Poly(dimethylsiloxane) (PDMS) microchannels are commonly used microfluidic structures that have a wide variety of biological testing applications, including the simulation of blood vessels to study the mechanics of vascular disease. In these studies in particular, the deformation of the channel due to the pressure inside is a critical parameter. We describe a method for using fluorescence microscopy to quantify the deformation of such channels under pressure driven flow. Additionally, the relationship between wall thickness and channel deformation is investigated. PDMS microchannels of varying top wall thickness were created using a soft lithography process. A solution of fluorescent dye is pumped through the channels at constant volume flow rates and illuminated. Pressure and fluorescence intensity are measured at five positions along the length of the channel. Fluorescence measurements are then used to determine deformation, using the linear relationship of dye layer thickness and intensity. A linear relationship between pressure and microchannel deformation is measured. Pressure drops and deformations closely correspond to values predicted by the model in most cases. Additionally, measured pressure drops are found to be up to 35% less than the pressure drop in a rigid-walled channel, and channel wall thickness is found to have an increasing effect as the channel wall thickness decreases.
Kim S, Zhen J, Popel AS, Intaglietta M, Johnson PC. Contributions of collision rate and collision efficiency to erythrocyte aggregation in postcapillary venules at low flow rates. Am J Physiol Heart Circ Physiol 293: H1947-H1954, 2007. First published July 6, 2007; doi:10.1152/ajpheart.00764.2006.-Red blood cell aggregation at low flow rates increases venous vascular resistance, but the process of aggregate formation in these vessels is not well understood. We previously reported that aggregate formation in postcapillary venules of the rat spinotrapezius muscle mainly occurs in a middle region between 15 and 30 m downstream from the entrance. In light of the findings in that study, the main purpose of this study was to test two hypotheses by measuring collision frequency along the length of the venules during low flow. We tested the hypothesis that aggregation rarely occurs in the initial 15-m region of the venule because collision frequency is very low. We found that collision frequency was lower than in other regions, but collision efficiency (the ratio of aggregate formation to collisions) was almost nil in this region, most likely because of entrance effects and time required for aggregation. Radial migration of red blood cells and Dextran 500 had no effect on collision frequency. We also tested the hypothesis that aggregation was reduced in the distal venule region because of the low aggregability of remaining nonaggregated cells. Our findings support this hypothesis, since a simple model based on the ratio of aggregatable to nonaggregatable red blood cells predicts the time course of collision efficiency in this region. Collision efficiency averaged 18% overall but varied from 0 to 52% and was highest in the middle region. We conclude that while collision frequency influences red blood cell aggregate formation in postcapillary venules, collision efficiency is more important. red blood cells; hemorheology; venous vascular resistance AT LOW SHEAR RATES, red blood cells in the blood of athletic species, but not sedentary species, tend to form clusters or linear stacks (rouleaux) (20). This feature has been attributed to a bridging phenomenon (7,14) or to an osmotic exclusion effect between adjacent cells by macromolecules (1, 19). Previous studies in this laboratory have shown that in the venular network, where shear rates are normally low, aggregation creates an inverse relation between flow rate and venous vascular resistance. The small venules contribute importantly to this relationship (10). This property may be important in maintaining a constant capillary hydrostatic pressure in skeletal muscle in athletic species where flow rate undergoes large changes (5). The aggregation also appears to influence the distribution of red blood cells in the capillary network by causing plasma skimming at bifurcations (12, 13) or by plugging capillaries and causing flow stasis at high levels of aggregation (16,17).While these previous studies indicate that aggregation is functionally important, relatively little is kno...
14. Results offer meaningful insights to assist in counseling patients prior to the surgical treatment of nephrolithiasis.
Percutaneous nephrolithotomy (PCNL) is the current standard of care for patients with a total renal stone burden > 20 mm. Gaining access to the kidney is a crucial step, as the position of the percutaneous tract can affect the ability to manipulate a nephroscope during the procedure. However, gaining percutaneous access using fluoroscopic guidance has a challenging learning curve, with only a minority of urologists can successfully establish the access. In addition to difficult access, the PCNL carries a risk of bleeding and the need for blood transfusion. Robotic assistance may be a key towards accurate and reliable access. Beyond assisting with renal access, a robotic platform can record data of importance related to the user's activities via sensor-equipped instruments. The analysis of these activities is crucial for understanding what constitutes a successful and safe procedure. In this paper, we harness the powers of machine learning to automatically analyze physicians' activities during robotic-assisted renal access using the Monarch®Platform, Urology. A machine learning framework based on a combination of a 1-dimensional U-net and random forests was developed to find consistent patterns in the sensor data characteristic of needle insertions. This framework retrospectively analyzed data previously obtained from 248 percutaneous renal access procedures. These procedures were performed on 18 human cadaveric models by 17 practicing urologists and one urologist proxy. The framework automatically recognized 94% of all first needle insertions in each procedure and labeled them with an accuracy of 0.81 in terms of the Dice coefficient. The recognition accuracy for secondary insertions was 66%. The automatically detected needle insertions were used to calculate clinical metrics such as tract length, anterior-posterior and cranial-caudal angles of the insertion site, as well as user skills such as trajectory deviation and targeting accuracy.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations –citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.