Helper-Dependent Adenovirus Vectors Elicit Intact Innate but Attenuated Adaptive Host Immune Responses In Vivo
Bibliographic record
Abstract
Helper-dependent adenovirus (HD-Ad) vectors with all adenoviral genes deleted mediate very long-term expression of therapeutic transgenes in a variety of animal models of disease. These vectors are associated with reduced toxicity and improved safety relative to traditional early region 1 deletion first-generation Ad (FG-Ad) vectors. Many studies have clearly demonstrated that FG-Ad vectors induce innate and adaptive immune responses in vivo; however, a comprehensive analysis of host immune responses to HD-Ad vectors has not yet been performed. In DBA/2 mice, intravenous injection of HD-Ad vectors encoding LacZ (HD-AdLacZ) or a murine secreted alkaline phosphatase (HD-AdSEAP) induced an early expression of inflammatory cytokine and chemokine genes in the liver, including interferon-inducible protein 10, macrophage inflammatory protein 2, and tumor necrosis factor alpha, and were expressed in a pattern similar to that induced by FG-Ad vectors encoding AdSEAP. Like AdSEAP, and consistent with the pattern of cellular gene expression, HD-AdLacZ and HD-AdSEAP induced the recruitment of CD11b-positive leukocytes to the transduced liver within hours of administration. AdSEAP also induced a second phase of liver inflammation, consisting of inflammatory gene expression and CD3-positive lymphocytic infiltrates 7 days posttransduction. In contrast, beyond 24 h no infiltrates or expression of inflammatory genes was detected in the livers of mice receiving HD-AdSEAP. Despite the lack of liver inflammation at 7 days, Ad-specific cytotoxic T lymphocytes could be detected in mice receiving HD-AdSEAP. This lack of liver inflammation was not due to reduced transduction since levels of transgene expression and the amounts of vector DNA in the liver were equivalent in mice receiving HD-AdSEAP and AdSEAP. These results demonstrate that HD-Ad vectors induce intact innate but attenuated adaptive immune responses in vivo.
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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 | 0.000 | 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".