Evaluation of a self-amplifying mRNA reporter vaccine in explant models of broiler chickens
Bibliographic record
Abstract
In order to minimize animal loss and economical loss, industrial poultry is heavily vaccinated against infectious agents. mRNA vaccination is an effective vaccination platform, yet little to no comprehensive, comparative studies in avians can be found. Nevertheless, poultry mRNA vaccination could prove to be very interesting due to the relatively low production cost, especially true when using self-amplifying mRNA (saRNA), and their extreme adaptability to new pathogens. The latter could be particularly useful when new pathogens join the stage or new variants arise. As a first step toward the investigation of saRNA vaccines in poultry, this study evaluates a luciferase-encoding saRNA in avian tracheal explants, conjunctival explants, primary chicken cecal cells and 18-day embryonated eggs. Naked saRNA in combination with RNase inhibitor and 2 different lipid-based formulations, that is, ionizable lipid nanoparticles (LNPs) and Lipofectamine Messenger Max, were evaluated. The saRNA-LNP formulation led to the highest bioluminescent signal in the tracheal explants, conjunctival explants and cecal cell cultures. A dose-response experiment with these saRNA-LNPs (33-900 ng/well) in these avian organoids and cells showed a nonlinear dose-response relationship. After in ovo administration, the highest dose of the saRNA-LNPs (5 µg) resulted in a visual expression as a weak bioluminescence signal could be seen. The other delivery approaches did not lead to a visual saRNA expression in the embryos. In conclusion, effective entry of saRNA encapsulated in LNPs followed by successful saRNA translation in poultry was established. Hence, mRNA vaccination in poultry could be possible, but further in vivo testing is needed.
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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 | 0.002 | 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 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".