Differential Role of TLR- and RLR-Signaling in the Immune Responses to Influenza A Virus Infection and Vaccination
Bibliographic record
Abstract
The innate immune system recognizes influenza A virus via TLR 7 or retinoic acid-inducible gene I in a cell-type specific manner in vitro, however, physiological function(s) of the MyD88- or interferon-beta promoter stimulator 1 (IPS-1)-dependent signaling pathways in antiviral responses in vivo remain unclear. In this study, we show that although either MyD88- or IPS-1-signaling pathway was sufficient to control initial antiviral responses to intranasal influenza A virus infection, mice lacking both pathways failed to show antiviral responses, resulting in increased viral load in the lung. By contrast, induction of B cells or CD4 T cells specific to the dominant hemagglutinin or nuclear protein Ags respectively, was strictly dependent on MyD88 signaling, but not IPS-1 signaling, whereas induction of nuclear protein Ag-specific CD8 T cells was not impaired in the absence of either MyD88 or IPS-1. Moreover, vaccination of TLR7- and MyD88-deficient mice with inactivated virus failed to confer protection against a lethal live virus challenge. These results strongly suggest that either the MyD88 or IPS-1 signaling pathway is sufficient for initial antiviral responses, whereas the protective adaptive immune responses to influenza A virus are governed by the TLR7-MyD88 pathway.
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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 | 0.001 | 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".