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HMGB1/TLR4 axis contributes to A/R‐induced cardiomyocyte apoptosis through potentiating TNFα/JNK pathway

2011· article· en· W3177453907 on OpenAlexaff
Xuemei Xu, Yongwei Yao, Raymond Kao, Claudio M. Martin, Rui Tao

Bibliographic record

VenueThe FASEB Journal · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNF-κB Signaling Pathways
Canadian institutionsLondon Health Sciences CentreLawson Health Research Institute
Fundersnot available
KeywordsApoptosisMyocyteTumor necrosis factor alphaWestern blotHMGB1ChemistryCell biologyTLR4Programmed cell deathMolecular biologySignal transductionBiologyEndocrinologyReceptorBiochemistry

Abstract

fetched live from OpenAlex

The present study is to explore the role of HMGB1/TLR4 axis in the myocyte apoptosis‐induced by A/R (an in vitro counterpart to I/R). Methods cardiomyocytes derived from wild type or TLR4 deficient mice were challenged with an A/R. HMGB1, TNFα expression (Western blot and ELISA), myocyte apoptosis (caspase 3 activity and cell death ELISA) and JNK and NFκB activation (p65 phosphorylation) (Western blot) assessed. Results A/R challenge to myocytes resulted in an increase in HMGB1 expression and extracellular release. Inhibition of HMGB1 attenuated the apoptosis and A/R‐induced TNFα production. Treatment of cardiomyocytes with recombinant HMGB1 (1–5 μg/ml) did not lead to myocyte apoptosis and TNFα production. Exogenous TNFα induced a moderate pro‐apoptotic effect on the myocytes; an effect substantially potentiated by HMGB1. TNFα activated both JNK and NFκB. However, degree of TNFα–induced JNK activation was greater than NFκB in the presence of HMGB1. Inhibition of JNK diminished the myocytes apoptosis‐induced by either TNFα or TNFα/HMGB1 cocktail. A/R‐challenge to TLR4 deficient myocytes increased HMGB1 but not apoptosis, TNFα production and JNK activation. Conclusions our results indicate myocyte HMGB1/TLR4 axis and TNFα work in concert to promote A/R‐induced myocyte apoptosis via JNK activation. (HSFO NA‐6316).

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.830

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.035
GPT teacher head0.242
Teacher spread0.207 · 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".

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Citations0
Published2011
Admission routes1
Has abstractyes

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