This work was supported by the Natural Sciences and Engineering Research Council of Canada. Microfabrication was performed with the support of the McGill Nanotools Microfab facility at McGill University and the Department of Electronics at Carleton University.

Blood is collected from healthy individuals with the approval of the ethics committee of the University of Ottawa (H11-13-06).
1. Microchannel Fabrication
The microchannels are fabricated based on the standard photolithography methods19.
<ol>
	<li>Design the microchannel geometry using a Computer Aided Design (CAD) software and print the configuration on a transparency photo-mask. These masks are crucial since they dictate the light path during the fabrication process. In this case, the microchannel dimensions are 120 &#181;m in thickness, 60 &#181;m in depth and 7 mm in length.</li>
	<li>In a cleanroom, spin coat an epoxy based negative photo-resist on a silicon wafer at 2,000 rpm for 30 sec to obtain the desired microchannel depth (60 &#181;m).</li>
	<li>Expose the wafer and the photo-mask under a UV lamp at 650 mJ/cm2 for 70 sec. Ensure to expose only the transparent areas of the photo-mask to the UV-light. The exposure of the transparent areas allows for polymerization of the chains resulting in a hardening of the photo-resist. Immerse the silicon piece into a developer to remove excess of photo-resist.</li>
	<li>Once the mold is fabricated, mix a silicon based elastomer and a curing agent at a ratio of 10:1 to create a solution of poly-dimethyl-siloxane (PDMS). Put the PDMS solution in a vacuum chamber to degas. Pour it into the mold and heat it at 60 &#176;C for 90 min to create microchannels. Then bond the individual channels to a glass slide using oxygen plasma bonding for 90 sec. 
	NOTE: the PDMS degas process is performed in order to eliminate the air bubbles engendered by the mixing process.</li>
	<li>Ensure that the microchannel dimensions allow for successful testing. In this protocol, the microchannels have a rectangular cross-section of 120 x 60 &#181;m. In comparison, an average RBC has a diameter of 8 &#181;m and a thickness of 2 &#181;m. Therefore, the microchannel width is sufficient to observe proper aggregation and accurately determine the velocity profiles.</li>
</ol>
2. Blood Preparation
<ol>
	<li>Collect blood from healthy volunteer donors, after approval of an ethics committee. Treat the blood with ethylenediaminetetraacetic acid (EDTA) present in the collection tubes (7.2 mg EDTA in 4 ml of blood). 
	NOTE: The EDTA is used to avoid blood clotting.</li>
	<li>Centrifuge the blood samples three times for 10 min at 1,400 x g (3,000 rpm) in order to separate the blood constituents. As a result of the centrifugation, observe three distinct layers. 
	NOTE: The three layers are the RBC layer (located at the bottom of the tube), the buffy coat (consisting of white blood cells and platelets located on top of the RBC layer) and the plasma layer (located on top of all the other constituents).
	<ol>
		<li>After the first centrifugation, collect blood plasma using a blood pipette. Avoid any contact with the buffy coat.</li>
		<li>Collect and dispose of the buffy coat in a container with bleach diluted at 10%.</li>
		<li>Add 3 ml of PBS pH 7.4 to each of the tubes with the remaining RBC layer and ensure the proper balance of the centrifuge. Gently mix the tubes and centrifuge once again at 1,400 x g (3,000 rpm) for 10 min. 
		NOTE: Ensure that the PBS solution does not contain any Magnesium or Calcium since they could alter the cell adhesion.</li>
		<li>Dispose of the PBS in the tubes after the second centrifugation and remove the remaining buffy coat if present. Repeat steps 2.2.3 and 2.2.4 for the third centrifugation to yield clean RBCs.</li>
	</ol>
	</li>
	<li>Mix the required amount (0.05, 0.1 and 0.15 ml) of the clean RBCs with plasma (0.95, 0.9 and 0.85 ml) in a 1 ml tube in order to obtain RBC-suspensions with the corresponding (5%, 10% and 15%) hematocrit. Check hematocrits with a microcentrifuge.</li>
</ol>
3. Fluids Preparation
Introduce two fluids in the double Y-microchannel: RBC-suspensions and PBS.
<ol>
	<li>Add 60 &#181;l of the fluorescent tracer particles solution (1% solid, dparticle = 0.86 &#181;m, &#955;abs = 542 nm and &#955;emission = 612 nm) into the 1 ml RBC-suspension tubes. 
	NOTE: The fluorescent tracer particles (internally dyed polystyrene particles) are used to measure the velocity of the flow within the microchannel. These particles fluoresce when exposed to the corresponding wavelength of the laser beam (&#955; = 542 nm).</li>
	<li>Prepare a PBS pH 7.4 solution and add 60 &#181;l of the same fluorescent tracer particles solution in 1 ml of the PBS solution.</li>
</ol>
4. Aggregates Size Measurements
<ol>
	<li>To insert the fluids (RBC-suspensions and PBS) in the microchannel, use two glass syringes of 25 &#181;l and 100 &#181;l. This will help to reduce the compliance of the system. Connect the microchannel to the syringes via tubing and connectors fitting the entry holes. Fill the glass syringes using the pressure difference existing between the fluid container and the syringe. Ensure no bubbles are present in the system. As an alternative method, use a pressure controlled system to drive both fluids in the microchannel.</li>
	<li>Place the microchannel on an inverted microscope stage connected to a high speed camera and a &#181;PIV system. Program the syringe pump to the desired flow rates (e.g., Q = 2 &#181;l/hr for blood engendering a flowrate of Q = 8 &#181;l/hr for PBS). 
	NOTE: Only one syringe pump is used. Using two different glass syringes, with two different internal diameters, it is possible to vary to the flowrate entering each branch of the Y-microchannel.</li>
	<li>Insert both fluids in the double Y-microchannel each from a different entry branch and at different flowrates as shown in Figure 1. In order to test different shear rates, change the pump flowrate. This maintains the same appropriate ratio (4 in this case) between the two branches20 (Figures 2 and 3). Wait for the flow to reach steady state before acquiring the measurements: visually inspect the high speed camera images for a smooth flow. 
	NOTE: The ratio is crucial in obtaining a linear velocity profile within the blood layer.</li>
	<li>Visualize the RBCs using the high speed camera. Connect the camera to a computer to control, record and save the images of the fluid flow. Once the two fluid flows reach steady state, start recording.
	<ol>
		<li>Acquire several images for better processing results. Determine an optimal camera exposure time for a clear image of the aggregates. 
		NOTE: The camera exposure time for this case was 0.5 msec. The choice of time interval between each frame is based on the camera frame rate and the flow rate in the microchannel. The time between each frame processed in this procedure was 60 msec. Therefore a camera capable of recording 18 frames per seconds is sufficient. 
		NOTE: Avoid blood settling in the tube and syringe, which could lead to erroneous measurements.</li>
	</ol>
	</li>
	<li>Using image processing techniques (a MATLAB program in this case) to ameliorate the image quality, detect the aggregates in each of the images based on pixel intensities (illustrated in Figure 4) as follows:
	<ol>
		<li>Enhance the images contrast using the histogram equalizer method to obtain a better image quality for each frame.</li>
		<li>Convert the greyscale images into binary images. For this purpose, set a threshold value, ranging from 0 to 1, that dictates the conversion of each pixel. Any pixel in the image below the threshold value will be detected as a black pixel, while the pixels with values larger than the threshold will be detected as white pixels.</li>
		<li>Fill the holes (if present and necessary) corresponding to the gaps within one aggregate for better results.</li>
		<li>Detect the cells by determining neighboring white pixels in the binary image so that adjacent cells are associated as aggregates.</li>
		<li>Label the different aggregates detected and convert the binary image into a red-green-blue (RGB) image for better visualization. Combine the original frames with each of the corresponding processed images to verify the efficiency of the image processing technique and ensure that all the cells are taken into consideration, as shown in Figure 5. Perform steps 4.5.1, 4.5.2, 4.5.3, 4.5.4 and 4.5.5 for all the frames captured.</li>
		<li>Calculate the area of each aggregate detected in the frame based on the number of pixels detected. Based on the lens magnification used, calculate the conversion factor, using a calibration reticule, and convert the results to &#181;m2. Average the aggregate sizes detected in each frame and then average the results for all frames to obtain the average aggregate size for each recording of RBC-suspensions.</li>
		<li>Calculate the area of one RBC to determine a representative estimated number of RBCs within each detected aggregate. Using these results, calculate the distribution of the percentage of RBCs within each aggregate as a function of the aggregate sizes (represented by the estimated number of cells in each aggregate), as shown in Figure 6. 
		NOTE: To measure the RBC aggregates, ImageJ software could be used (instead of MATLAB) to perform the same tasks on each frame.</li>
	</ol>
	</li>
</ol>
5. Fluid Velocity and Shear Rate Measurements
Determine the fluid velocity and hence the shear rate using a &#181;PIV system.
<ol>
	<li>Once the data is acquired using the high speed camera, switch to the double pulsed camera used for the &#181;PIV system. Use an imaging software for image acquisition of the flow and the image processing for velocity field determination.</li>
	<li>Take all the precautions necessary, depending on the class of the laser, before turning on the laser. Then turn on the system, the camera and the laser.</li>
	<li>Calibrate the camera based on the lens magnification used. For this purpose, use a microscale of 10 &#181;m precision under the microscope and set the size of 1 pixel in the image.</li>
	<li>Start the laser and visualize the particles in both fluids. Find the middle plane of the microchannel by focusing on the fastest particles in the flow (i.e., the fastest particles should be the brightest).</li>
	<li>Set the dt (time interval between two consecutive frames) to ensure the proper displacement of the particle. The fastest particles should move about 5 to 10 pixels between both images.</li>
	<li>Start recording the flow. Set the software to acquire 100 pairs of images, 5 msec apart. Perform steps 5.4, 5.5 and 5.6 for all the different RBC-suspensions and for different shear rates. 
	NOTE: More details of the methodology are given in the study of Pitts and Fenech21.</li>
	<li>Process the recordings acquired using the cross-correlation method with the imaging software. 
	NOTE: This consists of discretizing the pair of images into small windows of predetermined size (based on the fluid flow and the time interval chosen by the user) called correlation windows and following the displacement of the particles in each window.
	<ol>
		<li>First, determine if the images acquired require pre-processing (including background subtraction, &#8220;base-clipping&#8221;22 or image overlapping23,24) for better data processing.</li>
		<li>Then choose the correlation window size and shape, as well of the percentage of images overlapping. A detailed study was performed by Pitts et al.25 to determine the optimal parameters and image pre-processing techniques for blood flow in different channel configurations. Express the results as an average velocity field calculated from the 100 image pairs and the Root Mean Square (RMS) error in velocity.</li>
	</ol>
	</li>
	<li>Extract a velocity profile at the channel outlet, from the processed data as shown in Figure 7. For a better profile, average the velocity field in space. 
	NOTE: The bars composing the velocity profile correspond to the correlation window size chosen relative to the channel width. The RMS error in velocity is also shown in Figure 7, representing the error in the experimental velocity estimation.</li>
	<li>Turn off the laser once all the measurements and processing are performed,. Shut down all the components of the system: software, cameras, moving stage, computers and laser.</li>
	<li>To calculate the shear rate, first detect and estimate the blood thickness in the microchannel based on the high speed camera recording. For this purpose, average all the frames in the specific recording to obtain a background image of the video. Delimit the blood layer (as shown in Figure 8 for the RBC-suspensions flowing at 10 &#181;l/hr when suspended at 5%, 10% and 15% hematocrit). Obtain the velocity value for the corresponding blood layer thickness and calculate the shear rate by dividing the velocity value by the blood layer thickness.</li>
</ol>

<ol>
	<li>Perkkio, J., Keskinen, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hematocrit+reduction+in+bifurcations+due+to+plasma+skimming.">Hematocrit reduction in bifurcations due to plasma skimming.</a> Bull. Math. Biol. 45 (1), 41-50 (1983).</li><li>Chien, S., Jan, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ultrastructural+basis+of+the+mechanism+of+rouleaux+formation.">Ultrastructural basis of the mechanism of rouleaux formation.</a> Microvasc. Res. 5 (2), 155-166 (1973).</li><li>Neu, B., Meiselman, H. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Depletion-mediated+red+blood+cell+aggregation+in+polymer+solutions.">Depletion-mediated red blood cell aggregation in polymer solutions.</a> Biophys. J. 83 (5), 2482-2490 (2002).</li><li>Schmid-Sch&#246;nbein, H., Gaehtgens, P., Hirsch, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=On+the+shear+rate+dependence+of+red+cell+aggregation+in+vitro.">On the shear rate dependence of red cell aggregation in vitro.</a> J. Clin. Invest. 47 (6), 1447-1454 (1968).</li><li>Pries, A. R., Secomb, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Rheology+of+the+microcirculation.">Rheology of the microcirculation.</a> Clin. Hemorheol. Microcirc. 29 (3-4), 143-148 (2003).</li><li>Baskurt, O. K., Neu, B., Meiselman, H. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Red Blood Cell Aggregation. , (2011).</li><li>Cho, Y. I., Mooney, M. P., Cho, D. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hemorheological+disorders+in+diabetes+mellitus.">Hemorheological disorders in diabetes mellitus.</a> J. Diabetes Sci. Technol. 2 (6), 1130-1138 (2008).</li><li>Baskurt, O. K., Hardeman, M. R., Rampling, M. W., Meiselman, H. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Handbook of Hemorheology and Hemodynamics. , (2007).</li><li>Lindqvist, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+viscosity+of+the+blood+in+narrow+capillary+tubes.">The viscosity of the blood in narrow capillary tubes.</a> Am. J. Physiol.-Legacy Content. 96, 562-568 (1931).</li><li>Goldsmith, H. L., Cokelet, G. R., Gaehtgens, P. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=F&#229;hraeus:+Evolution+of+his+concepts+in+cardiovascular+physiology.">F&#229;hraeus: Evolution of his concepts in cardiovascular physiology.</a> Am. J. Physiol. 257 (3), H1005-H1015 (1989).</li><li>F&#229;hraeus, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+suspension+stability+of+the+blood.">The suspension stability of the blood.</a> Physiol. Rev. 9 (2), 241-274 (1929).</li><li>Bauersachs, R. M., Wenby, R. B., Meiselman, H. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Determination+of+specific+red+blood+cell+aggregation+indices+via+an+automated+system.">Determination of specific red blood cell aggregation indices via an automated system.</a> Clin. Hemorheol. 9 (1), 1-25 (1989).</li><li>Hardeman, M. R., Dobbe, J. G., Ince, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+laser-assisted+optical+rotational+cell+analyzer+(lorca)+as+red+blood+cell+aggregometer.">The laser-assisted optical rotational cell analyzer (lorca) as red blood cell aggregometer.</a> Clin. Hemorheol. Microcirc. 25 (1), 1-11 (2001).</li><li>Rampling, M. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Red+cell+aggregation+and+yield+stress.">Red cell aggregation and yield stress.</a> Clinical Blood Rheology. , (1988).</li><li>Dusting, J., Kaliviotis, E., Balabani, S., Yianneskis, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Coupled+human+erythrocyte+velocity+field+and+aggregation+measurements+at+physiological+haematocrit+levels.">Coupled human erythrocyte velocity field and aggregation measurements at physiological haematocrit levels.</a> J. Biomech. 42 (10), 1438-1443 (2009).</li><li>Kaliviotis, E., Dusting, J., Balabani, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Spatial+variation+of+blood+viscosity:+modelling+using+shear+fields+measured+by+a+&#181;PIV+based+technique.">Spatial variation of blood viscosity: modelling using shear fields measured by a &#181;PIV based technique.</a> Med. Eng. Phys. 33 (7), 824-831 (2011).</li><li>Sherwood, J. M., Kaliviotis, E., Dusting, J., Balabani, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Spatial+variation+of+blood+viscosity+and+velocity+distributions+of+aggregating+and+non-aggregating+blood+in+a+bifurcating+microchannel.">Spatial variation of blood viscosity and velocity distributions of aggregating and non-aggregating blood in a bifurcating microchannel.</a> Biomech. Model. Mechan. 13 (2), 259-273 (2014).</li><li>Chen, S., Barshtein, G., Gavish, B., Mahler, Y., Yedgar, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Monitoring+of+red+blood+cell+aggregability+in+a+flow+chamber+by+computerized+image+analysis.">Monitoring of red blood cell aggregability in a flow chamber by computerized image analysis.</a> Clin. Hemorhol. Microcirc. 14 (4), 497-508 (1994).</li><li>Xia, Y. N., Whitesides, G. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Soft+lithography.">Soft lithography.</a> Angewandte Chemie International Edition England. , 551-577 (1998).</li><li>Mehri, R., Mavriplis, C., Fenech, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Design+of+a+microfluidic+system+for+red+blood+cell+aggregation+investigation.">Design of a microfluidic system for red blood cell aggregation investigation.</a> J. Biomech. Eng. 136 (6), 064501-1-064501-5 (2014).</li><li>Pitts, K. L., Fenech, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Micro-particle+image+velocimetry+for+velocity+profile+measurements+of+micro+blood+flows.">Micro-particle image velocimetry for velocity profile measurements of micro blood flows.</a> J. Vis. Exp. (74), e50314 (2013).</li><li>Bitsch, L., Oleson, L. H., Westergaard, C. H., Bruus, H., Klank, H., Kutter, J. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Micro+particle-image+velocimetry+of+bead+suspensions+and+blood+flows.">Micro particle-image velocimetry of bead suspensions and blood flows.</a> Exp. Fluids. 39 (3), 507-513 (2005).</li><li>Wereley, S. T., Gui, L., Meinhart, C. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Advanced+algorithms+for+microscale+particle+image+velocimetry.">Advanced algorithms for microscale particle image velocimetry.</a> AIAA J. 40 (6), 1047-1105 (2002).</li><li>Nguyen, C. V., Fouras, A., Carberry, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Improvement+of+measurement+accuracy+in+micro+PIV+by+image+overlapping.">Improvement of measurement accuracy in micro PIV by image overlapping.</a> Exp. Fluids. 49 (3), 701-712 (2010).</li><li>Pitts, K. L., Mehri, R., Mavriplis, C., Fenech, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Micro-particle+image+velocimetry+measurement+of+blood+flow:+validation+and+analysis+of+data+pre-processing+and+processing+methods.">Micro-particle image velocimetry measurement of blood flow: validation and analysis of data pre-processing and processing methods.</a> Meas. Sci. Technol. 23 (10), 105302 (2012).</li><li>Bhamare, M. G., Patil, D. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automatic+blood+cell+analysis+by+using+digital+image+processing:+a+preliminary+study.">Automatic blood cell analysis by using digital image processing: a preliminary study.</a> Int. J. Eng. Res. Tech. 2 (9), 3135-3141 (2013).</li><li>Maitra, M., Gupta, R. K., Mukherjee, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Detection+and+counting+of+red+blood+cells+in+blood+cell+images+using+hough+transform.">Detection and counting of red blood cells in blood cell images using hough transform.</a> Int. J. Comput. Appl. 53 (16), 18-22 (2012).</li><li>Jambhekar, N. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Red+blood+cells+classification+using+image+processing.">Red blood cells classification using image processing.</a> Sci. Res. Repot. 1 (3), 151-154 (2011).</li><li>Otsu, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+threshold+selection+method+from+gray-level+histograms.">A threshold selection method from gray-level histograms.</a> IEEE Trans. Syst. Man. Cybern. 9 (1), 62-66 (1979).</li></ol>

The authors have nothing to disclose.

Using the present methodology, it is possible to analyze qualitatively and quantitatively the RBC aggregates under different flow conditions and hematocrits. For successful testing and aggregate detection, it is crucial to determine the appropriate velocity ratio between the two fluids at the microchannel entry. This ratio is very important to obtain an optimal blood layer thickness where the velocity profile is quasi-linear20.
Another key factor for successful testing is a good ima...

An erratum was issue for <a href="http://www.jove.com/video/52719">Controlled Microfluidic Environment for Dynamic Investigation of Red Blood Cell Aggregation</a>. The introduction section was updated.

An erratum was issued for <a href="http://www.jove.com/video/52719">Controlled Microfluidic Environment for Dynamic Investigation of Red Blood Cell Aggregation</a>. The introduction section was updated.

Erratum: Controlled Microfluidic Environment for Dynamic Investigation of Red Blood Cell Aggregation

Red Blood Cells (RBCs) play a crucial role in determining the rheological behavior of blood. They are almost singularly responsible for the particular properties of blood in vitro and in vivo. Under physiological conditions, RBCs occupy 40% to 45% of the blood volume. In microcirculation, RBCs only occupy up to 20% of the blood volume due to smaller vessel diameters and the plasma skimming effect1. This phenomenon of plasma reduction in microcirculation is known as the F&#229;hr&#230;us effect. At low shear rates, RBCs are able to bridge together and form one dimensional or three dimensional structures called &#8220;rouleaux&#8221; or aggregates, hence contributing to the non-Newtonian behavior of blood. However, the mechanism of RBC aggregation is not completely understood. Two theories exist to model the aggregation of RBCs: the bridging of cells theory due to the cross-linking of the macromolecules2 and the force attraction theory caused by depletion of the molecules due to the osmotic gradient3.
Typically, for human blood, aggregates form at very low shear rates4 ranging from 1 to 10 sec-1. Above this range, RBCs tend to disaggregate and flow separately within the vessel.
Understanding the conditions of the aggregates formation is of a great importance to the hemorheology field in terms of defining blood&#8217;s rheological behavior. These aggregates are often seen at the macrocirculation level (&#62;300 &#181;m diameter)5. At this scale, blood is considered as a Newtonian fluid and a homogenous mixture. However, these aggregates are rarely seen in the capillary level (4-10 &#181;m in diameter) and are usually an indication of pathological conditions such as diabetes6 and obesity. Other pathological conditions that could change RBC aggregation include inflammatory or infectious conditions, cardiovascular diseases such as hypertension or atherosclerosis, genetic disorders and chronic diseases7. Therefore, understanding the RBC aggregation mechanism and analyzing these entities (by defining a relationship between the size of these aggregates and the flow conditions) could lead to the understanding of the microrheological behavior of blood and hence relate it to clinical applications.
RBC aggregates can be altered by several factors such as the hematocrit (volume of RBCs in blood), the shear rate, the vessel diameter, the RBC membrane stiffness and the suspending medium composition8-10. Therefore, controlled conditions are required in order to effectively analyze the RBC aggregates. Several methods are able to analyze aggregate formation by providing static aggregation measurements (aggregation index) that offers relevant information about blood behavior. These methods include, inter alia, the erythrocyte sedimentation rate method11, the light transmission method12, the light reflection method13 and the low shear viscosity method14.
Few studies have attempted to study RBC aggregation and determine the degree of aggregation in controlled flow conditions15-17. However, these studies indirectly investigate RBC aggregate sizes by determining the ratio of the occupied space in a shearing system measured based on microscopic blood images providing information on the degree of aggregation as well as the local viscosity. Chen et al.18 presented a direct measurement technique for RBC aggregate sizes and provided RBC aggregate size distribution for different shear stresses by varying the flowrate of the suspensions while monitoring the pressure drop across a flow chamber. The shear stresses are calculated based on the monitored pressure using Stokes equation18.
We therefore present a new procedure to directly quantify RBC aggregates in a controlled microfluidic environment, dynamically, under specific, constant and measurable shear rates. The blood flow in the shear system is directly observed (perpendicularly to the flow direction), providing a different angle on flow investigation compared to previous studies15,18 and a visualization of the full domain of interest. RBC-suspensions are entrained, in a double Y-microchannel (as illustrated in Figure 1), with a Phosphate Buffered Saline (PBS) solution hence creating a shear flow in the blood layer. Within this blood layer a constant shear rate can be obtained. The RBC-suspensions are tested at different hematocrit (H) levels (5%, 10% and 15%) and under different shear rates (2-11 sec-1). The blood velocity and shear rate are determined using a micro Particle Image Velocimetry (&#181;PIV) system while the flow is visualized using a high speed camera. The results obtained are then processed with a MATLAB code based on the image intensities in order to detect the RBCs and determine aggregate sizes.

<table border="0" cellpadding="0" cellspacing="0">
	<tbody>
		<tr>
			<td>SU8-50 epoxy based negative Photo-resist</td>
			<td>MicroChem Corp.</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>SU8-50 developer</td>
			<td>MicroChem Corp.</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Poly(dimethylsiloxane) (PDMS) Sylgard-184</td>
			<td>Dow-Corning</td>
			<td>3097358-1004</td>
			<td></td>
		</tr>
		<tr>
			<td>PE-50 series Plasma system&#160;</td>
			<td>Plasma Etch</td>
			<td>PE-50 series</td>
			<td></td>
		</tr>
		<tr>
			<td>Blood collection tubes with K2 EDTA (ethylenediaminetetraacetic acid)</td>
			<td>FisherSci</td>
			<td>B367861</td>
			<td></td>
		</tr>
		<tr>
			<td>Centrifuge, i.e. Thermo Scientific CL2</td>
			<td>Thermo Scientific</td>
			<td>004260F</td>
			<td></td>
		</tr>
		<tr>
			<td>Poshpate buffered saline (PBS)</td>
			<td>Sigma Aldrich</td>
			<td>P5368-10PAK</td>
			<td></td>
		</tr>
		<tr>
			<td>Tracer fluorescent particles solution (15 mL)</td>
			<td>FisherSci</td>
			<td>R800</td>
			<td></td>
		</tr>
		<tr>
			<td>Aggregometer</td>
			<td>RheoMeditech</td>
			<td>Rheo Scan AnD300</td>
			<td></td>
		</tr>
		<tr>
			<td>Glass syringes (50 &#181;L)</td>
			<td>Hamilton</td>
			<td>80965</td>
			<td></td>
		</tr>
		<tr>
			<td>Tubing (Tygon)</td>
			<td>FisherSci</td>
			<td>AAA00001</td>
			<td></td>
		</tr>
		<tr>
			<td>High speed camera (Basler)</td>
			<td>Graftek Imaging Inc.</td>
			<td>basler acA2000-340km</td>
			<td>A camera capable of recording 18 frames per seconds could be used.&#160;</td>
		</tr>
		<tr>
			<td>Double pulsed camera&#160;</td>
			<td>LaVision</td>
			<td>Imager Intense</td>
			<td></td>
		</tr>
		<tr>
			<td>Microscope MITAS</td>
			<td>LaVision</td>
			<td>MITAS</td>
			<td></td>
		</tr>
		<tr>
			<td>Nd:YAG laser</td>
			<td>New Wave Research</td>
			<td>Solo-II</td>
			<td></td>
		</tr>
		<tr>
			<td>Syringe pump (Nexus3000 and PicoPlus)</td>
			<td>Chemyx Inc. and Harvard Apparatus</td>
			<td>Nexus3000 and PicoPlus</td>
			<td></td>
		</tr>
		<tr>
			<td>DaVis software</td>
			<td>LaVision</td>
			<td>Davis</td>
			<td></td>
		</tr>
	</tbody>
</table>

controlled microfluidic environment for dynamic investigation of red blood cell aggregation

Blood, as a non-Newtonian biofluid, represents the focus of numerous studies in the hemorheology field. Blood constituents include red blood cells, white blood cells and platelets that are suspended in blood plasma. Due to the abundance of the RBCs (40% to 45% of the blood volume), their behavior dictates the rheological behavior of blood especially in the microcirculation. At very low shear rates, RBCs are seen to assemble and form entities called aggregates, which causes the non-Newtonian behavior of blood. It is important to understand the conditions of the aggregates formation to comprehend the blood rheology in microcirculation. The protocol described here details the experimental procedure to determine quantitatively the RBC aggregates in microcirculation under constant shear rate, based on image processing. For this purpose, RBC-suspensions are tested and analyzed in 120 x 60 &#181;m poly-dimethyl-siloxane (PDMS) microchannels. The RBC-suspensions are entrained using a second fluid in order to obtain a linear velocity profile within the blood layer and thus achieve a wide range of constant shear rates. The shear rate is determined using a micro Particle Image Velocimetry (&#181;PIV) system, while RBC aggregates are visualized using a high speed camera. The videos captured of the RBC aggregates are analyzed using image processing techniques in order to determine the aggregate sizes based on the images intensities.

An example of the two-fluid flow in the double Y-microchannel is shown in Figure 2 for human RBCs suspended at 5%, 10% and 15% hematocrit and flowing at 10 &#181;l/hr. Figure 3 shows the difference in aggregate sizes when the flow in the channel is reduced from 10 &#181;l/hr to 5 &#181;l/hr for a hematocrit of 10%. This gives a qualitative notion of the sizes of the aggregates when varying the hematocrit and shear rate. Figure 5 follows the displacement of four human RBC...

Watch this Scientific Journal Video about Controlled Microfluidic Environment for Dynamic Investigation of Red Blood Cell Aggregation at JoVE.com

Controlled Microfluidic Environment for Dynamic Investigation of Red Blood Cell Aggregation

The protocol described details an experimental procedure to quantify Red Blood Cell (RBC) aggregates under a controlled and constant shear rate, based on image processing techniques. The goal of this protocol is to relate RBC aggregate sizes to the corresponding shear rate in a controlled microfluidic environment.

Blood, as a non-Newtonian biofluid, represents the focus of numerous studies in the hemorheology field. Blood constituents include red blood cells, white ...

controlled-microfluidic-environment-for-dynamic-investigation-red

Research

JoVE Journal

Bioengineering

11.7K Views.  University of Ottawa. The protocol described details an experimental procedure to quantify Red Blood Cell (RBC) aggregates under a controlled and constant shear rate, based on image processing techniques. The goal of this protocol is to relate RBC aggregate sizes to the corresponding shear rate in a controlled microfluidic environment.

Video: Controlled Microfluidic Environment for Dynamic Investigation of Red Blood Cell Aggregation

Microfabricated Platforms for Mechanically Dynamic Cell Culture

The ability to systematically probe in vitro cellular response to combinations of mechanobiological stimuli for tissue engineering, drug discovery or fundamental cell biology studies is limited by current bioreactor technologies, which cannot simultaneously apply a variety of mechanical stimuli to cultured cells. In order to address this issue, we have developed a series of microfabricated platforms designed to screen for the effects of mechanical stimuli in a high-throughput format. In this protocol, we demonstrate the fabrication of a microactuator array of vertically displaced posts on which the technology is based, and further demonstrate how this base technology can be modified to conduct high-throughput mechanically dynamic cell culture in both two-dimensional and three-dimensional culture paradigms.

In this protocol, we demonstrate the fabrication of a microactuator array of vertically displaced posts on which the technology is based, and how this base technology can be modified to conduct high-throughput mechanically dynamic cell culture in both two-dimensional and three-dimensional culture paradigms.

The ability to systematically probe in vitro cellular response to combinations of mechanobiological stimuli for tissue engineering, drug discovery or ...

Correlative Microscopy for 3D Structural Analysis of Dynamic Interactions

Cryo-electron tomography (cryoET) allows 3D visualization of cellular structures at molecular resolution in a close-to-physiological state1. However, direct visualization of individual viral complexes in their host cellular environment with cryoET is challenging2, due to the infrequent and dynamic nature of viral entry, particularly in the case of HIV-1. While time-lapse live-cell imaging has yielded a great deal of information about many aspects of the life cycle of HIV-13-7, the resolution afforded by live-cell microscopy is limited (~ 200 nm). Our work was aimed at developing a correlation method that permits direct visualization of early events of HIV-1 infection by combining live-cell fluorescent light microscopy, cryo-fluorescent microscopy, and cryoET. In this manner, live-cell and cryo-fluorescent signals can be used to accurately guide the sampling in cryoET. Furthermore, structural information obtained from cryoET can be complemented with the dynamic functional data gained through live-cell imaging of fluorescent labeled target.
In this video article, we provide detailed methods and protocols for structural investigation of HIV-1 and host-cell interactions using 3D correlative high-speed live-cell imaging and high-resolution cryoET structural analysis. HeLa cells infected with HIV-1 particles were characterized first by confocal live-cell microscopy, and the region containing the same viral particle was then analyzed by cryo-electron tomography for 3D structural details. The correlation between two sets of imaging data, optical imaging and electron imaging, was achieved using a home-built cryo-fluorescence light microscopy stage. The approach detailed here will be valuable, not only for study of virus-host cell interactions, but also for broader applications in cell biology, such as cell signaling, membrane receptor trafficking, and many other dynamic cellular processes.

We describe a correlative microscopy method that combines high-speed 3D live-cell fluorescent light microscopy and high-resolution cryo-electron tomography. We demonstrate the capability of the correlative method by imaging dynamic, small HIV-1 particles interacting with host HeLa cells.

Cryo-electron tomography (cryoET) allows 3D visualization of cellular structures at molecular resolution in a close-to-physiological state1. However, ...

Improved Method for the Preparation of a Human Cell-based, Contact Model of the Blood-Brain Barrier

The blood-brain barrier (BBB) comprises impermeable but adaptable brain capillaries which tightly control the brain environment. Failure of the BBB has been implied in the etiology of many brain pathologies, creating a need for development of human in vitro BBB models to assist in clinically-relevant research. Among the numerous BBB models thus far described, a static (without flow), contact BBB model, where astrocytes and brain endothelial cells (BECs) are cocultured on the opposite sides of a porous membrane, emerged as a simplified yet authentic system to simulate the BBB with high throughput screening capacity. Nevertheless the generation of such model presents few technical challenges. Here, we describe a protocol for preparation of a contact human BBB model utilizing a novel combination of primary human BECs and immortalized human astrocytes. Specifically, we detail an innovative method for cell-seeding on inverted inserts as well as specify insert staining techniques and exemplify how we use our model for BBB-related research.

Establishment of human models of the blood-brain barrier (BBB) can benefit research into brain conditions associated with BBB failure. We describe here an improved technique for preparation of a contact BBB model, which permits coculturing of human astrocytes and brain endothelial cells on the opposite sides of a porous membrane.

The blood-brain barrier (BBB) comprises impermeable but adaptable brain capillaries which tightly control the brain environment. Failure of the BBB has ...

Microfluidic Platform for Measuring Neutrophil Chemotaxis from Unprocessed Whole Blood

Neutrophils play an essential role in protection against infections and their numbers in the blood are frequently measured in the clinic. Higher neutrophil counts in the blood are usually an indicator of ongoing infections, while low neutrophil counts are a warning sign for higher risks for infections. To accomplish their functions, neutrophils also have to be able to move effectively from the blood where they spend most of their life, into tissues, where infections occur. Consequently, any defects in the ability of neutrophils to migrate can increase the risks for infections, even when neutrophils are present in appropriate numbers in the blood. However, measuring neutrophil migration ability in the clinic is a challenging task, which is time consuming, requires large volume of blood, and expert knowledge. To address these limitations, we designed a robust microfluidic assays for neutrophil migration, which requires a single droplet of unprocessed blood, circumvents the need for neutrophil separation, and is easy to quantify on a simple microscope. In this assay, neutrophils migrate directly from the blood droplet, through small channels, towards the source of chemoattractant. To prevent the granular flow of red blood cells through the same channels, we implemented mechanical filters with right angle turns that selectively block the advance of red blood cells. We validated the assay by comparing neutrophil migration from blood droplets collected from finger prick and venous blood. We also compared these whole blood (WB) sources with neutrophil migration from samples of purified neutrophils and found consistent speed and directionality between the three sources. This microfluidic platform will enable the study of human neutrophil migration in the clinic and the research setting to help advance our understanding of neutrophil functions in health and disease.

This protocol details an assay designed to measure human neutrophil chemotaxis from one droplet of whole blood with robust reproducibility. This approach circumvents the need for neutrophil separation and requires only a few minutes of assay preparation time. The microfluidic chip enables the repeated measure of neutrophil chemotaxis over time in infants or small mammals, where sample volume is limited.

Neutrophils play an essential role in protection against infections and their numbers in the blood are frequently measured in the clinic. Higher ...

Bead Aggregation Assays for the Characterization of Putative Cell Adhesion Molecules

Cell-cell adhesion is fundamental to multicellular life and is mediated by a diverse array of cell surface proteins. However, the adhesive interactions for many of these proteins are poorly understood. Here we present a simple, rapid method for characterizing the adhesive properties of putative homophilic cell adhesion molecules. Cultured HEK293 cells are transfected with DNA plasmid encoding a secreted, epitope-tagged ectodomain of a cell surface protein. Using functionalized beads specific for the epitope tag, the soluble, secreted fusion protein is captured from the culture medium. The coated beads can then be used directly in bead aggregation assays or in fluorescent bead sorting assays to test for homophilic adhesion. If desired, mutagenesis can then be used to elucidate the specific amino acids or domains required for adhesion. This assay requires only small amounts of expressed protein, does not require the production of stable cell lines, and can be accomplished in 4 days.

Here we present a simple, rapid method for characterizing the intrinsic adhesive properties of putative cell adhesion molecules. The secreted, epitope-tagged ectodomain of a cell adhesion molecule is captured from the culture medium on small, uniform functionalized beads. These beads can then be used immediately in simple bead aggregation assays.

Cell-cell adhesion is fundamental to multicellular life and is mediated by a diverse array of cell surface proteins. However, the adhesive interactions ...

Microfluidic Flow Chambers Using Reconstituted Blood to Model Hemostasis and Platelet Transfusion In Vitro

Blood platelets prepared for transfusion gradually lose hemostatic function during storage. Platelet function can be investigated using a variety of (indirect) in vitro experiments, but none of these is as comprehensive as microfluidic flow chambers. In this protocol, the reconstitution of thrombocytopenic fresh blood with stored blood bank platelets is used to simulate platelet transfusion. Next, the reconstituted sample is perfused in microfluidic flow chambers which mimic hemostasis on exposed subendothelial matrix proteins. Effects of blood donation, transport, component separation, storage and pathogen inactivation can be measured in paired experimental designs. This allows reliable comparison of the impact every manipulation in blood component preparation has on hemostasis. Our results demonstrate the impact of temperature cycling, shear rates, platelet concentration and storage duration on platelet function. In conclusion, this protocol analyzes the function of blood bank platelets and this ultimately aids in optimization of the processing chain including phlebotomy, transport, component preparation, storage and transfusion.

Microfluidic Flow Chambers Using Reconstituted Blood to Model Hemostasis and Platelet Transfusion In Vitro

Platelet transfusion and hemostasis was modeled using blood reconstitution and microfluidic flow chambers to investigate the function of blood banking platelets. The data demonstrate the consequences of platelet storage lesion on hemostasis, in vitro.

Blood platelets prepared for transfusion gradually lose hemostatic function during storage. Platelet function can be investigated using a variety of ...

Fully Automated Centrifugal Microfluidic Device for Ultrasensitive Protein Detection from Whole Blood

Enzyme-linked immunosorbent assay (ELISA) is a promising method to detect small amount of proteins in biological samples. The devices providing a platform for reduced sample volume and assay time as well as full automation are required for potential use in point-of-care-diagnostics. Recently, we have demonstrated ultrasensitive detection of serum proteins, C-reactive protein (CRP) and cardiac troponin I (cTnI), utilizing a lab-on-a-disc composed of TiO2 nanofibrous (NF) mats. It showed a large dynamic range with femto molar (fM) detection sensitivity, from a small volume of whole blood in 30 min. The device consists of several components for blood separation, metering, mixing, and washing that are automated for improved sensitivity from low sample volumes. Here, in the video demonstration, we show the experimental protocols and know-how for the fabrication of NFs as well as the disc, their integration and the operation in the following order: processes for preparing TiO2 NF mat; transfer-printing of TiO2 NF mat onto the disc; surface modification for immune-reactions, disc assembly and operation; on-disc detection and representative results for immunoassay. Use of this device enables multiplexed analysis with minimal consumption of samples and reagents. Given the advantages, the device should find use in a wide variety of applications, and prove beneficial in facilitating the analysis of low abundant proteins.

This protocol demonstrates how to achieve femto molar detection sensitivity of proteins in 10 &#181;L of whole blood within 30 min. This can be achieved by using electrospun nanofibrous mats integrated in a lab-on-a-disc, which offers high surface area as well as effective mixing and washing for enhanced signal-to-noise ratio.

Enzyme-linked immunosorbent assay (ELISA) is a promising method to detect small amount of proteins in biological samples. The devices providing a platform ...

3D Magnetic Stem Cell Aggregation and Bioreactor Maturation for Cartilage Regeneration

Cartilage engineering remains a challenge due to the difficulties in creating an in vitro functional implant similar to the native tissue. An approach recently explored for the development of autologous replacements involves the differentiation of stem cells into chondrocytes. To initiate this chondrogenesis, a degree of compaction of the stem cells is required; hence, we demonstrated the feasibility of magnetically condensing cells, both within thick scaffolds and scaffold-free, using miniaturized magnetic field sources as cell attractors. This magnetic approach was also used to guide aggregate fusion and to build scaffold-free, organized, three-dimensional (3D) tissues several millimeters in size. In addition to having an enhanced size, the tissue formed by magnetic-driven fusion presented a significant increase in the expression of collagen II, and a similar trend was observed for aggrecan expression. As the native cartilage was subjected to forces that influenced its 3D structure, dynamic maturation was also performed. A bioreactor that provides mechanical stimuli was used to culture the magnetically seeded scaffolds over a 21-day period. Bioreactor maturation largely improved chondrogenesis into the cellularized scaffolds; the extracellular matrix obtained under these conditions was rich in collagen II and aggrecan. This work outlines the innovative potential of magnetic condensation of labeled stem cells and dynamic maturation in a bioreactor for improved chondrogenic differentiation, both scaffold-free and within polysaccharide scaffolds.

Chondrogenesis from stem cells requires fine tuning the culture conditions. Here, we present a magnetic approach for condensing cells, an essential step to initiate chondrogenesis. In addition, we show that dynamic maturation in a bioreactor applies mechanical stimulation to the cellular constructs and enhances cartilaginous extracellular matrix production.

Cartilage engineering remains a challenge due to the difficulties in creating an in vitro functional implant similar to the native tissue. An approach ...

Multi-step Variable Height Photolithography for Valved Multilayer Microfluidic Devices

Microfluidic systems have enabled powerful new approaches to high-throughput biochemical and biological analysis. However, there remains a barrier to entry for non-specialists who would benefit greatly from the ability to develop their own microfluidic devices to address research questions. Particularly lacking has been the open dissemination of protocols related to photolithography, a key step in the development of a replica mold for the manufacture of polydimethylsiloxane (PDMS) devices. While the fabrication of single height silicon masters has been explored extensively in literature, fabrication steps for more complicated photolithography features necessary for many interesting device functionalities (such as feature rounding to make valve structures, multi-height single-mold patterning, or high aspect ratio definition) are often not explicitly outlined. 
Here, we provide a complete protocol for making multilayer microfluidic devices with valves and complex multi-height geometries, tunable for any application. These fabrication procedures are presented in the context of a microfluidic hydrogel bead synthesizer and demonstrate the production of droplets containing polyethylene glycol (PEG diacrylate) and a photoinitiator that can be polymerized into solid beads. This protocol and accompanying discussion provide a foundation of design principles and fabrication methods that enables development of a wide variety of microfluidic devices. The details included here should allow non-specialists to design and fabricate novel devices, thereby bringing a host of recently developed technologies to their most exciting applications in biological laboratories.

Multilayer microfluidic devices often involve the fabrication of master molds with complex geometries for functionality. This article presents a complete protocol for multi-step photolithography with valves and variable height features tunable to any application. As a demonstration, we fabricate a microfluidic droplet generator capable of producing hydrogel beads.

Microfluidic systems have enabled powerful new approaches to high-throughput biochemical and biological analysis. However, there remains a barrier to ...

A Microfluidic Flow Chamber Model for Platelet Transfusion and Hemostasis Measures Platelet Deposition and Fibrin Formation in Real-time

Microfluidic models of hemostasis assess platelet function under conditions of hydrodynamic shear, but in the presence of anticoagulants, this analysis is restricted to platelet deposition only. The intricate relationship between Ca2+-dependent coagulation and platelet function requires careful and controlled recalcification of blood prior to analysis. Our setup uses a Y-shaped mixing channel, which supplies concentrated Ca2+/Mg2+ buffer to flowing blood just prior to perfusion, enabling rapid recalcification without sample stasis. A ten-fold difference in flow velocity between both reservoirs minimizes dilution. The recalcified blood is then perfused in a collagen-coated analysis chamber, and differential labeling permits real-time imaging of both platelet and fibrin deposition using fluorescence video microscopy. The system uses only commercially available tools, increasing the chances of standardization. Reconstitution of thrombocytopenic blood with platelets from banked concentrates furthermore models platelet transfusion, proving its use in this research domain. Exemplary data demonstrated that coagulation onset and fibrin deposition were linearly dependent on the platelet concentration, confirming the relationship between primary and secondary hemostasis in our model. In a timeframe of 16 perfusion min, contact activation did not take place, despite recalcification to normal Ca2+ and Mg2+ levels. When coagulation factor XIIa was inhibited by corn trypsin inhibitor, this time frame was even longer, indicating a considerable dynamic range in which the changes in the procoagulant nature of the platelets can be assessed. Co-immobilization of tissue factor with collagen significantly reduced the time to onset of coagulation, but not its rate. The option to study the tissue factor and/or the contact pathway increases the versatility and utility of the assay.

This paper describes an experimental model of hemostasis that simultaneously measures platelet function and coagulation. Platelet and fibrin fluorescence is measured in real-time, and platelet adhesion rate, coagulation rate, and onset of coagulation are determined. The model is used to determine platelet procoagulant properties under flow in concentrates for transfusion.

Microfluidic models of hemostasis assess platelet function under conditions of hydrodynamic shear, but in the presence of anticoagulants, this analysis is ...