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Record W2779643662 · doi:10.1111/gbb.12446

A role for activity‐dependent epigenetics in the development and treatment of major depressive disorder

2017· review· en· W2779643662 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGenes Brain & Behavior · 2017
Typereview
Languageen
FieldNeuroscience
TopicTryptophan and brain disorders
Canadian institutionsMcGill University
Fundersnot available
KeywordsEpigenomeEpigeneticsEpigenomicsDNA methylationMajor depressive disorderNeuroscienceHistoneAntidepressantStressorPsychologyBiologyGeneGeneticsCognitionHippocampusGene expression

Abstract

fetched live from OpenAlex

Chronic stressors, during developmental sensitive periods and beyond, contribute to the risk of developing psychiatric conditions, including major depressive disorder (MDD). Epigenetic mechanisms including DNA methylation and histone modifications, at key stress response and neurotrophin genes, are increasingly implicated in mediating this risk. Although the exact mechanisms through which stressful environmental stimuli alter the epigenome are still unclear, research from the learning and memory fields indicates that epigenomic marks can be altered, at least in part, through calcium-dependent signaling cascades in direct response to neuronal activity. In this review, we highlight key findings from the stress, MDD, and learning and memory fields to propose a model where stress regulates downstream cellular functioning through activity-dependent epigenetic changes. Furthermore, we suggest that both typical and novel antidepressant treatments may exert positive influence through similar, activity-dependent pathways.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.997
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.118
GPT teacher head0.374
Teacher spread0.255 · 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