Cardioprotective c-kit+ cells are from the bone marrow and regulate the myocardial balance of angiogenic cytokines
Bibliographic record
Abstract
Clinical trials of bone marrow stem/progenitor cell therapy after myocardial infarction (MI) have shown promising results, but the mechanism of benefit is unclear. We examined the nature of endogenous myocardial repair that is dependent on the function of the c-kit receptor, which is expressed on bone marrow stem/progenitor cells and on recently identified cardiac stem cells. MI increased the number of c-kit+ cells in the heart. These cells were traced back to a bone marrow origin, using genetic tagging in bone marrow chimeric mice. The recruited c-kit+ cells established a proangiogenic milieu in the infarct border zone by increasing VEGF and by reversing the cardiac ratio of angiopoietin-1 to angiopoietin-2. These oscillations potentiated endothelial mitogenesis and were associated with the establishment of an extensive myofibroblast-rich repair tissue. Mutations in the c-kit receptor interfered with the mobilization of the cells to the heart, prevented angiogenesis, diminished myofibroblast-rich repair tissue formation, and led to precipitous cardiac failure and death. Replacement of the mutant bone marrow with wild-type cells rescued the cardiomyopathic phenotype. We conclude that, consistent with their documented role in tumorigenesis, bone marrow c-kit+ cells act as key regulators of the angiogenic switch in infarcted myocardium, thereby driving efficient cardiac repair.
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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".