Protective Roles for RGS2 in a Mouse Model of House Dust Mite-Induced Airway Inflammation
Bibliographic record
Abstract
The GTPase-accelerating protein, regulator of G-protein signalling 2 (RGS2) reduces signalling from G-protein-coupled receptors (GPCRs) that signal via Gαq. In humans, RGS2 expression is up-regulated by inhaled corticosteroids (ICSs) and long-acting β2-adrenoceptor agonists (LABAs) such that synergy is produced in combination. This may contribute to the superior clinical efficacy of ICS/LABA therapy in asthma relative to ICS alone. In a murine model of house dust mite (HDM)-induced airways inflammation, three weeks of intranasal HDM (25 μg, 3×/week) reduced lung function and induced granulocytic airways inflammation. Compared to wild type animals, Rgs2-/- mice showed airways hyperresponsiveness (increased airways resistance and reduced compliance). While HDM increased pulmonary inflammation observed on hematoxylin and eosin-stained sections, there was no difference between wild type and Rgs2-/- animals. HDM-induced mucus hypersecretion was also unaffected by RGS2 deficiency. However, inflammatory cell counts in the bronchoalveolar lavage fluid of Rgs2-/- animals were significantly increased (57%) compared to wild type animals and this correlated with increased granulocyte (neutrophil and eosinophil) numbers. Likewise, cytokine and chemokine (IL4, IL17, IL5, LIF, IL6, CSF3, CXCLl, CXCL10 and CXCL11) release was increased by HDM exposure. Compared to wild type, Rgs2-/- animals showed a trend towards increased expression for many cytokines/chemokines, with CCL3, CCL11, CXCL9 and CXCL10 being significantly enhanced. As RGS2 expression was unaffected by HDM exposure, these data indicate that RGS2 exerts tonic bronchoprotection in HDM-induced airways inflammation. Modest anti-inflammatory and anti-remodelling roles for RGS2 are also suggested. If translatable to humans, therapies that maximize RGS2 expression may prove advantageous.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".