Adenovirus Vector-Induced Expression of the C-X-C Chemokine IP-10 Is Mediated through Capsid-Dependent Activation of NF-κB
Bibliographic record
Abstract
The use of adenovirus vectors for gene therapy has been limited by well-defined cellular and humoral immune responses. We have previously shown that adenovirus vectors rapidly induce the expression of the C-X-C chemokine, interferon-inducible protein 10 (IP-10), in vivo. Various first-generation, type 5 adenovirus vectors, including adCMVbetagal and UV-psoralen-inactivated adenovirus, equally induced the expression of IP-10 mRNA as early as 3 h following infection in mouse renal epithelial cells (REC). Luciferase reporter experiments using deletional mutants of the murine IP-10 5'-flanking region revealed that transcriptional activation of the IP-10 promoter by adCMVbetagal was dependent on the -161- to -96-bp region upstream of the transcription start site. In electrophoretic mobility shift assays, adCMVbetagal, adCMV-GFP, FG140, and transcription-defective adenovirus induced protein binding to oligonucleotides containing a consensus sequence for NF-kappaB at position -113 of the IP-10 promoter. Supershift assays confirmed an increase in binding activity of NF-kappaB p65 but not p50 or cRel in REC cells infected with various replication-deficient adenoviruses. Coinfection of REC cells with adCMVbetagal and an adenoviral vector expressing IkappaBalpha resulted in suppression of adCMVbetagal-induced expression of IP-10 at 6 and 16 h, further strengthening the conclusion that adenovirus-induced activation of IP-10 is dependent on NF-kappaB. The induction of IP-10 appeared to be direct because infection with adenovirus vectors failed to induce the expression of the potent IP-10 stimulators, interferon gamma and tumor necrosis factor alpha. Together, these findings demonstrate that adenovirus vectors directly induce the expression of IP-10 through capsid dependent activation of NF-kappaB.
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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) | 0.003 | 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".