Insulin-dependent and -independent dynamics of insulin receptor trafficking in muscle cells
Bibliographic record
Abstract
Insulin resistance contributes to type 2 diabetes and can be driven by hyperinsulinemia. Insulin receptor (INSR) internalization and cell-surface dynamics at rest and during insulin exposure are incompletely understood in muscle cells. Using surfacing labelling and live-cell imaging, we observed robust basal internalization of INSR in C2C12 myoblasts, without an effect of added insulin. Mass-spectrometry using INSR knockout cells as controls, identified high-confidence binding partners, including proteins associated with internalization. We confirmed known interactors, including IGF1R, but also identified underappreciated INSR-binding factors such as ANXA2. AlphaFold-Multimer analysis of these INSR-binding proteins predicted potential INSR binding sites of these proteins. Protein-protein interaction network mapping suggested links between INSR and caveolin-mediated endocytosis. INSR interacted with both caveolin and clathrin heavy chain (CLTC) in mouse skeletal muscle and C2C12 myoblasts. Whole cell 2D super-resolution imaging revealed that high levels of insulin (20 nM) increased INSR colocalization with CAV1 but decreased its colocalization with CLTC. Single particle tracking confirmed the colocalization of cell-surface INSR with both over-expressed CAV1-mRFP and CLTC-mRFP. INSR tracks that colocalized with CAV1 exhibited longer radii and lifetimes, regardless of insulin exposure, compared to non-colocalized tracks, whereas insulin further increased the lifetime of INSR/CLTC colocalized tracks. Overall, these data suggest that muscle cells utilize both CAV1 and CLTC-dependent pathways for INSR dynamics and internalization.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".