Molecular markers of extracellular matrix remodeling in glioblastoma vessels: Microarray study of laser‐captured glioblastoma vessels
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
Glioblastoma multiforme (GBM) are the most malignant and vascularized brain tumors. The aberrant vascular phenotype of GBM could be exploited for diagnosis or therapeutic targeting. This study identified new molecular markers of GBM vessels, using a combination of laser capture microdissection (LCM) microscopy, RNA amplification, and microarray analyses to compare vessels from nonmalignant human brain and GBM tumors. Forty-two genes were differentially expressed in GBM vessels compared to nonmalignant brain vessels. Validation of differentially expressed genes was performed by literature mining, Q-PCR, and immunohistochemistry. Among the differentially expressed genes, only 64% were previously associated with vessels, angiogenesis, gliomas, and/or cancer. The upregulation of genes encoding secreted extracellular proteins IGFBP7 and SPARC was confirmed by Q-PCR in LCM-captured vessels. Whereas SPARC and IGFBP7 protein were absent in nonmalignant brain vessels, a distinct immunoreactivity patterns were observed in GBM sections whereby SPARC was strongly expressed in perivascular cells adjacent to GBM vessels while GBM endothelial cells were immunostained for IGFBP7. IGFBP7 immunoreactivity was also detected on the abluminal side of GBM vessels deposited between strands of vascular basal lamina. The study discerns unique molecular characteristics of GBM vessels compared with nonmalignant brain vessels that could potentially be used for diagnostic or therapeutic purposes.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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