Human Umbilical Cord Perivascular Cells Exhibit Enhanced Cardiomyocyte Reprogramming and Cardiac Function after Experimental Acute Myocardial Infarction
Bibliographic record
Abstract
We were interested in evaluating the ability of the mesenchymal stromal cell (MSC) population, human umbilical cord perivascular cells (HUCPVCs), to undergo cardiomyocyte reprogramming in an established coculture system with rat embryonic cardiomyocytes. Results were compared with human bone marrow-derived (BM) MSCs. The transcription factors GATA4 and Mef 2c were expressed in HUCPVCs but not BM-MSCs at baseline and, at 7 days, increased 7.6- and 3.5-fold, respectively, compared with BM-MSCs. Although cardiac-specific gene expression increased in both cell types in coculture, upregulation was more significant in HUCPVCs, consistent with Mef 2c-GATA4 synergism. Using a lentivector with eGFP transcribed from the α-myosin heavy chain (α-MHC) promoter, we found that cardiac gene expression was greater in HUCPVCs than BM-MSCs after 14 days coculture (52±17% vs. 29±6%, respectively). A higher frequency of HUCPVCs expressed α-MHC protein compared with BM-MSCs (11.6±0.9% vs. 5.3±0.3%); however, both cell types retained MSC-associated determinants. We also assessed the ability of the MSC types to mediate cardiac regeneration in a NOD/SCID γ mouse model of acute myocardial infarction (AMI). Fourteen days after AMI, cardiac function was significantly better in cell-treated mice compared with control animals and HUCPVCs exhibited greater improvement. Although human cells persisted in the infarct area, the frequency of α-MHC expression was low. Our results indicate that HUCPVCs exhibit a greater degree of cardiomyocyte reprogramming but that differentiation for both cell types is partial. We conclude that HUCPVCs may be preferable to BM-MSCs in the cell therapy of AMI.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".