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Granzyme B Induces Smooth Muscle Cell Apoptosis in the Absence of Perforin

2004· article· en· W2156460145 on OpenAlexaff
Jonathan C. Choy, Vivian H.Y. Hung, Arwen L. Hunter, Paul Cheung, Bruce Motyka, Ing Swie Goping, Tracy Sawchuk, R. Chris Bleackley, Thomas J. Podor, Bruce M. McManus, David J. Granville

Bibliographic record

VenueArteriosclerosis Thrombosis and Vascular Biology · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell death mechanisms and regulation
Canadian institutionsUniversity of AlbertaUniversity of British Columbia
Fundersnot available
KeywordsGranzyme BGranzymePerforinCell biologyGranzyme ABiologyProgrammed cell deathApoptosisExtracellularMolecular biologyChemistryCytotoxic T cellBiochemistryIn vitro

Abstract

fetched live from OpenAlex

OBJECTIVE: T cell-induced cytotoxicity, of which granzyme B is a key mediator, is believed to contribute to the pathogenesis of inflammatory vascular diseases. In this report, we investigate the mechanism of granzyme B-induced smooth muscle cell (SMC) death. METHODS AND RESULTS: The addition of purified granzyme B alone to cultured SMCs caused a significant reduction in cell viability. Chromatin condensation, phosphatidylserine externalization, and membrane blebbing were observed, indicating that the mechanism of granzyme B-induced SMC death was through apoptosis. Activated splenocytes from perforin-knockout mice induced SMC death through a granzyme B-mediated pathway. Inhibition of the proteolytic activities of caspases and granzyme B prevented granzyme B-induced SMC death, whereas attenuation of granzyme B internalization with mannose-6-phosphate (M6P) did not. Further, granzyme B induced the cleavage of several SMC extracellular proteins, including fibronectin, and reduced focal adhesion kinase phosphorylation. CONCLUSIONS: These results indicate that granzyme B can induce apoptosis of SMCs in the absence of perforin by cleaving extracellular proteins, such as fibronectin.

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 score0.918
Threshold uncertainty score0.472

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 head0.020
GPT teacher head0.249
Teacher spread0.228 · 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

Citations116
Published2004
Admission routes1
Has abstractyes

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