Toll-Like Receptor 7/8 Ligand, S28463, Suppresses <i>Ascaris suum</i> –induced Allergic Asthma in Nonhuman Primates
Bibliographic record
Abstract
S28463 (S28), a ligand for Toll-like receptor 7/8, has been shown to have antiinflammatory properties in rodent models of allergic asthma. The principle goal of this study was to assess whether these antiinflammatory effects can also be observed in a nonhuman primate (NHP) model of allergic asthma. NHPs were sensitized then challenged with natural allergen, Ascaris suum extract. The animals were treated with S28 orally before each allergen challenge. The protective effect of S28 in NHPs was assessed by measuring various asthma-related phenotypes. We also characterized the metabolomic and proteomic signatures of the lung environment and plasma to identify markers associated with the disease and treatment. Our data demonstrate that clinically relevant parameters, such as wheal and flare response, blood IgE levels, recruitment of white blood cells to the bronchoalveolar space, and lung responsiveness, are decreased in the S28-treated allergic NHPs compared with nontreated allergic NHPs. Furthermore, we also identified markers that can distinguish allergic from nonallergic or allergic and drug-treated NHPs, such as metabolites, phosphocreatine and glutathione, in the plasma and BAL fluid, respectively; and inflammatory cytokines, IL-5 and IL-13, in the bronchoalveolar lavage fluid. Our preclinical study demonstrates that S28 has potential as a treatment for allergic asthma in primate species closely related to humans. Combined with our previous findings, we demonstrate that S28 is effective in different models of asthma and in different species, and has the antiinflammatory properties clinically relevant for the treatment of allergic 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) | 0.000 | 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) | 0.002 | 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".