Endothelial Progenitor Cell and Mesenchymal Stem Cell Isolation, Characterization, Viral Transduction
Bibliographic record
Abstract
Endothelial progenitor cells (EPCs) and mesenchymal stem cells (MSCs) have emerged as potentially useful substrates for neovascularization and tissue repair and bioengineering. EPCs are a heterogeneous group of endothelial cell precursors originating in the hematopoietic compartment of the bone marrow. MSCs are a rare population of fibroblast-like cells derived from the bone marrow stroma, constituting approximately 0.001-0.01% of the nucleated cells in the marrow. Both cells types have been isolated from the bone marrow. In addition, EPC can be isolated from peripheral blood as well as the spleen, and MSC has also been isolated from peripheral adipose tissue. Several approaches have been used for the isolation of EPC and MSC, including density centrifugation and magnetic bead selection. Phenotypic characterization of both cell types is carried out using immunohistochemical detection and fluorescence-activated cell sorting analysis of cell-surface molecule expression. However, the lack of specific markers for each cell type renders their characterization difficult and ambiguous. In this chapter, we describe the methods that we use routinely for isolation, characterization, and genetic modification of EPC and MSC from human, rabbit, and mouse peripheral blood and bone marrow.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".