Single-Component Multilayered Self-Assembling Protein Nanoparticles Displaying Extracellular Domains of Matrix Protein 2 as a Pan-influenza A Vaccine
Bibliographic record
Abstract
The development of a cross-protective pan-influenza A vaccine remains a significant challenge. In this study, we designed and evaluated single-component self-assembling protein nanoparticles (SApNPs) presenting the conserved extracellular domain of matrix protein 2 (M2e) as vaccine candidates against influenza A viruses. The SApNP-based vaccine strategy was first validated for human M2e (hM2e) and then applied to tandem repeats of M2e from human, avian, and swine hosts (M2ex3). Vaccination with M2ex3 displayed on SApNPs demonstrated higher survival rates and less weight loss compared to the soluble M2ex3 antigen against the lethal challenges of H1N1 and H3N2 in mice. M2ex3 I3-01v9a SApNPs formulated with a squalene-based adjuvant were retained in the lymph node follicles over 8 weeks and induced long-lived germinal center reactions. Notably, a single low dose of M2ex3 I3-01v9a SApNP formulated with a potent adjuvant, either a Toll-like receptor 9 (TLR9) agonist or a stimulator of interferon genes (STING) agonist, conferred 90% protection against a lethal H1N1 challenge in mice. With the ability to induce robust and durable M2e-specific functional antibody and T cell responses, the M2ex3-presenting I3-01v9a SApNP provides a promising pan-influenza A vaccine candidate.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".