ShcB and ShcC Activation by the Trk Family of Receptor Tyrosine Kinases
Bibliographic record
Abstract
Activation of the neurotrophin Trk receptors is a key process in the survival and development of the nervous system. The signaling adapters ShcB and ShcC, but not ShcA, are thought to be the primary Shc adaptor proteins in neurons as both are highly expressed in both the developing and adult nervous system. Although a previous study suggested that ShcB and ShcC do not strongly interact with the Trk receptors (1), we find that ShcB and ShcC bind the Trk receptors in a phosphotyrosine-dependent manner via their N-terminal phosphotyrosine binding domain at Tyr(499) (TrkA) and Tyr(515) (TrkB), they are tyrosine-phosphorylated in response to neurotrophin stimulation, and they enhance the activation of mitogen-activated protein kinase in Trk-expressing cells. Moreover, neurotrophin treatment of primary cortical neurons stimulates ShcB/ShcC-Trk interaction and the tyrosine phosphorylation of ShcB/ShcC, indicating that they are bona fide targets of the Trk receptors in vivo. Interestingly, two proteins (pp60 and pp75) co-immunoprecipitate with ShcB and ShcC in response to neurotrophin stimulation in primary cortical neurons, suggesting a potential role of these unknown targets in neurotrophin signaling. Collectively, these results demonstrate that ShcB and ShcC, and their co-immunoprecipitating proteins, are activated by the Trk receptors in primary neurons.
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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) | 0.001 | 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) | 0.003 | 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".