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Record W1578676287 · doi:10.1111/gbb.12058

Emerging roles for <scp>MEF2</scp> transcription factors in memory

2013· review· en· W1578676287 on OpenAlexafffund
Asim J. Rashid, Christina Cole, Sheena A. Josselyn

Bibliographic record

VenueGenes Brain & Behavior · 2013
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics and Neurodevelopmental Disorders
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsMef2Transcription factorNeuroscienceSynaptic plasticityEnhancerBiologyTranscription (linguistics)Cell biologyGeneticsGeneReceptor

Abstract

fetched live from OpenAlex

In the brain, transcription factors are critical for linking external stimuli to protein production, enabling neurons and neuronal networks to adapt to the ever-changing landscape. Gene transcription and protein synthesis are also vital for the formation of long-term memory. Members of the myocyte enhancer factor-2 (MEF2) family of transcription factors have a well-characterized role in the development of a variety of tissues, but their role in the adult brain is only beginning to be understood. Recent evidence indicates that MEF2 regulates the structural and synaptic plasticity underlying memory formation. However, in stark contrast to most other transcription factors implicated in memory, MEF2-mediated transcription constrains (rather than promotes) memory formation. Here, we review recent data examining the role of MEF2 in adult memory formation in rodents.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.037
GPT teacher head0.304
Teacher spread0.267 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations78
Published2013
Admission routes2
Has abstractyes

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