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The expression ofMet/hepatocyte growth factor receptor gene in giant cell tumors of bone and other benign musculoskeletal tumors

2000· article· en· W2018795955 on OpenAlexaff
Riccardo Ferracini, Katia Scotlandi, E. Cagliero, Francesca Acquarone, Martina Olivero, Jay S. Wunder, Nicola Baldini

Bibliographic record

VenueJournal of Cellular Physiology · 2000
Typearticle
Languageen
FieldMedicine
TopicLiver physiology and pathology
Canadian institutionsMount Sinai Hospital
Fundersnot available
KeywordsHepatocyte growth factorReceptor tyrosine kinaseGiant Cell TumorsOncogeneCancer researchPathologyBiologyC-MetImmunohistochemistryReceptorHepatocyte Growth Factor ReceptorAutocrine signallingCellMedicineGiant cellCell cycle

Abstract

fetched live from OpenAlex

Overexpression of the hepatocyte growth factor receptor (Met/HGF receptor), a transmembrane tyrosine kinase encoded by the MET proto-oncogene, is involved in transformation and invasive behavior of human carcinomas and sarcomas. We have previously found that bone sarcomas express high levels of Met/HGF receptor while in some cases the ligand HGF is co-expressed with the receptor, activating an autocrine loop. In this study, we analyzed 40 biopsy samples of a collection of giant cell tumors and other rare benign tumors of bone for expression of the MET proto-oncogene. These included nonossifying fibromas, osteoblastomas, desmoplastic fibromas of bone, chondroblastomas, and giant cell tumors of bone. Snap frozen samples were tested for the MET and HGF gene expression by immuno-histochemistry and Western blotting with anti-MET antibodies and RT-PCR. Over 50% of all cases scored positive for MET expression being constantly positive in recurrent or locally aggressive lesions. Sporadic co-expression of the Met/HGF receptor and ligand is also demonstrated. Met/HGF receptor expression in benign bone neoplasms suggests its early involvement in sarcomagenesis.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.105
Threshold uncertainty score0.536

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.233
Teacher spread0.224 · 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 teacher head, 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

Citations17
Published2000
Admission routes1
Has abstractyes

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