Monocyte Derivatives Promote Angiogenesis and Myocyte Survival in a Model of Myocardial Infarction
Bibliographic record
Abstract
In this study, we have investigated the hypothesis that previously reported beneficial effect of peripheral blood mononuclear cells cultured under angiogenic conditions on cardiovascular function following ischemia is not limited to EPCs but also to monocytes contained therein. We first purified and analyzed the phenotype and secretome of human and murine blood monocytes cultured under angiogenic conditions (named MDs for monocyte derivatives) and tested their effect in a mouse model of myocardial infarction (MI). FACS analysis of MDs shows that these cells express mature endothelial cell markers and that their proliferative capacity is virtually absent, consistent with their end-differentiated monocytic ontogeny. MDs secreted significant levels of HGF, IGF-1, MCP-1, and sTNFR-1 relative to their monocyte precursors. MDs were unable to form vascular networks in vitro when cultured on matrix coated flasks. Treatment of murine HL-1 cardiomyocyte cell line with MD-conditioned medium reduced their death induced by TNF-alpha, staurosporine, and oxidative stress, and this effect was dependent upon MD-derived sTNFR-1, HGF, and IGF-1. We further demonstrate that MD secretome promoted endothelial cell proliferation and capacity to form vessels in vitro and this was dependent upon MD-derived MCP-1, HGF, and IGF-1. Echocardiography analysis showed that MD myocardial implantation improved left ventricle fractional shortening of mouse hearts following MI and was associated with reduced myocardial fibrosis and enhancement of angiogenesis. Transplanted MDs and their secretome participate in preserving functional myocardium after ischemic insult and attenuate pathological remodeling.
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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".