Metabolic Regulation of Hippocampal Neuroprogenitor Apoptosis After Irradiation
Bibliographic record
Abstract
The tumor suppressor p53 is an important regulator of cell fate response after DNA damage. Cell fate response following metabolic stresses has also been linked to p53-dependent pathways. In this study, we asked if 5'-adenosine monophosphate-activated protein kinase (AMPK), the master sensor of cellular energy balance, played a role in p53-dependent apoptosis of neural progenitor cells (NPCs) in the hippocampus after irradiation. Adult mice with targeted disruption of p53 or prkaa2 (gene that encodes AMPKα) in the brain were used to determine the role of p53 and AMPK, respectively, in radiation-induced apoptosis of NPCs in the hippocampus. The p53-dependent apoptosis of NPCs was associated with an increase in phospho-AMPK expression in the dentate gyrus at 8 hours after irradiation. Activation of AMPK was seen in granule neurons and subgranular NPCs. Compared with wildtype mice, apoptosis of NPCs was significantly attenuated in AMPK deficient (nestinCre: prkaa2fl/fl) mice after irradiation. AMPK deficiency did not however alter p53 activation in NPCs after irradiation. We conclude that AMPK may regulate apoptosis of hippocampal NPCs after irradiation. These findings suggest that cellular metabolism may play a role in determining cell fate response such as apoptosis after DNA damage in NPCs.
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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".