targeted and dual-agent PDT. The best result was obtained with the latter, resulting in no tumor being detected by H&E staining and S100 immunostaining. These initial pre-clinical results show the potential use of dual agent PDT enhanced by OCA for the treatment of pigmented cutaneous melanoma.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".