Progressive Mucinous Histiocytosis: Importance of Electron Microscopy to Confirm Diagnosis
Bibliographic record
Abstract
BACKGROUND: Progressive mucinous histiocytosis (PMH) is a benign, non-Langerhans cell histiocytosis with characteristic ultrastructural features that can be used for diagnosis. Once an important tool in dermatologic diagnosis, electron microscopy has been largely replaced by immunohistochemistry and immunofluorescence techniques today. However, electron microscopy occasionally still plays a crucial role in the diagnosis of dermatologic conditions. We report a case of PMH as an example of a dermatologic disorder that requires electron microscopy for its diagnosis. METHODS: A 60-year-old woman presented to our clinic with a history of small, sharply demarcated, skin-colored papules ranging from 2 to 5 mm in diameter distributed over the arms, forearms, and dorsal hands. The results of light microscopy, immunohistochemical studies, and clinical examination were inconclusive. Another biopsy for electron microscopy showed the characteristic features of PMH. CONCLUSION: This case demonstrates that a dermatopathology service still needs to have access to electron microscopy for diagnostic purposes to successfully diagnose a small number of rare conditions.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| 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".