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Record W2040931699 · doi:10.1182/blood-2007-08-108050

CD28 provides T-cell costimulation and enhances PI3K activity at the immune synapse independently of its capacity to interact with the p85/p110 heterodimer

2007· article· en· W2040931699 on OpenAlexaff
Fabien Garçon, Daniel T. Patton, Juliet L. Emery, Emilio Hirsch, Robert Rottapel, Takehiko Sasaki, Klaus Okkenhaug

Bibliographic record

VenueBlood · 2007
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsPrincess Margaret Cancer CentreOntario Institute for Cancer Research
FundersBiotechnology and Biological Sciences Research CouncilDirectorate for Biological Sciences
KeywordsImmunological synapseCell biologyCD28Immune systemSynapsePI3K/AKT/mTOR pathwayT cellBiologyNeuroscienceChemistrySignal transductionImmunologyT-cell receptor

Abstract

fetched live from OpenAlex

Activation of PI3K is among the earliest signaling events observed in T cells after conjugate formation with antigen-presenting cells (APCs). The relevant PI3K catalytic isoform and relative contribution of the TcR and CD28 to PI3K activity at the immune synapse have not been determined unequivocally. Using a quantitative imaging-based assay, we show that the PI3K activity at the T cell-APC contact area is dependent on the p110delta, but not the p110gamma, isoform of PI3K. CD28 enhanced PIP3 production at the T-cell synapse independently of its YMNM PI3K-recruitment motif that instead was required for efficient PKC recruitment. CD28 could partially compensate for the lack of p110delta activity during T-cell activation, which indicates that CD28 and p110delta act in parallel and complementary pathways to activate T cells. Consistent with this, CD28 and p110delta double-deficient mice were severely immune compromised. We therefore suggest that combined pharmaceutic targeting of p110delta activity and CD28 costimulation has potent therapeutic potential.

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 score0.028
Threshold uncertainty score0.342

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 studies0.0000.000
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 head0.010
GPT teacher head0.225
Teacher spread0.215 · 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

Citations147
Published2007
Admission routes1
Has abstractyes

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