Nootkatone attenuates airway inflammation in asthmatic mice through repressing ROS-induced NLRP3 inflammasome activation
Bibliographic record
Abstract
Nootkatone (NKT) exhibits potential pharmacological activities including anti-oxidation and anti-inflammation. Nevertheless, little is known about the roles of NKT in asthmatic airway inflammation. In the study, mice were sensitized and challenged with ovalbumin (OVA) to establish experimental allergic asthma model. After treatment with NKT, lung tissues, peripheral blood, and bronchoalveolar lavage fluid (BALF) were collected to assess inflammatory cytokines, oxidative stress, and pathological alternations. The effects of NKT on regulating reactive oxygen species (ROS)-induced NLR family pyrin domain containing 3 (NLRP3) inflammasome activation was assessed in IL-13-treated BEAS-2B cell model. We found that NKT treatment decreased the production of Th2 inflammatory cytokines (IL-4, IL-5, and IL-13) in BALF and IgE levels in serum, and alleviated inflammatory cell penetration, goblet cell proliferation, collagen accumulation, and mucus hypersecretion in lung tissues. NKT treatment mitigated oxidative stress and NLRP3 inflammasome activation in asthmatic mice. IL-13 treatment induced oxidative stress and NLRP3-mediated pyroptosis in BEAS-2B bronchial epithelial cells, whereas these effects were blocked by NKT. NKT protected against airway remodeling, as indicated by decreased epithelial-mesenchymal transition. Taken together, these results demonstrate that NKT mitigates asthmatic airway inflammation by inhibiting ROS-triggered NLRP3 activation and may be a potential agent for treating 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) | 0.001 | 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".