A comprehensive view of muscle glucose uptake: regulation by insulin, contractile activity, and exercise
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".