MFG-E8 Released by Apoptotic Endothelial Cells Triggers Anti-Inflammatory Macrophage Reprogramming
Bibliographic record
Abstract
Apoptotic endothelial cells are an important component of the "response to injury" process. Several atherosclerosis risk factors such as hyperglycemia and oxidized low-density lipoproteins, and immune injuries, such as antibodies and complement, induce endothelial cell apoptosis. While endothelial cell apoptosis is known to affect neighboring vascular wall cell biology, its consequences on macrophage reprogramming are ill defined. In this study, we report that apoptosis of human and mouse endothelial cells triggers the release of milk fat globule-epidermal growth factor 8 (MFG-E8) and reprograms macrophages into an anti-inflammatory cells. We demonstrated that MFG-E8 is released by apoptotic endothelial cells in a caspase-3-dependent manner. When macrophages were exposed to conditioned media from serum-starved apoptotic endothelial cells, they adopt a high anti-inflammatory, low pro-inflammatory cytokine/chemokine secreting phenotype that is lost if MFG-E8 is absent from the media. Macrophage treatment with recombinant MFG-E8 recapitulates the effect of conditioned media. Finally, we showed that MFG-E8-mediated reprogramming of macrophages occurs through increased phosphorylation of signal transducer and activator of transcription-3 (STAT-3). Taken together, our study suggests a key role of MFG-E8 release from apoptotic endothelial cells in macrophage reprogramming and demonstrates the importance of the apoptotic microenvironment in anti-inflammatory macrophage responses.
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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 | 0.000 |
| 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".