Abstract 201: First Characterization of Extracellular Vesicles Derived From Human Amniotic Stromal Stem Cells and Their Applications for Cardiac Repair and Rejuvenation
Bibliographic record
Abstract
The use of stem cells for cardiac repair after myocardial infarction (MI) is promising, yet clinical trials suggest that these cells fail to integrate into the native tissue. A more novel and safer approach to repair the cardiac tissue is the use of stem cell-derived extracellular vesicles (EVs), which have been shown to have similar therapeutic potential compared to direct injection of stem cells. Here, we investigated the use of EVs from amniotic stromal stem cells (ASCs) and their cytoprotective potential in cardiac endothelial cells and cardiomyocytes. Sequential ultracentrifugation and filtration was used to isolate all extracellular vesicles from the human ASCs secretome. Characterization and analysis of nanoparticles was done using Nanosight, transmission electron microscopy (TEM), Bradford assay and Western blotting. Proteomics analysis was used to further characterize EVs under normal and hypoxic conditions. Human cardiac microvascular endothelial cells and cardiomyocytes were treated with ASC-derived EVs and assessed for changes in phenotype through proliferation, metabolic activity and cell viability assays. ASCs were found to express several cardiac markers and beat together in culture. EVs derived from ASCs were found to be exosome-like, as determined by Nanosight tracking analysis, Western blotting for exosome markers and TEM. Proteomics analysis revealed the hypoxic EVs contained differentially expressed proteins involved in angiogenesis, anti-apoptosis, response to hypoxic stress and Wnt signaling. Human cardiac endothelial cells and cardiomyocytes treated with ASC-derived EVs after hypoxia displayed significantly increased cellular proliferation, metabolic activity and cytoprotection after hypoxia-induced injury compared to controls. Here, we provide the ground work for the use of ASC-derived EVs for cardiac repair after MI. Future work will utilize a rat MI model to determine the in vivo efficacy of EVs from hypoxic ASCs and their regenerative potential.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".