CysLT1 Receptor Engagement Induces Activator Protein-1– and NF-κB–Dependent IL-8 Expression
Bibliographic record
Abstract
Because cysteinyl-leukotrienes (cysLTs) are major protagonists in the pathophysiology of human asthma, and because neutrophils are involved in the more severe form of asthma, we studied the potential for leukotriene (LT) D(4) to induce synthesis of the chemokine IL-8 through activation of the CysLT1 receptor. We found LTD(4) to induce IL-8 gene expression in monocytic THP-1 cells and human dendritic cells with complete abrogation by selective CysLT1 antagonists. Human embryonic kidney-293 cells stably transfected with CysLT1 were used to better study the transcriptional regulation of the IL-8 promoter. Stimulation of the cells with graded concentrations of LTD(4) resulted in a time- and concentration-dependent induction of IL-8 transcription and protein synthesis. Use of IL-8 promoter mutants with substitutions in their NF-kappaB, activator protein (AP)-1, and NF-IL-6 binding elements revealed a requirement for NF-kappaB and AP-1, but not NF-IL-6, in LTD(4)-induced activation of the IL-8 promoter. Overexpression of dominant-negative IkappaBalpha inhibited the IL-8 transactivation induced by LTD(4). NF-kappaB DNA binding activity was induced by LTD(4), as determined by electrophoretic mobility shift assays, and could be supershifted by antibodies against p50 and p65. Supershift assays after LTD(4) stimulation also indicated the formation of a c-Jun/c-Fos complex. Moreover, our results demonstrate that LTD(4) upregulates the expression of c-fos and c-jun at the mRNA level. Our data show for the first time that LTD(4), via the CysLT1 receptor, can transcriptionally activate IL-8 production, with involvement of the transcription factors p50, p65, Fos, and Jun. These findings provide mechanistic and potentially therapeutic elements for modulation of the inflammatory component of asthma.
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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".