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Record W2771696550 · doi:10.1038/s41467-017-02225-5

HEB is required for the specification of fetal IL-17-producing γδ T cells

2017· article· en· W2771696550 on OpenAlexafffund
Tracy S. H. In, Ashton Trotman‐Grant, Shawn P. Fahl, Edward L.Y. Chen, Payam Zarin, Amanda J. Moore, David L. Wiest, Juan Carlos Zúñiga‐Pflücker, Michele K. Anderson

Bibliographic record

VenueNature Communications · 2017
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsCanada Research ChairsUniversity of TorontoSunnybrook Health Science Centre
FundersNational Institutes of HealthNational Institute of Allergy and Infectious DiseasesCanadian Institutes of Health ResearchSunnybrook Research Institute
KeywordsBiologyRAR-related orphan receptor gammaInterleukin 23PhenotypeCell biologyImmune systemGeneImmunologyTranscription factorGeneticsInterleukin 17

Abstract

fetched live from OpenAlex

Abstract IL-17-producing γδ T (γδT17) cells are critical components of the innate immune system. However, the gene networks that control their development are unclear. Here we show that HEB (HeLa E-box binding protein, encoded by Tcf12 ) is required for the generation of a newly defined subset of fetal-derived CD73 − γδT17 cells. HEB is required in immature CD24 + CD73 − γδ T cells for the expression of Sox4 , Sox13 , and Rorc , and these genes are repressed by acute expression of the HEB antagonist Id3. HEB-deficiency also affects mature CD73 + γδ T cells, which are defective in RORγt expression and IL-17 production. Additionally, the fetal TCRγ chain repertoire is altered, and peripheral Vγ4 γδ T cells are mostly restricted to the IFNγ-producing phenotype in HEB-deficient mice. Therefore, our work identifies HEB-dependent pathways for the development of CD73 + and CD73 − γδT17 cells, and provides mechanistic evidence for control of the γδT17 gene network by HEB.

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 score0.008

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 communication0.0000.000
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 head0.047
GPT teacher head0.316
Teacher spread0.269 · 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

Citations66
Published2017
Admission routes2
Has abstractyes

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Same venueNature CommunicationsSame topicImmune Cell Function and InteractionFrench-language works237,207