Platelet-derived Growth Factor Receptor-mediated Signal Transduction from Endosomes
Bibliographic record
Abstract
Although accumulated evidence supports the concept of endosomal signaling of receptor tyrosine kinases, most results are generated from studies of epidermal growth factor receptor (EGFR). It is not clear whether the concept of endosomal signaling could be generally applied to the other receptor tyrosine kinases. For example, platelet-derived growth factor receptor (PDGFR) is very similar to EGFR in terms of both signaling and trafficking; however, little is known about the endosomal signaling of PDGFR. In this research, we applied the same approaches from our recent studies regarding EGFR endosomal signaling to investigate the endosomal signaling of PDGFR. We showed in this communication that we are able to establish a system that allows the specific activation of endosome-associated PDGFR without the activation of the plasma membrane-associated PDGFR and without disrupting the overall endocytosis pathway. By using this system, we showed that endosomal activation of PDGFR recruits various signaling proteins including Grb2, SHC, phospholipase C-gamma1, and the p85alpha subunit of phosphatidylinositol 3-kinase into endosomes and forms signaling complexes with PDGFR. We also showed that endosomal PDGFR signaling is sufficient to activate the major signaling pathways implicated in cell proliferation and survival. Moreover, we demonstrate that endosomal PDGFR signaling is sufficient to generate physiological output including cell proliferation and cell survival.
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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".