Comparison of Human Adipose Derived Stem Cells with Human Bone Marrow Stem Cells in Myocardial Regenerative Therapy
Bibliographic record
Abstract
Background Cell therapy using Human Bone Marrow Stem Cells (HBMSCs) has been shown to improve heart function after a myocardial infarction. The harvesting technique involved with bone marrow stem cells is invasive and yields a low cell number. There is now an increasing interest in Human Adipose Derived Stem Cells (HADSCs) as they are abundant and readily accessible from liposuction material. The present study was undertaken to investigate if HADSCs are superior than HBMSCs in myocardial regenerative therapy. Results Both HADSCs and HBMSCs proliferated in a time dependent manner, however, the proliferative ability of HADSC was greater than the HBMSCs. In addition, both cells differentiated to the osteoblast lineage confirming their multipotency, when treated with induction medium. Furthermore, treatment of both cells with 5‐AC resulted in positive immunostaining of cardiac markers, troponinI and connexin 43, however the expression of these markers was enhanced in HADSCs. This was further confirmed by western blot analysis, however 5‐AC treatment did not exhibit cell contraction or multinucleation. Conclusion The data suggest that HADSCs may prove to be a more ideal type of cell for regenerative therapy in the future.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".