Fluticasone propionate and mometasone furoate have equivalent transcriptional potencies
Bibliographic record
Abstract
BACKGROUND: Glucocorticoids exert their anti-inflammatory effects mainly through transrepression of the transcription factors activator protein-1 (AP-1) and nuclear factor-kappa B (NF-kappaB). Certain adverse effects of glucocorticoids are mediated through gene transactivation. Fluticasone propionate (FP) and mometasone furoate (MF) are the most recently developed topical glucocorticoids for the treatment of airway disorders. Their relative capacities to repress AP-1 and NF-kappaB activities are not known and comparison of their transactivation potencies has given unclear results. OBJECTIVE: To determine the relative transactivation and transrepression potencies of FP and MF. METHODS: Transactivation assays were performed in HeLa cells carrying a glucocorticoid-inducible luciferase gene. To measure transrepressive potencies of FP and MF, A549 lung epithelial cells were transiently transfected with an AP-1- or NF-kappaB-dependent luciferase gene. Using an immunoassay, we also evaluated the ability of MF and FP to inhibit the production of Regulated upon Activation, Normal T-cell Expressed and Secreted (RANTES), a pro-inflammatory cytokine, whose gene is controlled by AP-1 and NF-kappaB. Areas under the dose-response curve were calculated to determine relative potencies. RESULTS: FP and MF are equipotent for transactivation. Both molecules show globally the same potency to inhibit AP-1 and NF-kappaB activities and RANTES production. MF and FP have very significant transcriptional effects at 2x10(-10) M, which is the peak concentration reached in the plasma after inhalation of high dosages. Indeed, they produce a 17-fold induction of luciferase in the transactivation assay, and inhibit AP-1 activity, NF-kappaB activity and RANTES release by approximately 40%. CONCLUSION: FP and MF have the same ability to trigger gene activation and also the same potency to inhibit AP-1 and NF-kappaB activities. Their strong transcriptional effects at 2x10(-10) M suggest that these compounds act not only topically but also systemically, with the risk of provoking concomitant adverse effects at high dosages.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".