Akt/Protein Kinase B Activation by Adenovirus Vectors Contributes to NFκB-Dependent CXCL10 Expression
Bibliographic record
Abstract
In gene therapy, the innate immune system is a significant barrier to the effective application of adenovirus (Ad) vectors. In kidney epithelium-derived (REC) cells, serotype 5 Ad vectors induce the expression of the chemokine CXCL10 (IP-10), a response that is dependent on NFkappaB. Compared to the parental vector AdLuc, transduction with the RGD-deleted vector AdL.PB resulted in reduced CXCL10 activation despite increasing titers, implying that RGD-alpha(V) integrin interactions contribute to adenovirus induction of inflammatory genes. Akt, a downstream effector of integrin signaling, was activated within 10 min of transduction with Ad vectors in a dose-dependent manner. Akt activation was not present following transduction with AdL.PB, confirming the importance of capsid-alpha(V) integrin interactions in Ad vector Akt activation. Inhibition of the phosphoinositide-3-OH kinase/Akt pathway by Wortmannin or Ly294002 compounds decreased Ad vector induction of CXCL10 mRNA. Similarly, adenovirus-mediated overexpression of the dominant negative AktAAA decreased CXCL10 mRNA expression compared to the reporter vector AdLacZ alone. The effect of Akt on CXCL10 mRNA expression occurred via NFkappaB-dependent transcriptional activation, since AktAAA overexpression and Ly294002 both inhibited CXCL10 and NFkappaB promoter activation in luciferase reporter experiments. These results show that Akt plays a role in the Ad vector activation of NFkappaB and CXCL10 expression. Understanding the mechanism underlying the regulation of host immunomodulatory genes by adenovirus vectors will lead to strategies that will improve the efficacy and safety of these agents for clinical use.
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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 | 0.001 |
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".