Abstract 207: Reduced Vascular Density in Human Adipose Tissue in Diabetes is Associated with Reduced Angiogenesis and De-differentiation of Endothelial Cells
Bibliographic record
Abstract
Emerging evidence suggests that impaired adipose tissue (AT) angiogenesis leads to metabolic dysfunction. The de-differentiation of endothelial cells (EC) into a mesenchymal phenotype (EndoMT) in AT vasculature could be a potential contributor to dysfunctional EC including impaired angiogenesis. One of the major drivers of EndoMT is TGF, and both macrophages and T cells infiltrating AT in obesity could contribute to EndoMT via TGF production. The objective of this project was to characterize angiogenesis and the EC phenotype in human AT vasculature. We examined functional angiogenesis and gene expression in omental (OM) AT from obese T2D subjects (BMI>33, HbA1c>6.5%) and non-diabetic (ND) subjects (BMI>33). Sprouting angiogenesis of AT explants embedded in matrigel was 1.5-fold higher in ND vs. T2D (p<0.05). Also, capillary and arteriolar density assessed as CD31 and α-SMC immuno-positivity, was 2-fold higher in ND vs. T2D. Using a Human Angiogenesis PCR Array we found that in T2D vs. ND OM AT, there was >2-fold down-regulation in expression of genes involved in cell proliferation and matrix remodeling (JAG, ID1, COL4A3, TIMP1 and CTGF) (p<0.05). In conclusion, in T2D in obesity there is a reduction in vascular density that can be explained in part by the reduced angiogenic potential. Next, we tested the hypothesis that a potential contributor to reduced angiogenesis is de-differentiation of EC in AT vasculature. We determined the molecular phenotype of EC isolated from human AT. Indeed, EC (CD34 + 31 + ) isolated from ND and T2D obese AT had significantly >10-fold up-regulation of mesenchymal genes (TGF-β, fibroblast specific protein-1 (FSP1), and Twist1) compared to dermal human microvascular endothelial cells (HMVEC) (p<0.001). Also, EC isolated from AT displayed a prominent oxidative metabolism compared to dermal HMVEC that utilized primarily glycolysis. This phenotype was similar to the one of TGF treated dermal HMVEC. Since glycolysis is required for angiogenic ECs, the low glycolytic flux of AT EC could contribute to impaired angiogenesis. In conclusion, EC isolated from obese and T2D patients show increased expression of mesenchymal markers and a metabolic shift towards the oxidative metabolism, which may explain reduced angiogenesis.
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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 | 0.000 | 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) | 0.004 | 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".