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Record W2030857804 · doi:10.1002/jor.1100180213

Met oncogene aberrant expression in canine osteosarcoma

2000· article· en· W2030857804 on OpenAlexaff
Riccardo Ferracini, Paola Angelini, E. Cagliero, Alessandra Linari, Marina Martano, Jay S. Wunder, Paolo Buracco

Bibliographic record

VenueJournal of Orthopaedic Research® · 2000
Typearticle
Languageen
FieldMedicine
TopicVeterinary Oncology Research
Canadian institutionsMount Sinai Hospital
Fundersnot available
KeywordsOsteosarcomaOncogeneCancer researchBiopsyMetastasisPathologyPrimary tumorMedicineBiologyCancerInternal medicineCell cycle

Abstract

fetched live from OpenAlex

The objective of this study was to investigate the role of the MET oncogene in canine osteosarcoma. Seven large-breed dogs affected by spontaneous skeletal osteosarcoma underwent en bloc tumor excision. Total RNA was extracted from frozen tumor samples and assessed for expression of the MET oncogene by Northern blot analysis. Five of seven biopsy samples expressed high levels of the MET oncogene; its expression in the primary tumors was comparable with that previously identified in primary osteosarcomas in humans. A lung metastasis from one of the dogs expressed MET at a higher level than did its primary tumor. Spontaneously arising osteosarcoma in dogs clinically and pathologically mimics the corresponding disease in humans. We previously demonstrated that the MET oncogene was aberrantly expressed in a high percentage of human osteosarcomas. The results of the current study also provide a molecular parallel between the tumors in dogs and humans. This in vivo model may be helpful in evaluating new strategies for therapy against osteosarcoma.

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 head0.104
GPT teacher head0.430
Teacher spread0.326 · 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

Citations52
Published2000
Admission routes1
Has abstractyes

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