Inclusion of the Bovine Neutrophil Beta-Defensin 3 with Glycoprotein D of Bovine Herpesvirus 1 in a DNA Vaccine Modulates Immune Responses of Mice and Cattle
Bibliographic record
Abstract
Bovine herpesvirus 1 (BoHV-1) causes recurrent respiratory and genital infections in cattle and predisposes them to lethal secondary infections. While modified live and killed BoHV-1 vaccines exist, these are not without problems. Development of an effective DNA vaccine for BoHV-1 has the potential to address these issues. As a strategy to enhance DNA vaccine immunity, a plasmid encoding the bovine neutrophil beta-defensin 3 (BNBD3) as a fusion with truncated glycoprotein D (tgD) and a mix of two plasmids encoding BNBD3 and tgD were tested in mice and cattle. In mice, coadministration of BNBD3 on the separate plasmid enhanced the tgD-induced gamma interferon (IFN-γ) response but not the antibody response. BNBD3 fused to tgD did not affect the antibody levels or the number of IFN-γ-secreting cells but increased the induction of tgD-specific cytotoxic T lymphocytes (CTLs). In cattle, the addition of BNBD3 as a fusion construct also modified the immune response. While the IgG and virus-neutralizing antibody levels were not affected, the number of IFN-γ-secreting cells was increased after BoHV-1 challenge, specifically the CD8(+) IFN-γ(+) T cells, including CD8(+) IFN-γ(+) CD25(+) CTLs. While reduced virus shedding, rectal temperature, and weight loss were observed, the level of protection was comparable to that observed in pMASIA-tgD-vaccinated animals. These data show that coadministration of BNBD3 with a protective antigen as a fusion in a DNA vaccine strengthened the Th1 bias and increased cell-mediated immune responses but did not enhance protection from BoHV-1 infection.
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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) | 0.000 | 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 | 0.001 |
| 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 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".