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Record W2740847816 · doi:10.7554/elife.23783

A sharp Pif1-dependent threshold separates DNA double-strand breaks from critically short telomeres

2017· article· en· W2740847816 on OpenAlexafffund
Jonathan Strecker, Sonia Stinus, Mariana Pliego Caballero, Rachel K. Szilard, Michael Chang, Daniel Durocher

Bibliographic record

VenueeLife · 2017
Typearticle
Languageen
FieldMedicine
TopicTelomeres, Telomerase, and Senescence
Canadian institutionsLunenfeld-Tanenbaum Research InstituteUniversity of TorontoMount Sinai Hospital
FundersCanadian Institutes of Health ResearchKrembil FoundationNederlandse Organisatie voor Wetenschappelijk Onderzoek
KeywordsTelomereTelomeraseBiologyDNATelomerase RNA componentCell biologyMolecular biologyGeneticsTelomerase reverse transcriptaseGene

Abstract

fetched live from OpenAlex

DNA double-strand breaks (DSBs) and short telomeres are structurally similar, yet they have diametrically opposed fates. Cells must repair DSBs while blocking the action of telomerase on these ends. Short telomeres must avoid recognition by the DNA damage response while promoting telomerase recruitment. In Saccharomyces cerevisiae, the Pif1 helicase, a telomerase inhibitor, lies at the interface of these end-fate decisions. Using Pif1 as a sensor, we uncover a transition point in which 34 bp of telomeric (TG1-3)n repeat sequence renders a DNA end insensitive to Pif1 action, thereby enabling extension by telomerase. A similar transition point exists at natural chromosome ends, where telomeres shorter than ~40 bp are inefficiently extended by telomerase. This phenomenon is not due to known Pif1 modifications and we instead propose that Cdc13 renders TG34+ ends insensitive to Pif1 action. We contend that the observed threshold of Pif1 activity defines a dividing line between DSBs and telomeres.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.048
GPT teacher head0.335
Teacher spread0.287 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations28
Published2017
Admission routes2
Has abstractyes

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