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Record W2948851098 · doi:10.2337/db19-1767-p

1767-P: Inflammatory Triggers of Lipolysis Act through IRE1 in Adipocytes

2019· article· en· W2948851098 on OpenAlexaboutno aff
Kevin P. Foley, Yong Chen, Kieran Kwok, Nicole G. Barra, Akhilesh K. Tamrakar, Yong Liu, Jonathan D. Schertzer

Bibliographic record

VenueDiabetes · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEndoplasmic Reticulum Stress and Disease
Canadian institutionsnot available
Fundersnot available
KeywordsLipolysisAdipocyteInternal medicineEndocrinologyAdipose tissueInflammationInsulin resistanceChemistryBiologyInsulinMedicine

Abstract

fetched live from OpenAlex

Hormones and inflammation can promote adipocyte lipolysis. Inflammation-induced insulin resistance can favor lipolysis, but the cellular mediators of unique lipolytic triggers are ill-defined. We found that ER stress discriminates inflammation-induced adipocyte lipolysis versus adrenergic-mediated lipolysis typical of hormones. Tauroursodeoxycholic acid (TUDCA) blocked adipocyte-autonomous lipolysis from multiple inflammatory ligands, including bacterial peptidoglycan (PGN), lipopolysaccharide (LPS) and tumor necrosis factor (TNF). TUDCA did not alter isoproterenol-induced lipolysis. Inhibiting inositol-requiring protein 1 (IRE1) kinase activity was sufficient to block lipolysis caused by inflammatory triggers and thapsigargin-induced ER stress. Tissue-specific deletion of IRE1 in mice confirmed that adipocyte-resident IRE1 was required for inflammatory ligand-induced lipolysis in adipose tissue. IRE1 kinase activity was dispensable for isoproterenol-induced lipolysis in adipocytes and adipose tissue. We found no role for typical unfolded protein responses as a mechanism linking ER stress to lipolysis, since IRE1 Rnase activity was not associated with changes in adipocyte lipolysis and adipose tissue from GRP78/BiP+/- mice had no change in lipolysis compared to littermate mice. Inhibiting IRE1 kinase activity blocked adipocyte NF-κB activation and Interleukin-6 (IL6) production in response to inflammatory ligands. However, inflammation-induced lipolysis mediated by IRE1 occurred independently from changes in insulin signaling in adipocytes, which further supported the concept that inflammatory triggers of lipolysis can work independent of hormone responses, including insulin resistance. Our results are consistent with IRE1-linked ER stress mediating an inflammation-induced lipolytic program independently from hormonal regulation of lipolysis. Targeting components of IRE1-kinase signaling may have value in obesity and inflammatory lipid disorders. Disclosure K.P. Foley: None. Y. Chen: None. K. Kwok: None. N.G. Barra: None. A.K. Tamrakar: None. Y. Liu: None. J.D. Schertzer: None. Funding Canadian Institutes of Health Research

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.020
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0200.011

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 head0.004
GPT teacher head0.214
Teacher spread0.210 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2019
Admission routes1
Has abstractyes

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