A Hemagglutinin 1 Carrying Plant-Based Virus-like Particle Vaccine Generates an Efficacious Cellular Response by Exploiting IL-1 Signaling in Both Adult and Aged Mice
Bibliographic record
Abstract
Abstract Inactivated influenza vaccines have struggled to provide consistent protection in older individuals. Circumventing immune senescence, an aging of the immune response characterized by weak humoral responses to vaccines, and unchecked inflammation during infection require novel immunization strategies. Plant-based virus-like particles (VLPs) bearing recombinant hemagglutinin proteins have been shown to provide protection in older animals in preclinical challenge studies, despite eliciting relatively low or absent humoral responses. The nature of the cellular response induced by these vaccines and its evolution during infection have not yet been fully characterized, however. Using a murine model that recapitulates features of human immune senescence, we assessed T cell responses to vaccination with a VLP bearing the hemagglutinin of H1N1/California 07/2009 (H1-VLP) before and after challenge in young and aged BALB/c mice (2 and 18 mo old, respectively). We report that two i.m. doses of H1-VLP (3 μg) vaccine 21 d apart generated H1-specific Th1 and Th2 cells associated with the prevention of prolonged pulmonary inflammation and mortality in both adult and aged mice. While investigating the regulation of cellular immunity, we identified a unique IL-1R1+ tissue-adapted regulatory T cell population in the lungs of both H1-VLP–vaccinated adult and aged mice, suggesting a novel regulatory T cell population associated with vaccine-mediated protection. Collectively, this study provides preclinical evidence that the plant-based H1-VLP vaccine may act, in part, by preventing exacerbated immune responses against influenza A.
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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".