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Record W2157173498 · doi:10.1128/jvi.00422-06

CD80 and CD86 Control Antiviral CD8 <sup>+</sup> T-Cell Function and Immune Surveillance of Murine Gammaherpesvirus 68

2006· article· en· W2157173498 on OpenAlexaff
Shinichiro Fuse, Joshua J. Obar, Sarah C. Bellfy, Erica K. Leung, Weijun Zhang, Edward J. Usherwood

Bibliographic record

VenueJournal of Virology · 2006
Typearticle
Languageen
FieldMedicine
TopicCytomegalovirus and herpesvirus research
Canadian institutionsMcMaster University
FundersNational Institute of Allergy and Infectious DiseasesNational Cancer InstituteNational Institutes of Health
KeywordsCD80CD86BiologyImmune systemCD28ImmunologyCytotoxic T cellT cellCD8AntibodyAntigenVirologyCD40In vitro

Abstract

fetched live from OpenAlex

The interactions between CD80 and CD86 on antigen-presenting cells and CD28 on T cells serve as an important costimulatory signal in the activation of T cells. Although the simplistic two-signal hypothesis has been challenged in recent years by the identification of different costimulators, this classical pathway has been shown to significantly impact antiviral humoral and cellular immune responses. How the CD80/CD86-CD28 pathway affects the control of chronic or latent infections has been less well characterized. In this study, we investigated its role in antiviral immune responses against murine gammaherpesvirus 68 (MHV-68) and immune surveillance using CD80/CD86(-/-) mice. In the absence of CD80/CD86, primary antiviral CD8(+) T-cell responses and the induction of neutralizing antibodies were severely impaired. During long-term immune surveillance, the virus-specific CD8(+) T cells were impaired in IFN-gamma production and secondary expansion and exhibited an altered phenotype. Surprisingly, a low level of viral reactivation in the lung was observed, and this effect was independent of CD28 and CTLA-4. Thus, CD80 and CD86, signaling through CD28 and possibly another unidentified receptor, are required for optimal immune surveillance and antiviral immune responses to murine gammaherpesvirus.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.608
Threshold uncertainty score0.610

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 science0.0000.000
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 head0.008
GPT teacher head0.251
Teacher spread0.243 · 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 designObservational
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

Citations71
Published2006
Admission routes1
Has abstractyes

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