The nerve growth factor precursor proNGF exhibits neurotrophic activity but is less active than mature nerve growth factor
Bibliographic record
Abstract
Nerve growth factor (NGF) promotes neuronal survival and differentiation and stimulates neurite outgrowth. NGF is synthesized as a precursor, proNGF, which undergoes post-translational processing to generate mature beta-NGF. It has been assumed that, in vivo, NGF is largely processed into the mature form and that mature NGF accounts for the biological activity. However, we recently showed that proNGF is abundant in CNS tissues whereas mature NGF is undetectable, suggesting that proNGF has biological functions beyond its role as a precursor. To determine whether proNGF exhibits biological activity, we mutagenized the precursor-processing site and expressed unprocessed, cleavage-resistant proNGF protein in insect cells. Survival and neurite outgrowth assays on murine superior cervical ganglion neurons and PC12 cells indicated that proNGF exhibits neurotrophic activity similar to mature 2.5S NGF, but is approximately fivefold less active. ProNGF binds to the high-affinity receptor, TrkA, as determined by cross-linking to PC12 cells, and is also slightly less active than mature NGF in promoting phosphorylation of TrkA and its downstream signaling effectors, Erk1/2, in PC12 and NIH3T3-TrkA cells. These data, coupled with our previous report that proNGF is the major form of NGF in the CNS, suggest that proNGF could be responsible for much of the biological activity normally attributed to mature NGF in vivo.
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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".