Chk2 regulates irradiation-induced, p53-mediated apoptosis in <i>Drosophila</i>
Bibliographic record
Abstract
The tumor suppressor function of p53 has been attributed to its ability to regulate apoptosis and the cell cycle. In mammals, DNA damage, aberrant growth signals, chemotherapeutic agents, and UV irradiation activate p53, a process that is regulated by several posttranslational modifications. In Drosophila melanogaster, however, the regulation modes of p53 are still unknown. Overexpression of D. melanogaster p53 (Dmp53) in the eye induced apoptosis, resulting in a small eye phenotype. This phenotype was markedly enhanced by coexpression with D. melanogaster Chk2 (DmChk2) and was almost fully rescued by coexpression with a dominant-negative (DN), kinase-dead form of DmChk2. DN DmChk2 also inhibited Dmp53-mediated apoptosis in response to DNA damage, whereas overexpression of Grapes (Grp), the Drosophila Chk1-homolog, and its DN mutant had no effect on Dmp53-induced phenotypes. DmChk2 also activated the Dmp53 transactivation activity in cultured cells. Mutagenesis of Dmp53 amino terminal Ser residues revealed that Ser-4 is critical for its responsiveness toward DmChk2. DmChk2 activates the apoptotic activity of Dmp53 and Ser-4 is required for this effect. Contrary to results in mammals, Grapes, the Drosophila Chk1-homolog, is not involved in regulating Dmp53. Chk2 may be the ancestral regulator of p53 function.
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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".