We would like to thank Shreya Shah for her proofreading and advice.

1. Doppler phantom preparation setup (Figure 2A)
<ol>
	<li>Connect the peristaltic pump, the blood mimicking fluid reservoir, the pulse dampener and the Doppler flow phantom with the plastic tubes.</li>
	<li>Choose the canal with a 4 mm diameter.</li>
	<li>Program the pump to eject 720 mL/min of fluid for 0.3 s and then to eject 50 mL/min for 0.7 s to respectively mimic the systole and diastole cardiac phases</li>
	<li>Run the pump and gently shake the pipes to expel potential air bubbles. 
	NOTE: The operator can choose a different canal diameter and different pump rate but will have to ensure that the ultrasound sequence is fast enough to acquire the fastest flow velocities. Eq. 3 presented later can help to design the sequence.</li>
</ol>
2. Ultrafast ultrasound scanner setup (Figure 2A)
<ol>
	<li>Connect the ultrafast-enabled research scanner to the host computer with the PCI express link.</li>
	<li>Change the transducer adapter on the ultrasound scanner to match the probe connector, then connect the probe.</li>
	<li>Run Matlab and activate the ultrasound scanner license. 
	NOTE: This section and the following implicitly assume the use of a Verasonics Vantage system.</li>
</ol>
3. Ultrasound sequence programming
<ol>
	<li>Using the examples scripts, design a conventional focused &#8220;B-Mode&#8221; (i.e., echography) sequence that will be used for probe positioning.
	<ol>
		<li>Set the imaging depth to 50 mm.</li>
		<li>Set the focal depth to 35 mm.</li>
	</ol>
	</li>
	<li>Using the examples scripts, design an ultrafast ultrasound sequence.
	<ol>
		<li>Set the imaging depth to 50 mm.</li>
		<li>Program 3 tilted plane-waves at [-3,0,3] degree.</li>
		<li>Set the pulse repetition frequency (PRF) to 12 kHz.</li>
		<li>Use 4 half-cycles for the ultrasound waveform, with a center frequency depending on the probe used. A center frequency of 5.2 MHz is assumed here.</li>
		<li>Set the total duration to 1 s.</li>
	</ol>
	</li>
</ol>
4. Probe positioning and data acquisition
<ol>
	<li>Apply ultrasound gel on the probe&#8217;s lens.</li>
	<li>Place the probe on the phantom and launch the B-Mode ultrasound sequence.</li>
	<li>Locate the canal of interest. The fluid appears darker than the surrounding tissue. Place the probe in longitudinal view.</li>
	<li>Manually maintain the probe in the position of interest.</li>
	<li>End the B-Mode sequence and launch the ultrafast sequence acquisition script.</li>
</ol>
5. Image reconstruction (Figure 2B)
<ol>
	<li>Once the sequence is over, save the raw data (also called Radio-Frequency data, &#8220;RF&#8221;).</li>
	<li>Launch the image reconstruction script using the ultrasound system default software. At the end of the process, the IQ data matrix should be created. 
	NOTE: The ultrasound echoes are recorded on each element of the probe and for each emission/reception, then stored in the RF data matrix. The image reconstruction applied the appropriate delay law to each channel and results in the so-called &#8220;IQ&#8221; (In-Phase/Quadrature) matrix. The complex IQ matrix has three dimensions: two for space (image depth and width) and one for time</li>
</ol>
6. Clutter filtering (Figure 2C)
NOTE: For steps 6-7, see the Matlab script provided in the Supplementary Material.
<ol>
	<li>Reshape the 3D (space x space x time) IQ matrix into a 2D (space x time) Casorati matrix, named IQr.</li>
	<li>Compute the singular value decomposition15 of IQr (Eq. 1). 
	<img alt="Equation 1" src="/files/ftp_upload/61838/61838equ01v3.jpg" /> Eq. 1</li>
	<li>Compute the Spatial Similarity Matrix C using the spatial singular vectors U as described by Baranger et al.18 (II, D), and identify the blood subspace boundaries N.</li>
	<li>Use this cutoff N to filter the IQ data as described in Demene et al.15 (II,C).</li>
</ol>
7. Flow visualization and velocity measurements (Figure 2C)
<ol>
	<li>Compute power Doppler map PD by integrating the envelope of the filtered data IQt along the temporal dimension (Eq. 2). The 3D coordinates z, x and t are respectively the depth, width and temporal dimension, nt and is the number of frames acquired. 
	<img alt="Equation 2" src="/files/ftp_upload/61838/61838equ02v5.jpg" /> Eq. 2</li>
	<li>Display the PD map in logarithm scale. To set the dynamic range, compute the mean PD in a region outside the canal and use this value in dB as the lower bound of the dynamic range. A typical dynamic range is [-30, 0] dB.</li>
	<li>Define a circular region of interest (ROI) on the image, containing 1 to 30 pixels.</li>
	<li>Average the IQf signal over the pixels of that ROI, to obtain a vector <img alt="Equation 3" src="/files/ftp_upload/61838/61838equ03v2.jpg" /> of nt time points.</li>
	<li>Compute and display the Doppler spectrogram of <img alt="Equation 4" src="/files/ftp_upload/61838/61838equ04v2.jpg" />, using the square magnitude of the Short-Time Fourier Transform (STFT).
	<ol>
		<li>Set the STFT window to a 60-samples Hann window.</li>
		<li>Set the STFT overlap to 90% of the window length.</li>
	</ol>
	</li>
	<li>Overlay the center frequency at each time point of the spectrogram.</li>
	<li>Convert the frequency f values into blood axial velocities vz using the Doppler formula (Eq. 3). c0 is the speed of sound in the medium and fTW the center frequency of the transmitted ultrasound waveform (here 5.2 MHz). 
	<img alt="Equation 5" src="/files/ftp_upload/61838/61838equ05v4.jpg" /> Eq. 3</li>
</ol>

<ol>
	<li>Doppler, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Ueber das farbige Licht der Doppelsterne und einiger anderer Gestirne des Himmels. , (2020).</li><li>Bonnefous, O., Pesqu&#233;, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Time+domain+formulation+of+pulse-Doppler+ultrasound+and+blood+velocity+estimation+by+cross+correlation.">Time domain formulation of pulse-Doppler ultrasound and blood velocity estimation by cross correlation.</a> Ultrasonic Imaging. 8 (2), 73-85 (2004).</li><li>Bercoff, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ultrafast+compound+doppler+imaging:+Providing+full+blood+flow+characterization.">Ultrafast compound doppler imaging: Providing full blood flow characterization.</a> IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control. 58 (1), 134-147 (2011).</li><li>Evans, D. H., Jensen, J. A., Nielsen, M. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ultrasonic+colour+Doppler+imaging.">Ultrasonic colour Doppler imaging.</a> Interface Focus. 1 (4), 490-502 (2011).</li><li>Nuffer, Z., Rupasov, A., Bekal, N., Murtha, J., Bhatt, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Spectral+Doppler+ultrasound+of+peripheral+arteries:+a+pictorial+review.">Spectral Doppler ultrasound of peripheral arteries: a pictorial review.</a> Clinical Imaging. 46, 91-97 (2017).</li><li>Jensen, J. A., Nikolov, S. I., Gammelmark, K. L., Pedersen, M. 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No conflict of interest

Several variations are possible around the main frame of this protocol.
Hardware concerns 
If the user supplies its custom host computer, the motherboard and the computer&#8217;s case must have an available PCI express slot. The CPU must also have enough PCIe lanes to handle all the devices.
Probe selection 
The ultrasound probe (also named transducer) is chosen according to the spatial resolution needed and to the geometr...

Ultrasound imaging is one of the most commonly used imaging techniques in clinical practice and research activities. The combination of ultrasound wave emission in the biological tissues followed by the recording of the backscattered echoes allows the reconstruction of anatomical images, the so-called &#8220;B-Mode&#8221;. This method is perfectly adapted for soft tissue imaging, such as biological tissues, which typically permit the penetration of ultrasound over several centimeters, with a propagation speed of &#8776;1540 m/s. Depending on the center frequency of the ultrasound probe, images with a resolution from 30 &#181;m to 1 mm are obtained. Furthermore, it is well known that the motion of an acoustic source, affects the physical characteristics of the associated waves. Particularly, the link between the frequency shifts of a wave relative to the speed of its source is described as the Doppler effect1, whose simplest manifestation is the changing siren&#8217;s pitch of a moving ambulance. Ultrasound imaging has long used this physical effect to observe the moving red blood cells2, and it proposes a variety of imaging modes commonly labelled &#8220;Doppler imaging&#8221;. These modes enable the assessment of blood flows in very different applications and organs, such as brain, heart, kidney or peripheral arteries.
Remarkably, most of the currently available ultrasound systems rely on the same technology, referred to as conventional ultrasound. The underlying principles are the following: an acoustic beam insonifies the field of view and is swept along the ultrasound transducer aperture. For each position of the beam, the echoes are recorded and converted into a line of the final image. By progressively moving the beam along the transducer, the whole field of view can be imaged line-per-line (Figure 1, left panel). This strategy was well adapted to the electrical constraints and computing power prevailing until the beginning of the 21st century. Nonetheless, it has several drawbacks. Among these, the final framerate is limited to a few hundred images per second by the beam scanning process. In terms of blood flow, this relatively low framerate affects the maximum flow velocities that can be detected, which is dictated by the sampling criteria of Shannon-Nyquist3. Moreover, conventional Doppler must deal with a complex tradeoff. In order to assess the blood flow velocity in a particular region of interest (ROI), several echoes coming from that ROI have to be successively recorded. This implies that the ultrasound beam is temporarily maintained in a fixed position. The longer the echo ensemble, the better the velocity estimation will be for that ROI. However, to produce a complete image of the field of view, the beam must scan the medium. Therefore, one can sense the conflict between these two constraints: holding the beam to precisely assess the velocity along one line, or moving the beam to produce an image. The different conventional Doppler modes (i.e., Color Doppler or Pulse Wave Doppler) directly reflect this tradeoff. Typically, the Color Doppler produces a low-fidelity flow map used for localizing the vessels4, and the Pulse Wave Doppler is then used to accurately quantify the flow in a previously identified vessel5.
These two limitations (low framerate and localization/quantification tradeoff) are overcome with very high-framerate emerging techniques. Among these, the synthetic aperture approach6 or the multiline transmit technique can be cited7. In this study, we focus on the so-called Ultrafast ultrasound method. Introduced two decades ago8,9,10, this method also relies on the emission/reception of ultrasounds, but with a radically different pattern. Indeed, instead of using a scanning focused beam, ultrafast imaging uses plane wave or diverging waves, which are able to insonify the field of view with a single emission. Following that single emission, the associated electronics is also able to receive and process the huge number of echoes originating from the whole field of view. At the end, an image can be reconstructed from a single emission/reception pattern11 (Figure 1, right panel). These unfocused emissions can have a low signal to noise ratio (SNR) due to the spread of the acoustical energy. This can be tackled by emitting several titled plane-waves (or diverging waves with different sources) and by adding the resulting images. This method is named &#8220;coherent compounding&#8221;12. Two major consequences arise. Firstly, the framerate only depends on the ultrasound time of flight and can reach typical values from 1 to 10 kHz. Secondly, this ensures the data continuity in both spatial and temporal dimensions, also referred to as spatiotemporal coherence. The conventional localization/quantification tradeoff is thus broken. This combination of a high framerate and spatiotemporal coherence has a tremendous impact on the ability to detect blood flows with ultrasound. As compared to conventional ultrasound, ultrafast ultrasound provides full characterization of the blood flow3. Practically, the user has access to the velocity time course in every pixel of the image, for the whole duration of the acquisition (typically &#8776;1 s), with a timescale given by the framerate (typically, a framerate of 5 kHz for a temporal resolution of 200 &#181;s). This high framerate makes the method suitable for a wide range of application such as fast flow in moving organs like heart chambers13 or myocardium with the coronary micro-perfusion14. Furthermore, it has been shown that its spatiotemporal coherence strongly improves its ability to separate slow blood flow from background moving tissues, therefore increasing the sensitivity to micro-vascular flow15. This capacity gives access to the micro vasculature of the brain in both animals16 and humans17.
Hence, ultrafast ultrasound is well suited to image blood flow in a variety of situations. It is restricted to soft biological tissues and will be strongly affected by the presence of hard interfaces such as bones, or gas cavity such as the lung. The tuning of the physical parameters of the ultrasound sequence allows the study of both slow (down to 1 mm/s11,16) and fast flows (up to several m/s). A tradeoff exists between the spatial resolution and the depth of penetration. Typically, a resolution of 50 &#181;m can be achieved at the cost of a penetration around 5 mm. Conversely, the penetration can be extended to 15-20 cm at the cost of a resolution of 1 mm. It is worth noting that most ultrafast scanners such as the one used in this article only provide 2D images.
Here, we propose a simple protocol to introduce the concept of Ultrafast Doppler imaging, using a programmable research ultrasound scanner and Doppler phantom mimicking a vessel (artery or vein) embedded in biological tissue.

<table>
	<tbody>
		<tr>
			<td>Blood-mimicking fluid</td>
			<td>CIRS Inc, Norfolk, Virginia, USA</td>
			<td>069DTF</td>
			<td></td>
		</tr>
		<tr>
			<td>Doppler flow phantom</td>
			<td>CIRS Inc, Norfolk, Virginia, USA</td>
			<td>ATS523A</td>
			<td></td>
		</tr>
		<tr>
			<td>Matlab</td>
			<td>MathWorks, Natick, Massachusetts, United States</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Peristaltic pump / Doppler flow pump</td>
			<td>CIRS Inc, Norfolk, Virginia, USA</td>
			<td>769</td>
			<td>Include tubings and pulse dampener</td>
		</tr>
		<tr>
			<td>Transducer adpter</td>
			<td>Verasonics, Kirkland, Washington, USA</td>
			<td>UTA 408-GE</td>
			<td></td>
		</tr>
		<tr>
			<td>Ultrafast ultrasound research scanner</td>
			<td>Verasonics, Kirkland, Washington, USA</td>
			<td>Vantage 256</td>
			<td></td>
		</tr>
		<tr>
			<td>Ultrasound probe/transducer</td>
			<td>GE Healthcare</td>
			<td>GE 9L-D</td>
			<td></td>
		</tr>
	</tbody>
</table>

blood flow imaging with ultrafast doppler

The pulsed-Doppler effect is the main technique used in clinical echography to assess blood flow. Applied with conventional focused ultrasound Doppler modes, it has several limits. Firstly, a finely tuned signal filtering operation is needed to distinguish blood flows from surrounding moving tissues. Secondly, the operator must choose between localizing the blood flows or quantifying them. In the last two decades, ultrasound imaging has undergone a paradigm shift with the emergence of ultrafast ultrasound using unfocused waves. In addition to a hundredfold increase in framerate (up to 10000 Hz), this new technique also breaks the conventional quantification/localization trade-off, offering a complete blood flow mapping of the field of view and a simultaneous access to fine velocities measurements at the single-pixel level (down to 50 &#181;m). This data continuity in both spatial and temporal dimensions strongly improves the tissue/blood filtering process, which results in an increase sensitivity to small blood flow velocities (down to 1 mm/s). In this method paper, we aim to introduce the concept of ultrafast Doppler as well as its main parameters. Firstly, we summarize the physical principles of unfocused wave imaging. Then, we present the Doppler signal processing main steps. Particularly, we explain the practical implementation of the critical tissue/blood flow separation algorithms and on the extraction of velocities from these filtered data. This theoretical description is supplemented by in vitro experiences. A tissue phantom embedding a canal with flowing blood-mimicking fluid is imaged with a research programmable ultrasound system. A blood flow image is obtained and the flow characteristics are displayed for several pixels in the canal. Finally, a review of in vivo applications is proposed, showing examples in several organs such as carotids, kidney, thyroid, brain and heart.

The quality of the acquisition and the post-processing is firstly assessed by visual inspection. The shape of the canal must be clearly visible in the power Doppler image, and the tissue area must appear dark. If the power Doppler signal is not restricted to the canal, it can mean that either the clutter filter step went wrong (SVD threshold is too low), or the probe experienced a strong movement during the acquisition.
After visual inspection, the study of the spectrogram inside the canal can...

Watch this Scientific Journal Video about Blood Flow Imaging with Ultrafast Doppler at JoVE.com

Blood Flow Imaging with Ultrafast Doppler

This protocol shows how to apply ultrafast ultrasound Doppler imaging to quantify blood flows. After a 1 s long acquisition, the experimenter has access to a movie of the full field of view with axial velocity values for each pixel every &#8776;0.3 ms (depending on the ultrasound time of flight).

The pulsed-Doppler effect is the main technique used in clinical echography to assess blood flow. Applied with conventional focused ultrasound Doppler ...

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7.3K Views.  The Hospital for Sick Children, PGCRL Research Institute. This protocol shows how to apply ultrafast ultrasound Doppler imaging to quantify blood flows. After a 1 s long acquisition, the experimenter has access to a movie of the full field of view with axial velocity values for each pixel every ≈0.3 ms (depending on the ultrasound time of flight).

Video: Blood Flow Imaging with Ultrafast Doppler

Analyzing Cellular Internalization of Nanoparticles and Bacteria by Multi-spectral Imaging Flow Cytometry

Nanoparticulate systems have emerged as valuable tools in vaccine delivery through their ability to efficiently deliver cargo, including proteins, to antigen presenting cells1-5. Internalization of nanoparticles (NP) by antigen presenting cells is a critical step in generating an effective immune response to the encapsulated antigen. To determine how changes in nanoparticle formulation impact function, we sought to develop a high throughput, quantitative experimental protocol that was compatible with detecting internalized nanoparticles as well as bacteria. To date, two independent techniques, microscopy and flow cytometry, have been the methods used to study the phagocytosis of nanoparticles. The high throughput nature of flow cytometry generates robust statistical data. However, due to low resolution, it fails to accurately quantify internalized versus cell bound nanoparticles. Microscopy generates images with high spatial resolution; however, it is time consuming and involves small sample sizes6-8. Multi-spectral imaging flow cytometry (MIFC) is a new technology that incorporates aspects of both microscopy and flow cytometry that performs multi-color spectral fluorescence and bright field imaging simultaneously through a laminar core. This capability provides an accurate analysis of fluorescent signal intensities and spatial relationships between different structures and cellular features at high speed.
	Herein, we describe a method utilizing MIFC to characterize the cell populations that have internalized polyanhydride nanoparticles or Salmonella enterica serovar Typhimurium. We also describe the preparation of nanoparticle suspensions, cell labeling, acquisition on an ImageStreamX system and analysis of the data using the IDEAS application. We also demonstrate the application of a technique that can be used to differentiate the internalization pathways for nanoparticles and bacteria by using cytochalasin-D as an inhibitor of actin-mediated phagocytosis.

In this article, we describe a method utilizing multi-spectral imaging flow cytometry to quantify the internalization of polyanhydride nanoparticles or bacteria by RAW 264.7 cells.

Nanoparticulate  systems have emerged as valuable tools in vaccine delivery through their  ability to efficiently deliver cargo, including proteins, to ...

Wide-field Fluorescent Microscopy and Fluorescent Imaging Flow Cytometry on a Cell-phone

Fluorescent microscopy and flow cytometry are widely used tools in biomedical research and clinical diagnosis. However these devices are in general relatively bulky and costly, making them less effective in the resource limited settings. To potentially address these limitations, we have recently demonstrated the integration of wide-field fluorescent microscopy and imaging flow cytometry tools on cell-phones using compact, light-weight, and cost-effective opto-fluidic attachments. In our flow cytometry design, fluorescently labeled cells are flushed through a microfluidic channel that is positioned above the existing cell-phone camera unit. Battery powered light-emitting diodes (LEDs) are butt-coupled to the side of this microfluidic chip, which effectively acts as a multi-mode slab waveguide, where the excitation light is guided to uniformly excite the fluorescent targets. The cell-phone camera records a time lapse movie of the fluorescent cells flowing through the microfluidic channel, where the digital frames of this movie are processed to count the number of the labeled cells within the target solution of interest. Using a similar opto-fluidic design, we can also image these fluorescently labeled cells in static mode by e.g. sandwiching the fluorescent particles between two glass slides and capturing their fluorescent images using the cell-phone camera, which can achieve a spatial resolution of e.g. ~ 10 &mu;m over a very large field-of-view of ~ 81 mm2. This cell-phone based fluorescent imaging flow cytometry and microscopy platform might be useful especially in resource limited settings, for e.g. counting of CD4+ T cells toward monitoring of HIV+ patients or for detection of water-borne parasites in drinking water.

We review our recent results on the integration of fluorescent microscopy and imaging flow cytometry tools on a cell-phone using compact and cost-effective opto-fluidic attachments. These cell-phone based micro-analysis devices might be useful for cytometric analysis, such as performing various cell counting tasks as well as for high-throughput screening of e.g., water samples in resource limited settings.

Fluorescent microscopy and flow cytometry are widely used tools in biomedical research and clinical diagnosis. However these devices are in general ...

Localization and Relative Quantification of Carbon Nanotubes in Cells with Multispectral Imaging Flow Cytometry

Carbon-based nanomaterials, like carbon nanotubes (CNTs), belong to this type of nanoparticles which are very difficult to discriminate from carbon-rich cell structures and de facto there is still no quantitative method to assess their distribution at cell and tissue levels. What we propose here is an innovative method allowing the detection and quantification of CNTs in cells using a multispectral imaging flow cytometer (ImageStream, Amnis). This newly developed device integrates both a high-throughput of cells and high resolution imaging, providing thus images for each cell directly in flow and therefore statistically relevant image analysis. Each cell image is acquired on bright-field (BF), dark-field (DF), and fluorescent channels, giving access respectively to the level and the distribution of light absorption, light scattered and fluorescence for each cell. The analysis consists then in a pixel-by-pixel comparison of each image, of the 7,000-10,000 cells acquired for each condition of the experiment. Localization and quantification of CNTs is made possible thanks to some particular intrinsic properties of CNTs: strong light absorbance and scattering; indeed CNTs appear as strongly absorbed dark spots on BF and bright spots on DF with a precise colocalization.
This methodology could have a considerable impact on studies about interactions between nanomaterials and cells given that this protocol is applicable for a large range of nanomaterials, insofar as they are capable of absorbing (and/or scattering) strongly enough the light.

In this study, the main purpose was to monitor the cellular uptake and eventual exocytosis of carbon nanotubes (CNTs). From this perspective, we proposed here a unique method using multispectral imaging flow cytometry allowing a quantification and localization of CNTs in a statistically relevant number of cells.

Carbon-based nanomaterials, like carbon nanotubes (CNTs), belong to this type of nanoparticles which are very difficult to discriminate from carbon-rich ...

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 ...

Sensitive Detection of Proteopathic Seeding Activity with FRET Flow Cytometry

Increasing evidence supports transcellular propagation of toxic protein aggregates, or proteopathic seeds, as a mechanism for the initiation and progression of pathology in several neurodegenerative diseases, including Alzheimer's disease and the related tauopathies. The potentially critical role of tau seeds in disease progression strongly supports the need for a sensitive assay that readily detects seeding activity in biological samples. 
By combining the specificity of fluorescence resonance energy transfer (FRET), the sensitivity of flow cytometry, and the stability of a monoclonal cell line, an ultra-sensitive seeding assay has been engineered and is compatible with seed detection from recombinant or biological samples, including human and mouse brain homogenates. The assay employs monoclonal HEK 293T cells that stably express the aggregation-prone repeat domain (RD) of tau harboring the disease-associated P301S mutation fused to either CFP or YFP, which produce a FRET signal upon protein aggregation. The uptake of proteopathic tau seeds (but not other proteins) into the biosensor cells stimulates aggregation of RD-CFP and RD-YFP, and flow cytometry sensitively and quantitatively monitors this aggregation-induced FRET. The assay detects femtomolar concentrations (monomer equivalent) of recombinant tau seeds, has a dynamic range spanning three orders of magnitude, and is compatible with brain homogenates from tauopathy transgenic mice and human tauopathy subjects. With slight modifications, the assay can also detect seeding activity of other proteopathic seeds, such as &#945;-synuclein, and is also compatible with primary neuronal cultures. The ease, sensitivity, and broad applicability of FRET flow cytometry makes it useful to study a wide range of protein aggregation disorders.

Cell-to-cell transfer of protein aggregates, or proteopathic seeds, may underlie the progression of pathology in neurodegenerative diseases. Here, a novel FRET flow cytometry assay is described that enables specific and sensitive detection of seeding activity from recombinant or biological samples.

Increasing evidence supports transcellular propagation of toxic protein aggregates, or proteopathic seeds, as a mechanism for the initiation and ...

In Vitro Model of Physiological and Pathological Blood Flow with Application to Investigations of Vascular Cell Remodeling

Vascular disease is a common cause of death within the United States. Herein, we present a method to examine the contribution of flow dynamics towards vascular disease pathologies. Unhealthy arteries often present with wall stiffening, scarring, or partial stenosis which may all affect fluid flow rates, and the magnitude of pulsatile flow, or pulsatility index. Replication of various flow conditions is the result of tuning a flow pressure damping chamber downstream of a blood pump. Introduction of air within a closed flow system allows for a compressible medium to absorb pulsatile pressure from the pump, and therefore vary the pulsatility index. The method described herein is simply reproduced, with highly controllable input, and easily measurable results. Some limitations are recreation of the complex physiological pulse waveform, which is only approximated by the system. Endothelial cells, smooth muscle cells, and fibroblasts are affected by the blood flow through the artery. The dynamic component of blood flow is determined by the cardiac output and arterial wall compliance. Vascular cell mechano-transduction of flow dynamics may trigger cytokine release and cross-talk between cell types within the artery. Co-culture of vascular cells is a more accurate picture reflecting cell-cell interaction on the blood vessel wall and vascular response to mechanical signaling. Contribution of flow dynamics, including the cell response to the dynamic and mean (or steady) components of flow, is therefore an important metric in determining disease pathology and treatment efficacy. Through introducing an in vitro co-culture model and pressure damping downstream of blood pump which produces simulated cardiac output, various arterial disease pathologies may be investigated.

In Vitro Model of Physiological and Pathological Blood Flow with Application to Investigations of Vascular Cell Remodeling

This protocol replicates physiological or pathological blood flow in vitro to aid in determining cell response in disease pathologies. By introducing a pressure damping chamber downstream of a blood pump, blood flow across the vasculature can be recapitulated and imposed on a monolayer of vascular endothelium or a mimetic co-culture.

Vascular disease is a common cause of death within the United States. Herein, we present a method to examine the contribution of flow dynamics towards ...

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 ...

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 ...

Conducting Multiple Imaging Modes with One Fluorescence Microscope

Fluorescence microscopy is a powerful tool to detect biological molecules in situ and monitor their dynamics and interactions in real-time. In addition to conventional epi-fluorescence microscopy, various imaging techniques have been developed to achieve specific experimental goals. Some of the widely used techniques include single-molecule fluorescence resonance energy transfer (smFRET), which can report conformational changes and molecular interactions with angstrom resolution, and single-molecule detection-based super-resolution (SR) imaging, which can enhance the spatial resolution approximately ten&#160;to twentyfold compared to diffraction-limited microscopy. Here we present a customer-designed integrated system, which merges multiple imaging methods in one microscope, including conventional epi-fluorescent imaging, single-molecule detection-based SR imaging, and multi-color single-molecule detection, including smFRET imaging. Different imaging methods can be achieved easily and reproducibly by switching optical elements. This set-up is easy to adopt by any research laboratory in biological sciences with a need for routine and diverse imaging experiments at a reduced cost and space relative to building separate microscopes for individual purposes.

Here we present a practical guide of building an integrated microscopy system, which merges conventional epi-fluorescent imaging, single-molecule detection-based super-resolution imaging, and multi-color single-molecule detection, including single-molecule fluorescence resonance energy transfer imaging, into one set-up in a cost-efficient way.

Fluorescence microscopy is a powerful tool to detect biological molecules in situ and monitor their dynamics and interactions in real-time. In addition to ...

Characterizing Single-Molecule Conformational Changes Under Shear Flow with Fluorescence Microscopy

Single-molecule behavior under mechanical perturbation has been characterized widely to understand many biological processes. However, methods such as atomic force microscopy have limited temporal resolution, while F&#246;rster resonance energy transfer (FRET) only allow conformations to be inferred. Fluorescence microscopy, on the other hand, allows real-time in situ visualization of single molecules in various flow conditions. Our protocol describes the steps to capture conformational changes of single biomolecules under different shear flow environments using fluorescence microscopy. The shear flow is created inside microfluidic channels and controlled by a syringe pump. As demonstrations of the method, von Willebrand factor (VWF) and lambda DNA are labeled with biotin and fluorophore and then immobilized on the channel surface. Their conformations are continuously monitored under variable shear flow using total internal reflection (TIRF) and confocal fluorescence microscopy. The reversible unraveling dynamics of VWF are useful for understanding how its function is regulated in human blood, while the conformation of lambda DNA offers insights into the biophysics of macromolecules. The protocol can also be widely applied to study the behavior of polymers, especially biopolymers, in varying flow conditions and to investigate the rheology of complex fluids.

We present a protocol for immobilizing single macromolecules in microfluidic devices and quantifying changes in their conformations under shear flow. This protocol is useful for characterizing the biomechanical and functional properties of biomolecules such as proteins and DNA in a flow environment.

Single-molecule behavior under mechanical perturbation has been characterized widely to understand many biological processes. However, methods such as ...