NLRP3 Inflammasome Inhibition by MCC950 Reduces Atherosclerotic Lesion Development in Apolipoprotein E–Deficient Mice—Brief Report
Bibliographic record
Abstract
Objective— Inflammasomes are multiprotein complexes, and their activation has been associated with cardiovascular disease. Inflammasome activation leads to secretion of caspase-1 by innate immune cells, resulting in the activation of interleukin-1β. Recently, a potent and selective inhibitor of the NLRP3 inflammasome, MCC950, was described. In this study, we investigated the effect of MCC950 on atherosclerotic lesion development in apoE −/− mice. Approach and Results— First, we determined the efficacy of MCC950 in vitro. Bone marrow–derived macrophages and dendritic cells were stimulated with lipopolysaccharide and cholesterol crystals resulting in high levels of interleukin-1β release, which was inhibited by MCC950. In vivo MCC950 treatment reduced lipopolysaccharide–induced interleukin-1β secretion, without affecting the tumor necrosis factor-α response. Subsequently, atherosclerotic plaques were induced in Western-type diet fed apoE −/− mice by semiconstrictive perivascular collar placement at the carotid arteries, after which the mice received MCC950 (10 mg/kg) or vehicle control 3× per week intraperitoneally for 4 weeks. After euthanize, atherosclerotic plaque size and volume were quantified in hematoxylin-eosin–stained 10-µm cryosections throughout the artery. MCC950 treatment significantly reduced the development of atherosclerotic lesions as determined by maximal stenosis, average plaque size, and plaque volume. Although the amount of collagen and the necrotic core size were not affected, the number of macrophages in the plaque was significantly reduced on treatment. In addition, VCAM-1 (vascular cell adhesion molecule 1) and ICAM-1 (intercellular adhesion molecule 1) mRNA expression was significantly reduced in the carotids of MCC950-treated mice. Conclusions— These findings show that specific inhibition of the NLRP3 inflammasome using MCC950 can be a promising therapeutic approach to inhibit atherosclerotic lesion development.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".