Cathepsin S in a Murine Model of Allergic Asthma (B108)
Bibliographic record
Abstract
Abstract Cathepsin S (Cat S), expressed predominately on antigen presenting cells, has been proposed as a therapeutic target for asthma. We used genetic and pharmacological tools to investigate the role of Cat S in murine models of allergic asthma. Mice null for Cat S were protected from OVA-induced pulmonary inflammation, but exhibited no protection from OVA-induced airway hyper-reactivity. To determine the role of Cat S during the challenge phase, we identified a potent and selective Cat S inhibitor, Compound A (Cpd A, IC50 mCat S = 0.6 nM, ≥470 fold selective vs mCat B, K, L), which inhibited antigen presentation in a mouse cell-based assay (IC50 = 44 nM). The prodrug of Cpd A, Cpd B, gave excellent plasma levels of Cpd A when dosed in mice by gavage, or in food. In vivo competition in mice with an irreversible pan-selective cysteine cathepsin probe showed that Cpd B gave selective inhibition of lung and spleen Cat S at 1 mpk, but lost selectivity at 50 mpk. Cpd B was dosed in mice (10, 100 mpk in food) over 4 days of the challenge period in the murine ovalbumin model. Both doses had no effect on bronchoalveolar lavage infiltrating cells, despite showing high levels of Cat S inhibition. Thus, Cat S inhibition in a therapeutic mode does not attenuate airway inflammation in antigen sensitised mice suggesting that anti-Cat S therapy would not be an effective asthma treatment.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| 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".