p53 Activation Domain 1 Is Essential for PUMA Upregulation and p53-Mediated Neuronal Cell Death
Bibliographic record
Abstract
The p53 tumor suppressor gene has been implicated in the regulation of apoptosis in a number of different neuronal death paradigms. Because of the importance of p53 in neuronal injury, we questioned the mechanism underlying p53-mediated apoptosis in neurons. Using adenoviral-mediated gene delivery, reconstitution experiments, and mice carrying a knock-in mutation in the endogenous p53 gene, we show that the transactivation function of p53 is essential to induce neuronal cell death. Although p53 possesses two transactivation domains that can activate p53 targets independently, we demonstrate that the first activation domain (ADI) is required to drive apoptosis after neuronal injury. Furthermore, the BH3-only proteins Noxa and PUMA exhibit differential regulation by the two transactivation domains. Here, we show that Noxa can be induced by either activation domain, whereas PUMA induction requires both activation domains to be intact. Unlike Noxa, the upregulation of PUMA alone is sufficient to induce neuronal cell death. We demonstrate, therefore, that the first transactivation domain of p53 is indispensable for the induction of neuronal cell death.
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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 | 0.001 |
| 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".