Endothelial cell CD36 optimizes tissue fatty acid uptake
Bibliographic record
Abstract
Movement of circulating fatty acids (FAs) to parenchymal cells requires their transfer across the endothelial cell (EC) barrier. The multiligand receptor cluster of differentiation 36 (CD36) facilitates tissue FA uptake and is expressed in ECs and parenchymal cells such as myocytes and adipocytes. Whether tissue uptake of FAs is dependent on EC or parenchymal cell CD36, or both, is unknown. Using a cell-specific deletion approach, we show that EC, but not parenchymal cell, CD36 deletion increased fasting plasma FAs and postprandial triglycerides. EC-Cd36-KO mice had reduced uptake of radiolabeled long-chain FAs into heart, skeletal muscle, and brown adipose tissue; these uptake studies were replicated using [11C]palmitate PET scans. High-fat diet-fed EC-CD36-deficient mice had improved glucose tolerance and insulin sensitivity. Both EC and cardiomyocyte (CM) deletion of CD36 reduced heart lipid droplet accumulation after fasting, but CM deletion did not affect heart glucose or FA uptake. Expression in the heart of several genes modulating glucose metabolism and insulin action increased with EC-CD36 deletion but decreased with CM deletion. In conclusion, EC CD36 acts as a gatekeeper for parenchymal cell FA uptake, with important downstream effects on glucose utilization and insulin action.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".