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Record W2079818797 · doi:10.1139/o10-138

Activation and function of immediate-early genes in the nervous systemThis paper is one of a selection of papers in a Special Issue entitled 31st Annual International Asilomar Chromatin and Chromosomes Conference, and has undergone the Journal’s usual peer review process.

2011· review· en· W2079818797 on OpenAlexafffundvenue
Beatriz Pérez-Cadahı́a, Bojan Drobic, James Davie

Bibliographic record

VenueBiochemistry and Cell Biology · 2011
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics and Neurodevelopmental Disorders
Canadian institutionsUniversity of Manitoba
FundersCanadian Institutes of Health ResearchSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsNeuroscienceBiologyChromatinNeuroplasticityImmediate early geneGeneNervous systemPhenotypeTranscription factorFunction (biology)PsychologyGeneticsGene expression

Abstract

fetched live from OpenAlex

Immediate-early genes have important roles in processes such as brain development, learning, and responses to drug abuse. Further, immediate-early genes play an essential role in cellular responses that contribute to long-term neuronal plasticity. Neuronal plasticity is a characteristic of the nervous system that is not limited to the first stages of brain development but persists in adulthood and seems to be an inherent feature of everyday brain function. The plasticity refers to the neuron's capability of showing short- or long-lasting phenotypic changes in response to different stimuli and cellular scenarios. In this review, we focus on the immediate-early genes encoding transcription factors (AP-1 and Egr) that are relevant for neuronal responses. Our current understanding of the mechanisms involved in the induction of the immediate-early genes is presented.

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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.021
GPT teacher head0.254
Teacher spread0.233 · 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

Citations138
Published2011
Admission routes3
Has abstractyes

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