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Record W2093982674 · doi:10.1002/eji.201040298

c‐Rel but not NF‐κB1 is important for T regulatory cell development

2010· article· en· W2093982674 on OpenAlexafffund
Elissa K. Deenick, Alisha R. Elford, Marc Pellegrini, Håkan Hall, Tak W. Mak, Pamela S. Ohashi

Bibliographic record

VenueEuropean Journal of Immunology · 2010
Typearticle
Languageen
FieldImmunology and Microbiology
TopicT-cell and B-cell Immunology
Canadian institutionsUniversity of TorontoOntario Institute for Cancer Research
FundersCanadian Institutes of Health Research
KeywordsBiologyCell biologyT-cell receptorCD28Treg cellSignal transductionT cellReceptorImmunologyIL-2 receptorImmune systemGenetics

Abstract

fetched live from OpenAlex

Regulatory T (Treg) cells are crucial for maintaining peripheral tolerance and controlling T-cell responses. The generation of Treg in the thymus requires TCR triggering and CD28 costimulation. Engagement of these receptors induces a number of signalling pathways, including the activation of NF-kappaB via PKCtheta and the Bcl-10/CARMA1/MALT complex. Previous studies have shown that PKCtheta, Bcl-10 and CARMA1 are important for Treg development. It is unclear, however, whether different members of the NF-kappaB family contribute to Treg development or homeostasis. In this study, we show that Treg numbers are reduced in the absence of c-Rel but not NF-kappaB1 (p50). Furthermore, using mixed bone marrow chimeras from WT and KO animals, we demonstrate that the requirement for PKCtheta, Bcl-10 and c-Rel is T-cell intrinsic, and cannot be rescued by the presence of WT cells. Therefore, c-Rel and NF-kappaB1 have differential roles in Treg development.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.376
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.011
GPT teacher head0.206
Teacher spread0.195 · 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; both teacher heads agree on what is shown here.

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

Citations64
Published2010
Admission routes2
Has abstractyes

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