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Record W2056127350 · doi:10.1002/biof.99

MT1‐MMP and integrins: Hand‐to‐hand in cell communication

2010· review· en· W2056127350 on OpenAlexaff
Pilar Gonzalo, Vanessa Moreno, Beatriz G. Gálvez, Alicia G. Arroyo

Bibliographic record

VenueBioFactors · 2010
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtease and Inhibitor Mechanisms
Canadian institutionsTellabs (Canada)
FundersMinisterio de Ciencia e InnovaciónCentro Nacional de Investigaciones CardiovascularesComunidad de MadridFundación Ramón Areces
KeywordsIntegrinMatrix metalloproteinaseCell biologyExtracellular matrixAngiogenesisIntracellularCell adhesionTransmembrane proteinBiologyExtracellularCell adhesion moleculeCellSignal transductionCell signalingCytosolChemistryReceptorBiochemistryEnzymeCancer research

Abstract

fetched live from OpenAlex

Integrins are transmembrane adhesion receptors essential for cell communication with the environment and in particular with the extracellular matrix (ECM). ECM components can be processed by several enzymes; one of the largest families involved in this task being matrix metalloproteinases (MMPs). MT1-MMP (membrane type 1-matrix metalloproteinase) is a membrane-anchored MMP with important roles in processes such as tissue development, tumor invasion, and angiogenesis. In addition to its catalytic-dependent functions, MT1-MMP can interact, via its cytosolic tail, with intracellular components, and trigger signaling pathways that impact cell decisions. These features make MT1-MMP similar to integrins, because both are able to integrate events in the extracellular and intracellular milieus. Accordingly, it is probably no coincidence that MT1-MMP often associates and functionally cooperates with distinct integrins at specific cellular compartments. In this review, we discuss aspects of the molecular and functional interplay between MT1-MMP and integrins in distinct cellular and biological contexts.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.004

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 head0.293
Teacher spread0.270 · 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

Citations50
Published2010
Admission routes1
Has abstractyes

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