The transferrin receptor defines two distinct contraction-responsive GLUT4 vesicle populations in skeletal muscle.
Bibliographic record
Abstract
Insulin and contraction increase glucose transport in an additive fashion in skeletal muscle. However, it is still unclear whether they do so by inducing the recruitment of GLUT4 transporters from the same or distinct intracellular compartments to the plasma membrane and the T-tubules. Using the transferrin receptor as a recognized marker of recycling endosomes, we have examined whether insulin and/or contraction recruit GLUT4 from this pool to either the plasma membranes or T-tubules, isolated by subcellular fractionation of perfused hindlimb muscles. Either stimulus independently increased GLUT4 translocation from an intracellular fraction to both the plasma membrane and T-tubules. The combination of insulin and contraction induced a marked (approximately threefold) and almost fully additive increase in GLUT4 content, but only in the plasma membrane. Insulin did not stimulate transferrin receptor recruitment from the GLUT4-containing intracellular fraction to either the plasma membrane or the T-tubules. In contrast, contraction stimulated the recruitment of the transferrin receptor from the same GLUT4-containing intracellular fraction to the plasma membrane but not to the T-tubules. Contraction-induced recruitment of the transferrin receptor was also observed from immunopurified GLUT4 vesicles. It is concluded that muscle contraction stimulates translocation of GLUT4 from two distinct intracellular compartments: 1) a population of recycling endosomes that is selectively recruited to the plasma membrane and 2) from GLUT4 storage vesicles that are also insulin-responsive and recruited to both the plasma membrane and the T-tubules. The lack of additive translocation of GLUT4 to the T-tubules may be linked to the failure of GLUT4-containing recycling endosomes to be recruited to these structures.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".