Microneedle delivery of trivalent influenza vaccine to the skin induces long-term cross-protection
Bibliographic record
Abstract
A painless self-immunization method with effective and broad cross-protection is urgently needed to prevent infections against newly emerging influenza viruses. In this study, we investigated the cross-protection efficacy of trivalent influenza vaccine containing inactivated A/PR/8/34 (H1N1), A/Hong Kong/68 (H3N2) and B/Lee/40 after skin vaccination using microneedle patches coated with this vaccine. Microneedle vaccination of mice in the skin provided 100% protection against lethal challenges with heterologous pandemic strain influenza A/California/04/09, heterogeneous A/Philippines/2/82 and B/Victoria/287 viruses 8 months after boost immunization. Cross-reactive serum IgG antibody responses against heterologous influenza viruses A/California/04/09, A/Philippines/2/82 and B/Victoria/287 were induced at high levels. Hemagglutination inhibition titers were also maintained at high levels against these heterogeneous viruses. Microneedle vaccination induced substantial levels of cross-reactive IgG antibody responses in the lung and cellular immune responses, as well as cross-reactive antibody-secreting plasma cells in the spleen. Viral loads in the lung were significantly (p < 0.05) reduced. All mice survived after viral challenges. These results indicate that skin vaccination with trivalent vaccine using a microneedle array could provide protection against seasonal epidemic or new pandemic strain of influenza viruses.
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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) | 0.001 | 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".