Cytomorphologic spectrum of mixed pituitary adenoma-gangliocytomas: a report of two cases.
Bibliographic record
Abstract
BACKGROUND: Mixed pituitary adenoma-gangliocytomas are rare tumors with a broad morphologic spectrum. Smear cytology is a useful tool for recognizing these tumors in an intraoperative setting. CASES: The patients were 45 and 30 years old, and both presented with headache. Intraoperative smears in both cases showed a tumor composed of adenomatous and neuronal elements, in varying proportions. The first case had sheets of monotonous neuroendocrine-type cells with occasional interspersed ganglion cells. The second case, however, had a prominent fibrillary background and was predominantly neurocytic, with a mixture of large ganglion-like cells, intermediate cells, and only rare adenomatous cells. CONCLUSION: The diagnostic features of mixed pituitary adenoma-gangliocytomas can be recognized on intraoperative smear preparations. Smear preparations are often more useful than frozen sections because freezing artifacts may mask one of the two components of the tumor. The proportion of adenomatous and neuronal elements can vary widely from case to case. Careful search for a neuronal component should be made, especially if there is a clinical history of a pituitary adenoma showing incomplete response to hormonal therapy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".