Prime-pull vaccination with a plant-derived virus-like particle influenza vaccine elicits a broad immune response and protects aged mice from death and frailty after challenge
Bibliographic record
Abstract
Abstract Background Administered intramuscularly (IM), plant-derived, virus-like-particle (VLP) vaccines based on the influenza hemagglutinin (HA) protein elicit both humoral and cellular responses that can protect aged mice from lethal challenge. Unlike split virus vaccines, VLPs can be administered by different routes including intranasally (IN). We evaluated novel vaccine strategies such as prime-pull (IM boosted by IN) and multi-modality vaccination (IM and IN given simultaneously). We wished to determine if these approaches would provide better quality protection in old mice after less severe (borderline-lethal) challenge (ie: immunogenicity, frailty and survival). Results Survival rates were similar in all vaccinated groups. Antibody responses were modest in all groups but tended to be higher in VLP groups compared to inactivated influenza vaccine (IIV) recipients. All VLP groups had higher splenocyte T cell responses than the split virus group. Lung homogenate chemokine/cytokine levels and virus loads were lower in the VLP groups compared to IIV recipients 3 days after challenge ( p < 0.05 for viral load vs all VLP groups combined). The VLP-vaccinated groups also had less weight loss and recovered more rapidly than the IIV recipients. There was limited evidence of an immunologic or survival advantage with IN delivery of the VLP vaccine. Conclusion Compared to IIV, the plant-derived VLP vaccine induced a broader immune response in aged mice (cellular and humoral) using either traditional (IM/IM) or novel schedules (multi-modality, prime-pull).
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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".