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Record W2044800165 · doi:10.1093/neuonc/2.3.145

Localization of gelatinase-A and gelatinase-B mRNA and protein in humangliomas

2000· article· en· W2044800165 on OpenAlexaff
Sheetal A. Raithatha, Huong Muzik, N. Barry Rewcastle, Randal N. Johnston, Dylan R. Edwards, Peter Forsyth

Bibliographic record

VenueNeuro-Oncology · 2000
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtease and Inhibitor Mechanisms
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsGelatinase AMMP9GelatinaseGliomaMatrix metalloproteinaseMMP2Fibroblast activation protein, alphaAngiogenesisIn situ hybridizationNeovascularizationBiologyImmunohistochemistryTumor progressionCancer researchPathologyProteasesMolecular biologyMessenger RNAMedicineEnzymeImmunologyCancerDownregulation and upregulationGeneBiochemistry

Abstract

fetched live from OpenAlex

Malignant gliomas maintain a poor prognosis and survival rate due to their marked local invasive growth and neovascularization. Matrix metalloproteinases (MMPs) have been implicated in glioma invasion and angiogenesis, but it is unknown whether they are produced by the tumor cells or surrounding stroma. Using in situ hybridization and immunohistochemistry, we found expression of mRNA for both gelatinase-A (MMP2) and gelatinase-B (MMP9) localized to tumor cells and vascular structures in glioma sections. Gelatinase-A protein expression was detected most prominently in tumor cells, with very little signal seen in vasculature. Gelatinase-B protein expression was prominent in vascular structures but was also expressed in tumor cells. Our data show that these proteases are produced by glioma cells and vascular structures and suggest that synthetic MMP inhibitors might be useful in this disease.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.009
GPT teacher head0.245
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations95
Published2000
Admission routes1
Has abstractyes

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