Bibliographic record
Abstract
Melanoma is a pigmented tumor that originates from the melanocytes; pigmented cells present throughout the body, including skin and iris.The cutaneous form is the most common type, and it represents about 5% of the skin tumors diagnosed in Brazil.Although it does not have a high incidence, it represents about 80% to 85% of all skin tumor deaths.The second most frequent type of melanoma is ocular.It represents 5% of all melanoma cases and is a potentially lethal disease, especially when it causes metastasis.The main therapeutic approach for melanomas, in general, is surgery, with resection of the cutaneous lesion or enucleation in the case of ocular melanoma.Other techniques such as adjuvant immunotherapy, palliative chemotherapy, and radiotherapy are also used.However, they have low efficacy and several side effects.Photodynamic therapy is a therapeutic modality based on the interaction of light at specific wavelength and photosensitizer, in the presence of molecular oxygen, leading the cell to death.As melanoma is a pigmented cancer, it usually does not respond well to photodynamic therapy due to the high absorption of light on the surface of the tumor, making volumetric eradication impossible.This project investigated optical strategies for the diagnosis and treatment of melanoma.For the diagnosis, it was evaluated the fluorescence lifetime technique to differentiate melanoma and normal skin.A sensitivity of 99.4%, specificity of 97.4% and accuracy of 98.4% were achieved using linear discrimination analysis.For the cutaneous melanoma treatment, PDT combined to optical clearing agents (OCAs) was investigated.Vascular and cell-target photosensitizers were evaluated combined or not to OCAs.OCA improved PDT response in all pigmented tumors treated, but the best results were achieved when a dual-photosensitizer treatment combined to OCA was performed.The treatment of conjunctival melanoma was conducted using 2photon excitation photodynamic therapy.The advantage of this technique is the use of infrared light, in a wavelength that melanin has a low absorption, improving the light penetration into the tumor.The tumor histology shows that apoptosis was induced only at the treatment site, with no damage to the surrounding tissue.Additionally, a single TPE-PDT session could treat the entire tumor.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".