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Record W2141427930 · doi:10.4049/jimmunol.165.3.1352

CTLA-4 (CD152) Can Inhibit T Cell Activation by Two Different Mechanisms Depending on Its Level of Cell Surface Expression

2000· article· en· W2141427930 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Journal of Immunology · 2000
Typearticle
Languageen
FieldImmunology and Microbiology
TopicT-cell and B-cell Immunology
Canadian institutionsWestern University
Fundersnot available
KeywordsCD28Cell biologyCTLA-4T cellCytoplasmCellChemistrySignal transductionBiologyImmunologyBiochemistryImmune system

Abstract

fetched live from OpenAlex

CTLA-4 (CD152) engagement results in down-regulation of T cell activation. Two mechanisms have been postulated to explain CTLA-4 inhibition of T cell activation: negative signaling and competitive antagonism of CD28:B7-mediated costimulation. We assessed the contributions of these two mechanisms using a panel of T cell lines expressing human CTLA-4 with mutations in the cytoplasmic region. Under conditions of B7-independent costimulation, inhibition of IL-2 production following CTLA-4 engagement required the CTLA-4 cytoplasmic region. In contrast, under B7-dependent costimulation, inhibition of IL-2 production by CTLA-4 engagement was directly proportional to CTLA-4 cell surface levels and did not require its cytoplasmic region. Thus, CTLA-4 down-regulates T cell activation by two different mechanisms-delivery of a negative signal or B7 sequestration-that are operational depending on the levels of CTLA-4 surface expression. These two mechanisms may have distinct functional outcomes: rapid inhibition of T cell activation or induction of T cell anergy.

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.

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)0.001
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 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 score0.006
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.028
GPT teacher head0.238
Teacher spread0.210 · 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