Prior administration of staphylococcal enterotoxin B augments the CD8+ T cell response to influenza A virus.
Bibliographic record
Abstract
Abstract Staphylococcal enterotoxin B (SEB) is a bacterial protein capable of binding up to 20% of the entire T cell repertoire. T cells that have come into contact with SEB initially proliferate and secrete inflammatory cytokines; however, this is followed by anergy or death of the affected cells. This population of deleted or functionally inactivated cells is likely to include T cell clones that are important for immunity to other pathogens such as influenza A virus (IAV). For this reason, we hypothesize that SEB exposure will alter the magnitude and breadth of the CD8+ T cell response to IAV. Using mouse model of intraperitoneal vaccination with IAV, we found that prior exposure to SEB actually increased the number of IAV-specific CD8+ T cells for several IAV epitopes during the primary phase of the immune response. The number of cells specific for these epitopes remained elevated even after the peak of the primary CD8+ T cell response had passed. In addition, repetition of the first experiment with several different naturally circulating and lab-adapted strains of IAV gave similar results, showing that the effect of SEB on virus-specific CD8+ T cells is the same for a potentially diverse range of IAV strains. Furthermore, the ability of the CD8+ T cells to kill target cells pulsed with cognate IAV antigen was also enhanced after SEB exposure, for both primary and memory CD8+ T cells. Curiously, we did not observe an effect of SEB when it is given in the context of a replicative IAV infection in the lungs. This work reveals an unexpected role for SEB as an enhancer of CD8+ T cell immunity in this model.
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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) | 0.001 | 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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".