IL-33 Reduces Macrophage Foam Cell Formation
Why this work is in the frame
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Bibliographic record
Abstract
The development of atherosclerosis, a chronic inflammatory disease characterized by the formation of arterial fibrotic plaques, has been shown to be reduced by IL-33 in vivo. However, whether IL-33 can directly affect macrophage foam cell formation, a key feature of atherosclerotic plaques, has not been determined. In this study, we investigated whether IL-33 reduces macrophage foam cell accumulation in vivo and if IL-33 reduces their formation in vitro using THP-1 and primary human monocyte-derived macrophages. In Apolipoprotein E(-/-) mice fed on a high fat diet, IL-33 treatment significantly reduced the accumulation of macrophage-derived foam cells in atherosclerotic plaques. IL-33 also reduced macrophage foam cell formation in vitro by decreasing acetylated and oxidized low-density lipoprotein uptake, reducing intracellular total and esterified cholesterol content and enhancing cholesterol efflux. These changes were associated with IL-33-mediated reduction in the expression of genes involved in modified low-density lipoprotein uptake, such as CD36, and simultaneous increase in genes involved in cholesterol efflux, including Apolipoprotein E, thereby providing a mechanism for such an action for this cytokine. IL-33 also decreased the expression of key genes implicated in cholesterol esterification and triglyceride storage, including Acyl-CoA:cholesterol acyltransferase 1 and Adipocyte differentiation-related protein. Furthermore, using bone marrow-derived macrophages from ST2(-/-) mice, we demonstrate that the IL-33 receptor, ST2, is integral to the action of IL-33 on macrophage foam cell formation. In conclusion, IL-33 has a protective role in atherosclerosis by reducing macrophage foam cell formation suggesting that IL-33 maybe a potential therapeutic agent against atherosclerosis.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it