Paracrine effects of transplanted myoblasts and relaxin on post‐infarction heart remodelling
Bibliographic record
Abstract
In the post-infarcted heart, grafting of precursor cells may partially restore heart function but the improvement is modest and the mechanisms involved remain to be elucidated. Here, we explored this issue by transplanting C2C12 myoblasts, genetically engineered to express enhanced green fluorescent protein (eGFP) or eGFP and the cardiotropic hormone relaxin (RLX) through coronary venous route to swine with experimental chronic myocardial infarction. The rationale was to deliver constant, biologically effective levels of RLX at the site of cell engraftment. One month after engraftment, histological analysis showed that C2C12 myoblasts selectively settled in the ischaemic scar and were located around blood vessels showing an activated endothelium (ICAM-1-,VCAM-positive). C2C12 myoblasts did not trans-differentiate towards a cardiac phenotype, but did induce extracellular matrix remodelling by the secretion of matrix metalloproteases (MMP) and increase microvessel density through the expression of vascular endothelial growth factor (VEGF). Relaxin-producing C2C12 myoblasts displayed greater efficacy to engraft the post-ischaemic scar and to induce extracellular matrix re-modelling and angiogenesis as compared with the control cells. By echocardiography, C2C12-engrafted swine showed improved heart contractility compared with the ungrafted controls, especially those producing RLX. We suggest that the beneficial effects of myoblast grafting on cardiac function are primarily dependent on the paracrine effects of transplanted cells on extracellular matrix remodelling and vascularization. The combined treatment with myoblast transplantation and local RLX production may be helpful in preventing deleterious cardiac remodelling and may hold therapeutic possibility for post-infarcted patients.
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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) | 0.001 | 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".