Cutaneous melanocytoneuroma: the first case of a distinctive intraneural tumor with dual nerve sheath and melanocytic differentiation
Bibliographic record
Abstract
Many melanocytic nevi contain areas similar to nerve sheath tumors (NST) and NSTs with melanin have been described. There are some NSTs with at least partial intraneural location, including neurofibromas, plexiform neurofibromas, granular cell tumors and the recently described, dendritic cell neurofibroma with pseudorosettes. We describe the case of an NST with melanocytic differentiation and intraneural location, for which we suggest the term 'melanocytoneuroma' (MCN). It arose in the skin of a 67-year-old woman with no previous history of melanoma or neurofibromatosis. The lesion presented as a papule and histologically consisted of a dermal nodule without junctional melanocytic activity. The lesion comprised an intraneural proliferation of large epithelioid eosinophilic cells with prominent cell borders imparting a 'plant-like' appearance. The cells were also seen within adjacent nerve twigs and were positive for S100, Melan-A, HMB-45, microphthalmia transcription factor and PGP 9.5. The lesion was entirely surrounded by an epithelial membrane antigen-positive-perineurial coat and the individual tumor cells were invested by laminin and collagen type-IV-positive basal lamina-like material. The lesion did not show any evidence of atypia and following complete excision, no recurrence has been documented. In conclusion, this unusual lesion represents an intraneural proliferation with melanocytic and nerve sheath cell differentiation, to which we have accorded the appellation, MCN.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".