Synthetic double-stranded RNA enhances airway inflammation and remodelling in a rat model of asthma
Bibliographic record
Abstract
Respiratory viral infections are frequently associated with exacerbations of asthma. Double-stranded RNA (dsRNA) produced during viral infections may be one of the stimuli for exacerbation. We aimed to assess the potential effect of dsRNA on certain aspects of chronic asthma through the administration of polyinosine-polycytidylic acid (poly I:C), synthetic dsRNA, to a rat model of asthma. Brown Norway rats were sensitized to ovalbumin and challenged three times to evoke airway remodelling. The effect of poly I:C on the ovalbumin-induced airway inflammation and structural changes was assessed from bronchoalveolar lavage fluid and histological findings. The expression of cytokines and chemokines was evaluated by real-time quantitative reverse transcription PCR and ELISA. Ovalbumin-challenged animals showed an increased number of total cells and eosinophils in bronchoalveolar lavage fluid compared with PBS-challenged controls. Ovalbumin-challenged animals treated with poly I:C showed an increased number of total cells and neutrophils in bronchoalveolar lavage fluid compared with those without poly I:C treatment. Ovalbumin-challenged animals showed goblet cell hyperplasia, increased airway smooth muscle mass, and proliferation of both airway epithelial cells and airway smooth muscle cells. Treatment with poly I:C enhanced these structural changes. Among the cytokines and chemokines examined, the expression of interleukins 12 and 17 and of transforming growth factor-β(1) in ovalbumin-challenged animals treated with poly I:C was significantly increased compared with those of the other groups. Double-stranded RNA enhanced airway inflammation and remodelling in a rat model of bronchial asthma. These observations suggest that viral infections may promote airway remodelling.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".