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New Roles for Matrix Metalloproteinases in Metastasis

2005· article· en· W2043911483 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

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.

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)0.001
metaresearch head score (Gemma)0.002
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: none
Teacher disagreement score0.821
Threshold uncertainty score0.633

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.023
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