Endothelial Cell CD36 Reduces Atherosclerosis and Controls Systemic Metabolism
Bibliographic record
Abstract
High-fat Western diets contribute to tissue dysregulation of fatty acid and glucose intake, resulting in obesity and insulin resistance and their sequelae, including atherosclerosis. New therapies are desperately needed to interrupt this epidemic. The significant idea driving this research is that the understudied regulation of fatty acid entry into tissues at the endothelial cell (EC) interface can provide novel therapeutic targets that will greatly modify health outcomes and advance health-related knowledge. Dysfunctional endothelium, defined as activated, pro-inflammatory, and pro-thrombotic, is critical in atherosclerosis initiation, in modulating thrombotic events that could result in myocardial infarction and stroke, and is a hallmark of insulin resistance. Dyslipidemia from high-fat diets overwhelmingly contributes to the development of dysfunctional endothelium. CD36 acts as a receptor for pathological ligands generated by high-fat diets and in fatty acid uptake, and therefore, it may additionally contribute to EC dysfunction. We created EC CD36 knockout (CD36°) mice using cre-lox technology and a cre-promoter that does not eliminate CD36 in hematopoietic cells (Tie2e cre). These mice were studied on different diets, and crossed to the low density lipoprotein receptor (LDLR) knockout for atherosclerosis assessment. Our data show that EC CD36° and EC CD36°/LDLR° mice have metabolic changes suggestive of an uncompensated role for EC CD36 in fatty acid uptake. The mice lacking expression of EC CD36 had increased glucose clearance compared with controls when fed with multiple diets. EC CD36° male mice showed increased carbohydrate utilization and decreased energy expenditure by indirect calorimetry. Female EC CD36°/LDLR° mice have reduced atherosclerosis. Taken together, these data support a significant role for EC CD36 in systemic metabolism and reveal sex-specific impact on atherosclerosis and energy substrate use.
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How this classification was reachedexpand
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) | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".