Reduced Glioma Growth Following Dexamethasone or Anti‐Angiopoietin 2 Treatment
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
All patients with glioblastoma, the most aggressive and common form of brain cancer, develop cerebral edema. This complication is routinely treated with dexamethasone, a steroidal anti-inflammatory drug whose effects on brain tumors are not fully understood. Here we show that dexamethasone can reduce glioma growth in mice, even though it depletes infiltrating T cells with potential antitumor activity. More precisely, T cells with helper or cytotoxic function were sensitive to dexamethasone, but not those that were negative for the CD4 and CD8 molecules, including gammadelta and natural killer (NK) T cells. The antineoplastic effect of dexamethasone was indirect, as it did not meaningfully affect the growth and gene expression profile of glioma cells in vitro. In contrast, hundreds of dexamethasone-modulated genes, notably angiopoietin 2 (Angpt2), were identified in cultured cerebral endothelial cells by microarray analysis. The ability of dexamethasone to attenuate Angpt2 expression was confirmed in vitro and in vivo. Selective neutralization of Angpt2 using a peptide-Fc fusion protein reduced glioma growth and vascular enlargement to a greater extent than dexamethasone, without affecting T cell infiltration. In conclusion, this study suggests a mechanism by which dexamethasone can slow glioma growth, providing a new therapeutic target for malignant brain tumors.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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