The procedures in this study were approved by the Institutional Review Board at University of Illinois at Chicago (2022–1129) and in accordance with the Declaration of Helsinki. Participants provided verbal and written informed consents before participating in this study.

Twenty young and healthy adults (24–39 years) volunteered for this study. Participants were excluded from the study if any of the following were present: smoking, cardiovascular, pulmonary, metabolic, neurological diseases, hypertension or hypotension, diabetes, obesity (body mass index [BMI] > 35 kg/m2), anti-inflammatory medication, and pregnancy. Women of childbearing age were tested for pregnancy with a urine-based test. Menstrual cycle was not controlled in this study since previous studies have shown little influence on peripheral PWV and blood flow (Augustine et al. 2018; Adkisson et al. 2010; D'Urzo et al. 2018). Based on the Paffenberger Physical Activity questionnaire all subjects were classified as physically active.

This study consisted of a single visit to the Integrative Physiology Laboratory. Participants (n = 20) were asked to refrain from caffeine, alcohol, and exercise for at least 24-h before study visit. They were also asked to fast for at least 4-h before their test. After signing the consent and measurement of height and weight, participants rested quietly in the supine position for 10 min in a dark and temperature-controlled room before instrumentation, with the supine position maintained throughout the study visit.

Blood Pressure was continuously monitored throughout the experiments via photoplethysmography (Finometer Pro, Finapres Medical System, Amsterdam, Netherlands) on the middle finger of the left hand. The pulsatile and mean blood pressure signals were sampled at 1000 Hz using PowerLab (AD instruments, Colorado Springs, CO, United States) for subsequent data analysis (LabChart).

Brachial blood flow from the right arm was measured using a high-resolution ultrasonography with a 5–13 MHz linear probe placed proximal to the antecubital fossa (Prosound Alpha 7, Hitachi-Aloka, Japan). Brachial artery diameter (B-mode) and flow velocity (Doppler mode) were simultaneously acquired using dual mode on the ultrasound and both were simultaneously visualized longitudinally on the screen throughout baseline, exercise/compression, and recovery. Mean blood flow velocity (Vm) was obtained with the probe positioned to maintain an insonation angle of < 60°. The video was recorded and post-processed using FMD Studio Cardiovascular Suite software (QUIPU, Pisa, Italy) at a frequency of 25 frames per second to acquire continuous measures of blood flow velocity and mean diameter during baseline, exercise or passive compressions, and recovery. Sec-by-sec data were exported to an Excel file (Microsoft, Redmond, WA) for post processing and brachial blood flow was computed using the following equation:

$$}\left( }\cdot}^}} } \right)\, = \,\left( }_}} \, \times \,0} \right)}(\pi r^} )$$

Where Vm is the mean brachial velocity in cm·sec−1, multiplied by 60 for conversion to cm·min−1 and r2 is the brachial artery radius (cm) squared. Area under the blood flow curve (AUC) was calculated with the trapezoidal method using the GraphPad Prism software (GraphPad by Dotmatics, Boston, MA).

Brachial-radial PWV was measured on the right arm using tonometers (Millar Instruments) held in place simultaneously on the right proximal medial brachial artery at the antecubital fossa and the longitudinal lateral radial artery near the wrist line. The locations of the tonometers were marked using a permanent marker and the average distance between tonometers was 24.2 ± 2.3 cm for all participants. The tonometer signals were sampled at 1000 Hz using PowerLab (AD instruments, Colorado Springs, CO, United States). Using a LabChart macro, PWV was calculated using the “foot-to-foot” method via the second derivative of the brachial and radial pressure waves. The transit times (foot-to-foot) of at least 7 consecutive brachial-radial waves were recorded and averaged. The distance between measurement points on the brachial and radial arteries on the right arm was measured with a tape measure. PWV was calculated as brachial-radial distance (meters) / transit time (seconds).

Pilot studies were conducted in 5 young healthy subjects to calculate the coefficient of variance (CV) in PWV from separate measurements made after repositioning the tonometers. The CV for PWV at resting baseline was 1.7% and for PWV 5-min after 50% MVC handgrip exercise was 5.0%.

After instrumentation, participants squeezed a handgrip dynamometer (Jamar, Bolingbrook, IL) with the right hand 3 times with maximal force, with 1 min of rest between trials. The highest value was recorded as the participant’s maximal voluntary contraction (MVC). Participants rested for at least 10 min, then performed 5 min of rhythmic handgrip exercise at either 30% or 50% of MVC in a randomized order. Exercise intensities were chosen based on pilot studies demonstrating that 50% MVC was the highest intensity that people were able to sustain for 5 min without fatigue. The exercise consisted of a 2-s contraction followed by a 2-s relaxation with visual feedback from a force gauge projected on the ceiling to achieve the right amount of force. Subjects rested for 30-min between workloads. Blood flow was measured continuously at baseline (1 min), throughout exercise (5 min) and the first 4 min of recovery (10 min total). Brachial-radial PWV was measured at baseline and 5, 15, and 30 min after contractions had ceased.

Thirty minutes after completing the second bout of handgrip exercise, participants remained in the supine position and an automated wide pressure cuff (20 cm width, model CC17, Hokanson, Bellevue, WA) was placed on their right forearm. The pressure cuff was set to rapidly inflate to 200 mmHg and deflate for 5 min (2 s on, 2 s off) using an automated cuff inflation unit (Hokanson E20, Bellevue, WA). Brachial blood flow was measured continuously at baseline (1 min), during compressions (5 min), and the first 4 min of recovery (10 min total). Brachial-radial PWV was measured at baseline and 5, 15, and 30 min after passive mechanical compressions had ceased.

Sample size for this study was calculated based on the variability in studies from Sugawara et al. (Sugawara et al. 2003) and Heffernan et al. (Heffernan et al. 2007b). The results of the power analysis for a two-way repeated measures ANOVA interaction indicated that 18 participants were necessary to detect a meaningful difference of 0.85 m/sec in PWV with 80% power and an alpha at 0.05.

Prior to analyses, normality of the data was confirmed by using the Kolmogorov–Smirnov Test (SPSS V24, IBM Armonk, NY). PWV, blood flow, brachial diameter and blood pressure were analyzed with a two-way (condition x time) repeated measures ANOVA (using SPSS). Blood flow AUC was analyzed with a one-way repeated measures ANOVA. Post-hoc comparisons were done with a Bonferroni correction for multiple comparisons. The relative influence of multiple factors on changes in peripheral PWV was assessed with a mixed linear model (using the lmer function from the lme4 package in R statistical software, version 4.2.2) with fixed effects of condition (30% intensity and 50% intensity), time, BF AUC, brachial diameter, and baseline PWV and a random effect factor of subject ID with a random intercept nested within the subject. The variance–covariance structure for the random effects had a single intercept for each subject and no correlation between random effects (i.e., the identity matrix was used for the variance–covariance structure).

Significance level was set at α = 0.05 and all data are presented as mean ± standard deviation (SD).