Real‐time visualization of melanin granules in normal human skin using combined multiphoton and reflectance confocal microscopy
Bibliographic record
Abstract
BACKGROUND: Recent advances in biomedical optics have enabled dermal and epidermal components to be visualized at subcellular resolution and assessed noninvasively. Multiphoton microscopy (MPM) and reflectance confocal microscopy (RCM) are noninvasive imaging modalities that have demonstrated promising results in imaging skin micromorphology, and which provide complementary information regarding skin components. This study assesses whether combined MPM/RCM can visualize intracellular and extracellular melanin granules in the epidermis and dermis of normal human skin. METHODS: We perform MPM and RCM imaging of in vivo and ex vivo skin in the infrared domain. The inherent three-dimensional optical sectioning capability of MPM/RCM is used to image high-contrast granular features across skin depths ranging from 50 to 90 μm. The optical images thus obtained were correlated with conventional histologic examination including melanin-specific staining of ex vivo specimens. RESULTS: MPM revealed highly fluorescent granular structures below the dermal-epidermal junction (DEJ) region. Histochemical staining also demonstrated melanin-containing granules that correlate well in size and location with the granular fluorescent structures observed in MPM. Furthermore, the MPM fluorescence excitation wavelength and RCM reflectance of cell culture-derived melanin were equivalent to those of the granules. CONCLUSION: This study suggests that MPM can noninvasively visualize and quantify subepidermal melanin in situ.
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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) | 0.000 | 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) | 0.001 | 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 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".