Inhibition of Antigen-induced Eosinophilia and Airway Hyperresponsiveness by Antisense Oligonucleotides Directed against the Common β Chain of IL-3, IL-5, GM-CSF Receptors in a Rat Model of Allergic Asthma
Bibliographic record
Abstract
Airway obstruction, hyperresponsiveness, and the accumulation and persistence within the airways of inflammatory cells characterize asthma. Interleukin (IL)-3, granulocyte macrophage colony- stimulating factor (GM-CSF), and IL-5 are among several cytokines that have been shown to be increased in asthma and to contribute to atopic inflammation. They mediate their effect via receptors that have a common beta subunit (beta(c)). We hypothesized that blocking of this common beta(c) would impair the airway response to antigen. We report that an antisense (AS) phosphorothioate oligodeoxynucleotide (ODN) found to specifically inhibit transcription of the beta(c) in rat bone marrow cells also caused inhibition of beta(c) mRNA expression and of immunoreactive cells within the lungs of Brown Norway (BN) rats when injected intratracheally (p < 0.01). Inhibition of beta(c) significantly reduced (p < 0.01) experimentally induced eosinophilia in vivo in ovalbumin (OVA)-sensitized BN rats after antigen challenge. Furthermore, when compared with mismatch-treated rats, beta(c) AS-ODN caused inhibition of antigen-induced airway hyperresponsiveness to leukotriene D4. Taken together, our findings demonstrate that the common beta(c) of IL-3, IL-5, and GM-CSF receptors is involved in the eosinophil influx and airway hyperresponsiveness that follow OVA challenge and underscore the potential utility of a topical antisense approach targeting beta(c) for the treatment of asthma.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".