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Record W2010789207 · doi:10.2174/1876525400901010046

Matrix Metalloproteinase Activity in the Stromal Cell of Giant Cell Tumor of Bone

2009· article· en· W2010789207 on OpenAlexafffund
Alexander Rabinovich, Isabella W.Y. Mak, Robert W. Cowan, Robert Turcotte, Nigel Colterjohn, Gurmit Singh, Michelle Ghert

Bibliographic record

VenueThe Open Bone Journal · 2009
Typearticle
Languageen
FieldMedicine
TopicBone Tumor Diagnosis and Treatments
Canadian institutionsMcGill University Health CentreHamilton Health SciencesJuravinski Cancer CentreMontreal General HospitalMcMaster University
FundersCanadian Institutes of Health ResearchU.S. Public Health Service
KeywordsStromal cellGiant-cell tumor of boneGiant cellPathologyBone resorptionMatrix metalloproteinaseChemistryImmunohistochemistryOsteoblastBone cellCancer researchBiologyMedicineIn vitroCell biologyInternal medicineBiochemistry

Abstract

fetched live from OpenAlex

Giant cell tumor of bone (GCT) is a destructive and potentially metastatic bone tumour in which the characteristic giant cells have classically been considered the culprits in bone destruction. However, the neoplastic element of the tumour consists of propagative osteoblast-like stromal cells that may play a role in bone resorption. The objectives of this study were to determine the expression and activity of the gelatinases, matrix metalloproteinase (MMP)-2 and -9, in GCT stromal cells, and to determine if these cells have bone-resorbing capabilities. We performed immunohistochemistry on clinical specimens, and real-time polymerase chain reaction (PCR) and zymography on cell lysates and conditioned media from cultured clinical GCT specimens in order to evaluate the expression and activity of MMP-2 and-9 in GCT stromal cells. Our results support the fact that GCT stromal cells express MMP-2 and MMP-9 and are capable of gelatin degradation in vitro. These cells may therefore play a role in bone destruction in GCT.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

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 head0.021
GPT teacher head0.303
Teacher spread0.282 · 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 designBench or experimental
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

Citations13
Published2009
Admission routes2
Has abstractyes

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