A role for decorin in a murine model of allergen-induced asthma
Bibliographic record
Abstract
Decorin (Dcn) is an extracellular matrix proteoglycan, which affects airway mechanics, airway-parenchymal interdependence, airway smooth muscle proliferation and apoptosis, and transforming growth factor-β bioavailability. As Dcn deposition is differentially altered in asthma, we questioned whether Dcn deficiency would impact the development of allergen-induced asthma in a mouse model. Dcn(-/-) and Dcn(+/+) mice (C57Bl/6) were sensitized with ovalbumin (OA) and challenged intranasally 3 days/wk × 3 wk. After OA challenge, mice were anesthetized, and respiratory mechanics measured under baseline conditions and after delivery of increasing concentrations of methacholine aerosol. Complex impedance was partitioned into airway resistance and tissue elastance and damping. Bronchoalveolar lavage was performed. Lungs were excised, and tissue sections evaluated for inflammatory cell influx, α-smooth muscle actin, collagen, biglycan, and Dcn deposition. Changes in TH-2 cytokine mRNA and protein were also measured. Airway resistance was increased in OA-challenged Dcn(+/+) mice only (P < 0.05), whereas tissue elastance and damping were increased in both OA-challenged Dcn(+/+) and Dcn(-/-), but more so in Dcn(+/+) mice (P < 0.001). Inflammation and collagen staining within the airway wall were increased with OA in Dcn(+/+) only (P < 0.001 and P < 0.01, respectively, vs. saline). IL-5 and IL-13 mRNA were increased in lung tissue of OA-challenged Dcn(+/+) mice. Dcn deficiency resulted in more modest OA-induced hyperresponsiveness, evident at the level of the central airways and distal lung. Differences in physiology were accompanied by differences in inflammation and remodeling. These findings may be, in part, due to the well-described ability of Dcn to bind transforming growth factor-β and render it less bioavailable.
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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 | 0.000 |
| 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) | 0.002 | 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".