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Record W2786912169 · doi:10.1016/j.celrep.2018.01.020

Learning and Age-Related Changes in Genome-wide H2A.Z Binding in the Mouse Hippocampus

2018· article· en· W2786912169 on OpenAlexafffund
Gilda Stefanelli, Amber Azam, Brandon J. Walters, Mark A. Brimble, Caroline P. Gettens, Pascale Bouchard-Cannon, Hai‐Ying Mary Cheng, Andrew M. Davidoff, Klotilda Narkaj, Jeremy J. Day, Andrew Kennedy, Iva B. Zovkic

Bibliographic record

VenueCell Reports · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
FundersNational Institute of General Medical SciencesNational Institute on Drug AbuseNatural Sciences and Engineering Research Council of CanadaNational Institutes of HealthConnaught FundHospital for Sick Children
KeywordsHistoneNeuroplasticityHippocampusBiologyTranscription (linguistics)NucleosomeGeneGene expressionBasal (medicine)NeuroscienceGeneticsEndocrinology

Abstract

fetched live from OpenAlex

Histone variants were recently discovered to regulate neural plasticity, with H2A.Z emerging as a memory suppressor. Using whole-genome sequencing of the mouse hippocampus, we show that basal H2A.Z occupancy is positively associated with steady-state transcription, whereas learning-induced H2A.Z removal is associated with learning-induced gene expression. AAV-mediated H2A.Z depletion enhanced fear memory and resulted in gene-specific alterations of learning-induced transcription, reinforcing the role of H2A.Z as a memory suppressor. H2A.Z accumulated with age, although it remained sensitive to learning-induced eviction. Learning-related H2A.Z removal occurred at largely distinct genes in young versus aged mice, suggesting that H2A.Z is subject to regulatory shifts in the aged brain despite similar memory performance. When combined with prior evidence of H3.3 accumulation in neurons, our data suggest that nucleosome composition in the brain is reorganized with age.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.294

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.009
GPT teacher head0.239
Teacher spread0.230 · 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

Citations102
Published2018
Admission routes2
Has abstractyes

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