Simvastatin Decreases Endothelial Progenitor Cell Apoptosis in the Kidney of Hypertensive Hypercholesterolemic Pigs
Bibliographic record
Abstract
OBJECTIVE: Hypertension and hypercholesterolemia might interfere with renal repair mechanisms. We hypothesized that simvastatin improves the survival of endothelial progenitor cells (EPC) in the renal microenvironment imposed by concurrent renovascular hypertension and dietary hypercholesterolemia (HTC). METHODS AND RESULTS: Pigs were studied after 12 weeks of no intervention (n=6), HTC (n=6), or HTC+ oral simvastatin supplementation (80 mg/day, n=5). EPC were also isolated and studied in vitro after exposure to the proapoptotic oxidized low-density lipoprotein with or without coincubation with simvastatin. Renal hemodynamics, function, and endothelial function were evaluated in vivo, and the number of CD34+/KDR+ EPC, apoptosis, oxidative stress, inflammation, and fibrosis in renal tissue studied ex vivo. Compared with normal kidney, the HTC kidney showed endothelial dysfunction and increased oxidative stress, interstitial macrophage filtration, and fibrosis. The number of EPC in the kidney increased, as did their apoptosis (0.85+/-0.24% versus 0.22+/-0.07%, P<0.05 versus normal). Simvastatin did not affect blood pressure, cholesterol levels, basal renal function, or number of renal EPC in HTC, but it improved endothelial function; blunted renal oxidative stress, inflammation, and fibrosis; and attenuated EPC apoptosis (to 0.37+/-0.09%, P<0.05 versus HTC). Simvastatin also significantly decreased oxidized low-density lipoprotein-induced EPC apoptosis in vitro. CONCLUSION: EPC are recruited but undergo apoptosis in the HTC kidney, likely because of a hostile microenvironment. Simvastatin rescues renal repair mechanisms in HTC and counteracts renal damage, which may account for its protective effects on the kidney during exposure to cardiovascular risk factors.
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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) | 0.001 | 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 | 0.001 |
| 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".