ProNGF, but Not NGF, Switches from Neurotrophic to Apoptotic Activity in Response to Reductions in TrkA Receptor Levels
Bibliographic record
Abstract
Nerve growth factor (NGF) promotes the survival and differentiation of neurons. NGF is initially synthesized as a precursor, proNGF, which is the predominant form in the central nervous system. NGF and proNGF bind to TrkA/p75NTR to mediate cell survival and to sortilin/p75NTR to promote apoptosis. The ratio of TrkA to p75NTR affects whether proNGF and mature NGF signal cell survival or apoptosis. The purpose of this study was to determine whether the loss of TrkA influences p75NTR or sortilin expression levels, and to establish whether proNGF and mature NGF have a similar ability to switch between cell survival and cell death. We systematically altered TrkA receptor levels by priming cells with NGF, using small interfering RNA, and using the mutagenized PC12nnr5 cell line. We found that both NGF and proNGF can support cell survival in cells expressing TrkA, even in the presence of p75NTR and sortilin. However, when TrkA is reduced, proNGF signals cell death, while NGF exhibits no activity. In the absence of TrkA, proNGF-induced cell death occurs, even when p75NTR and sortilin levels are reduced. These results show that proNGF can switch between neurotrophic and apoptotic activity in response to changes in TrkA receptor levels, whereas mature NGF cannot. These results also support the model that proNGF is neurotrophic under normal circumstances, but that a loss in TrkA in the presence of p75NTR and sortilin, as occurs in neurodegenerative disease or injury, shifts proNGF, but not NGF, signalling from cell survival to cell death.
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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".