The genome of self-complementary adeno-associated viral vectors increases Toll-like receptor 9–dependent innate immune responses in the liver
Bibliographic record
Abstract
Although adeno-associated viral (AAV) vectors have been successfully used in hepatic gene transfer for treatment of hemophilia and other diseases in animals, adaptive immune responses blocked long-term transgene expression in patients on administration of single-stranded AAV serotype-2 vector. More efficient vectors have been developed using alternate capsids and self-complimentary (sc) genomes. This study investigated their effects on the innate immune profile on hepatic gene transfer to mice. A mild and transient up-regulation of myeloid differentiation primary response gene (88), TLR9, TNF-α, monocyte chemotactic protein-1, IFN-γ inducible protein-10, and IFN-α/β expression in the liver was found after single-stranded AAV vector administration, regardless of the capsid sequence. In contrast, scAAV vectors induced higher increases of these transcripts, upregulated additional proinflammatory genes, and increased circulating IL-6. Neutrophil, macrophage, and natural killer cell liver infiltrates were substantially higher on injection of scAAV. Some but not all of these responses were Kupffer cell dependent. Independent of the capsid or expression cassette, scAAV vectors induced dose-dependent innate responses by signaling through TLR9. Increased innate responses to scAAV correlated with stronger adaptive immune responses against capsid (but not against the transgene product). However, these could be blunted by transient inhibition of TLR9.
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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 | 0.000 |
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".