Activity-dependent release of precursor nerve growth factor, conversion to mature nerve growth factor, and its degradation by a protease cascade
Bibliographic record
Abstract
In this report, we provide direct demonstration that the neurotrophin nerve growth factor (NGF) is released in the extracellular space in an activity-dependent manner in its precursor form (proNGF) and that it is in this compartment that its maturation and degradation takes place because of the coordinated release and the action of proenzymes and enzyme regulators. This converting protease cascade and its endogenous regulators (including tissue plasminogen activator, plasminogen, neuroserpin, precursor matrix metalloproteinase 9, and tissue inhibitor metalloproteinase 1) are colocalized in neurons of the cerebral cortex and released upon neuronal stimulation. We also provide evidence that this mechanism operates in in vivo conditions, as the CNS application of inhibitors of converting and degrading enzymes lead to dramatic alterations in the tissue levels of either precursor NGF or mature NGF. Pathological alterations of this cascade in the CNS might cause or contribute to a lack of proper neuronal trophic support in conditions such as cerebral ischemia, seizure and Alzheimer's disease or, conversely, to excessive local production of neurotrophins as reported in inflammatory arthritis pain.
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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".