Electrical pulse stimulation induces GLUT4 translocation in C<sub>2</sub>C<sub>12</sub>myotubes that depends on Rab8A, Rab13, and Rab14
Bibliographic record
Abstract
The signals mobilizing GLUT4 to the plasma membrane in response to muscle contraction are less known than those elicited by insulin. This disparity is undoubtedly due to lack of suitable in vitro models to study skeletal muscle contraction. We generated C2C12myotubes stably expressing HA-tagged GLUT4 (C2C12-GLUT4 HA) that contract in response to electrical pulse stimulation (EPS) and investigated molecular mechanisms regulating GLUT4 HA. EPS (60 min, 20 V, 1 Hz, 24-ms pulses at 976-ms intervals) elicited a gain in surface GLUT4 HA (GLUT4 translocation) comparably to insulin or 5-amino imidazole-4-carboxamide ribonucleotide (AICAR). A myosin II inhibitor prevented EPS-stimulated myotube contraction and reduced surface GLUT4 by 56%. EPS stimulated AMPK and CaMKII phosphorylation, and EPS-stimulated GLUT4 translocation was reduced in part by small interfering (si)RNA-mediated AMPKα1/α2 knockdown, compound C, siRNA-mediated Ca2+/calmodulin-dependent protein kinase (CaMKII)δ knockdown, or CaMKII inhibitor KN93. Key regulatory residues on the Rab-GAPs AS160 and TBC1D1 were phosphorylated in response to EPS. Stable expression of an activated form of the Rab-GAP AS160 (AS160-4A) diminished EPS- and insulin-stimulated GLUT4 translocation, suggesting regulation of GLUT4 vesicle traffic by Rab GTPases. Knockdown of each Rab8a, Rab13, or Rab14 reduced, in part, GLUT4 translocation induced by EPS, whereas only Rab8a, or Rab14 knockdown reduced the AICAR response. In conclusion, EPS involves Rab8a, Rab13, and Rab14 to elicit GLUT4 translocation but not Rab10; moreover, Rab10 and Rab13 are not engaged by AMPK activation alone. C2C12-GLUT4 HA cultures constitute a valuable in vitro model to investigate molecular mechanisms of contraction-stimulated GLUT4 translocation.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".