Angiogenic Capacity of Human Adipose-Derived Stromal Cells During Adipogenic Differentiation: An <i>In Vitro</i> Study
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Improving vascularization of engineered adipose tissue constructs is a major challenge in the field of plastic surgery. Although human adipose-derived stromal cells (hASCs) are known to release factors that stimulate new blood vessel formation, detailed information about the effects of adipogenic differentiation on the angiogenic potential of hASCs remains largely unknown. In the present study, we studied the expression and secretion of a large panel of angiogenic factors during hASC differentiation and evaluated the effects of hASC-conditioned medium (hASC-CM) on endothelial cells. METHODS: hASCs were cultured on adipogenic medium or basal medium. Conditioned medium was collected, and cells were harvested following 0, 3, 7, 14, and 22 days of culture. The stage of adipogenic differentiation of hASC was assessed using Oil Red O staining, fatty acid binding protein-4 gene expression, and glycerol-3-phosphate dehydrogenase activity. RESULTS: Gene expression of vascular endothelial growth factor (VEGF), placental growth factor, angiopoietin-1 (ANGPT1), angiopoietin-2 (ANGPT2), and protein secretion of VEGF significantly increased during short-term adipogenic differentiation of hASCs. Moreover, conditioned medium from differentiated hASCs strongly enhanced endothelial cell numbers compared to conditioned medium from undifferentiated hASCs. CONCLUSION: In vitro adipogenic differentiation of hASCs improves their ability to support endothelial viable cell numbers and suggests that hASCs differentiated for a short period potentially improve angiogenic responses for in vivo implantation.
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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 it