Functional and histopathological improvement of the post‐infarcted rat heart upon myoblast cell grafting and relaxin therapy
Bibliographic record
Abstract
Although the myocardium contains progenitor cells potentially capable of regenerating tissue upon lethal ischaemic injury, their actual role in post-infarction heart healing is negligible. Therefore, transplantation of extra-cardiac stem cells is a promising therapeutic approach for post-infarction heart dysfunction. Paracrine cardiotropic factors released by the grafted cells, such as the cardiotropic hormone relaxin (RLX), may beneficially influence remodelling of recipient hearts. The current study was designed to address whether grafting of mouse C2C12 myoblasts, genetically engineered to express green fluorescent protein (C2C12/GFP) or GFP and RLX (C2C12/RLX), are capable of improving long-term heart remodelling in a rat model of surgically induced chronic myocardial infarction. One month after myocardial infarction, rats were treated with either culture medium (controls), or C2C12/GFP cells, or C2C12/RLX cells plus exogenous RLX, or exogenous RLX alone. The therapeutic effects were monitored for 2 further months. Cell transplantation and exogenous RLX improved the main echocardiographic parameters of cardiac function, increased myocardial viability (assessed by positron emission tomography), decreased cardiac sclerosis and myocardial cell apoptosis and increased microvascular density in the post-infarction scar tissue. These effects were maximal upon treatment with C2C12/RLX plus exogenous RLX. These functional and histopathological findings provide further experimental evidence that myoblast cell grafting can improve myocardial performance and survival during post-infarction heart remodelling and dysfunction. Further, this study provides a proof-of-principle to the novel concept that genetically engineered grafted cells can be effectively employed as cell-based vehicles for the local delivery of therapeutic cardiotropic substances, such as RLX, capable of improving adverse heart remodelling.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".