Bibliographic record
Abstract
AIMS: Understanding the mechanisms by which insulin regulates glucose transporter 4 (GLUT4) traffic in skeletal muscle has been a major challenge since the discoveries of glucose transporter's translocation and the cloning of GLUT4. Here we summarize our work of the past 5 years on the regulation of GLUT4 traffic in skeletal muscle cells. METHODS: L6 cells overexpressing GLUT4 harbouring an exofacial myc epitope gave us the opportunity to perform dynamic assessments of GLUT4 exocytosis, endocytosis, as well as a means to follow GLUT4 molecules along their journey through intracellular compartments. RESULTS: We found that insulin stimulation, which results in the expected gain in surface GLUT4, is mostly attributed to enhanced GLUT4 exocytosis, and does not significantly affect the initial rate of internalization. Two mechanisms by which insulin enhances GLUT4 exocytosis are described: 'Pull' relates to actin remodelling-based segregation of the insulin signalling molecules and the directed recruitment of GLUT4/VAMP2 containing vesicles. 'Push' is the accelerated inter-endosomal transit of endocytosed GLUT4 molecules through the recycling endosome. The interface between the two types of regulatory input by insulin is suggested to be the budding of GLUT4 from the transferrin receptor (TfR)-containing, recycling endosome. CONCLUSIONS: We propose a model on the identity of the GLUT4 pools responsible for GLUT4 recruitment to the plasma membrane in the basal state, or following insulin or hyperosmolarity stimuli.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".