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Record W2775911035 · doi:10.4049/jimmunol.1701470

EZH2 Represses the B Cell Transcriptional Program and Regulates Antibody-Secreting Cell Metabolism and Antibody Production

2017· article· en· W2775911035 on OpenAlexfundno aff
Muyao Guo, Madeline J. Price, Dillon G. Patterson, Benjamin G. Barwick, Robert R Haines, Anna Kania, John Bradley, Troy D. Randall, Jeremy M. Boss, Christopher D. Scharer

Bibliographic record

VenueThe Journal of Immunology · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsnot available
FundersNational Institute of Allergy and Infectious DiseasesNational Institute of General Medical SciencesNational Institutes of HealthYork UniversityEmory University
KeywordsAntibodyCellMetabolismChemistryCell biologyBiologyMolecular biologyImmunologyBiochemistry

Abstract

fetched live from OpenAlex

Abstract Epigenetic remodeling is required during B cell differentiation. However, little is known about the direct functions of epigenetic enzymes in Ab-secreting cells (ASC) in vivo. In this study, we examined ASC differentiation independent of T cell help and germinal center reactions using mice with inducible or B cell–specific deletions of Ezh2. Following stimulation with influenza virus or LPS, Ezh2-deficient ASC poorly proliferated and inappropriately maintained expression of inflammatory pathways, B cell–lineage transcription factors, and Blimp-1–repressed genes, leading to fewer and less functional ASC. In the absence of EZH2, genes that normally gained histone H3 lysine 27 trimethylation were dysregulated and exhibited increased chromatin accessibility. Furthermore, EZH2 was also required for maximal Ab secretion by ASC, in part due to reduced mitochondrial respiration, impaired glucose metabolism, and poor expression of the unfolded-protein response pathway. Together, these data demonstrate that EZH2 is essential in facilitating epigenetic changes that regulate ASC fate, function, and metabolism.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.180
Threshold uncertainty score0.362

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.011
GPT teacher head0.283
Teacher spread0.272 · 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

Citations139
Published2017
Admission routes1
Has abstractyes

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