Bibliographic record
Abstract
ABSTRACT Endocytosis plays important roles in regulating EGFR signaling. We previously found that EGFR endocytosis during mitosis is mediated differently than during interphase. While the regulation of EGFR endocytosis in interphase is well understood, little is known regarding the regulation of EGFR endocytosis during mitosis. Here, we studied the mechanisms regulating mitotic EGFR endocytosis. We found that contrary to interphase cells, mitotic EGFR endocytosis is more reliant on the activation of the E3 ligase CBL. At high EGF doses, inhibition of inhibited EGFR endocytosis of mitotic cells, but not of interphase cells. Moreover, the endocytosis of mutant EGFR Y1045F-YFP was strongly delayed. The endocytosis of truncated EGFR Δ1044-YFP that does not bind to CBL was completely inhibited. EGF induced stronger ubiquitination of mitotic EGFR than interphase EGFR and mitotic EGFR is trafficked to lysosome for degradation. Furthermore, during mitosis low doses of EGF also stimulate EGFR endocytosis by NCE. Contrary to interphase, CBL and the CBL-binding regions of EGFR were required for mitotic EGFR endocytosis at low doses. This may be due to the mitotic ubiquitination of the EGFR even at low EGF doses. In conclusion, mitotic EGFR endocytosis solely proceed through CBL-mediated NCE.
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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 | 0.000 |
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".