MétaCan
Menu
Back to cohort

New Roles for Matrix Metalloproteinases in Metastasis

2005· article· en· W2043911483 on OpenAlexaff
Mélanie Demers, Julie Couillard, Simon Bélanger, Yves St‐Pierre

Bibliographic record

VenueCritical Reviews in Immunology · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtease and Inhibitor Mechanisms
Canadian institutionsArmand Frappier MuseumInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsMatrix metalloproteinaseMetastasisExtracellular matrixIntravasationStromaPrimary tumorCancer researchAngiogenesisBiologyTumor progressionMatrix (chemical analysis)SecretionCell biologyCancerChemistryImmunologyImmunohistochemistryGeneticsEndocrinology

Abstract

fetched live from OpenAlex

To form tumors successfully at sites remote from the primary tumor, metastatic cells must be endowed with particular properties. They must detach from the primary tumor and enter the blood circulation, where they must resist hemodynamic shearstress, "home" to the target organ, successfully extravasate, and then migrate through dense stroma to a site favorable for tumor growth. Recent results with genetically engineered mouse models have generated data which clearly challenge the classic dogma stating that matrix metalloproteinases (MMPs) promote metastasis solely by modulating the remodeling of extracellular matrix (ECM). Instead, it is becoming clear that MMPs and their natural inhibitors have multiple biological functions that not only challenge our view on how MMPs promote metastasis, but also raise for the first time the idea that secretion of MMPs by the host could protect it from tumor growth, at least in some types of cancer or at specific stages of tumor progression.

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)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0020.006
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.023
GPT teacher head0.341
Teacher spread0.318 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations36
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueCritical Reviews in ImmunologySame topicProtease and Inhibitor MechanismsFrench-language works237,207