Plexiform intraneural granular cell tumour of a digital cutaneous sensory nerve
Bibliographic record
Abstract
An intraneural location for benign granular cell tumours, as well as plexiform architecture with perineural localisation of granular cell tumours of the skin, has been described. We describe the first case of a plexiform intraneural granular cell tumour, morphologically akin to a plexiform neurofibroma. It presented in a 23-year-old woman who had multiple soft-tissue digital lesions on her right hand and one lesion on her left hand. The lesions presented with sensory neurological changes on physical examination. A plexiform architecture with an elongated mass with lobular growth, entirely encased within a fibrovascular connective tissue epineurial/perineurial coat, was noted. The histological findings of a monotonous polygonal and spindle cell proliferation with banal nuclear morphology and granular eosinophilic cytoplasm was typical of a granular cell tumour. The tumour was positive for the usual markers including periodic acid Schiff (PAS), S100 and CD68, and the intraneural location was demonstrated with recognition of the residual nerve bundles and myelinated axons on Luxol fast blue (LFB) staining. There was no history of neurofibromatosis type 1 or 2 in this patient. Recognition of this entity is important, as the natural history of this plexiform lesion is unknown, and the presence of multiple additional nodules in this patient requires further clinical follow-up. Granular cell tumours are benign neoplasms of presumed peripheral nerve, Schwann cell origin. They have been described in numerous locations including the skin and soft tissue, breast, tongue, oesophagus and many other sites.1–4 They have also been reported to be multiple in many cases1,3,5,6 and associated with other malignant neoplasms.7 Plexiform granular cell tumours have been described in the skin, which are characterised by a lobular growth pattern with perineural involvement, …
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".