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Record W1992373328 · doi:10.1189/jlb.0610357

TLR engagement prior to virus infection influences MHC-I antigen presentation in an epitope-dependent manner as a result of nitric oxide release

2010· article· en· W1992373328 on OpenAlexafffund
Sarah Siddiqui, Attiya Alatery, Agnieszka Kuś, Sameh Basta

Bibliographic record

VenueJournal of Leukocyte Biology · 2010
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Response and Inflammation
Canadian institutionsOttawa Regional Cancer FoundationUniversity of OttawaQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyTLR3EpitopeTLR2Innate immune systemAntigen presentationAntigenImmunologyTLR4Acquired immune systemCross-presentationToll-like receptorImmune systemMajor histocompatibility complexMHC class IT cell

Abstract

fetched live from OpenAlex

Microorganisms contain PAMPs that can interact with different TLR-Ls. Cooperative signals from these receptors may modify innate and adaptive immune responses to invading pathogens. Therefore, a better understanding of the role TLRs play in initiating host defense during infections requires assessing the influence of multiple TLR engagement on pAPC activation and antigen presentation. In this study, we investigated the effects of combined TLR2, TLR3, or TLR4 engagement on DC activation and the presentation of LCMV antigens focusing on the major epitopes derived from NP and GP proteins encoded by the virus. Our results demonstrate that combined TLR ligation affected antigen presentation of NP(205-212), GP(33-41), and GP(276-286), but not NP(396-404). The altered antigen presentation was associated with changes in proteasomal activities and NO production as a result of TLR engagement. Taken together, the data demonstrate that combined TLR ligation could result in changes of innate effectors that may directly influence the adaptive immune response.

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)0.001
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 score0.292
Threshold uncertainty score0.498

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.019
GPT teacher head0.318
Teacher spread0.300 · 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

Citations17
Published2010
Admission routes2
Has abstractyes

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