Stimulus-Selective Regulation of Human Mast Cell Gene Expression, Degranulation and Leukotriene Production by Fluticasone and Salmeterol
Bibliographic record
Abstract
Despite the fact that glucocorticoids and long acting beta agonists are effective treatments for asthma, their effects on human mast cells (MC) appear to be modest. Although MC are one of the major effector cells in the underlying inflammatory reactions associated with asthma, their regulation by these drugs is not yet fully understood and, in some cases, controversial. Using a human immortalized MC line (LAD2), we studied the effects of fluticasone propionate (FP) and salmeterol (SM), on the release of early and late phase mediators. LAD2 cells were pretreated with FP (100 nM), SM (1 µM), alone and in combination, at various incubation times and subsequently stimulated with agonists substance P, C3a and IgE/anti-IgE. Degranulation was measured by the release of β-hexosaminidase. Cytokine and chemokine expression were measured using quantitative PCR, ELISA and cytometric bead array (CBA) assays. The combination of FP and SM synergistically inhibited degranulation of MC stimulated with substance P (33% inhibition compared to control, n = 3, P<.05). Degranulation was inhibited by FP alone, but not SM, when MC were stimulated with C3a (48% inhibition, n = 3, P<.05). As previously reported, FP and SM did not inhibit degranulation when MC were stimulated with IgE/anti-IgE. FP and SM in combination inhibited substance P-induced release of tumor necrosis factor (TNF), CCL2, and CXCL8 (98%, 99% and 92% inhibition, respectively, n = 4, P<.05). Fluticasone and salmeterol synergistically inhibited mediator production by human MC stimulated with the neuropeptide substance P. This synergistic effect on mast cell signaling may be relevant to the therapeutic benefit of combination therapy in 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) | 0.000 | 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 | 0.000 |
| 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 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".