DNA methylation profiling of a lipomatous meningioma: illustrative case
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Lipomatous meningiomas are an extremely rare, benign meningioma subtype subcategorized under metaplastic meningioma in the most recent 2021 update to the World Health Organization classification. They make up less than 0.3% of all meningiomas and, to date, less than 70 cases have been reported in the literature, none of which have undergone molecular profiling. This study aims to promote the utility of molecular profiling to better diagnose these rare tumors. OBSERVATIONS: The authors present the first case of a lipomatous meningioma with DNA methylation profiling that both confirmed its benign biology and uncovered unique cytogenetic changes. Molecular characterization of a lipomatous meningioma confirmed its diagnosis as a distinct, benign meningioma subtype and revealed several copy number variations on chromosome 8 and in NF2 and SMARCB1. Here we discuss some of the radiological and histopathological features of lipomatous meningiomas, how they can be used to distinguish from other meningiomas and other similarly presenting tumors, and a brief literature review discussing the pathophysiology and presentation of this rare tumor. LESSONS: This study provides evidence supporting the use of molecular profiling to diagnose lipomatous meningiomas and guide their clinical management more accurately.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it