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Record W2001514360 · doi:10.2174/1568010033484133

Emerging Features in the Regulation of MMP-9 Gene Expression for the Development of Novel Molecular Targets and Therapeutic Strategies

2003· review· en· W2001514360 on OpenAlexaff
Yves St‐Pierre, Céline Van Themsche, Pierre‐Olivier Estève

Bibliographic record

VenueCurrent Drug Targets - Inflammation & Allergy · 2003
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtease and Inhibitor Mechanisms
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsCell biologyMatrix metalloproteinaseStromal cellBiologyTranscription factorExtracellular matrixGene expressionRegulation of gene expressionCancer researchGeneGenetics

Abstract

fetched live from OpenAlex

Matrix metalloproteinase 9 (MMP-9; gelatinase B) belongs to the subfamily of MMPs that play an important role in tissue remodelling in normal and pathological inflammatory processes. MMP-9 is a major secretion product of macrophages and a component of cytoplasmic granules of neutrophils. The enzyme is also secreted by lymphocytes and stromal cells upon stimulation by inflammatory cytokines, or upon delivery of bi-directional activation signals following integrin-mediated cell-cell or cell-extracellular matrix (ECM) contacts. Since the integrity of the tissue architecture is closely dependent of the delicate balance between MMPs and their inhibitors, excessive production of MMP-9 is linked to tissue damage and degenerative inflammatory disorders. As a consequence, regulation of gene transcription and tissue-specific expression of MMP-9 in normal and diseased states are being actively investigated to pave the way for new therapeutic targets. The objective of this article is to provide an overview of recent developments in the field of mmp-9 gene expression in different cell types, from the triggering of cell-surface receptors, to the activation of cytoplasmic mediators and transcription factors responsible for the activation of MMP-9 promoter. We will then focus on emerging evidence showing that transcription of mmp-9 gene can be controlled by epigenetic mechanisms. The usefulness of targeting the signalling pathways regulating MMP-9 expression for the treatment of inflammatory disorders and other indications will be discussed in light of these findings.

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)0.001
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.662
Threshold uncertainty score0.784

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.030
GPT teacher head0.309
Teacher spread0.279 · 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
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

Citations70
Published2003
Admission routes1
Has abstractyes

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