Cerebellar liponeurocytoma: a rare intracranial tumor with possible familial predisposition. Case report
Bibliographic record
Abstract
The biological origin of cerebellar liponeurocytomas is unknown, and hereditary forms of this disease have not been described. Here, the authors present clinical and histopathological findings of a young patient with a cerebellar liponeurocytoma who had multiple immediate family members who harbored similar intracranial tumors. A 37-year-old otherwise healthy woman presented with a history of progressive headaches. Lipomatous medulloblastoma had been diagnosed previously in her mother and maternal grandfather, and her maternal uncle had a supratentorial liponeurocytoma. MRI revealed a large, poorly enhancing, lipomatous mass emanating from the superior vermis that produced marked compression of posterior fossa structures. An uncomplicated supracerebellar infratentorial approach was used to resect the lesion. Genetic and histopathological analyses of the lesion revealed neuronal, glial, and lipomatous differentiation and confirmed the diagnosis of cerebellar liponeurocytoma. A comparison of the tumors resected from the patient and, 22 years previously, her mother revealed similar features. Cerebellar liponeurocytoma is a poorly understood entity. This report provides novel evidence of an inheritable predisposition for tumor development. Accurate diagnosis and reporting of clinical outcomes and associated genetic and histopathological changes are necessary for guiding prognosis and developing recommendations for patient care.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".