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Record W2122889219 · doi:10.14814/phy2.12277

Voluntary physical activity prevents insulin resistance in a tissue specific manner

2015· article· en· W2122889219 on OpenAlexafffund
Jessica L. Sarvas, Jeffrey S. Otis, Neelam Khaper, Simon J. Lees

Bibliographic record

VenuePhysiological Reports · 2015
Typearticle
Languageen
FieldMedicine
TopicAdipokines, Inflammation, and Metabolic Diseases
Canadian institutionsNOSM UniversityLakehead University
FundersNational Institute on AgingNational Institutes of HealthNational Institute on Alcohol Abuse and AlcoholismBanting Research Foundation
KeywordsInsulin resistanceInsulinMedicineResistance (ecology)BioinformaticsComputational biologyInternal medicineEndocrinologyBiologyEcology

Abstract

fetched live from OpenAlex

Physical inactivity and a sedentary lifestyle are risk factors for the development of type 2 diabetes. Here, we identified the effects 8 weeks of voluntary physical activity had on the prevention of insulin resistance in mouse skeletal muscles and liver (a hallmark of T2D). To do this, 8 week old C57BL/6J mice with (RUN) and without (SED) voluntary access to running wheels were fed a standard rodent chow ad libitum for 8 weeks. In the liver, there was a 2.5-fold increase in insulin stimulated Akt(SER) (473) phosphorylation, and a threefold increase in insulin-stimulated (0.5 U/kg) GSK3β(SER) (9) phosphorylation in RUN compared to SED mice. Although not induced in skeletal muscles, there was a twofold increase in SOCS3 expression in SED compared to RUN mice in the liver. There was no difference in the glucose tolerance test between groups. This study was the first to show differences in liver insulin sensitivity after 8 weeks of voluntary physical activity, and increased SOCS3 expression in the liver of sedentary mice compared to active mice. These findings demonstrate that even in young mice that would normally be considered healthy, the lack of physical activity leads to insulin resistance representing the initial pathogenesis of impaired glucose metabolism leading to type 2 diabetes.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.736
Threshold uncertainty score0.565

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 head0.047
GPT teacher head0.316
Teacher spread0.269 · 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 designObservational
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

Citations13
Published2015
Admission routes2
Has abstractyes

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