DNA Damage and Oxidative Stress Induced-p53 Activity In Astrocytes causes Growth Arrest
Bibliographic record
Abstract
An increasing body of evidence suggests that astrocytes play a key role in modulating neuronal fate during acute and chronic neurodegenerative conditions. Following CNS injury, an upregulation of p53 has been noted in both neurons and reactive astrocytes. p53 is an extremely important protein in determining cell fate decisions and its activation can result in the transcriptional induction of target genes that regulate apoptosis, autophagy, senescence and cell-cycle arrest. We found that p53 is upregulated in primary cortical astrocytes following oxidative stress and DNA damage and that this upregulation results in the p53-dependent transcriptional induction of several target genes involved in the induction of apoptosis, autophagy and cell-cycle arrest. However, we found that oxidative stress and DNA damage induced p53 activation did not cause a significant induction of apoptosis or autophagy in astrocytes but preferentially induced cell cycle arrest. Specifically we found that p53 activation resulted in a significant induction of the cyclin-dependent kinase inhibitor p21 and a marked reduction in astrocyte proliferation as determined by XTT assay and BrdU labelling. These processes were found to be p53-dependent as they were abrogated in p53-deficient astrocytes. In summary we have determined that the primary effect of p53 activation in astrocytes in the induction of cell cycle arrest which may limit astrogliosis during CNS injury.
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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) | 0.002 | 0.001 |
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".