Molecular Imaging of Mesenchymal Stem Cell
Bibliographic record
Abstract
BACKGROUND: Mesenchymal stem cells (MSCs) can differentiate into endothelial cells in vivo. However, it is unknown if the differentiated MSCs persist in vivo and if this potential persistence contributes to functional improvement after experimental myocardial infarction. METHODS AND RESULTS: We generated a lentivector encoding 2 distinct reporter genes, one driven by a constitutive murine stem cell virus promoter and the other driven by an endothelial-specific Tie-2 promoter. The endothelial specificity of the lentivector was validated by its expression in endothelial cells but not in human MSCs (hMSCs). The lentivirus-transduced hMSCs were injected into peri-infarct areas of the hearts of severe combined immune-deficient mice. Persistence of injected cells was tracked by bioluminescence imaging (BLI) and verified by immunohistochemical staining. The BLI signal from the endothelial-specific reporter revealed that hMSCs differentiated into endothelial cells 48 hours after injection. However, both the constitutive and endothelial-specific BLI signals disappeared by day 50. Nonetheless, the improvement in left ventricle ejection fraction with hMSC therapy persisted for up to 6 months. Immunohistochemical staining showed that hMSC-derived endothelial cells integrated into endogenous CD31(+) vessels. Furthermore, hMSC-transplanted hearts had more CD31(+) vessels and a lesser degree of cardiac fibrosis compared with the controls at 6 months. CONCLUSIONS: hMSCs differentiated into endothelial cells and integrated into blood vessels after experimental myocardial infarction. The differentiated hMSCs only lasted for up to 50 days in vivo, but improvement in cardiac function persisted for up to 6 months. Increased angiogenesis and decreased fibrosis were associated with cardiac functional improvement after hMSC transplantation.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".