Uterine-Derived CD11b Cells Significantly Increase Vasculogenesis and Promote Myocardial Healing in Ischemic Cardiomyopathy
Bibliographic record
Abstract
Ischemic heart disease is the leading cause of mortality in industrialized countries. Cell transplantation could restore function of the ischemic heart likely through the mechanism of cell-induced angiogenesis. We have previously shown that cells isolated from uteri increase angiogenesis and alleviate cardiac dysfunction when transplanted after MI. However, which uterine cell type contributes to angiogenesis is unknown. Here we report that uterine-derived CD11b cells significantly increase vasculogenesis and promote myocardial healing in ischemic cardiomyopathy. We have established a novel and simple methodology for uterine CD11b cell isolation and enrichment and demonstrate that this technique can be used for purifying and establishing viable CD11b cell cultures in rats. The isolated fresh CD11b cells were transplanted into ischemic rat hearts 5 days after injury. Following transplantation, vasculogenesis significantly increased in ischemic cardiac tissue, which reduced infarct size and restored myocardial function and perfusion compared with controls. Thus, uterine CD11b cells have the potential to promote functional healing when implanted after ischemic cardiomyopathy. Importantly, we have demonstrated a novel means by which CD11b cells can be easily purified and cultured for cell transplantation.
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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) | 0.002 | 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".