Cell migration by a FRS2‐adaptor dependent membrane relocation of ret receptors
Bibliographic record
Abstract
During development neural progenitor cells migrate with extraordinary precision to inhabit tissues and organs far from their initial position. Little is known about the cellular basis for directional guidance by tyrosine kinase receptors (RTKs). RET is a RTK with important functions in guiding the migration of neuronal cells, and RET dysregulation leads to clinical disease such as agangliosis of the colon. We show here that RET migration in neuroepitheliomal and non-neuronal cells is elicited by the activation of specific signaling pathways initiated by the competitive recruitment of the FRS2 adaptor molecule to tyrosine 1062 (Y1062) in RET. FRS2 selectively recruited RET to focal complexes and led to activation of SRC family kinases and focal adhesion kinase (FAK). Activation of SRC depended on its direct interaction with RET at a different intracellular tyrosine (Y981) and activation of molecular signaling from these two separate sites in concert regulated migration. Our data suggest that an important function for FRS2 is to concentrate RET in membrane foci, leading to an engagement of specific signaling complexes localized in these membrane domains.
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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".