Priming with DNA encoding E2 and boosting with E2 protein formulated with CpG oligodeoxynucleotides induces strong immune responses and protection from Bovine viral diarrhea virus in cattle
Bibliographic record
Abstract
The objective of this study was to develop an optimal vaccination strategy for Bovine viral diarrhea virus (BVDV). The E2 protein of BVDV plays a major protective role against BVDV infection. In order to be able to compare DNA, protein and DNA prime-protein boost regimens, a plasmid was constructed encoding a secreted form of the NADL strain E2 protein (pMASIA-tPAsDeltaE2). Furthermore, a pure secreted recombinant DeltaE2 (rDeltaE2) protein was produced. The rDeltaE2 protein was formulated with a combination of Emulsigen and CpG oligodeoxynucleotide. Groups of calves were immunized with pMASIA-tPAsDeltaE2 or with rDeltaE2, or first with pMASIA-tPAsDeltaE2 and then with rDeltaE2. To evaluate the protection against BVDV, calves were challenged with BVDV strain NY-1 after the last immunization. Although all immunized calves developed humoral and cellular immune responses, the antibody responses in the DNA prime-protein boost group were stronger than those elicited by either the DNA vaccine or the protein vaccine. In particular, E2-specific antibody titres were enhanced significantly after boosting the DeltaE2 DNA-primed calves with rDeltaE2 protein. Moreover, protection against BVDV challenge was obtained in the calves treated with the DNA prime-protein boost vaccination regimen, as shown by a significant reduction in weight loss, viral excretion and lymphopenia, compared with the unvaccinated calves and the animals immunized with the DNA or protein only. These results demonstrate the advantage of a DNA prime-protein boost vaccination approach in an outbred species.
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 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 | 0.000 | 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) | 0.000 | 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".