Limited Endothelial Plasticity of Mesenchymal Stem Cells Revealed by Quantitative Phenotypic Comparisons to Representative Endothelial Cell Controls
Bibliographic record
Abstract
Considerable effort has been directed toward deriving endothelial cells (ECs) from adipose-derived mesenchymal stem cells (ASCs) since 2004, when it was first suggested that ECs and adipocytes share a common progenitor. While the capacity of ASCs to express endothelial markers has been repeatedly demonstrated, none constitute conclusive evidence of an endothelial phenotype as all reported markers have been detected in other, non-endothelial cell types. In this study, quantitative phenotypic comparisons to representative EC controls were used to determine the extent of endothelial differentiation being achieved with ASCs. ASCs were harvested from human subcutaneous abdominal white adipose tissue, and their endothelial differentiation was induced using well-established biochemical stimuli. Reverse transcription quantitative real-time polymerase chain reaction and parallel reaction monitoring mass spectrometry were used to quantify their expression of endothelial genes and corresponding proteins, respectively. Flow cytometry was used to quantitatively assess their uptake of acetylated low-density lipoprotein (AcLDL). Human umbilical vein, coronary artery, and dermal microvascular ECs were used as positive controls to reflect the phenotypic heterogeneity between ECs derived from different vascular beds. Biochemically conditioned ASCs were found to upregulate their expression of endothelial genes and proteins, as well as AcLDL uptake, but their abundance remained orders of magnitude lower than that observed in the EC controls despite their global proteomic heterogeneity. The findings of this investigation demonstrate the strikingly limited extent of endothelial differentiation being achieved with ASCs using well-established biochemical stimuli, and underscore the importance of quantitative phenotypic comparisons to representative primary cell controls in studies of differentiation. Stem Cells Translational Medicine 2019;8:35-45.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".