Effects of Aggregation on Blood Sedimentation and Conductivity

Zhbanov, A. I.; Yang, Sung

doi:10.1371/journal.pone.0129337

Cited by 70 publications

(64 citation statements)

References 51 publications

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“…Accordingly to the acquisition criteria of confocal sections along z -dimension, the maximum height reached by the thrombi results H z − stack = 43 ± 7 μ m (n = 31). Blood conductivity is estimated as σ blood = 0.59 ± 0.19 S/m, at a measured hematocrit percentage of 42.60 ± 1.98%, values that appear perfectly in agreement with previously published data [ 29 , 30 ]. This quantity is estimated by FUSEIT, starting from the impedance value at the beginning of each experiment, when no thrombus is formed.…”

Section: Resultssupporting

confidence: 89%

Impedance biosensor for real-time monitoring and prediction of thrombotic individual profile in flowing blood

et al. 2017

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A new biosensor for the real-time analysis of thrombus formation is reported. The fast and accurate monitoring of the individual thrombotic risk represents a challenge in cardiovascular diagnostics and in treatment of hemostatic diseases. Thrombus volume, as representative index of the related thrombotic status, is usually estimated with confocal microscope at the end of each in vitro experiment, without providing a useful behavioral information of the biological sample such as platelets adhesion and aggregation in flowing blood. Our device has been developed to work either independently or integrated with the microscopy system; thus, images of the fluorescently labeled platelets are acquired in real-time during the whole blood perfusion, while the global electrical impedance of the blood sample is simultaneously monitored between a pair of specifically designed gold microelectrodes. Fusing optical and electrical data with a novel technique, the dynamic of thrombus formation events in flowing blood can be reconstructed in real-time, allowing an accurate extrapolation of the three-dimensional shape and the spatial distribution of platelet thrombi forming and growing within artificial capillaries. This biosensor is accurate and it has been used to discriminate different hemostatic conditions and to identify weakening and detaching platelet aggregates. The results obtained appear compatible with those quantified with the traditional optical method. With advantages in terms of small size, user-friendliness and promptness of response, it is a promising device for the fast and automatic individual health monitoring at the Point of Care (POC).

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Section: Resultssupporting

confidence: 89%

Impedance biosensor for real-time monitoring and prediction of thrombotic individual profile in flowing blood

et al. 2017

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“…As another approach, RBC aggregation can be quantified by measuring the sedimentation distances of RBCs in a blood sample during a specific duration (i.e., ESR). Unlike the conventional Westergren ESR method, a microfluidic-based ESR measurement is quantified by measuring the conductivity of the blood sample in a PDMS chamber with a square cross-section (i.e., each side = 4 mm, depth = 5 mm) [43]. Owing to the continuous ESR in the driving syringe, RBC-free regions (or depleted regions) expand from the top layer with an elapse of time.…”

Section: Introductionmentioning

confidence: 99%

Microfluidic-Based Biosensor for Blood Viscosity and Erythrocyte Sedimentation Rate Using Disposable Fluid Delivery System

Kang

2020

Micromachines

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To quantify the variation of red blood cells (RBCs) or plasma proteins in blood samples effectively, it is necessary to measure blood viscosity and erythrocyte sedimentation rate (ESR) simultaneously. Conventional microfluidic measurement methods require two syringe pumps to control flow rates of both fluids. In this study, instead of two syringe pumps, two air-compressed syringes (ACSs) are newly adopted for delivering blood samples and reference fluid into a T-shaped microfluidic channel. Under fluid delivery with two ACS, the flow rate of each fluid is not specified over time. To obtain velocity fields of reference fluid consistently, RBCs suspended in 40% glycerin solution (hematocrit = 7%) as the reference fluid is newly selected for avoiding RBCs sedimentation in ACS. A calibration curve is obtained by evaluating the relationship between averaged velocity obtained with micro-particle image velocimetry (μPIV) and flow rate of a syringe pump with respect to blood samples and reference fluid. By installing the ACSs horizontally, ESR is obtained by monitoring the image intensity of the blood sample. The averaged velocities of the blood sample and reference fluid (<UB>, <UR>) and the interfacial location in both fluids (αB) are obtained with μPIV and digital image processing, respectively. Blood viscosity is then measured by using a parallel co-flowing method with a correction factor. The ESR is quantified as two indices (tESR, IESR) from image intensity of blood sample (<IB>) over time. As a demonstration, the proposed method is employed to quantify contributions of hematocrit (Hct = 30%, 40%, and 50%), base solution (1× phosphate-buffered saline [PBS], plasma, and dextran solution), and hardened RBCs to blood viscosity and ESR, respectively. Experimental Results of the present method were comparable with those of the previous method. In conclusion, the proposed method has the ability to measure blood viscosity and ESR consistently, under fluid delivery of two ACSs.

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“…For this reason, biochemical analyses, such as biomarkers in cardiovascular diseases and disorders [ 4 ] or DNA [ 5 ], do not show sufficient promise for the early detection of cardiovascular diseases [ 6 ]. Since the associations between coronary heart diseases and blood rheology have been sufficiently investigated [ 3 , 7 , 8 ], several biophysical properties such as the viscosity [ 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 ], erythrocyte sedimentation rate (ESR) [ 17 , 18 , 19 , 20 , 21 , 22 ], hematocrit [ 23 , 24 , 25 ], aggregation [ 26 , 27 , 28 , 29 , 30 , 31 , 32 ], and deformability [ 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 ] are employed to detect variations in blood samples. Among them, blood viscosity varies depending on several factors, such as the plasma viscosity, hematocrit, red blood cell (RBC) aggregation, and deformability.…”

Section: Introductionmentioning

confidence: 99%

“…After a certain amount of time, blood flow stops and aggregates in rouleaux form. Then, RBC aggregation is measured by quantifying the temporal variations of image intensity [ 17 ] or electric impedance [ 18 ] (i.e., a syllectogram [ 20 ]). A repetitive measurement is conducted after agitating blood flow with a pinch valve [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

Microfluidic-Based Measurement Method of Red Blood Cell Aggregation under Hematocrit Variations

Kang

2017

Sensors

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Red blood cell (RBC) aggregation and erythrocyte sedimentation rate (ESR) are considered to be promising biomarkers for effectively monitoring blood rheology at extremely low shear rates. In this study, a microfluidic-based measurement technique is suggested to evaluate RBC aggregation under hematocrit variations due to the continuous ESR. After the pipette tip is tightly fitted into an inlet port, a disposable suction pump is connected to the outlet port through a polyethylene tube. After dropping blood (approximately 0.2 mL) into the pipette tip, the blood flow can be started and stopped by periodically operating a pinch valve. To evaluate variations in RBC aggregation due to the continuous ESR, an EAI (Erythrocyte-sedimentation-rate Aggregation Index) is newly suggested, which uses temporal variations of image intensity. To demonstrate the proposed method, the dynamic characterization of the disposable suction pump is first quantitatively measured by varying the hematocrit levels and cavity volume of the suction pump. Next, variations in RBC aggregation and ESR are quantified by varying the hematocrit levels. The conventional aggregation index (AI) is maintained constant, unrelated to the hematocrit values. However, the EAI significantly decreased with respect to the hematocrit values. Thus, the EAI is more effective than the AI for monitoring variations in RBC aggregation due to the ESR. Lastly, the proposed method is employed to detect aggregated blood and thermally-induced blood. The EAI gradually increased as the concentration of a dextran solution increased. In addition, the EAI significantly decreased for thermally-induced blood. From this experimental demonstration, the proposed method is able to effectively measure variations in RBC aggregation due to continuous hematocrit variations, especially by quantifying the EAI.

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Effects of Aggregation on Blood Sedimentation and Conductivity

Cited by 70 publications

References 51 publications

Impedance biosensor for real-time monitoring and prediction of thrombotic individual profile in flowing blood

Impedance biosensor for real-time monitoring and prediction of thrombotic individual profile in flowing blood

Microfluidic-Based Biosensor for Blood Viscosity and Erythrocyte Sedimentation Rate Using Disposable Fluid Delivery System

Microfluidic-Based Measurement Method of Red Blood Cell Aggregation under Hematocrit Variations

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