Symptomatic Granular Cell Tumor Involving the Pituitary Gland in a Dog: A Case Report and Review of the Literature
Bibliographic record
Abstract
A granular cell tumor involving the pituitary gland, optic chiasm and ventral pyriform lobes was discovered in a 12-year-old Labrador Retriever. Clinical signs included acute blindness, seizures, ataxia, weakness, and behavioral changes. The diagnosis was established by histopathologic and ultrastructural examination of neoplastic tissues collected at necropsy. Granular cell tumors involving the central nervous system are well documented in humans but rarely have been described in dogs. The location of the neoplasm and the clinical symptoms seen in this dog closely parallel those of a rare syndrome in humans commonly described as symptomatic parasellar or pituitary granular cell tumors. The cell of origin for these tumors is still highly debated, and attempts to characterize human granular cell tumors through immunohistochemistry have produced conflicting results. An immunohistochemical profile of this neoplasm revealed focal positive staining for vimentin with a lack of staining for neuron-specific enolase, glial fibrillary acidic protein, S-100, and synaptophysin. All neoplastic cells were strongly positive with the periodic acid-Schiff reaction.
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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) | 0.002 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".