Dendritic cell targeted HIV‐1 gag protein vaccine provides help to a recombinant Newcastle disease virus vectored vaccine including mobilization of protective CD8<sup>+</sup> T cells
Bibliographic record
Abstract
Abstract Introduction Recombinant Newcastle Disease virus (rNDV) vectored vaccines are safe mucosal applicable vaccines with intrinsic immune‐modulatory properties for the induction of efficient immunity. Like all viral vectored vaccines repeated inoculation via mucosal routes invariably results to immunity against viral vaccine vectors. To obviate immunity against viral vaccine vectors and improve the ability of rNDV vectored vaccines in inducing T cell immunity in murine air way we have directed dendritic cell targeted HIV‐1 gag protein (DEC‐Gag) vaccine; for the induction of helper CD4+ T cells to a Recombinant Newcastle disease virus expressing codon optimized HIV‐1 Gag P55 (rNDV‐L‐Gag) vaccine. Methods We do so through successive administration of anti‐DEC205‐gagP24 protein plus polyICLC (DEC‐Gag) vaccine and rNDV‐L‐Gag. First strong gag specific helper CD4+ T cells are induced in mice by selected targeting of anti‐DEC205‐gagP24 protein vaccine to dendritic cells (DC) in situ together with polyICLC as adjuvant. This targeting helped T cell immunity develop to a subsequent rNDV‐L‐Gag vaccine and improved both systemic and mucosal gag specific immunity. Results This sequential DEC‐Gag vaccine prime followed by an rNDV‐L‐gag boost results to improved viral vectored immunization in murine airway, including mobilization of protective CD8+ T cells to a pathogenic virus infection site. Conclusion Thus, complementary prime boost vaccination, in which prime and boost favor distinct types of T cell immunity, improves viral vectored immunization, including mobilization of protective CD8+T cells to a pathogenic virus infection site such as the murine airway.
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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) | 0.002 | 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".