Impact of the NGF Maturation and Degradation Pathway on the Cortical Cholinergic System Phenotype
Bibliographic record
Abstract
Cortical cholinergic atrophy plays a significant role in the cognitive loss seen with aging and in Alzheimer's disease (AD), but the mechanisms leading to it remain unresolved. Nerve growth factor (NGF) is the neurotrophin responsible for the phenotypic maintenance of basal forebrain cholinergic neurons in the mature and fully differentiated CNS. In consequence, its implication in cholinergic atrophy has been suspected; however, no mechanistic explanation has been provided. We have previously shown that the precursor of NGF (proNGF) is cleaved extracellularly by plasmin to form mature NGF (mNGF) and that mNGF is degraded by matrix metalloproteinase 9. Using cognitive-behavioral tests, Western blotting, and confocal and electron microscopy, this study demonstrates that a pharmacologically induced chronic failure in extracellular NGF maturation leads to a reduction in mNGF levels, proNGF accumulation, cholinergic degeneration, and cognitive impairment in rats. It also shows that inhibiting NGF degradation increases endogenous levels of the mature neurotrophin and increases the density of cortical cholinergic boutons. Together, the data point to a mechanism explaining cholinergic loss in neurodegenerative conditions such as AD and provide a potential therapeutic target for the protection or restoration of this CNS transmitter system in aging and AD.
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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".