Immunization with a bovine herpesvirus 1 glycoprotein B DNA vaccine induces cytotoxic T-lymphocyte responses in mice and cattle
Bibliographic record
Abstract
Virus-specific cytotoxic T lymphocytes (CTLs) are considered to be important in protection against and recovery from viral infections. In this study, several approaches to induce cytotoxicity against bovine herpesvirus 1 (BHV-1) were evaluated. Vaccination of C57BL/6 mice with BHV-1 induced a strong humoral, but no CTL, response, which may be due to downregulation of major histocompatibility complex class I molecules. In contrast, vaccinia virus expressing glycoprotein B (gB) elicited a weaker antibody response, but strong cytotoxicity, in mice. As an approach to inducing both strong humoral and cellular immune responses, a plasmid vector was then used to express gB. Both antibody and CTL responses were induced by the plasmid encoding gB in C57BL/6 and C3H mice, regardless of the type of vector backbone. This demonstrated that DNA immunization induces a broad-based immune response to BHV-1 gB. Interestingly, removal of the membrane anchor, which resulted in secretion of gB from transfected cells, did not result in reduced cytotoxicity. Here, it is shown that, compared with the cell-associated counterpart, plasmid-encoded secreted protein may induce enhanced immune responses in cattle. Therefore, calves were immunized intradermally with pMASIAtgB, a plasmid encoding the secreted form of gB (tgB), using a needle-free injection system. This demonstrated that pMASIAtgB elicited both humoral responses and activated gamma interferon-secreting CD8+ CTLs, suggesting that a DNA vaccine expressing tgB induces a CTL response in the natural host of BHV-1.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".