Focal adhesion kinase mediates the interferon-γ-inducible GTPase-induced phosphatidylinositol 3-kinase/Akt survival pathway and further initiates a positive feedback loop of NF-κB activation
Bibliographic record
Abstract
Interferon-gamma-inducible GTPase (IGTP) expression is upregulated in coxsackievirus B3 (CVB3)-infected murine heart and inhibits CVB3-induced apoptosis through activation of the PI3 kinase/Akt pathway. However, the mechanism of this pathway activation is unknown. In this study, using doxcycycline-inducible Tet-On HeLa cells that overexpress IGTP, we have demonstrated that focal adhesion kinase (FAK) is phosphorylated in response to IGTP expression and that transfection of the Tet-On HeLa cells with a dominant negative FAK (FRNK) blocks Akt activation. Furthermore, induction of IGTP also promoted the NF-kappaB activation as evidenced by its enhanced nuclear translocation, binding to transcriptional promoters and increased transcriptional activity. However, FRNK transfection and phosphatidylinositol 3-kinase (PI3K) inhibitor LY294002 both blocked the IGTP-induced translocation and NF-kappaB activation. Furthermore, silencing NF-kappaB with siRNAs significantly inhibited the phosphorylation of FAK and Akt, but not their total expression levels, indicating that NF-kappaB activation is required for the IGTP-induced activation of FAK and PI3K/Akt. Finally, blocking this survival pathway by transfection of FRNK or silencing of NF-kappaB reduced CVB3 replication and enhanced cell death during CVB3 infection. Taken together, these results suggest that FAK is a mediator upstream of PI3K/Akt and NF-kappaB functions as a downstream effector and also positively regulates the activity of upstream kinases.
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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) | 0.002 | 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".