The Brain NGF Metabolic Pathway in Health and in Alzheimer’s Pathology
Bibliographic record
Abstract
Emerging research has re-emphasized the role of the cortical cholinergic system in the symptomology and progression of Alzheimer’s disease (AD). Basal forebrain (BF) cholinergic nuclei depend on target-derived NGF for survival during development and for the maintenance of a classical cholinergic phenotype during adulthood. In AD, BF cholinergic neurons lose their cholinergic phenotype and function, suggesting an impairment in NGF-mediated trophic support. We propose that alterations to the enzymatic pathway that controls the maturation of proNGF to mature NGF and the latter’s ulterior degradation underlie this pathological process. Indeed, the NGF metabolic pathway has been demonstrated to be impaired in AD and other amyloid pathologies, and pharmacological manipulation of NGF metabolism has consequences in vivo for both levels of proNGF/NGF and the phenotype of BF cholinergic neurons. The NGF pathway may also have potential as a biomarker of cognitive decline in AD, as its changes can predict future cognitive decline in patients with Down syndrome as they develop preclinical Alzheimer’s pathology. New evidence suggests that the cholinergic system, and by extension NGF, may have a greater role in the progression of AD than previously realized, as changes to the BF precede and predict changes to the entorhinal cortex, as anticholinergic drugs increase odds of developing AD, and as the use of donepezil can reduce rates of hippocampal and cortical thinning. These findings suggest that new, more sophisticated cholinergic therapies should be capable of preserving the basal forebrain thus having profound positive effects as treatments for 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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".