A VSV-vector vaccine simultaneously targeting H5N1 hemagglutinin (HA) and matrix protein 2 (M2) induces robust neutralizing and ADCC antibody responses and provides full protection against lethal H5N1 infection in a mouse model
Bibliographic record
Abstract
Abstract Human (avian) influenza A viruses, especially highly pathogenic avian influenza (HPAI) viruses, pose a significant public health threat, and a multivalent vaccine is the primary prophylactic measure to control these viruses. To establish such a vaccine, we generated two multivalent vesicular stomatitis virus (VSV)-based vaccine candidates (V-EtM2e/H5 05 and V-EtM2e/H5 22 ) and characterized their ability to induce protective immune responses. Our results revealed that vaccine immunization in mice induced high humoral immune responses against both the HPAI hemagglutinin (HA) protein and the ectodomain of M2 (M2e) protein. Intriguingly, vaccine-immunized mouse sera exhibited highly efficient neutralizing activity against the corresponding H5 pseudovirus and mediated potent and broad antibody-dependent cellular cytotoxicity (ADCC) activity against M2e derived from human and avian influenza H5, H1, H3, and H7 viruses. Furthermore, both intranasal and intramuscular immunization provided efficient protection against HPAI H5N1 virus challenge in mice, with a 100% survival rate and a nondetectable viral load in several tissues. Notably, noninvasive mucosal (IN) delivery of V-EtM2e/H5 22 achieved protection equal to that of IM delivery at a 100-fold lower immunizing dose. These findings provide strong evidence for the effectiveness of a multivalent VSV-based vaccine against human (avian) influenza A 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) | 0.001 | 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".