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Record W2754869002 · doi:10.4049/jimmunol.1700888

Cutting Edge: Endogenous IFN-β Regulates Survival and Development of Transitional B Cells

2017· article· en· W2754869002 on OpenAlexaff
Jennie A Hamilton, Qi Wu, PingAr Yang, Bao Luo, Shanrun Liu, Huixian Hong, Jun Li, Mark R. Walter, Eleanor N. Fish, Hui‐Chen Hsu, John D. Mountz

Bibliographic record

VenueThe Journal of Immunology · 2017
Typearticle
Languageen
FieldImmunology and Microbiology
TopicT-cell and B-cell Immunology
Canadian institutionsUniversity of TorontoUniversity Health Network
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Cancer InstituteNational Institute of Allergy and Infectious DiseasesU.S. Department of Veterans Affairs
KeywordsBiologyB cellTLR7Downregulation and upregulationCell biologyEndogenySpleenImmune systemImmunologyGeneGeneticsAntibodyInnate immune systemToll-like receptorEndocrinology

Abstract

fetched live from OpenAlex

Abstract The transitional stage of B cell development is a formative stage in the spleen where autoreactive specificities are censored as B cells gain immune competence, but the intrinsic and extrinsic factors regulating survival of transitional stage 1 (T1) B cells are unknown. We report that B cell expression of IFN-β is required for optimal survival and TLR7 responses of transitional B cells in the spleen and was overexpressed in T1 B cells from BXD2 lupus-prone mice. Single-cell gene expression analysis of B6 Ifnb+/+ versus B6 Ifnb−⁄– T1 B cells revealed heterogeneous expression of Ifnb in wild-type B cells and distinct gene expression patterns associated with endogenous IFN-β. Single-cell analysis of BXD2 T1 B cells revealed that Ifnb is expressed in early T1 B cell development with subsequent upregulation of Tlr7 and Ifna1. Together, these data suggest that T1 B cell expression of IFN-β plays a key role in regulating responsiveness to external factors.

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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.027
GPT teacher head0.229
Teacher spread0.202 · 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

Citations35
Published2017
Admission routes1
Has abstractyes

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