The effect of neuropeptide Y on cell survival and neurotrophin expression in in-vitro models of Alzheimer’s disease
Bibliographic record
Abstract
Alzheimer's disease (AD) is a disorder characterized by the accumulation of abnormally folded protein fragments in neurons, i.e., β-amyloid (Aβ) and tau protein, leading to cell death. Several neuropeptides present in the central nervous system (CNS) are believed to be involved in the pathophysiology of AD. Among them, neuropeptide Y (NPY), a small peptide widely distributed throughout the brain, has generated interest because of its role in neuroprotection against excitotoxicity in animal models of AD. In addition, it has been shown that NPY modulates neurogenesis. Interestingly, these latter effects are similar to those elicited by neurotrophins, which are critical molecules for the function and survival of neurons that degenerate during the course of AD. In this review we summarize the evidence for the involvement of NPY and neurotrophins in AD pathogenesis, and the similarity between them in CNS neurons. Finally, we recapitulate our recent in-vitro evidence for the involvement of neurotrophin nerve growth factor (NGF) and brain-derived neurotrophic factor (BDNF) in the neuroprotective effect elicited by NPY in AD neuron-like models (neuroblastoma cells or primary cultures exposed to toxic concentrations of Aβ's pathogenic fragment 25-35), and propose a putative mechanism based on NPY-induced inhibition of voltage-dependent Ca(2+) influx in pre- and post-synaptic neurons.
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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) | 0.001 | 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 | 0.001 |
| 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".