Dominant suppressor genes of p53-induced apoptosis in <i>Drosophila melanogaster</i>
Bibliographic record
Abstract
One of the major functions of programmed cell death (apoptosis) is the removal of cells that suffered oncogenic mutations, thereby preventing cancerous transformation. By making use of a Double-Headed-EP (DEP) transposon, a P element derivative made in our laboratory, we made an insertional mutagenesis screen in Drosophila melanogaster to identify genes that, when overexpressed, suppress the p53-activated apoptosis. The DEP element has Gal4-activatable, outward-directed UAS promoters at both ends, which can be deleted separately in vivo. In the DEP insertion mutants, we used the GMR-Gal4 driver to induce transcription from both UAS promoters and tested the suppression effect on the apoptotic rough eye phenotype generated by an activated UAS-p53 transgene. By DEP insertions, 7 genes were identified, which suppressed the p53-induced apoptosis. In 4 mutants, the suppression effect resulted from single genes activated by 1 UAS promoter (Pka-R2, Rga, crol, and Spt5). In the other 3 (Orct2, Polr2M, and stg), deleting either UAS promoter eliminated the suppression effect. In qPCR experiments, we found that the genes in the vicinity of the DEP insertion also showed an elevated expression level. This suggested an additive effect of the nearby genes on suppressing apoptosis. In the eukaryotic genomes, there are coexpressed gene clusters. Three of the DEP insertion mutants are included, and 2 are in close vicinity of separate coexpressed gene clusters. This raises the possibility that the activity of some of the genes in these clusters may help the suppression of the apoptotic cell death.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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) | 0.002 | 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".