Early MR1 upregulation on antigen-presenting cells following influenza A virus immunization: implications for co-infections and superinfections 3103
Bibliographic record
Abstract
Abstract Description Influenza A viruses (IAVs) remain a global health threat due to their high mutation rates, which complicate vaccine efficacy. Targeting mucosa-associated invariant T (MAIT) cells, an innate-like T cell subset, has been linked to improved vaccine strategies. We investigated the expression of MHC class I-related protein 1 (MR1), essential for MAIT cell activation against bacterial pathogens, on antigen-presenting cells in C57BL/6 mice immunized with A/Puerto Rico/8/1934 (PR8) (H1N1) and A/Hong Kong/1/1968 (HK) (H3N2) IAV strains. Flow cytometry revealed significant MR1 upregulation on F4/80+ macrophages and CD11c+ dendritic cells in the peritoneal cavity, lungs, spleen, and blood at 24 hours and sustained for at least 3 days. MR1 upregulation was notably reduced with heat-inactivated PR8, highlighting a requirement for active viral replication. In vivo administration of poly(I:C), but not Imiquimod, recapitulated IAV immunization, suggesting a role for TLR3 triggering in this setting. In human cell cultures, MR1 upregulation was accompanied by MHC I downregulation, indicating the selectivity of the observed phenomenon for MR1. Additionally, PR8 exposure activated primary human MAIT cells, as evidenced by CD38 and HLA-DR expression. Since MR1 presents bacterial metabolites to MAIT cells, eliciting antibacterial responses, we propose that anti-IAV vaccination not only protects against these viruses but also primes the immune system to combat secondary bacterial infections. Topic Categories Mucosal and Regional Immunology (MUC)
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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) | 0.002 | 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".