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Record W2121360960 · doi:10.1093/intimm/dxl019

IL-4 influences the differentiation and the susceptibility to activation-induced cell death of human naive CD8+ T cells

2006· article· en· W2121360960 on OpenAlexafffund
Catherine Riou, Alain R. Dumont, Bader Yassine‐Diab, Elias K. Haddad, Rafick‐Pierre Sékaly

Bibliographic record

VenueInternational Immunology · 2006
Typearticle
Languageen
FieldImmunology and Microbiology
TopicT-cell and B-cell Immunology
Canadian institutionsHôpital Saint-Luc
FundersCanadian Institutes of Health ResearchCanada Research Chairs
KeywordsIL-2 receptorT cellCD8Cell biologyT-cell receptorGranzyme BCytotoxic T cellBiologyNaive T cellImmunologyChemistryAntigenImmune systemIn vitroBiochemistry

Abstract

fetched live from OpenAlex

It is now well established that the cytokine environment influences the activation, differentiation, proliferation and death of T lymphocytes during the primary response to antigen. Using an in vitro model, we investigated the influence of IL-4, added at the onset of TCR stimulation, on phenotypic and functional markers of naive CD8+ T cell activation including the up-regulation of activation markers, proliferation as well as the susceptibility to activation-induced cell death (AICD). We report that IL-4, unlike IL-2 added at the onset of repeated TCR stimulation of naive CD8+ T cells prevents AICD, in part due to its ability to maintain the level of the survival-related protein Bcl-2. Moreover, TCR-triggered activation of naive CD8+ T cells in the presence of IL-4 leads to the development of a CD8+ T cell subset that proliferates normally, but which fails to exhibit characteristic activation parameters such as the up-regulation of CD25 and Granzyme B. Taken together, these results demonstrate that exposure to IL-4 during primary activation influences CD8+ T cell differentiation by inducing the development of a sub-population of AICD-resistant, proliferation-competent cells that do not show some of the typical features of CD8+ T cell activation.

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)0.000
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 score0.080
Threshold uncertainty score0.581

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.012
GPT teacher head0.244
Teacher spread0.232 · 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

Citations23
Published2006
Admission routes2
Has abstractyes

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