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Abnormal Microglia and Enhanced Inflammation-Related Gene Transcription in Mice with Conditional Deletion of<i>Ctcf</i>in<i>Camk2a-Cre</i>-Expressing Neurons

2017· article· en· W2769387217 on OpenAlexfundno aff
Bryan E. McGill, Ruteja A. Barve, Susan E. Maloney, Amy Strickland, Nicholas Rensing, Peter L. Wang, Michael Wong, Richard D. Head, David F. Wozniak, Jeffrey Milbrandt

Bibliographic record

VenueJournal of Neuroscience · 2017
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsnot available
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Center for Advancing Translational SciencesNational Cancer InstituteIntellectual and Developmental Disabilities Research Center, Washington University School of Medicine in St. LouisAlvin J. Siteman Cancer CenterNational Institutes of HealthNational Center for Research ResourcesNational Institute of Neurological Disorders and StrokeInstitute of Clinical and Translational SciencesIntellectual and Developmental Disabilities Research CenterNational Institute on AgingHope Center for Neurological DisordersNational Heart, Lung, and Blood InstituteMcGill University
KeywordsCTCFBiologyMicrogliaChromatinForebrainTranscription factorCell biologyNeuroscienceGeneticsGeneInflammationImmunologyCentral nervous systemEnhancer

Abstract

fetched live from OpenAlex

CCCTC-binding factor (CTCF) is an 11 zinc finger DNA-binding domain protein that regulates gene expression by modifying 3D chromatin structure. Human mutations inCTCFcause intellectual disability and autistic features. Knocking outCtcfin mouse embryonic neurons is lethal by neonatal age, but the effects of CTCF deficiency in postnatal neurons are less well studied. We knocked outCtcfpostnatally in glutamatergic forebrain neurons under the control ofCamk2a-Cre. CtcfloxP/loxP;Camk2a-Cre+(CtcfCKO) mice of both sexes were viable and exhibited profound deficits in spatial learning/memory, impaired motor coordination, and decreased sociability by 4 months of age.CtcfCKO mice also had reduced dendritic spine density in the hippocampus and cerebral cortex. Microarray analysis of mRNA fromCtcfCKO mouse hippocampus identified increased transcription of inflammation-related genes linked to microglia. Separate microarray analysis of mRNA isolated specifically fromCtcfCKO mouse hippocampal neurons by ribosomal affinity purification identified upregulation of chemokine signaling genes, suggesting crosstalk between neurons and microglia inCtcfCKO hippocampus. Finally, we found that microglia inCtcfCKO mouse hippocampus had abnormal morphology by Sholl analysis and increased immunostaining for CD68, a marker of microglial activation. Our findings confirm thatCtcfKO in postnatal neurons causes a neurobehavioral phenotype in mice and provide novel evidence that CTCF depletion leads to overexpression of inflammation-related genes and microglial dysfunction. SIGNIFICANCE STATEMENTCCCTC-binding factor (CTCF) is a DNA-binding protein that organizes nuclear chromatin topology. Mutations inCTCFcause intellectual disability and autistic features in humans. CTCF deficiency in embryonic neurons is lethal in mice, but mice with postnatal CTCF depletion are less well studied. We find that mice lackingCtcfinCamk2a-expressing neurons (CtcfCKO mice) have spatial learning/memory deficits, impaired fine motor skills, subtly altered social interactions, and decreased dendritic spine density. We demonstrate thatCtcfCKO mice overexpress inflammation-related genes in the brain and have microglia with abnormal morphology that label positive for CD68, a marker of microglial activation. Our findings suggest that inflammation and dysfunctional neuron–microglia interactions are factors in the pathology of CTCF deficiency.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.023
GPT teacher head0.259
Teacher spread0.236 · 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 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

Citations81
Published2017
Admission routes1
Has abstractyes

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