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Elevation of Global O-GlcNAc in Rodents Using a Selective O-GlcNAcase Inhibitor Does Not Cause Insulin Resistance or Perturb Glucohomeostasis

2010· article· en· W2022647011 on OpenAlexafffund
Matthew S. Macauley, Xiaoyang Shan, Scott A. Yuzwa, T.M. Gloster, David J. Vocadlo

Bibliographic record

VenueChemistry & Biology · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGlycosylation and Glycoproteins Research
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchHealth CanadaCanada Research ChairsUniversity of ManitobaSimon Fraser UniversityMichael Smith Health Research BCWellcome Trust
KeywordsInsulin resistanceInsulinInternal medicineEndocrinologyIn vivoBiologyMedicineBiotechnology

Abstract

fetched live from OpenAlex

The O-GlcNAc modification is proposed to be a nutrient sensor with studies suggesting that global increases in O-GlcNAc levels cause insulin resistance and impaired glucohomeostasis. We address this hypothesis by using a potent and selective inhibitor of O-GlcNAcase, known as NButGT, in a series of in vivo studies. Treatment of rats and mice with NButGT, for various time regimens and doses, dramatically increases O-GlcNAc levels throughout all tissues but does not perturb insulin sensitivity or alter glucohomeostasis. NButGT also does not affect the severity or onset of insulin resistance induced by a high-fat diet. These results suggest that pharmacological increases in global O-GlcNAc levels do not cause insulin resistance nor do they appear to disrupt glucohomeostasis. Therefore, the protective benefits of elevated O-GlcNAc levels may be achieved without deleteriously affecting glucohomeostasis.

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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.017
GPT teacher head0.319
Teacher spread0.302 · 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

Citations77
Published2010
Admission routes2
Has abstractyes

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