ProNGF and Neurodegeneration in Alzheimer’s Disease
Bibliographic record
Abstract
Profound and early basal forebrain cholinergic neuron (BFCN) degeneration is a hallmark of Alzheimer’s disease. Loss of synapses between basal forebrain and hippocampal and cortical target tissue correlates highly with the degree of dementia and is thought to be the primary mechanism of memory loss. BFCNs depend for their survival, connectivity and function on the neurotrophin nerve growth factor (NGF) which is retrogradely transported from its sites of synthesis in cortex and hippocampus. The form of NGF found in human brain is proNGF. ProNGF binds to the NGF receptors TrkA and p75NTR, but it binds more strongly to p75NTR and more weakly to TrkA than does mature NGF. This renders proNGF more sensitive to receptor balance than mature NGF. In healthy brain, where BFCNs express both TrkA and p75NTR, proNGF is neurotrophic, activating TrkA-dependent signaling pathways such as MAPK and Akt-mTOR and eliciting cell survival and neurite outgrowth. However, if TrkA is lost or if p75NTR is increased, proNGF activates p75NTR-dependent apoptotic pathways such as JNK. This receptor sensitivity serves as a neurotrophic/apoptotic switch that eliminates BFCNs that cannot maintain TrkA/p75NTR balance and therefore synaptic connections with their targets. TrkA is increasingly lost in mild cognitive impairment (MCI) and Alzheimer’s disease. In addition, proNGF accumulates at BFCN terminals in cortex and hippocampus, reducing the amount of trophic factor that reaches BFCN cell bodies. The loss of TrkA and accumulation of proNGF occur early in MCI and correlate with cognitive impairment. Increased levels of proNGF and reduced levels of TrkA lead to BFCN neurodegeneration and eventual p75NTR-dependent apoptosis. In addition, in Alzheimer’s disease BFCNs suffer from reduced TrkA-dependent retrograde transport which reduces neurotrophic support. Thus, BFCNs are particularly vulnerable to Alzheimer’s disease due to their dependence upon retrograde trophic support from proNGF signaling and transport.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".