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Record W2788415549 · doi:10.1002/1873-3468.12982

Electrical pulse stimulation induces GLUT4 translocation in a Rac‐Akt‐dependent manner in C2C12 myotubes

2018· letter· en· W2788415549 on OpenAlexaff
Fang Hu, Nana Li, Zhu Li, Chang Zhang, Yingying Yue, Qian Liu, Liming Chen, Philip J. Bilan, Wenyan Niu

Bibliographic record

VenueFEBS Letters · 2018
Typeletter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism, Diabetes, and Cancer
Canadian institutionsHospital for Sick Children
FundersTianjin Science and Technology CommitteeTianjin Municipal Bureau of Public HealthNational Natural Science Foundation of China
KeywordsGLUT4Protein kinase BMyogenesisPhosphorylationGlucose uptakeSkeletal muscleChemistryCell biologyStimulationChromosomal translocationMyocyteBiochemistryBiologyInsulinEndocrinology

Abstract

fetched live from OpenAlex

Muscle contraction increases skeletal muscle glucose uptake, but the underlying mechanisms are not fully elucidated. While important for insulin-stimulated glucose uptake, the role of Akt in contraction-stimulated muscle glucose uptake is controversial. In our study, C2C12 skeletal muscle myotubes were contracted by electrical pulse stimulation (EPS). We found that EPS leads to Akt phosphorylation on sites S473 and T308 in a time-dependent manner. The Akt inhibitor MK2206 partly reduces EPS-stimulated GLUT4 translocation without affecting EPS-stimulated AMPK phosphorylation. EPS activates Rac1 GTP-binding, and EPS-stimulated GLUT4 translocation is partly inhibited by Rac1 inhibitor II and siRac1. Interestingly, both Rac1 inhibitor II and siRac1 inhibit EPS-stimulated Akt phosphorylation on sites S473 and T308. Our findings implicate a Rac1-Akt signaling pathway in EPS-stimulated GLUT4 translocation in C2C12 myotubes.

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)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.011
GPT teacher head0.245
Teacher spread0.233 · 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

Citations39
Published2018
Admission routes1
Has abstractyes

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