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Record W2029117013 · doi:10.1002/jcb.21629

Glycogen synthase kinase‐3beta suppresses tumor necrosis factor‐alpha expression in cardiomyocytes during lipopolysaccharide stimulation

2007· article· en· W2029117013 on OpenAlexaff
E Shen, Jue Fan, Tianqing Peng

Bibliographic record

VenueJournal of Cellular Biochemistry · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicWnt/β-catenin signaling in development and cancer
Canadian institutionsLawson Health Research InstituteWestern University
Fundersnot available
KeywordsGSK-3GSK3BTumor necrosis factor alphaGlycogen synthaseProtein kinase BLipopolysaccharideStimulationSignal transductionKinasePhosphorylationBiologyChemistryMolecular biologyEndocrinologyCell biology

Abstract

fetched live from OpenAlex

This study was to investigate the role of glycogen synthase kinase-3beta (GSK-3beta) in cardiomyocyte tumor necrosis factor-alpha (TNF-alpha) expression induced by lipopolysaccharide (LPS). In cultured neonatal mouse cardiomyocytes, LPS induced TNF-alpha expression and increased GSK-3beta activation. Inhibition of GSK-3beta by SB216763 or by over-expression of a dominant negative mutant of GSK-3beta significantly enhanced TNF-alpha expression in LPS-stimulated cardiomyocytes, in association with an increase in p65 phosphorylation. In contrast, over-expression of GSK-3beta by adenoviral vectors containing wild-type GSK-3beta or a constitutively active GSK-3beta attenuated TNF-alpha expression induced by LPS. Further evidence to support the inhibitory role of GSK-3beta in TNF-alpha expression is that protein kinase B (Akt) signaling, an upstream inhibitor of GSK-3beta, promotes TNF-alpha expression in LPS-stimulated cardiomyocytes and this action of Akt signaling can be mimicked by GSK-3beta inactivation. Our study demonstrates that GSK-3beta plays an inhibitory role in cardiomyocyte TNF-alpha expression during LPS stimulation, and it may be a potential therapeutic target for sepsis.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score1.000

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 head0.008
GPT teacher head0.240
Teacher spread0.232 · 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.

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

Citations24
Published2007
Admission routes1
Has abstractyes

Explore more

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