Amniotic stem cells for cellular cardiomyoplasty: Promises and premises
Bibliographic record
Abstract
Cellular cardiomyoplasty is undergoing intensive investigation as a new form of therapy for severely damaged hearts. Among several cell types, mesenchymal stem cells (MSCs) have been proposed as a potential cell source. MSC can be found in adult tissues or in fetal tissues like the umbilical chord blood, amniotic membrane, or amniotic fluid (AF). AF-MSCs have properties intermediate between embryonic and adult MSC, which make them particularly attractive for cellular regeneration. It has been shown that MSC could differentiate in cardiomyocytes-like cells in vitro. In some animal models, it has also been shown that transplanted MSC could engraft and show some cardiomyocytes-like characteristics. Since MSC do not express HLA-DR and present in vitro and in vivo immunosuppressive properties, they can be envisioned to be used in allogenic cellular cardiomyoplasty. Based on these promises, MSC from adult donors are currently used in small safety and feasibility trials. No clinical trial using AF-MSC has been performed yet. Still, the exact role of true cell repopulation and in situ cardiomyocytes differentiation versus pure paracrine effect after cell transplantation is currently much debated. Cellular cardiomyoplasty is a fascinating new area of investigation in regenerative medicine. Although considerable knowledge has been gained over the last decade on the use of MSC as a potential stem cell (SC) source, many issues remain unsolved. Because of several limitations in animal models, clinical studies in highly selected patients balancing the risks and benefits are required. In that regard, MSCs obtained from the fetal AF are a potential new source of SCs that need to be further investigated for cellular cardiomyoplasty.
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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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".