Progenitor cells and vascular function are impaired in patients with chronic kidney disease
Bibliographic record
Abstract
BACKGROUND: Endothelial dysfunction contributes to accelerated atherosclerosis in chronic kidney disease (CKD). Bone marrow-derived endothelial progenitor cells (EPC) constitute an endogenous vascular repair system protecting against atherosclerosis. Smooth muscle progenitor cells (SPC) may stimulate atherosclerosis development. We hypothesized that an imbalance in EPC and SPC occurs in CKD, which may contribute to the increased cardiovascular disease (CVD) risk. METHODS: EPC and SPC outgrowth from mononuclear cells (MNC), EPC migratory function and circulating CD34(+)KDR(+)-EPC were measured in 49 patients with varying degrees of CKD on regular therapy and 33 healthy volunteers. Renal function, CKD cause, CVD history and endothelial dysfunction parameters were determined as factors of influence on progenitor cells. RESULTS: Patients had reduced EPC outgrowth compared to controls [9 (2-22) vs 12 (1-38) cells/10(3) MNC, P = 0.026], independent of CKD cause and degree, whereas SPC outgrowth levels were higher in patients with more impaired kidney function (r = -0.397, P = 0.008). Patients had lower CD34(+)KDR(+)-EPC compared to controls [9 (0-52) vs 19 (4-110) cells/10(5) granulocytes, P = 0.004]. CVD history and increased endothelial dysfunction markers were related to lower EPC levels. Progenitor cell outgrowth was shifted towards SPC with progression of endothelial damage. Reduction in EPC could not be attributed to decreases in progenitor cell-mobilizing factors SDF-1 alpha and VEGF as levels increased with progressive kidney and endothelial dysfunction, while EPC remained low. CONCLUSIONS: Our data suggest that, already in mild CKD, EPC-mediated endogenous vascular regeneration is impaired, while SPC levels increase with declining kidney function.
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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) | 0.000 | 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 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".