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Record W2084400594 · doi:10.4161/cc.7.23.7186

DNA damage-induced upregulation of miR-709 in the germline downregulates BORIS to counteract aberrant DNA hypomethylation

2008· article· en· W2084400594 on OpenAlexaff
Jan Tamminga, Palak Kathiria, Igor Koturbash, Olga Kovalchuk

Bibliographic record

VenueCell Cycle · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsBiologyDNA damageDNA methylationmicroRNAGermlineMolecular biologyDownregulation and upregulationDNA repairMethylationRegulation of gene expressionDNAGeneGeneticsCancer researchGene expressionCell biology

Abstract

fetched live from OpenAlex

MicroRNAs as potent regulators of gene expression are involved in spermatogenesis, yet their role in response of germline to genotoxic stress is obscure. We studied the microRNAome profile of X-ray irradiated mouse testes using the microarray technique. We found that radiation exposure significantly affected microRNA expression in testes. Mir-709 was the most abundant in both control and irradiated testes, and a big difference in miR-709 levels was observed between the control and exposed group. We found that miR-709 targets the Brother of the Regulator of Imprinted Sites (BORIS), an important regulator of DNA methylation and imprinting. Here, we for the first time show that the DNA damage-induced and ATR/Rfx1-mediated increase of miR-709 expression in exposed testes may be a protective mechanism that effectively decreases a cellular level of BORIS to prevent massive aberrant erasure of DNA methylation after radiation exposure.

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 score0.001
Threshold uncertainty score0.004

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.015
GPT teacher head0.256
Teacher spread0.241 · 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

Citations58
Published2008
Admission routes1
Has abstractyes

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