Characterization of <scp>AQX</scp>‐1125, a small‐molecule <scp>SHIP1</scp> activator
Bibliographic record
Abstract
BACKGROUND: The efficacy of AQX-1125, a small-molecule SH2-containing inositol-5'-phosphatase 1 (SHIP1) activator and clinical development candidate, is investigated in rodent models of inflammation. EXPERIMENTAL APPROACH: AQX-1125 was administered orally in a mouse model of passive cutaneous anaphylaxis (PCA) and a number of rodent models of respiratory inflammation including: cigarette smoke, LPS and ovalbumin (OVA)-mediated airway inflammation. SHIP1 dependency of the AQX-1125 mechanism of action was investigated by comparing the efficacy in wild-type and SHIP1-deficient mice subjected to an intrapulmonary LPS challenge. RESULTS: AQX-1125 exerted anti-inflammatory effects in all of the models studied. AQX-1125 decreased the PCA response at all doses tested. Using bronchoalveolar lavage (BAL) cell counts as an end point, oral or aerosolized AQX-1125 dose dependently decreased the LPS-mediated pulmonary neutrophilic infiltration at 3-30 mg kg⁻¹ and 0.15-15 μg kg⁻¹ respectively. AQX-1125 suppressed the OVA-mediated airway inflammation at 0.1-10 mg kg⁻¹. In the smoke-induced airway inflammation model, AQX-1125 was tested at 30 mg kg⁻¹ and significantly reduced the neutrophil infiltration of the BAL fluid. AQX-1125 (10 mg kg⁻¹) decreased LPS-induced pulmonary neutrophilia in wild-type mice but not in SHIP1-deficient mice. CONCLUSIONS: The SHIP1 activator, AQX-1125, suppresses leukocyte accumulation and inflammatory mediator release in rodent models of pulmonary inflammation and allergy. As shown in the mouse model of LPS-induced lung inflammation, the efficacy of the compound is dependent on the presence of SHIP1. Pharmacological SHIP1 activation may have clinical potential for the treatment of pulmonary inflammatory 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 | 0.000 |
| 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".