Segmental Neurofibromatosis Follows Blaschko’s Lines or Dermatomes Depending on the Cell Line Affected: Case Report and Literature Review
Bibliographic record
Abstract
BACKGROUND: Segmental neurofibromatosis type 1 (NF-1) has the characteristic features of generalized NF-1 but is isolated to a particular segment of the body. Segmental NF-1 results from a postzygotic mutation during embryogenesis in the NF-1 gene on chromosome 17. The embryologic timing of the mutation and cell types affected predict the clinical phenotype. OBJECTIVE: We present a case of a 52-year-old woman with segmental neurofibromas isolated to the right cheek and neck. We review the recent literature on the genetic and cellular differences between the various clinical manifestations of segmental NF-1. METHODS: A MEDLINE search for cases of segmental neurofibromatosis was conducted. RESULTS: In patients with segmental NF-1 presenting as neurofibromas-only, the distribution follows a neural distribution in dermatomes because the genetic mutation appears to be limited to Schwann cells. In patients with pigmentary changes only, the NF-1 mutation has been shown to occur in fibroblasts and the distribution tends to follow the lines of Blaschko. CONCLUSION: Our patient's neurofibromas were secondary to a postzygotic mutation in the NF-1 gene of neural crest-derived cells. This mutation most likely occurred later in embryogenesis in cells that had already differentiated to Schwann cells and were committed to the dermatomal distribution of the right neck and cheek region (C2).
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| 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) | 0.003 | 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".