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Values for SVDU were calculated by averaging aortic blood velocity values over 1 min at baseline, during the final minute of each drug infusion, during the interval between the third and fouth minute following NG administration, and in the final minute of each stage of LBNP, SHG and HUT. The following equation was used: Total peripheral resistance was calculated Doxorubicin mouse from mean arterial pressure and cardiac output () using the following equation: Cardiac output by Modelflow was calculated online by the proprietary software of the Finometer? device by analysis of the finger pressure waveform using a three-element [aortic characteristic impedance (Z0), Windkessel compliance (Cw) and peripheral resistance (Rp)] non-linear equation dependent on the pressure�Carea relationship of the aorta. Age, sex, height and weight for each subject were entered into the unit prior to testing, and these parameters were used to determine the individual aortic pressure�Carea relationship. Pressure�Carea relationship allows for computation of Z0 and Cw, while Rp is adapted by the model. All statistical computations selleck chemicals llc were made using statistical analysis software (SAS Institute, Cary, NC, USA). Data are presented as means ��s.d. Absolute values and relative changes for each protocol were plotted as histograms and Q�CQ plots to determine normality of the data. The significance of changes in cardiovascular indices from baseline, and between conditions, was determined by fixed effects regression analysis (SAS, using the proc mixed procedure). This model was chosen for its ability to control for all the stable characteristics of the individuals, over repeated measures, by using only within-individual variation to estimate the regression coefficients (Allison, 2006). The significance Sulfatase of differences between measurement techniques was determined using Bland�CAltman analysis (Bland & Altman, 1986; Mantha et al. 2000). The relationship between change in TPR from baseline and SV measurement bias was fitted using a linear model. A probability of P