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The following primary antibodies (all from Dako, Hamburg, Germany) were used: anti-smooth muscle cell actin (clone HHF35, dilution 1:200), anti-Factor VIII (clone F8/86, dilution 1:500), anti-CD68 (clone Oxygenase KP1, dilution 1:2,000), and anti-CD45 (clone 2B11, dilution 1:100). Visualization was performed with APAAP ChemMate Detection Kit (Dako). Blood sampling was performed ��2 days before surgical intervention by vein puncture. Venous blood was centrifuged at 2000 g for 10 minutes at 20��C and stored at ?70��C until analysis. Serum indicators, such as blood urea nitrogen, creatinine, calcium, phosphate, and red cell, white cell, and platelet counts were measured according to standardized techniques in the Institute of Clinical Chemistry at our institution. The eGFR was calculated by using the four-variables Modification of Diet in Renal Diseases formula.24 MMPs were quantified in serum samples using Quantikine enzyme-linked immunosorbent assay (ELISA) for human MMP-1, -2, -3, -7, -8, and NU7441 purchase -9 (R&D Systems, Wiesbaden-Nordenstadt, Germany), according to the manufacturer's protocol. Fibrinogen activity was determined by measuring the clotting time (Dade Behring, Schwalbach, Germany). ELISA kits were used to measure high-sensitive C-reactive protein (Life Diagnostics, West Chester, Pa), serum fetuin A (Biovendor GmbH, Heidelberg, Germany), and the concentration of total osteoprotegerin (R&D Systems). The blood vessel rigidity (pulse pressure) was calculated as a difference between systolic and diastolic blood pressure. Differences between groups are reported as a mean �� standard deviation for continuous variables or as a percentage for categoric variables. The one-sample Kolmogorov-Smirnov test was performed to check for normal distribution. Non-normally distributed samples were transformed by common transformation methods (log, LN, square root), whether normality this website can be achieved. The t test was used for normally distributed samples, the Mann-Whitney approach for nonparametric samples, and the Fisher exact test for nominal variables. Correlations between continuous variables were quantified by using the Spearman rank correlation coefficient. Linear regression analysis was performed to adjust the results for relevant clinical parameters such as age, sex, smoking, coronary heart disease, or neurologic symptoms. Correction for multiple testing was determined by using the Benjamini and Hochberg approach that considers the fraction of the false positives over the amount of tests declared significant and does not reduce the overall statistical power. 19 Values of P