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Record W4229873741 · doi:10.3410/f.725785109.793549699

Faculty Opinions recommendation of Distinct but Concerted Roles of ATR, DNA-PK, and Chk1 in Countering Replication Stress during S Phase.

2018· dataset· en· W4229873741 on OpenAlexaff
Frédéric Charron, Lukas Tamayo-Orrego

Bibliographic record

VenueFaculty Opinions – Post-Publication Peer Review of the Biomedical Literature · 2018
Typedataset
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsMontreal Clinical Research Institute
FundersNational Institutes of HealthWellcome TrustMassachusetts General Hospital
KeywordsReplication (statistics)DNA replicationComputational biologyDNAGeneticsDNA damageBiologyPsychologyVirology

Abstract

fetched live from OpenAlex

The ATR-Chk1 pathway is critical for DNA damage responses and cell cycle progression.Chk1 inhibition is more deleterious to cycling cells than ATR inhibition, raising questions about ATR and Chk1 functions in the absence of extrinsic replication stress.Here, we show that a key role of ATR in S phase is to coordinate RRM2 accumulation and origin firing.ATR inhibitor (ATRi) induces massive ssDNA accumulation and replication catastrophe in a fraction of early S-phase cells.In other S-phase cells, however, ATRi induces moderate ssDNA and triggers a DNA-PK and Chk1-mediated backup pathway to suppress origin firing.The backup pathway creates a threshold such that ATRi selectively kills cells under high replication stress, whereas Chk1 inhibitor induces cell death at a lower threshold.The levels of ATRi-induced ssDNA correlate with ATRi sensitivity in a panel of cell lines, suggesting that ATRi-induced ssDNA could be predictive of ATRi sensitivity in cancer cells.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.055
Threshold uncertainty score0.185

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0050.007
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0550.043

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.

Opus teacher head0.042
GPT teacher head0.436
Teacher spread0.395 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreDataset

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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