RESUMO
Currently, there are no ex vivo systems that can model the motion of peripheral arteries and allow for the evaluation of pharmacokinetics (PK) of endovascular devices. The objective of this study was to develop a novel peripheral simulating bioreactor system to evaluate drug pharmacokinetics of stents. We utilized 3D-printed and off-the-shelf components to construct a peripheral-simulating bioreactor system capable of mimicking the motion of peripheral arteries. Servo motors were primarily used to shorten/elongate, twist, and bend explanted porcine carotid arteries. To evaluate the pharmacokinetics in the bioreactor, drug-eluting stents were deployed within explanted arteries and subjected to vascular motion along with pulsatile flow conditions. Following 30 min and 24 h, the arteries were removed, and paclitaxel levels were measured. Scanning electron microscopy was also performed to evaluate the stent surface. Arterial paclitaxel levels of the stent-treated arteries were found to be higher at 30 min than at 24 h following pulsatile and no vascular motion and even higher at 24 h following pulsatile flow and vascular motion. The residual drug on the stent significantly decreased from 30 min to 24 h. Scanning electron microscopy confirmed the loss of paclitaxel coating at 24 h and greater disturbance in stents under peripheral motion versus pulsatile only. This system represents the first ex vivo system to determine the PK of drug-eluting stents under physiological flow and vascular motion conditions. This work provides a novel system for a quick and inexpensive preclinical tool to study acute drug tissue concentration kinetics of drug-releasing interventional vascular devices designed for peripheral applications.
RESUMO
Americans spend most of their time indoors at home, but comprehensive characterization of in-home air pollution is limited by the cost and size of reference-quality monitors. We assembled small "Home Health Boxes" (HHBs) to measure indoor PM2.5, PM10, CO2, CO, NO2, and O3 concentrations using filter samplers and low-cost sensors. Nine HHBs were collocated with reference monitors in the kitchen of an occupied home in Fort Collins, Colorado, USA for 168 h while wildfire smoke impacted local air quality. When HHB data were interpreted using gas sensor manufacturers' calibrations, HHBs and reference monitors (a) categorized the level of each gaseous pollutant similarly (as either low, elevated, or high relative to air quality standards) and (b) both indicated that gas cooking burners were the dominant source of CO and NO2 pollution; however, HHB and reference O3 data were not correlated. When HHB gas sensor data were interpreted using linear mixed calibration models derived via collocation with reference monitors, root-mean-square error decreased for CO2 (from 408 to 58 ppm), CO (645 to 572 ppb), NO2 (22 to 14 ppb), and O3 (21 to 7 ppb); additionally, correlation between HHB and reference O3 data improved (Pearson's r increased from 0.02 to 0.75). Mean 168-h PM2.5 and PM10 concentrations derived from nine filter samples were 19.4 µg m-3 (6.1% relative standard deviation [RSD]) and 40.1 µg m-3 (7.6% RSD). The 168-h PM2.5 concentration was overestimated by PMS5003 sensors (median sensor/filter ratio = 1.7) and underestimated slightly by SPS30 sensors (median sensor/filter ratio = 0.91).