Endothelial cell CD36 mediates stroke-induced brain injury via BBB dysfunction and monocyte infiltration in normal and obese conditions
Bibliographic record
Abstract
CD36 expressed in multiple cell types regulates inflammation, vascular function, and innate immunity. Specifically, CD36 in microvascular endothelial cells (ECs) signals to elicit inflammation and causes EC death. This study investigated roles for EC-CD36 on acute stroke pathology in normal and obese conditions. Obesity induced by a high-fat diet (HD) selectively increased CD36 expression in ECs, not in monocytes/macrophages, in the post-ischemic brain. Mice deficient CD36 in ECs (EC CD36−/− ) showed reduced injury size and vascular permeability in normal conditions. While control mice fed a HD developed obesity and aggravated stroke injury, EC CD36−/− mice were resistant to develop an obesity phenotype. Subjecting EC CD36−/− mice to stroke resulted in reduced injury size and BBB disruption. Moreover, the mice had reduced MCP-1 and CCR2 gene expression, resulting in reduced monocyte trafficking with improved survival and acute motor function. Reduced MCP-1 and CCR2 expression was still evident in EC CD36−/− mice subjected to severe stroke, suggesting that monocyte trafficking is an infarct-independent metabolic effect associated with specific EC-CD36 deletion. Our findings demonstrate the importance of EC-CD36 in developing vascular comorbidities and suggest that targeting EC-CD36 is a potential preventative strategy to normalize vascular risk factors, leading to improved acute stroke outcomes.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".