Development and characterization of influenza M2 ectodomain and/or hemagglutinin stalk-based dendritic cell-targeting vaccines
Bibliographic record
Abstract
A universal influenza vaccine is required for broad protection against influenza infection. Here, we revealed the efficacy of novel influenza vaccine candidates based on Ebola glycoprotein dendritic cell (DC)-targeting domain (EΔM) fusion protein technology. The four copies of ectodomain matrix protein of influenza (tM2e) or M2e hemagglutinin stalk (HA stalk) peptides (HM2e) were fused with EΔM to generate EΔM-tM2e or EΔM-HM2e, respectively. We demonstrated that EΔM-HM2e- or EΔM-tM2e-pseudotyped viral particles can efficiently target DC/macrophages in vitro and induced significantly high titers of anti-HA and/or anti-M2e antibodies in mice. Significantly, the recombinant vesicular stomatitis virus (rVSV)-EΔM-tM2e and rVSV-EΔM-HM2e vaccines mediated rapid and potent induction of M2 or/and HA antibodies in mice sera and mucosa. Importantly, vaccination of rVSV-EΔM-tM2e or rVSV-EΔM-HM2e protected mice from influenza H1N1 and H3N2 challenges. Taken together, our study suggests that rVSV-EΔM-tM2e and rVSV-EΔM-HM2e are promising candidates that may lead to the development of a universal vaccine against different influenza strains.
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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) | 0.000 | 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 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".