CD8 <sup>+</sup> T Cell Immunodominance in Lymphocytic Choriomeningitis Virus Infection Is Modified in the Presence of Toll-Like Receptor Agonists
Bibliographic record
Abstract
Currently, we have limited understanding of how Toll-like receptor (TLR) engagement by microbial products influences the immune response during a concurrent virus infection. In this study, we established that dual TLR2 plus TLR3 (designated TLR2+3) stimulation alters the immunodominance hierarchies of lymphocytic choriomeningitis virus (LCMV) epitopes by reducing NP396-specific CD8+ T cell responses and shifting it to a subdominant position. The shift in immunodominance occurred due to a reduction in antigen uptake and the reduced cross-presentation of NP396, a major LCMV immunodominant epitope that is efficiently cross-presented. Moreover, the altered immunodominance was dependent on TLR stimulation occurring at the site of infection. Finally, as lipopolysaccharide failed to induce the same phenomenon, the data suggest that these findings are dependent not only on the dual engagement of the TRIF/MyD88 pathways but also on how TLR agonists activate antigen-presenting cells. Taken together, our data demonstrate a novel role for TLR ligands in regulating antiviral CD8+ T cell responses due to the regulation of the cross-presentation of cell-associated antigens.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".