Protective lactogenic immunity conferred by an edible peptide vaccine to bovine rotavirus produced in transgenic plants
Bibliographic record
Abstract
Vaccines produced in transgenic plants constitute a promising alternative to conventional immunogens, presenting the possibility of stimulating secretory and systemic immunity against enteric pathogens when administered orally. Protection against enteric pathogens affecting newborn animals requires, in most cases, the stimulation of lactogenic immunity. Here, the group presents the development of an experimental immunogen based on expression of an immunorelevant peptide, eBRV4, of the VP4 protein of bovine rotavirus (BRV), which has been described as harbouring at least one neutralizing epitope as well as being responsible for the adsorption of the virus to epithelial cells. The eBRV4 epitope was efficiently expressed in transgenic alfalfa as a translational fusion protein with the highly stable reporter enzyme beta-glucuronidase (betaGUS), which served as a carrier, stabilized the synthesized peptide and facilitated screening for the higher expression levels in plants. Correlation of expression of the eBRV4 epitope in plants with those presenting the highest betaGUS activities was confirmed by a Western blot assay specific for the BRV peptide. The eBRV4 epitope expressed in plants was effective in inducing an anti-rotavirus antibody response in adult female mice when administered either intraperitoneally or orally and, more importantly, suckling mice born from immunized female mice were protected against oral challenge with virulent rotavirus. These results demonstrate the feasibility of inducing lactogenic immunity against an enteric pathogen using an edible vaccine produced in transgenic plants.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".