Optical clearing of melanoma<i>in vivo</i>: characterization by diffuse reflectance spectroscopy and optical coherence tomography
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Melanoma is the most aggressive type of skin cancer, with significant risk of fatality. Due to its pigmentation, light-based imaging and treatment techniques are limited to near the tumor surface, which is inadequate, for example, to evaluate the microvascular density that is associated with prognosis. White-light diffuse reflectance spectroscopy (DRS) and near-infrared optical coherence tomography (OCT) were used to evaluate the effect of a topically applied optical clearing agent (OCA) in melanoma in vivo and to image the microvascular network. DRS was performed using a contact fiber optic probe in the range from 450 to 650 nm. OCT imaging was performed using a swept-source system at 1310 nm. The OCT image data were processed using speckle variance and depth-encoded algorithms. Diffuse reflectance signals decreased with clearing, dropping by ∼ 90% after 45 min. OCT was able to image the microvasculature in the pigmented melanoma tissue with good spatial resolution up to a depth of ∼ 300 μm without the use of OCA; improved contrast resolution was achieved with optical clearing to a depth of ∼ 750 μm in tumor. These findings are relevant to potential clinical applications in melanoma, such as assessing prognosis and treatment responses. Optical clearing may also facilitate the use of light-based treatments such as photodynamic therapy.
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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 | 0.001 |
| 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 it