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Record W4413915917 · doi:10.1016/j.redox.2025.103856

Oxidatively damaged DNA in DNA repair-deficient and ethanol-exposed fetal brains induces gene dysregulation and mitochondrial dysfunction associated with neurodevelopmental disorders

2025· article· en· W4413915917 on OpenAlexafffund
Ashley P. Cheng, Piriththiv Dhavarasa, Jana van Heeswyk, S Richards, Li Xuan, Aaron M. Shapiro, Peter G. Wells

Bibliographic record

VenueRedox Biology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism and Genetic Disorders
Canadian institutionsProvincial Health Services AuthorityUniversity of Toronto
FundersLeslie Dan Faculty of Pharmacy, University of TorontoCanadian Institutes of Health ResearchHospital for Sick ChildrenUniversity of Toronto
KeywordsMitochondrial DNADNA damageFetusGeneBiologyDNADNA repairGeneticsCell biologyMolecular biologyPregnancy

Abstract

fetched live from OpenAlex

Oxidatively damaged DNA caused by reactive oxygen species (ROS) in the fetal brain contributes to neurodevelopmental disorders (NDDs), but the mechanism is unclear. We investigated the impact of this DNA damage on the developing fetal brain using a DNA repair-deficient oxoguanine glycosylase 1 (Ogg1) knockout (KO) mouse model, exposed during pregnancy to physiological (saline)- and ethanol (EtOH)-enhanced ROS levels. Oxidatively damaged DNA in saline-exposed Ogg1 KO vs. wild-type (WT) fetal brains was increased, and further enhanced by EtOH exposure. These OGG1-and EtOH-dependent patterns of DNA damage were reflected in: (a) increased gene dysregulation in saline-exposed KO brains, and greatly exacerbated by EtOH, notably in the long-term synaptic potentiation pathway, crucial for learning and memory; (b) impaired mitochondrial metabolism in cultured primary Ogg1 KO neurons; and, (c) sex-dependent learning and memory disorders. These results suggest oxidatively damaged DNA in DNA repair-deficient fetal brains contributes to NDDs by altering gene expression and mitochondrial metabolism.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.849
Threshold uncertainty score0.732

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 head0.007
GPT teacher head0.226
Teacher spread0.219 · 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 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

Citations2
Published2025
Admission routes2
Has abstractyes

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