Selective CB2 Receptor Agonist, HU-308, Reduces Systemic Inflammation in Endotoxin Model of Pneumonia-Induced Acute Lung Injury
Bibliographic record
Abstract
Acute respiratory distress syndrome (ARDS) and sepsis are risk factors contributing to mortality in patients with pneumonia. In ARDS, also termed acute lung injury (ALI), pulmonary immune responses lead to excessive pro-inflammatory cytokine release and aberrant alveolar neutrophil infiltration. Systemic spread of cytokines is associated with systemic complications including sepsis, multi-organ failure, and death. Thus, dampening pro-inflammatory cytokine release is a viable strategy to improve outcome. Activation of cannabinoid type II receptor (CB2) has been shown to reduce cytokine release in various in vivo and in vitro studies. Herein, we investigated the effect of HU-308, a specific CB2 agonist, on systemic and pulmonary inflammation in a model of pneumonia-induced ALI. C57Bl/6 mice received intranasal endotoxin or saline, followed by intravenous HU-308, dexamethasone, or vehicle. ALI was scored by histology and plasma levels of select inflammatory mediators were assessed by Luminex assay. Intravital microscopy (IVM) was performed to assess leukocyte adhesion and capillary perfusion in intestinal and pulmonary microcirculation. HU-308 and dexamethasone attenuated LPS-induced cytokine release and intestinal microcirculatory impairment. HU-308 modestly reduced ALI score, while dexamethasone abolished it. These results suggest administration of HU-308 can reduce systemic inflammation without suppressing pulmonary immune response in pneumonia-induced ALI and systemic inflammation.
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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) | 0.001 | 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 | 0.000 |
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".