A novel mouse AAV6 hACE2 transduction model of wild-type SARS-CoV-2 infection studied using synDNA immunogens
Bibliographic record
Abstract
More than 100 million people have been infected with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Common laboratory mice are not susceptible to wild-type SARS-CoV-2 infection, challenging the development and testing of effective interventions. Here, we describe the development and testing of a mouse model for SARS-CoV-2 infection based on transduction of the respiratory tract of laboratory mice with an adeno-associated virus vector ( AAV6 ) expressing human ACE-2 ( AAV6.2FF-hACE2 ). We validated this model using a previously described synthetic DNA vaccine plasmid, INO-4800 ( pS ). Intranasal instillation of AAV6.2FF-hACE2 resulted in robust hACE2 expression in the respiratory tract. pS induced robust cellular and humoral responses. Vaccinated animals were challenged with 10 5 TCID 50 SARS-CoV-2 (hCoV-19/Canada/ON-VIDO-01/2020) and euthanized four days post-challenge to assess viral load. One immunization resulted in 50% protection and two immunizations were completely protective. Overall, the AAV6.2FF-hACE2 mouse transduction model represents an easily accessible, genetically diverse mouse model for wild-type SARS-CoV-2 infection and preclinical evaluation of potential interventions.
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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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".