Despite Antiatherogenic Metabolic Characteristics, SCD1-Deficient Mice Have Increased Inflammation and Atherosclerosis
Bibliographic record
Abstract
OBJECTIVE: Absence of stearoyl-CoA desaturase-1 (SCD1) in mice reduces plasma triglycerides and provides protection from obesity and insulin resistance, which would be predicted to be associated with reduced susceptibility to atherosclerosis. The aim of this study was to determine the effect of SCD1 deficiency on atherosclerosis. METHODS AND RESULTS: Despite an antiatherogenic metabolic profile, SCD1 deficiency increases atherosclerosis in hyperlipidemic low-density lipoprotein receptor (LDLR)-deficient mice challenged with a Western diet. Lesion area at the aortic root is significantly increased in males and females in two models of SCD1 deficiency. Inflammatory changes are evident in the skin of these mice, including increased intercellular adhesion molecule (ICAM)-1 and ulcerative dermatitis. Increases in ICAM-1 and interleukin-6 are also evident in plasma of SCD1-deficient mice. HDL particles demonstrate changes associated with inflammation, including decreased plasma apoA-II and apoA-I and paraoxonase-1 and increased plasma serum amyloid A. Lipopolysaccharide-induced inflammatory response and cholesterol efflux are not altered in SCD1-deficient macrophages. In addition, when SCD1 deficiency is limited to bone marrow-derived cells, lesion size is not altered in LDLR-deficient mice. CONCLUSIONS: These studies reinforce the crucial role of chronic inflammation in promoting atherosclerosis, even in the presence of antiatherogenic biochemical and metabolic characteristics.
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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) | 0.000 | 0.000 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".