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Record W2174267452 · doi:10.4049/jimmunol.1501140

Priming of Qualitatively Superior Human Effector CD8+ T Cells Using TLR8 Ligand Combined with FLT3 Ligand

2015· article· en· W2174267452 on OpenAlexaff
Anna Lissina, Olivia Briceño, Georgia Afonso, Martin Larsen, Emma Gostick, David A. Price, Roberto Mallone, Victor Appay

Bibliographic record

VenueThe Journal of Immunology · 2015
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsInstitute of Infection and Immunity
FundersAgence Nationale de la RechercheWellcome Trust
KeywordsPriming (agriculture)EffectorLigand (biochemistry)CD8ChemistryCytotoxic T cellCell biologyBiologyImmunologyMolecular biologyImmune systemBiochemistryReceptorIn vitro

Abstract

fetched live from OpenAlex

The quality of Ag-specific CD8(+) T cell responses is central to immune efficacy in infectious and malignant settings. Inducing effector CD8(+) T cells with potent functional properties is therefore a priority in the field of immunotherapy. However, the optimal assessment of new treatment strategies in humans is limited by currently available testing platforms. In this study, we introduce an original model of in vitro CD8(+) T cell priming, based on an accelerated dendritic cell coculture system, which uses unfractionated human PBMCs as the starting material. This approach enables the rapid evaluation of adjuvant effects on the functional properties of human CD8(+) T cells primed from Ag-specific naive precursors. We demonstrate that a selective TLR8 agonist, in combination with FLT3L, primes high-quality CD8(+) T cell responses. TLR8L/FLT3L-primed CD8(+) T cells displayed enhanced cytotoxic activity, polyfunctionality, and Ag sensitivity. The acquisition of this superior functional profile was associated with increased T-bet expression induced via an IL-12-dependent mechanism. Collectively, these data validate an expedited route to vaccine delivery or optimal T cell expansion for adoptive cell transfer.

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 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 score0.020
Threshold uncertainty score0.736

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 integrity0.0000.001
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 head0.035
GPT teacher head0.290
Teacher spread0.255 · 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

Citations38
Published2015
Admission routes1
Has abstractyes

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