Two Doses of Bovine Viral Diarrhea Virus DNA Vaccine Delivered by Electroporation Induce Long-Term Protective Immune Responses
Bibliographic record
Abstract
Bovine viral diarrhea virus (BVDV) is a pathogen of major importance in cattle, so there is a need for new effective vaccines. DNA vaccines induce balanced immune responses and are relatively inexpensive and thus promising for both human and veterinary applications. In this study, newborn calves with maternal antibodies were vaccinated intramuscularly (i.m.) with a BVDV E2 DNA vaccine with the TriGrid Delivery System for i.m. delivery (TDS-IM). Two doses of this vaccine spaced 6 or 12 weeks apart were sufficient to induce significant virus-neutralizing antibody titers, numbers of activated T cells, and reduction in viral shedding and clinical presentations after BVDV-2 challenge. In contrast to the placebo-treated animals, the vaccinated calves did not lose any weight, which is an excellent indicator of the well-being of an animal and has a significant economic impact. Furthermore, the interval between the two vaccinations did not influence the magnitude of the immune responses or degree of clinical protection, and a third immunization was not necessary or beneficial. Since electroporation may enhance not only the magnitude but also the duration of immunity after DNA immunization, the interval between vaccination and challenge was extended in a second trial, which showed that two doses of this E2 DNA vaccine again significantly reduced clinical disease against BVDV for several months. These results are promising and support this technology for use against infectious diseases in cattle and large species, including humans, in general.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| 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".