Immunomagnetic Isolation and Enrichment of Microvascular Endothelial Cells from Human Adipose Tissue
Bibliographic record
Abstract
Human adipose tissue-resident microvascular endothelial cells are not only garnering attention for their emergent role in the pathogenesis of obesity-related metabolic disorders, but are also of considerable interest for vascular tissue engineering due, in part, to the abundant, accessible, and uniquely dispensable nature of the tissue. Here, we delineate a protocol for the acquisition of microvascular endothelial cells from human fat. A cheaper, smaller, and simpler alternative to fluorescence-assisted cell sorting for the immunoselection of cells, our protocol adapts magnet-assisted cell sorting for the isolation of endothelial cells from enzymatically digested adipose tissue and the subsequent enrichment of their primary cultures. Strategies are employed to mitigate the non-specific uptake of immunomagnetic microparticles, enabling the reproducible acquisition of human adipose tissue-resident microvascular endothelial cells with purities ≥98%. They exhibit morphological, molecular, and functional hallmarks of endothelium, yet retain a unique proteomic signature when compared with endothelial cells derived from different vascular beds. Their cultures can be expanded for >10 population doublings and can be maintained at confluence for at least 28 days without being overgrown by residual stromal cells from the cell sorting procedure. The isolation of human adipose tissue-resident microvascular endothelial cells can be completed within 6 hours and their enrichment within 2 hours, following approximately 7 days in culture. Graphical abstract.
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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) | 0.000 | 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 | 0.000 |
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".