Proteinase activated receptor‐2‐mediated dual oxidase‐2 up‐regulation is involved in enhanced airway reactivity and inflammation in a mouse model of allergic asthma
Bibliographic record
Abstract
Airway epithelial cells (AECs) express a variety of receptors, which sense danger signals from various aeroallergens/pathogens being inhaled constantly. Proteinase-activated receptor 2 (PAR-2) is one such receptor and is activated by cockroach allergens, which have intrinsic serine proteinase activity. Recently, dual oxidases (DUOX), especially DUOX-2, have been shown to be involved in airway inflammation in response to Toll-like receptor activation. However, the association between PAR-2 and DUOX-2 has not been explored in airways of allergic mice. Therefore, this study investigated the contribution of DUOX-2/reactive oxygen species (ROS) signalling in airway reactivity and inflammation after PAR-2 activation. Mice were sensitized intraperitoneally with intact cockroach allergen extract (CE) in the presence of aluminium hydroxide followed by intranasal challenge with CE. Mice were then assessed for airway reactivity, inflammation, oxidative stress (DUOX-2, ROS, inducible nitric oxide synthase, nitrite, nitrotyrosine and protein carbonyls) and apoptosis (Bax, Bcl-2, caspase-3). Challenge with CE led to up-regulation of DUOX-2 and ROS in AECs with concomitant increases in airway reactivity/inflammation and parameters of oxidative stress, and apoptosis. All of these changes were significantly inhibited by intranasal administration of ENMD-1068, a small molecule antagonist of PAR-2 in allergic mice. Administration of diphenyliodonium to allergic mice also led to improvement of allergic airway responses via inhibition of the DUOX-2/ROS pathway; however, these effects were less pronounced than PAR-2 antagonism. The current study suggests that PAR-2 activation leads to up-regulation of the DUOX-2/ROS pathway in AECs, which is involved in regulation of airway reactivity and inflammation via oxidative stress and apoptosis.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".