Hyperosmolarity Reduces GLUT4 Endocytosis and Increases Its Exocytosis from a VAMP2-independent Pool in L6 Muscle Cells
Bibliographic record
Abstract
The intracellular traffic of the glucose transporter 4 (GLUT4) in muscle cells remains largely unexplored. Here we make use of L6 myoblasts stably expressing GLUT4 with an exofacially directed Myc-tag (GLUT4myc) to determine the exocytic and endocytic rates of the transporter. Insulin caused a rapid (t(12) = 4 min) gain, whereas hyperosmolarity (0.45 m sucrose) caused a slow (t(12) = 20 min) gain in surface GLUT4myc molecules. With prior insulin stimulation followed by addition of hypertonic sucrose, the increase in surface GLUT4myc was partly additive. Unlike the effect of insulin, the GLUT4myc gain caused by hyperosmolarity was insensitive to wortmannin or to tetanus toxin cleavage of VAMP2 and VAMP3. Disappearance of GLUT4myc from the cell surface was rapid (t(12) = 1.5 min). Insulin had no effect on the initial rate of GLUT4myc internalization. In contrast, hyperosmolarity almost completely abolished GLUT4myc internalization. Surface GLUT4myc accumulation in response to hyperosmolarity was only partially blocked by inhibition of tyrosine kinases with erbstatin analog (erbstatin A) and genistein. However, neither inhibitor interfered with the ability of hyperosmolarity to block GLUT4myc internalization. We propose that hyperosmolarity increases surface GLUT4myc by preventing GLUT4 endocytosis and stimulating its exocytosis via a pathway independent of phosphatidylinositol 3-kinase activity and of VAMP2 or VAMP3. A tetanus toxin-insensitive v-SNARE such as TI-VAMP detected in these cells, might mediate membrane fusion of the hyperosmolarity-sensitive pool.
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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) | 0.001 | 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".