VEGFR2 Expression and TGF-β Signaling in Initial and Recurrent High-Grade Human Glioma
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
OBJECTIVE: Bevacizumab has promising activity against glioma, although reasons for poor efficacy and variable response rates in certain patients are unclear. Vascular endothelial growth factor receptor 2 (VEGFR2) is heterogeneously expressed within the microvasculature of various malignancies. Moreover, transforming growth factor β (TGF-β), a negative prognostic factor for glioma, is intimately involved in angiogenesis including VEGFR2 regulation. Our objective was to associate expression of VEGFR2 and TGF-β activity with clinicopathological features of human glioma. METHODS: Expression patterns determined by immunohistochemistry for VEGFR2 and phosphorylated Smad2 in human gliomas were compared to overall survival, progression-free survival (PFS), initial versus recurrent tumors and tumor grade. RESULTS: Endothelial VEGFR2 expression was low or undetectable in normal tissue but the proportion of VEGFR2-positive vessels increased with tumor grade. Decreased PFS was associated with tumors whose vessels had increased proportions of VEGFR2 at recurrence. Neither parenchymal nor endothelial cell p-Smad2 was associated with tumor grade; however, the former was negatively correlated with overall survival in glioblastoma multiforme. CONCLUSIONS: The molecular phenotype of the vasculature based on the status of VEGFR2 but not p-Smad2 is related to aspects of glioma progression and patient response. Changes in VEGFR2-positive vessels may account for variable therapeutic efficacy of anti-angiogenic agents.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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