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Record W2008014055 · doi:10.1021/bi901656f

Updated Biological Roles for Matrix Metalloproteinases and New “Intracellular” Substrates Revealed by Degradomics

2009· review· en· W2008014055 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBiochemistry · 2009
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtease and Inhibitor Mechanisms
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsProteasesProteomicsMatrix metalloproteinaseShotgun proteomicsComputational biologyExtracellular matrixIntracellularCell biologyBiologyExtracellularChemistryBiochemistryEnzymeGene

Abstract

fetched live from OpenAlex

Shotgun proteomics techniques are conceptually unbiased, but data interpretation and follow-up experiments are often constrained by dogma, established beliefs that are accepted without question, that can dilute the power of proteomics and hinder scientific progress. Proteomics and degradomics, the characterization of all proteases, inhibitors, and protease substrates by genomic and proteomic techniques, have exponentially expanded the known substrate repertoire of the matrix metalloproteinases (MMPs), even to include intracellular proteins with newly recognized extracellular functions. Thus, the dogma that MMPs are dowdy degraders of extracellular matrix has been resolutely overturned, and the metamorphosis of MMPs into modulators of multiple signaling pathways has been facilitated. Here we review progress made in the field of degradomics and present a current view of the MMP degradome.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
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 score0.495
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.031
GPT teacher head0.297
Teacher spread0.266 · 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