Interaction of monocytic cells with respiratory syncytial virus results in activation of NF-κB and PKC-α/β leading to up-regulation of IL-15 gene expression
Bibliographic record
Abstract
Respiratory syncytial virus (RSV) is a major human respiratory pathogen, particularly for infants. RSV is also a powerful inducer of cytokines, one of which is IL-15, an important immunoregulatory cytokine. IL-15 plays a key role in NK and T cell development and differentiation and also regulates NK cell/macrophage interaction, as well as monocyte/macrophage and granulocyte function. We have shown previously that different viruses up-regulate IL-15 gene expression in human PBMCs. Recently, we found that RSV induces the expression of IL-15 mRNA in the monocytic line THP-1. The signaling pathway involved in such virus-induced up-regulation of IL-15 has not yet been identified. We report here a study describing this mechanism. Because of the involvement of the protein kinase C (PKC) and the transcription factor NF-kappaB in the regulation of others cytokines by RSV as well as the involvement of NF-kappaB in the transactivation of IL-15, our hypothesis was that RSV induced the expression of IL-15 in THP-1 cells through the PKC and NF-kappaB activation. We demonstrate here that RSV-induced up-regulation of IL-15 expression in THP-1 cells involves the phosphorylation of PKC-alpha/beta. Further, inhibition of PKC by different specific inhibitors blocks this up-regulation. Using the electromobility shift assay, we show that the activated form of NF-kappaB binds to the IL-15 promoter sequence. We further confirm, using an ELISA assay, the involvement of p65 in the transcription of IL-15. This study, demonstrating the ability of RSV to induce IL-15 expression, might explain, at least in part, the exacerbated, inflammatory response triggered by RSV infection.
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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 | 0.001 |
| 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".