Novel mechanisms to ATP‐dependent glucose uptake in skeletal muscle cells
Bibliographic record
Abstract
Contraction and insulin stimulate glucose influx into muscle, and contraction further sensitizes muscle to insulin. Insulin signals via α,β class I phosphatidylinositol 3‐kinase (PI3Kα,β) to Akt, but contraction signals remain elusive. Interestingly, ATP is released by contracting muscle, and it was recently reported that extracellular ATP can act auto/paracrinely on muscle cells. Our aim was to investigate if ATP induces glucose uptake in muscle cells and promotes insulin action. Rat primary myotubes transiently transfected with GLUT4myc and L6 myoblasts stably expressing GLUT4myc were exposed to 9s 6V electric stimulation (ES); insulin (100 nM, 5 min) or ATP (100 uM, 5min). Uptake of the fluorescent hexose 2NBDG was assayed in real time. Surface GLUT4 was measured by anti‐myc antibodies in fixed, unpermeabilizad cells. Phosphorylation of Akt and its target AS160 was detected with site‐specific antibodies. ES, insulin and ATP each stimulated glucose uptake, GLUT4 translocation, Akt and AS160 phosphorylation. ATP added prior to insulin increased glucose uptake beyond insulin's effect. Inhibitors of Akt (AktVIII), PI3Kα–γ (LY294002), PI3Kγ (AS605240) or dominant‐negative PI3Kγ and Akt inhibited the ATP‐effect. In sum, ES or ATP promote glucose uptake via GLUT4, and ATP adds to insulin action. These effects may be mediated by PI3‐Kγ and Akt and contribute to glucose uptake during muscle activity. Support: FONDAP 15010006, AT‐24100067, CIHR‐MT12601.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".