Cutaneous melanin exhibiting fluorescence emission under near-infrared light excitation
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
Under ultraviolet and visible light excitation, melanin is essentially a nonfluorescent substance. This work reports our study on near-infrared (NIR) fluorescence properties of melanins, and explores potential applications of NIR fluorescence techniques for evaluating skin disorders involving melanin. The NIR fluorescence spectrum is obtained using a fiber optic NIR spectrometer under 785-nm laser excitation. In vitro measurements are performed on synthetic dihydroxyphenylalanine (DOPA) melanin, melanin extracted from Sepia ink sacs, human hair, animal fur, and bird feathers. Paired spectral comparisons of white and black skin appendages show that melanization of hair, fur, or feathers more than doubles the NIR fluorescence. In vivo NIR autofluorescence of normal dorsal and volar forearm skin of 52 volunteers is measured. Dorsal forearm skin, which is darker than volar skin, exhibits significantly greater NIR fluorescence. Patients with vitiligo (n=4), compound nevus (n=3), nevus of Ota (n=1), superficial spreading melanoma (n=3), and postinflammatory hyperpigmentation (n=1) are also evaluated. NIR fluorescence is greater within the lesion than the surrounding normal skin for all these conditions except vitiligo, where the converse was true. The observed melanin NIR fluorescence provides a new approach to in vitro and in vivo melanin detection and quantification that may be particularly useful for evaluating pigmented skin lesions.
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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 | 0.001 |
| 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 it