Clinical translation of mesenchymal stem cells in ischemic heart failure: Challenges and future perspectives
Bibliographic record
Abstract
Myocardial infarction (MI) with resulting congestive heart failure is one of the leading causes of death worldwide. Current therapies for treating MI, such as devices, traditional medicine, and surgeries, come with many limitations as patients in their final stages of heart failure have little chances of experiencing any reversible changes. In recent decades, Mesenchymal stem cell (MSC) based therapy has become one of the most popular and rapidly developing fields in treating MI. Their supremacy for clinical applications is partially due to their unique properties and encouraging pre-clinical outcomes in various animal disease models. However, the majority of clinical trials registered for MSC therapy for diverse human diseases, including MI, have fallen short of expectations. This review intends to discuss the recent advances in the clinical application of using MSCs for cardiac repair and discuss challenges facing the clinical translation of MSCs for cardiac regeneration such as restoration of endothelial-cardiomyocyte crosstalk, immunomodulation and immune rejection, poor homing and migration, as well as low retention and survival. Furthermore, we will discuss recent strategies being investigated to help overcome some of these challenges.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".