Macrophage-produced VEGFC is induced by efferocytosis to ameliorate cardiac injury and inflammation
Bibliographic record
Abstract
Clearance of dying cells by efferocytosis is necessary for cardiac repair after myocardial infarction (MI). Recent reports have suggested a protective role for vascular endothelial growth factor C (VEGFC) during acute cardiac lymphangiogenesis after MI. Here, we report that defective efferocytosis by macrophages after experimental MI led to a reduction in cardiac lymphangiogenesis and Vegfc expression. Cell-intrinsic evidence for efferocytic induction of Vegfc was revealed after adding apoptotic cells to cultured primary macrophages, which subsequently triggered Vegfc transcription and VEGFC secretion. Similarly, cardiac macrophages elevated Vegfc expression levels after MI, and mice deficient for myeloid Vegfc exhibited impaired ventricular contractility, adverse tissue remodeling, and reduced lymphangiogenesis. These results were observed in mouse models of permanent coronary occlusion and clinically relevant ischemia and reperfusion. Interestingly, myeloid Vegfc deficiency also led to increases in acute infarct size, prior to the amplitude of the acute cardiac lymphangiogenesis response. RNA-Seq and cardiac flow cytometry revealed that myeloid Vegfc deficiency was also characterized by a defective inflammatory response, and macrophage-produced VEGFC was directly effective at suppressing proinflammatory macrophage activation. Taken together, our findings indicate that cardiac macrophages promote healing through the promotion of myocardial lymphangiogenesis and the suppression of inflammatory cytokines.
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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) | 0.001 | 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 | 0.001 |
| 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".