PD1-based DNA vaccine amplifies HIV-1 GAG-specific CD8+ T cells in mice
Bibliographic record
Abstract
Viral vector-based vaccines that induce protective CD8+ T cell immunity can prevent or control pathogenic SIV infections, but issues of preexisting immunity and safety have impeded their implementation in HIV-1. Here, we report the development of what we believe to be a novel antigen-targeting DNA vaccine strategy that exploits the binding of programmed death-1 (PD1) to its ligands expressed on dendritic cells (DCs) by fusing soluble PD1 with HIV-1 GAG p24 antigen. As compared with non-DC-targeting vaccines, intramuscular immunization via electroporation (EP) of the fusion DNA in mice elicited consistently high frequencies of GAG-specific, broadly reactive, polyfunctional, long-lived, and cytotoxic CD8+ T cells and robust anti-GAG antibody titers. Vaccination conferred remarkable protection against mucosal challenge with vaccinia GAG viruses. Soluble PD1-based vaccination potentiated CD8+ T cell responses by enhancing antigen binding and uptake in DCs and activation in the draining lymph node. It also increased IL-12-producing DCs and engaged antigen cross-presentation when compared with anti-DEC205 antibody-mediated DC targeting. The high frequency of durable and protective GAG-specific CD8+ T cell immunity induced by soluble PD1-based vaccination suggests that PD1-based DNA vaccines could potentially be used against HIV-1 and other pathogens.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.002 |
| 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".