HIV-1-specific exosome targeted CD8+ T cell Vaccine. (45.24)
Bibliographic record
Abstract
Abstract Severe immuno-suppression due to immuno-tolerance and CD4 T cells depletion is the distinguishing feature of HIV-1 infection. Although highly active antiviral therapy (HAART) is available to halt progression of AIDS, it has its own inherent defects, including incomplete protection with associated side effects, and economical concerns. In addition, most of the currently available vaccines fail to induce effective CD8 CTL against HIV-1 in absence of CD4 T cells. Previously, our laboratory showed the efficacy of novel exosome (EXO)-targeted CD4 T cell vaccine (aTexo) with uptake of ova-specific dendritic (DC)-cell-released exosomes in the absence of CD4 T cells using highly metastasizing tumor model. In the present study, we find that aTexo vaccine prepared from active CD8 T cells is capable to induce CD8 CTLs, and its effect is mediated through IL-2 secretion, acquired pMHC I complexes, and partially on CD80 and CD40L costimulators. We have constructed an adenovirus-gp120 vector, which will be used to harvest gp-120-specific exosomes following DC infection, and established various tumor cell lines by transfecting gp-120 gene. We propose to generate gp-120-specific aTexo vaccine and test its efficacy in the presence or absence of CD4 T cells. These studies may significantly impact the development of novel therapeutic vaccines against HIV-1 infection.
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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 | 0.000 |
| 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".