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Prohibitin attenuates insulin‐stimulated glucose and fatty acid oxidation in adipose tissue by inhibition of pyruvate carboxylase

2006· article· en· W4242774713 on OpenAlexaff
Mahmood Vessal, Suresh Mishra, Sabyasachi Moulik, Liam J. Murphy

Bibliographic record

VenueFEBS Journal · 2006
Typearticle
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsProhibitinBiochemistryMitochondrionChemistryAdipose tissuePyruvate decarboxylationAdipocyteBeta oxidationPyruvate carboxylaseGlucose uptakeFatty acidInsulinMitochondrial biogenesisBiologyCell biologyMetabolismCitric acid cycleEndocrinology

Abstract

fetched live from OpenAlex

Prohibitin (PHB-1) is a highly conserved protein involved in mitochondrial biogenesis and function. It is secreted in lipid droplets from adipocytes and is present in the circulation. In adipose tissue it functions as a membrane receptor and can target binding partners to the mitochondria. Here we report that PHB-1 has a hitherto undescribed role as an inhibitor of pyruvate carboxylase (PC). As a consequence, it can modulate insulin-stimulated glucose and fatty acid oxidation. It had no effect on insulin-stimulated 2-deoxglucose uptake by isolated adipocytes but inhibited insulin-stimulated oxidation of [14C]glucose with a half-maximal concentration of approximately 4 nM. It also inhibited oleic acid oxidation in glucose-depleted adipocytes via depletion of oxaloacetate. In vitro experiments using broken-cell assays confirmed that PHB-1 inhibited PC. MALDI-TOF analysis of proteins identified by cross-linking of PHB-1 to adipocyte membranes indicated that PHB-1 is closely associated with PC and EH domain 2 (EHD2). On the basis of these data, we propose that PHB-1 is recycled between the extracellular space and the mitochondria by a mechanism involving lipid rafts and EHD2 and can modulate mitochondrial fuel metabolism by inhibition of PC.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.628

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 head0.009
GPT teacher head0.252
Teacher spread0.243 · 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

Citations56
Published2006
Admission routes1
Has abstractyes

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