Colony Forming Unites-Endothelial Progenitor Cells (CFU-EPCs): A Surrogate Marker for Diabetic Retinopathy and High Cardiovascular Mortality Rate
Bibliographic record
Abstract
Purpose: Diabetic retinopathy is a risk factor for increased cardiovascular death. Our purpose was to find a significant difference in levels of endothelial progenitor cells (EPCs) in the peripheral blood of patients at different stages of diabetic retinopathy. Design: A prospective study. Colony forming units of endothelial progenitor cells (CFU-EPCs) in peripheral blood were counted. 40 subjects were enrolled (10 healthy [41±8 y], 10 type 2 diabetes mellitus (T2DM) [64±12 y] without retinopathy, 10 T2DM patients [62±26 y] with non-proliferative retinopathy (NPDR), 10 T2DM patients [66±9 y] with proliferative retinopathy (PDR)). The study was approevd by the ethics committee of the hospital and every subject signed a soncent form before enrollment. Methods: Growing CFU-EPCs was by the Hill's EPCs protocol. Blood was drawn early in the morning and was processed within 1 hour. Mononuclear cells were separated and cultured on fibronectin-coated plates with EndoCult medium (StemCell technologies, Vancouver BC Canada) for 5 days. CFU-EPCs were counted on day 5 (an average of 8 wells). Results: Healthy subjects had 36±8 CFU-EPCs, patients without retinopathy had 13±12 CFU-EPCs (p<0.01), patients with NPDR 22±26 CFU-EPCs (p=NS), and 2±2 CFU-EPCs in patients with PDR (p<0.01). A significant difference was found between patients with PDR and with NPDR (p<0.05). Conclusions: CFU-EPCs are inhibited in T2DM patients with DPR. Levels of CFU-EPCs may be used as a surrogate biologic marker for severity of diabetic retinopathy and for cumulative vascular risk.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".