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Record W7074076426

Functional live-cell imaging demonstrates that beta1-integrin promotes type IV collagen degradation by breast and prostate cancer cells.

2008· article· en· W7074076426 on OpenAlexaff

Bibliographic record

VenueScholarship at UWindsor (University of Windsor) · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNuclear Structure and Function
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsMatrix metalloproteinaseExtracellular matrixProstate cancerCathepsinBasement membraneExtracellularSecretionProteolysisCathepsin LProteolytic enzymes
DOInot available

Abstract

fetched live from OpenAlex

The ability of tumor cells to adhere to, migrate on, and remodel extracellular matrices is mediated by cell surface receptors such as beta1-integrins. Here we conducted functional live-cell imaging in real time to investigate the effects of modulating beta1-integrin expression and function on proteolytic remodeling of the extracellular matrix. Human breast and prostate cancer cells were grown on reconstituted basement membrane containing a quenched fluorescent form of collagen IV. Generation of cleavage products and the resulting increases in fluorescence were imaged and quantified. Decreases in the expression and activity of beta1-integrin reduced digestion of quenched fluorescent-collagen IV by the breast and prostate cancer cells and correspondingly their invasion through and migration on reconstituted basement membrane. Decreased extracellular matrix degradation also was associated with changes in the constituents of proteolytic pathways: decreases in secretion of the cysteine protease cathepsin B, the matrix metalloproteinase (MMP)-13, and tissue inhibitors of metalloproteinases (TIMP)-1 and 2; a decrease in expression of MMP-14 or membrane type 1 MMP; and an increase in secretion of TIMP-3. This is the first study to demonstrate through functional live-cell imaging that downregulation of beta1-integrin expression and function reduces proteolysis of collagen IV by breast and prostate cancer cells.

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)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.332
Threshold uncertainty score0.812

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.010
GPT teacher head0.184
Teacher spread0.174 · 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
GenreEmpirical

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

Citations1
Published2008
Admission routes1
Has abstractyes

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