Immunization with a Lentiviral Vector Stimulates both CD4 and CD8 T Cell Responses to an Ovalbumin Transgene
Bibliographic record
Abstract
Lentiviral vectors encoding antigens are promising vaccine candidates because they transduce dendritic cells (DC) in vivo and prime CTL responses. Here we examine their stimulation of antigen-specific CD4(+) T cells, critical for protective immunity against tumors or infectious disease. We constructed lentiviral vectors (lentivectors) expressing ovalbumin, which was secreted (OVA), cytoplasmic (OVAcyt), or fused to either invariant chain (Ii-OVA) or transferrin receptor (TfR-OVA) sequences, targeting the MHC class II presentation pathway. Murine DC infected with the various lentivectors could stimulate OT-I (CD8(+), OVA TCR transgenic) T cells and all except OVAcyt could also stimulate OT-II (CD4(+), OVA TCR transgenic) T cells in vitro. Direct injection of the OVA-, Ii-OVA-, or TfR-OVA-expressing vectors into mice resulted in a CD4(+) T cell response, as shown by expansion of adoptively transferred OT-II T cells and upregulation of CD44 on these cells. The Ii-OVA vector was the most potent inducer of IFN-gamma-secreting CD4(+) and CD8(+) T cells and was the only vector to protect mice completely from challenge with OVA-expressing tumor cells. Therefore directly injected lentivectors can stimulate CD4(+) T cells; both CD4(+) and CD8(+) responses can be enhanced by targeting the antigen to the MHC class II pathway.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.001 | 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".