Selective Transcriptional Down-Regulation of Human Rhinovirus-Induced Production of CXCL10 from Airway Epithelial Cells via the MEK1 Pathway
Bibliographic record
Abstract
Human rhinovirus (HRV) infections can trigger exacerbations of lower airway diseases. Infection of airway epithelial cells induces production of a number of proinflammatory chemokines that may exacerbate airway inflammation, including CXCL10, a chemoattractant for type 1 lymphocytes and NK cells. Primary human bronchial epithelial cells and the BEAS-2B human bronchial epithelial cell line were used to examine the role of MAPK pathways in HRV-16-induced production of CXCL10. Surprisingly, PD98059 and U0126, two inhibitors of the MEK1/2-ERK MAPK pathway, significantly enhanced HRV-16-induced CXCL10 mRNA and protein. This enhancement was not seen with IFN-beta-induced production of CXCL10. Studies using small interfering RNA revealed that knockdown of MEK1, but not MEK2, was associated with enhanced HRV-induced CXCL10 production. Promoter construct studies revealed that PD98059 and U0126 enhanced HRV-16-induced transcriptional activation of CXCL10. HRV-16-induced promoter activation was regulated by two NF-kappaB binding sites, kappaB1 and kappaB2, and by an IFN-stimulated response element. Inhibitors of the MEK1/2-ERK pathway did not alter HRV-16-induced activation of tandem repeat kappaB1 or kappaB2 constructs, nor did they alter HRV-16-induced nuclear translocation/binding of NF-kappaB to either kappaB1 or kappaB2 recognition sequences. Furthermore, PD98059 and U0126 did not alter phosphorylation or degradation of IkappaBalpha. In contrast, inhibitors of the MEK1/2-ERK pathway, and small interfering RNA knockdown of MEK1, enhanced nuclear translocation/binding of IFN regulatory factor (IRF)-1 to the IFN-stimulated response element recognition sequence in HRV-16 infected cells. We conclude that activation of MEK1 selectively down-regulates HRV-16-induced expression of CXCL10 via modulation of IRF-1 interactions with the gene promoter in human airway epithelial cells.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.001 | 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 teacher head, 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".