Intranasal Antibody Gene Transfer in Mice and Ferrets Elicits Broad Protection Against Pandemic Influenza
Bibliographic record
Abstract
The emergence of a new influenza pandemic remains a threat that could result in a substantial loss of life and economic disruption worldwide. Advances in human antibody isolation have led to the discovery of monoclonal antibodies (mAbs) that have broad neutralizing activity against various influenza strains, although their direct use for prophylaxis is impractical. To overcome this limitation, our approach is to deliver antibody via adeno-associated virus (AAV) vectors to the site of initial infection, which, for respiratory viruses such as influenza, is the nasopharyngeal mucosa. AAV vectors based on serotype 9 were engineered to express a modified version of the previously isolated broadly neutralizing mAb to influenza A, FI6. We demonstrate that intranasal delivery of AAV9.FI6 into mice afforded complete protection and log reductions in viral load to 100 LD₅₀ (median lethal dose) of three clinical isolates of H5N1 and two clinical isolates of H1N1, all of which have been associated with historic human pandemics (including H1N1 1918). Similarly, complete protection was achieved in ferrets challenged with lethal doses of H5N1 and H1N1. This approach serves as a platform for the prevention of natural or deliberate respiratory diseases for which a protective antibody is available.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".