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Record W4210262561 · doi:10.1016/j.ynstr.2022.100434

Epigenetic mechanisms impacted by chronic stress across the rodent lifespan

2022· article· en· W4210262561 on OpenAlexafffund
Angie Dion, Paula Muñoz, Tamara B. Franklin

Bibliographic record

VenueNeurobiology of Stress · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEpigenomeEpigeneticsOffspringRodentNeuroscienceAnxietyBiologyPsychological resiliencePrenatal stressChronic stressPsychologyDevelopmental psychologyDNA methylationGeneticsPregnancyPsychiatryEcology

Abstract

fetched live from OpenAlex

Exposures to stress at all stages of development can lead to long-term behavioural effects, in part through changes in the epigenome. This review describes rodent research suggesting that stress in prenatal, postnatal, adolescent and adult stages leads to long-term changes in epigenetic regulation in the brain which have causal impacts on rodent behaviour. We focus on stress-induced epigenetic changes that have been linked to behavioural deficits including poor learning and memory, and increased anxiety-like and depressive-like behaviours. Interestingly, aspects of these stress-induced behavioural changes can be transmitted to offspring across several generations, a phenomenon that has been proposed to result via epigenetic mechanisms in the germline. Here, we also discuss evidence for the differential impact of stress on the epigenome in males and females, conscious of the fact that the majority of published studies have only investigated males. This has led to a limited picture of the epigenetic impact of stress, highlighting the need for future studies to investigate females as well as males.

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 score0.003

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 head0.007
GPT teacher head0.254
Teacher spread0.247 · 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

Citations48
Published2022
Admission routes2
Has abstractyes

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