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Satb1 Is an Activity-Modulated Transcription Factor Required for the Terminal Differentiation and Connectivity of Medial Ganglionic Eminence-Derived Cortical Interneurons

2012· article· en· W2007091385 on OpenAlexaff
Jennie Close, Han Xu, Natalia De Marco García, Renata Batista‐Brito, Elsa Rossignol, Bernardo Rudy, Gord Fishell

Bibliographic record

VenueJournal of Neuroscience · 2012
Typearticle
Languageen
FieldNeuroscience
TopicNeurogenesis and neuroplasticity mechanisms
Canadian institutionsUniversité de Montréal
FundersNational Institute of Neurological Disorders and StrokeNational Institute of Mental Health
KeywordsGanglionic eminenceInterneuronParvalbuminBiologyNeuroscienceTranscription factorExcitatory postsynaptic potentialInhibitory postsynaptic potentialGABAergicGeneGenetics

Abstract

fetched live from OpenAlex

Although previous work identified transcription factors crucial for the specification and migration of parvalbumin (PV)-expressing and somatostatin (SST)-expressing interneurons, the intrinsic factors required for the terminal differentiation, connectivity, and survival of these cell types remain uncharacterized. Here we demonstrate that, within subpopulations of cortical interneurons, Satb1 (special AT-rich binding protein) promotes terminal differentiation, connectivity, and survival in interneurons that express PV and SST. We find that conditional removal of Satb1 in mouse interneurons results in the loss of a majority of SST-expressing cells across all cortical layers, as well as some PV-expressing cells in layers IV and VI, by postnatal day 21. SST-expressing cells initially migrate to the cortex in Satb1 mutant mice, but receive reduced levels of afferent input and begin to die during the first postnatal week. Electrophysiological characterization indicates that loss of Satb1 function in interneurons results in a loss of functional inhibition of excitatory principal cells. These data suggest that Satb1 is required for medial ganglionic eminence-derived interneuron differentiation, connectivity, and survival.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.158
Threshold uncertainty score0.532

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.091
GPT teacher head0.309
Teacher spread0.218 · 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

Citations146
Published2012
Admission routes1
Has abstractyes

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