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Record W2144194261 · doi:10.1172/jci32693

OX40 ligand expressed by DCs costimulates NKT and CD4+ Th cell antitumor immunity in mice

2007· article· en· W2144194261 on OpenAlexaff
Jamal Zaini, Sita Andarini, Minoru Tahara, Yasuo Saijo, Naoto Ishii, Kazuyoshi Kawakami, Masaru Taniguchi, Kazuo Sugamura, Toshihiro Nukiwa, Toshiaki Kikuchi

Bibliographic record

VenueJournal of Clinical Investigation · 2007
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsInstitute of Aging
FundersMinistry of Education, Culture, Sports, Science and TechnologyJapan Research Foundation for Clinical PharmacologyCell Science Research Foundation
KeywordsNatural killer T cellCD1DImmunologyBiologyT cellCancer researchCell biologyImmune system

Abstract

fetched live from OpenAlex

The exceptional immunostimulatory capacity of DCs makes them potential targets for investigation of cancer immunotherapeutics. We show here in mice that TNF-alpha-stimulated DC maturation was accompanied by increased expression of OX40 ligand (OX40L), the lack of which resulted in an inability of mature DCs to generate cellular antitumor immunity. Furthermore, intratumoral administration of DCs modified to express OX40L suppressed tumor growth through the generation of tumor-specific cytolytic T cell responses, which were mediated by CD4+ T cells and NKT cells. In the tumors treated with OX40L-expressing DCs, the NKT cell population significantly increased and exhibited a substantial level of IFN-gamma production essential for antitumor immunity. Additional studies evaluating NKT cell activation status, in terms of IFN-gamma production and CD69 expression, indicated that NKT cell activation by DCs presenting alpha-galactosylceramide in the context of CD1d was potentiated by OX40 expression on NKT cells. These results show a critical role for OX40L on DCs, via binding to OX40 on NKT cells and CD4+ T cells, in the induction of antitumor immunity in tumor-bearing mice.

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)0.003
metaresearch head score (Gemma)0.001
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 score0.096
Threshold uncertainty score0.412

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
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 integrity0.0000.001
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 head0.037
GPT teacher head0.327
Teacher spread0.291 · 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

Citations113
Published2007
Admission routes1
Has abstractyes

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