Regulation of epidermal growth factor receptor signaling by clathrin‐coated membrane microdomains (603.2)
Bibliographic record
Abstract
Epidermal Growth Factor (EGF) binding to its receptor (EGFR) activates several signaling intermediates including Akt, leading to control of cell survival and metabolism. Concomitantly, ligand‐bound EGFR is rapidly incorporated into clathrin‐coated pits, eventually leading to receptor internalization. Whether clathrin scaffolds have functions at the cell surface prior to internalization, such as facilitating EGFR signaling, is poorly understood. To determine if clathrin scaffolds are required for activation of specific EGFR signaling pathways, we employed selective perturbation of clathrin (which prevents formation of clathrin scaffolds) and dynamin (which allows formation of clathrin scaffolds but prevents EGFR endocytosis). We find that siRNA gene silencing or pharmacological inhibition of clathrin, but not of dynamin, inhibits activation of the Akt pathway by EGFR but not receptor autophosphorylation. Using total internal reflection fluorescence microscopy, we have examined the localization of EGFR signaling intermediates vis‐à‐vis clathrin‐coated pits. Our findings indicate that clathrin scaffolds may represent unique signaling microdomains within the plasma membrane, a function that can be separated from the role of clathrin in endocytosis. Grant Funding Source : Supported by the Canadian Institutes of Health Research
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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 | 0.000 |
| 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".