CITED2 Signals through Peroxisome Proliferator-Activated Receptor-γ to Regulate Death of Cortical Neurons after DNA Damage
Bibliographic record
Abstract
DNA damage is an important initiator of neuronal apoptosis and activates signaling events not yet fully defined. Using the camptothecin-induced DNA damage model in neurons, we previously showed that cyclin D1-associated cell cycle cyclin-dependent kinases (Cdks) (Cdk4/6) and p53 activation are two major events leading to activation of the mitochondrial apoptotic pathway. With gene array analyses, we detected upregulation of Cited2, a CBP (cAMP response element-binding protein-binding protein)/p300 interacting transactivator, in response to DNA damage. This upregulation was confirmed by reverse transcription-PCR and Western blot. CITED2 was functionally important because CITED2 overexpression promotes death, whereas CITED2 deficiency protects. Cited2 upregulation is upstream of the mitochondrial death pathway (BAX, Apaf1, or cytochrome c release) and appears to be independent of p53. However, inhibition of the Cdk4 blocked Cited2 induction. The Cited2 prodeath mechanism does not involve Bmi-1 or p53. Instead, Cited2 activates peroxisome proliferator-activated receptor-gamma (PPARgamma), an activity that we demonstrate is critical for DNA damage-induced death. These results define a novel neuronal prodeath pathway in which Cdk4-mediated regulation of Cited2 activates PPARgamma and consequently caspase.
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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".