PapMV nanoparticles improve mucosal immune responses to the trivalent inactivated flu vaccine
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Trivalent inactivated flu vaccines (TIV) are currently the best means to prevent influenza infections. However, the protection provided by TIV is partial (about 50%) and it is needed to improve the efficacy of protection. Since the respiratory tract is the main site of influenza replications, a vaccine that triggers mucosal immunity in this region can potentially improve protection against this disease. Recently, PapMV nanoparticles used as an adjuvant in a formulation with TIV administered by the subcutaneous route have shown improving the immune response directed to the TIV and protection against an influenza challenge. FINDINGS: In the present study, we showed that intranasal instillation with a formulation containing TIV and PapMV nanoparticles significantly increase the amount of IgG, IgG2a and IgA in lungs of vaccinated mice as compared to mice that received TIV only. Instillation with the adjuvanted formulation leads to a more robust protection against an influenza infection with a strain that is lethal to mice vaccinated with the TIV. CONCLUSIONS: We demonstrate for the first time that PapMV nanoparticles are an effective and potent mucosal adjuvant for vaccination.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 it