Interaction of Survival and Death Signaling in Basal Forebrain Neurons: Roles of Neurotrophins and Proneurotrophins
Bibliographic record
Abstract
Proneurotrophins bind with high affinity to p75 neurotrophin receptor (p75NTR) and lack the capacity to bind Trk receptors, suggesting that proneurotrophins can elicit apoptosis via p75NTR even in cells expressing survival-promoting Trk receptors. In the CNS, basal forebrain (BF) neurons are particularly vulnerable to degeneration in Alzheimer's disease, and are among the few populations of brain neurons that express p75NTR throughout life. These neurons also express Trk receptors and may be concomitantly exposed to both proneurotrophins and mature neurotrophins during development, disease, or after injury. We investigated the interaction of mature and proneurotrophin signaling in these CNS neurons. Kainic acid-induced seizures elicited production of pro-NGF by BF astrocytes before caspase activation in p75NTR-positive BF neurons, demonstrating local production of proneurotrophins under pathological conditions and suggesting apoptotic signaling in vivo. Mechanisms of proneurotrophin-induced death were analyzed in cultured BF neurons, and required both p75NTR and its coreceptor sortilin. Surprisingly, exposure to both mature neurotrophins and proneurotrophins demonstrated that Trk phosphorylation did not prevent pro-NGF-induced apoptosis via p75NTR. However, activation of PI3K (phosphatidylinositol 3-kinase)/Akt and MEK (mitogen-activated protein kinase kinase)/Erk pathways prevented pro-NGF-induced apoptosis, revealing a novel critical checkpoint in survival versus apoptotic signaling downstream of Trk activation, and suggesting that pro-NGF blocks survival signaling by preventing Akt and Erk activation. This study shows that proneurotrophins are produced in the brain under pathological conditions, and can elicit apoptosis of BF neurons even when Trk receptors are activated.
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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) | 0.000 | 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".