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Record W4409106846 · doi:10.1152/physrev.00033.2024

A comprehensive view of muscle glucose uptake: regulation by insulin, contractile activity, and exercise

2025· review· en· W4409106846 on OpenAlexafffund
Erik A. Richter, Philip J. Bilan, Amira Klip

Bibliographic record

VenuePhysiological Reviews · 2025
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism, Diabetes, and Cancer
Canadian institutionsHospital for Sick Children
FundersCanadian Institutes of Health ResearchNovo Nordisk Fonden
KeywordsGLUT4Glucose transporterGlucose uptakeSarcolemmaSkeletal muscleInsulinBiologyCarbohydrate metabolismInternal medicineIntracellularEndocrinologyMuscle contractionCell biologyBiochemistryMedicine

Abstract

fetched live from OpenAlex

Skeletal muscle is the main site of glucose deposition in the body during meals and the major glucose utilizer during physical activity. Although in both instances the supply of glucose from the circulation to the muscle is of paramount importance, in most conditions the rate-limiting step in glucose uptake, storage, and utilization is the transport of glucose across the muscle cell membrane. This step is dependent upon the translocation of the insulin- and contraction-responsive glucose transporter GLUT4 from intracellular storage sites to the sarcolemma and T tubules. Here, we first analyze how glucose can traverse the capillary wall into the muscle interstitial space. We then review the molecular processes that regulate GLUT4 translocation in response to insulin and muscle contractions and the methodologies utilized to unravel them. We further discuss how physical activity and inactivity, respectively, lead to increased and decreased insulin action in muscle and touch upon sex differences in glucose metabolism. Although many key processes regulating glucose uptake in muscle are known, the advent of newer and bioinformatics tools has revealed further molecular signaling processes reaching a staggering level of complexity. Much of this molecular mapping has emerged from cellular and animal studies and more recently from application of a variety of -omics in human tissues. In the future, it will be imperative to validate the translatability of results drawn from experimental systems to human physiology.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.975
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
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 head0.049
GPT teacher head0.337
Teacher spread0.289 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations36
Published2025
Admission routes2
Has abstractyes

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