TLR7 ligand prevents allergen-induced airway hyperresponsiveness and eosinophilia in allergic asthma by a MYD88-dependent and MK2-independent pathway
Bibliographic record
Abstract
Asthma is one of the leading causes of childhood hospitalization, and its incidence is on the rise throughout the world. Currently, the standard treatment for asthma is the use of corticosteroids to try to suppress the inflammatory reaction taking place in the bronchial tree. Using a murine model of atopic allergic asthma employing a methacholine-hyperresponsive (A/J) as well as a hyporesponsive (C57BL/6) strain of mice sensitized and challenged with ovalbumin, we show that treatment with a synthetic Toll-like receptor 7 (TLR7) ligand (S-28463, a member of the imidazoquinoline family) prevents development of the asthmatic phenotype. Treatment with S-28463 resulted in a reduction of airway resistance and elastance following ovalbumin sensitization and challenge. This was accompanied by a dramatic reduction in infiltration of leukocytes, especially eosinophils, into the lungs of both C57BL/6 and A/J mice following OVA challenge. Treatment with S-28463 also abolished both the elevation in serum IgE level as well as the induction of IL-4, IL-5, and IL-13 by OVA challenge. The protective effects of S-28463 were also observed in MK2 knockout, but not MYD88 knockout, mice. We did not observe a switch in cytokine profile from T(H)2 to T(H)1, as both IL-12p70 and IFN-gamma levels were reduced following S-28463 treatment. These results clearly demonstrate the anti-inflammatory effect of imidazoquinolines in an allergic asthma model as well as the clinical potential of TLR7 ligands in the treatment of allergic diseases.
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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) | 0.000 | 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 | 0.001 |
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".