Tumor-Derived Cell Culture Model for the Investigation of Meningioma Biology
Bibliographic record
Abstract
Meningioma is the most common primary central nervous system tumor. Although mostly nonmalignant, meningioma can cause serious complications by mass effect and vasogenic edema. While surgery and radiation improve outcomes, not all cases can be treated due to eloquent location. Presently no medical treatment is available to slow meningioma growth owing to incomplete understanding of the underlying pathology, which in turn is due to the lack of high-fidelity tissue culture and animal models. We propose a simple and rapid method for the establishment of meningioma tumor-derived primary cultures. These cells can be maintained in culture for a limited time in serum-free media as spheres and form adherent cultures in the presence of 4% fetal calf serum. Many of the tissue samples show expression of the lineage marker PDG2S, which is typically retained in matched cultured cells, suggesting the presence of cells of arachnoid origin. Furthermore, nonarachnoid cells including vascular endothelial cells are also present in the cultures in addition to arachnoid cells, potentially providing a more accurate tumor cell microenvironment, and thus making the model more relevant for meningioma research and high-throughput drug screening.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".