25-hydroxyvitamin D3 exerts a protective effect on coronary artery lesions in a mouse model of Kawasaki disease by inhibiting JAK1/STAT3 and TLR4 pathways
Bibliographic record
Abstract
Background: Kawasaki disease (KD) is an acute vasculitis in children, and the resultant inflammatory process can lead to coronary artery aneurysms. The study aimed to investigate the role of 25-hydroxyvitamin D3 (25-OH-D3), a stable circulating form of vitamin D3, in KD mouse models. Methods: The KD mouse model was established through intraperitoneal injection of 500 μg Lactobacillus casei cell wall extract (LCWE). 25-OH-D3 was intraperitoneally injected to mice before and after LCWE injection. The mice were euthanized 7, 14, or 28 days after LCWE injection. Hematoxylin-eosin staining was performed to observe inflammation in mouse coronary artery tissues. ELISA was conducted to assess serum levels of inflammatory cytokines (tumour necrosis factor α and interleukin-1 beta ). Aorta areas and maximal aorta diameters were measured. Western blotting was performed to measure factors involved in JAK1/STAT3 and TLR4 signalling pathways. Results: LCWE caused inflammatory cell infiltration in mouse coronary arteries, leading to high heart vessel inflammation scores, coronary artery lesion scores, and inflammatory cytokine levels within 28 days. In addition, LCWE induced the development of abdominal aorta aneurysms and dilatations. 25-OH-D3 exerted a protective role in the KD mouse model by inhibiting coronary artery lesions and inflammation. Moreover, 25-OH-D3 suppressed LCWE-induced activation of the JAK1/STAT3 and TLR4 pathways in coronary artery tissues. Conclusion: 25-OH-D3 ameliorates LCWE-induced coronary artery lesions and inflammation in mice by inhibiting the JAK1/STAT3 and TLR4 pathways.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".