Proneurotrophins Require Endocytosis and Intracellular Proteolysis to Induce TrkA Activation
Bibliographic record
Abstract
The uncleaved, pro-form of nerve growth factor (proNGF) functions as a pro-apoptotic ligand for the p75 neurotrophin receptor (p75NTR). However, some reports have indicated that proneurotrophins bind and activate Trk receptors. In this study, we have examined proneurotrophin receptor binding and activation properties in an attempt to reconcile these findings. We show that proNGF readily binds p75NTR expressed in HEK293T cells but does not interact with TrkA expressed under similar circumstances. Importantly, proNGF activates TrkA tyrosine phosphorylation, induces Erk and Akt activation, and causes PC12 cell differentiation. We show that inhibiting endocytosis or furin activity reduced TrkA activation induced by proNGF but not that induced by mature NGF and that proNGF123, a mutant form of NGF lacking dibasic cleavage sites in the prodomain, does not induce TrkA phosphorylation in PC12 cells. Therefore, endocytosis and cleavage appear to be prerequisites for proNGF-induced TrkA activity. We also found that proBDNF induces activation of TrkB in cerebellar granule neurons and that proBDNF cleavage by furin and metalloproteases facilitates this effect. Taken together, these data indicate that under physiological conditions, proneurotrophins do not directly bind or activate Trk receptors. However, endocytosis and cleavage of proneurotrophins produce processed forms of neurotrophins that are capable of inducing Trk activation.
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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".