Antiatherosclerotic effect of dehydrocorydaline on ApoE−/− mice: inhibition of macrophage inflammation
Bibliographic record
Abstract
Abstract Despite improvements in cardiovascular disease (CVD) outcomes by cholesterol-lowering statin therapy, the high rate of CVD is still a great concern worldwide. Dehydrocorydaline (DHC) is an alkaloidal compound isolated from the traditional Chinese herb Corydalis yanhusuo . Emerging evidence shows that DHC has anti-inflammatory and antithrombotic benefits, but whether DHC exerts any antiatherosclerotic effects remains unclear. Our study revealed that intraperitoneal (i.p.) injection of DHC in apolipoprotein E-deficient (ApoE −/− ) mice not only inhibited atherosclerosis development but also improved aortic compliance and increased plaque stability. In addition, DHC attenuated systemic and vascular inflammation in ApoE −/− mice. As macrophage inflammation plays an essential role in the pathogenesis of atherosclerosis, we next examined the direct effects of DHC on bone marrow-derived macrophages (BMDMs) in vitro. Our RNA-seq data revealed that DHC dramatically decreased the levels of proinflammatory gene clusters. We verified that DHC significantly downregulated proinflammatory interleukin (IL)-1β and IL-18 mRNA levels in a time- and concentration-dependent manner. Furthermore, DHC decreased lipopolysaccharide (LPS)-induced inflammation in BMDMs, as evidenced by the reduced protein levels of CD80, iNOS, NLRP3, IL-1β, and IL-18. Importantly, DHC attenuated LPS-induced activation of p65 and the extracellular signal-regulated kinase 1/2 (ERK1/2) pathway. Thus, we conclude that DHC ameliorates atherosclerosis in ApoE −/− mice by inhibiting inflammation, likely by targeting macrophage p65- and ERK1/2-mediated 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) | 0.001 | 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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".