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Record W4410497778 · doi:10.1111/febs.70136

Increased chromatin accessibility underpins senescence

2025· review· en· W4410497778 on OpenAlexafffund
Stéphane Lopes‐Paciencia, Gerardo Ferbeyre

Bibliographic record

VenueFEBS Journal · 2025
Typereview
Languageen
FieldMedicine
TopicTelomeres, Telomerase, and Senescence
Canadian institutionsUniversité de MontréalCentre Hospitalier de l’Université de Montréal
FundersInstitute of Cancer Research
KeywordsChromatinSenescenceTelomereBiologyCell biologyChromatin remodelingContext (archaeology)HistoneEpigenomeCellular senescenceEpigeneticsGeneticsDNA methylationPhenotypeGene expressionDNAGene

Abstract

fetched live from OpenAlex

Senescence is a cellular state induced by various stressors or extracellular signals, but a universal pathway that triggers this process irrespective of the initial stressor has yet to be identified. Recent data indicate that chromatin opening, particularly in the noncoding genome, is a hallmark of cellular senescence. We propose a model in which this increased chromatin accessibility mediated by transcription factors downstream of the senescence-inducing stressors acts as a decisive factor to commit cells toward the senescence fate. Engagement toward senescence is then determined by the balance between mechanisms that increase or decrease chromatin accessibility and can be influenced by modulating the activity of specific histone-modifying complexes. Traits of senescent cells, such as increased nuclear and nucleolar size, the secretion of pro-inflammatory cytokines, reduced rRNA biogenesis, telomere dysfunction, expression of retrotransposons and endogenous retroviruses, as well as DNA damage, can all be attributed to increased chromatin accessibility. This concept suggests potential targets to tilt the balance toward the senescence response in the context of future therapies against cancer and age-related diseases.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.957
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.057
GPT teacher head0.384
Teacher spread0.327 · 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 teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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

Citations9
Published2025
Admission routes2
Has abstractyes

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