Targeting with Bovine CD154 Enhances Humoral Immune Responses Induced by a DNA Vaccine in Sheep
Bibliographic record
Abstract
CD40-CD154 interactions play an important role in regulating humoral and cell-mediated immune responses. Recently, these interactions have been exploited for the development of therapeutic and preventive treatments. The objective of this study was to test the ability of bovine CD154 to target a plasmid-encoded Ag to CD40-expressing APCs. To achieve this, a plasmid coding for bovine CD154 fused to a truncated secreted form of bovine herpesvirus 1 glycoprotein D (tgD), pSLIAtgD-CD154, was constructed. The chimeric tgD-CD154 was expressed in vitro in COS-7 cells and reacted with both glycoprotein D- and CD154-specific Abs. Both tgD and tgD-CD154 were capable of binding to epithelial cells, whereas only tgD-CD154 bound to B cells. Furthermore, dual-labeling of ovine PBMCs revealed that tgD-CD154 was bound by primarily B cells. The functional integrity of the tgD-CD154 chimera was confirmed by the induction of both IL-4-dependent B cell proliferation and tgD-specific lymphoproliferative responses in vitro. Finally, sheep immunized with pSLIAtgD-CD154 developed a more rapid primary tgD-specific Ab response and a significantly stronger tgD-specific secondary response when compared with animals immunized with pSLIAtgD and control animals. Similarly, virus-neutralizing Ab titers were significantly higher after secondary immunization with pSLIAtgD-CD154. These results demonstrate that using CD154 to target plasmid-expressed Ag can significantly enhance immune responses induced by a DNA vaccine.
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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 | 0.001 | 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".