Montelukast Inhibits Leukotriene Stimulation of Human Dendritic Cells in vitro
Bibliographic record
Abstract
BACKGROUND: Leukotrienes are potent inflammatory mediators which modulate immune responses and induce bronchoconstriction in susceptible individuals. Montelukast (MK) is a leukotriene receptor (CysLT1) antagonist that has been shown to prevent exacerbation of asthma. Considering the plethora of potential cellular targets for MK, specific mechanisms for its therapeutic action are still not fully understood. In vitro, we determined whether human dendritic cell function could be affected by leukotriene C(4) (LTC(4)) treatment and whether MK had potential in modulating this response. We also studied the effect of LTC(4) in the context of response to an airway virus (respiratory syncytial virus, RSV). METHODS: Human monocyte-derived dendritic cells (moDCs) exposed to LTC(4), MK, or both, were cocultured with autologous T cells, with or without RSV. The effects of LTC(4) and MK on cell function were determined by ELISA and proliferation assays. RESULTS: Both moDCs and their precursors--monocytes--express LTC(4) receptor CysLT1, making them potential targets for MK. moDCs cultured with LTC(4) release the eosinophil chemoattractant RANTES (CCL5) and induce greater T cell proliferation. Both were blocked by the presence of MK. MK treatment, albeit anti-inflammatory, did not interfere with the moDC-dependent T cell-proliferative responses induced by RSV. CONCLUSIONS: LTC(4), chronically present in the airways of asthma patients, could induce an exaggerated inflammatory response to airway infection via dendritic cell activation, which would be prevented by MK. Our study provides additional insight into the mechanisms of action of this leukotriene receptor antagonist.
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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) | 0.001 | 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".