Abstract 623: The PARP3- and ATM-dependent phosphorylation of APLF facilitates DNA double-strand break repair.
Bibliographic record
Abstract
Abstract APLF is a forkhead associated (FHA)-containing protein with poly(ADP-ribose)-binding zinc finger (PBZ) domains, which undergoes ionizing radiaiton (IR)-induced and ATM-dependent phosphorylation at serine-116 (Ser116). Here we demonstrate that the phosphorylation of APLF at Ser116 in human U2OS cells by ATM is dependent on PARP3 levels and the APLF PBZ domains. The interaction of APLF at sites of DNA damage was diminished by the single substitution of APLF Ser116 to alanine, and the cellular depletion or chemical inhibition of ATM or PARP3 also altered the retention of APLF at sites of laser-induced DNA damage, and impaired the accumulation of Ser116-phosphorylated APLF at IR-induced γH2AX foci in human cells. The data further suggest that ATM and PARP3 participate in a common signaling pathway to facilitate APLF-Ser116 phosphorylation, which, in turn, appears to be required for efficient DNA double-strand break (DSB) repair kinetics and cell survival following IR. Collectively, these findings provide a more detailed understanding of the molecular pathway that leads to the phosphorylation of APLF following DNA damage, and suggest that Ser116-APLF phosphorylation facilitates APLF-dependent DSB repair. Citation Format: Christine A. Koch, Amanda L. Fenton, Purnata Shirodkar, Li Meng. The PARP3- and ATM-dependent phosphorylation of APLF facilitates DNA double-strand break repair. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 623. doi:10.1158/1538-7445.AM2013-623
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".