Identification of a novel antigen presenting cell population modulating anti-influenza type-2 immunity (131.3)
Bibliographic record
Abstract
Abstract Anti-influenza type 2 (T2) immunity contributes to both immunoprotection and immunopathology, yet the underlying mechanisms modulating T2 immunity remain ill-defined. Here, we describe a novel murine antigen (Ag) presenting cell (APC) population, designated virus activated plasmacytoid (VAP) cells: mPDCA1+CD11c-TcR-β-B220-CD19-CD38+CD44intCD45+Gr1+. VAP cells are bone marrow derived leukocytes. Phenotypic, morphologic and molecular characterization distinguished VAP cells from other immune cell populations. Pulmonary influenza A virus infection activates circulating VAP cells to enter the lungs and produce interleukin (IL)-25, a strong inducer of T2 pulmonary inflammation. Subsequently, VAP cells capture viral Ag in the lungs and migrate to the draining lymph node (DLN) and spleen, with delayed kinetics relative to DCs, where they show APC activity. In the DLN, influenza virus activated VAP cells produce IL-4 and induce T helper (TH) 2 effector cell polarization by modulating GATA-3 expression. Finally, adoptive transfer of influenza virus activated VAP cells enhanced TH2 effector T cell responses in influenza virus infected recipient mice and subsequently, anti-influenza T2 humoral responses including IgG1 and G2b were significantly increased. Collectively, our results highlight the importance of VAP cells as novel immuno-modulators of T2 immunity against influenza A virus infection in mouse. These studies were supported by a Canadian Institutes of Health Research grant MOP-15094 to E.N.F. J.K.Y. was supported by a Connaught Scholarship and an Ontario Graduate Scholarship in Science and Technology.
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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 | 0.000 |
| 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".