Vascular stem cells in diabetic complications: evidence for a role in the pathogenesis and the therapeutic promise
Bibliographic record
Abstract
Long standing diabetes leads to structural and functional alterations in both the micro- and the macro-vasculature. Vascular endothelial cells (ECs) are the primary target of the hyperglycemia-induced adverse effects. Vascular stem cells that give rise to endothelial progenitor cells (EPCs) and mesenchymal progenitor cells (MPCs) represent an attractive target for cell therapy for diabetic patients. A number of studies have reported EPC dysfunction as a novel participant in the culmination of the diabetic complications. The controversy behind the identity of EPCs and the similarity between these progenitor cells to hematopoietic cells has led to conflicting results. MPCs, on the other hand, have not been examined for a potential role in the pathogenesis of the complications. These multipotent cells, however, do show a therapeutic role. In this article, we summarize the vascular changes that occur in diabetic complications highlighting some of the common features, the key findings that illustrate an important role of vascular stem cells (VSCs) in the pathogenesis of chronic diabetic complications, and provide mechanisms by which these cells can be used for therapy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".