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ER stress dictates inflammatory, but not hormonal, lipolytic triggers in adipocytes

2018· article· en· W3176917357 on OpenAlexafffundabout
Jonathan D. Schertzer, Kevin P. Foley, Brittany M. Duggan, Mark Heal, Wendy Chi, Nicole G. Barra

Bibliographic record

VenueThe FASEB Journal · 2018
Typearticle
Languageen
FieldNeuroscience
TopicNuclear Receptors and Signaling
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLipolysisEndocrinologyInternal medicineInflammationChemistryAdipose tissueBiologyMedicine

Abstract

fetched live from OpenAlex

Objective Obesity is characterized by inflammation that can impair endocrine control of cell metabolism. The triggers and stress responses of these immune‐mediated defects are ill‐defined. There is a reciprocal relationship between inflammation and lipolysis in adipocytes, but hormones and adrenergic signals can also stimulate lipolytic programs in adipocytes. This study aimed to identify the cell stress responses that differentiate inflammatory and hormonal triggers of lipolysis in adipocytes. Methods Lipolysis was measured by glycerol release from 3T3‐L1 adipocytes treated with inhibitors of ER stress, inositol‐requiring protein 1α (IRE1α) or tyrosine kinases before stimulation with inflammatory lypolytic stimuli. The inflammatory stimuli included bacterial peptidoglycan, lipopolysaccharide, and tumor necrosis factor. The Hormonal or adrenergic stimuli tested included isoproterenol and forskolin. Inflammation was characterized by Il6 secretion and NF‐κβ activity. Results Inhibition of the kinase activity of IRE1α was sufficient to block lipolysis and Il6 secretion caused by thapsigargin‐induced ER‐stress in adipocytes. Inhibition of IRE1α kinase activity blocked augmented lipolysis from inflammatory, but not hormonal stimuli. Inhibition of IRE1α also blocked augmented Il6 secretion from all inflammatory stimuli. Inhibition of IRE1α blocked the increased NF‐κB activity from all inflammatory stimuli except for lipopolysaccharide. Inhibition of ABL kinases with imatinib did not alter lipolysis. Inhibition of IRE1α RNase activity did not alter lipolysis. The potent RIPK2 inhibitor ponatinib blocked lipolysis, Il6 secretion, and NF‐κβ activation stimulated by peptidoglycan, but did not alter lipolysis from other inflammatory stimuli, despite attenuated Il6 secretion. Conclusions The ER stress sensor IRE1α is essential for inflammation‐induced lipolysis and Il6 secretion in adipocytes. Neither RIPK2 nor NF‐κβ can fully capture the IRE1α lipolyitic pathway from inflammatory stimuli. These findings show that IRE1α discriminates inflammation‐induced lipolysis linked to ER stress from hormonal or adrenergic triggers of adipocyte lipolysis. Support or Funding Information This research is supported by operating grants to JDS from the Natural Sciences and Engineering Research Council (NSERC). JDS held CDA Scholar (SC‐5‐12‐3891‐JS) and CIHR New Investigator awards (MSH‐136665) and holds a Canada Research Chair in Metabolic Inflammation. BD was supported by an Ontario Graduate Scholarship (OGS). KF is supported by an NSERC postdoctoral fellowship. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

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 score0.003
Threshold uncertainty score0.803

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
GPT teacher head0.253
Teacher spread0.226 · 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

Citations0
Published2018
Admission routes3
Has abstractyes

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