Diagnostic and pathogenic features of calcifying pseudoneoplasm of the neuraxis
Bibliographic record
Abstract
Calcifying pseudoneoplasm of the neuraxis (CAPNON) is a rare tumefactive lesion with unclear pathogenesis. It is diagnosed by pathological findings of the typical histological features that include granular amorphous cores with palisading spindle to epithelioid cells, variable fibrous stroma, foreign-body reaction with giant cells, and calcification/ossification occasionally with psammoma bodies. However, its histopathology may be variable and currently immunohistochemistry plays a limited role in its diagnosis and understanding the pathogenesis. In this study, we examined 6 cases of CAPNONs including 3 intracranial and 3 spinal epidural lesions (age range: 59–69 years; 3 males and 3 females). Immunohistochemistry revealed that all CAPNON cores contain abundant positive deposits of neurofilament protein (NFP), which was supported by electron microscopy finding of filaments (8–13 nm in diameter). In comparison, no NFP positivity was found in 5 psammomatous/metaplastic meningiomas or 7 intervertebral tissue lesions with calcification/ossification. In addition, CAPNON cellular areas showed variable numbers of CD8+ cytotoxic T-cells with less CD4+ T-cells and a decreased ratio of CD4/CD8+ cells, versus the intervertebral tissue lesions without CD8+ or CD4+ cells. Our findings suggest that NFP may be a principal constituent of CAPNONs, and thus involved in the pathogenesis of CAPNON. Given the decreased CD4/CD8 ratio, the pathogenic process of CAPNON is possibly immune- mediated. LEARNING OBJECTIVES The presentation will enable the learner to: 1. Discuss histopathological features of calcifying pseudoneoplasm of the neuraxis (CAPNON) with variation of non-core components. 2. Explore diagnostic and pathogenic roles of immunohistochemical markers including neurofilament protein and CD4/CD8 in CAPNON.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".