Characterization of PIDD, a death domain-containing p53 target gene
Bibliographic record
Abstract
The p53 tumour suppressor promotes cell cycle arrest or apoptosis in response to diverse stress stimuli. p53-mediated cell death depends in large part on transcriptional upregulation of target genes. One of these targets, p53-induced protein with a death domain (PIDD), was shown to function as a mediator of p53-dependent apoptosis. Previous work in our lab demonstrated that antisense inhibition of PIDD expression attenuated p53-mediated apoptosis suggesting that PIDD expression is required for apoptosis. The work presented here is a characterization of the protein and the apoptotic pathways involved downstream of PIDD. Here we describe the generation and validation of a PIDD polyclonal antibody, and demonstrate its usefulness for Western blotting, immunoprecipitation and immunofluorescence (IF) analysis. These studies demonstrate that PIDD is a cytoplasmic protein and that PIDD is upregulated by p53 activation and in response to DNA damage. In addition, we show that PIDD-induced death and growth suppression in embryonic fibroblasts are dependent on the adaptor protein RAIDD (receptor-interacting protein (RIP)-associated ICH-1/CED-3 homologous protein with a death domain). We also provide evidence that PIDD-induced cell death is associated with the early activation of caspase-2, and later activation of caspase-3 and caspase-7. Our results also show that caspase-2-/- MEFs in contrast to RAIDD-/- MEFs are only partially resistant to PIDD. These findings suggest that caspase-2 contributes to PIDD-mediated cell death but that it is not the sole effector of this pathway.
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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 | 0.001 |
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".