The Rad9A checkpoint protein is required for nuclear localization of the claspin adaptor protein
Bibliographic record
Abstract
The interaction between the 911 complex, via Rad9A, and Claspin is required for activation of the Chk1-mediated checkpoint response, along with ATR, TopBp1, and the 911 clamp loader complex Rad17/RFC. Despite the importance of the Rad9A-Claspin interaction in the cell cycle, this interaction has yet to be characterized. In this work we show this interaction persists in a variety of different conditions. During the course of this study we also determined the nuclear localization of Rad9A affected the localization of the Claspin protein, leading us to the conclusion that Rad9A is able to affect Claspin cellular localization. This was verified experimentally using a Rad9A-null cell line and reconstitution of Wt Rad9A. We also show that in meS cells the Rad9A paralog, Rad9B, is also capable of affecting Claspin localization. Together, these data suggest that Rad9 plays a role in locating Claspin to sites of DNA damage, facilitating its role during the Chk1-mediated checkpoint response. Since disruption of both Rad9A and Claspin has been shown to abolish Chk1 activation, we postulate that Rad9A-mediated Claspin localization is a vital step during checkpoint activation.
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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".