MétaCan
Menu
Back to cohort
Record W2036363758 · doi:10.3389/fgene.2014.00411

SUV39H1 downregulation induces deheterochromatinization of satellite regions and senescence after exposure to ionizing radiation

2014· article· en· W2036363758 on OpenAlexaff
Corinne Sidler, Dongping Li, Bo Wang, Igor Kovalchuk, Olga Kovalchuk

Bibliographic record

VenueFrontiers in Genetics · 2014
Typearticle
Languageen
FieldMedicine
TopicTelomeres, Telomerase, and Senescence
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsDownregulation and upregulationSenescenceRadiation sensitivityCell cycleBiologyEpigeneticsDNA damageIonizing radiationCancer researchCell cycle checkpointCell biologyHistone H3MethyltransferaseDNA repairApoptosisHistoneGeneGeneticsDNAIrradiationMethylation

Abstract

fetched live from OpenAlex

While the majority of cancer patients are exposed to ionizing radiation during diagnostic and therapeutic procedures, age-dependent differences in radiation sensitivity are not yet well understood. Radiation sensitivity is characterized by the appearance of side effects to radiation therapy, such as secondary malignancies, developmental deficits, and compromised immune function. However, the knowledge of the molecular mechanisms that trigger these side effects is incomplete. Here we used an in vitro system and showed that low-senescent normal human diploid fibroblasts (WI-38) senesce in response to 5 Gy IR, while highly senescent cultures do not show changes in cell cycle regulation and only a slight increase in the percentage of senescent cells. Our study shows that this is associated with changes in the expression of genes responsible for cell cycle progression, apoptosis, DNA repair, and aging, as well as transcriptional and epigenetic regulators. Furthermore, we propose a role of the downregulation of SUV39H1 expression, a histone methyltransferase that specifically trimethylates H3K9, and the corresponding reduction in H3K9me3 levels in the establishment of IR-induced senescence.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.195
Threshold uncertainty score0.519

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.229
Teacher spread0.220 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations15
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in GeneticsSame topicTelomeres, Telomerase, and SenescenceFrench-language works237,207