Trk‐dependent ADAM17 activation facilitates neurotrophin survival signaling
Bibliographic record
Abstract
Signaling by TrkA and TrkB receptor tyrosine kinase is required for peripheral neuron survival. TrkA and TrkB signaling is facilitated by the p75 neurotrophin receptor (p75NTR), a member of the tumor necrosis factor (TNF) receptor superfamily, through mechanisms that remain obscure. Here, we demonstrate that TrkA and TrkB induces MEK-dependent phosphorylation of the transmembrane cysteine protease ADAM17 (a disintegrin and metalloprotease 17) at the intracellular residue threonine 735. Phosphorylation at this site activates ADAM17 and causes cleavage of p75NTR and production of the receptors' intracellular domain (p75NTR(ICD)) in PC12 cells and in primary cerebellar granule neurons. We show that Trk-induced ADAM17 phosphorylation and generation of the p75NTR(ICD) is required for neurotrophin-induced Erk and Akt activation and for neurotrophin-dependent survival signaling. Survival of PC12 cells maintained in 10 ng/ml nerve growth factor drops by 47% in cells depleted of ADAM17; this survival deficit is resolved if the p75NTR(ICD) is overexpressed in the ADAM17 depleted cells. These studies identify a novel signaling circuit in which Trk activates ADAM17-dependent p75NTR(ICD) production to feedback to sustain Trk signaling and Trk-dependent 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) | 0.002 | 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".