Name: spatial temporal analysis of fieldwise flow in microvasculature
Uploaded: 2019-11-18T14:00:00
Description: Watch this Scientific Journal Video about Spatial Temporal Analysis of Fieldwise Flow in Microvasculature at JoVE.com

Studies presented here were supported by funding from the National Institutes of Health (NIH U01 GM111243 and NIH NIDDK P30 DK079312). Intravital microscopy studies were conducted at the Indiana Center for Biological Micros&#173;copy. We thank Dr. Malgorzata Kamocka for technical assistance with microscopy.

All animal experiments were approved and conducted according to the Institutional Animal Care and Use Committee guidelines of Indiana University, and adhered to the NRC guide for the care and use of animals.
1. Surgical Preparation for Intravital Microscopy
NOTE: This is not a survival surgery. Once section 1 &#34;Surgical preparation for intravital microscopy&#8221; is begun, work cannot be paused until the completion of section 2 &#34;Intravital mic...

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There are multiple critical steps in this protocol. First, minimization of motion during intravital imaging of the liver is essential for generating movies that are usable for capillary flow analysis using STAFF. Due to the proximity of the diaphragm, short periods of respiration-induced motion occur, with the secured liver returning to its initial position after each breath. Securing the surgically exposed liver against the coverslip-bottomed dish using gauze, then imaging from below using an inverted microscope serves ...

The microvasculature plays a critical role in physiology, ensuring effective perfusion of tissues under changing conditions. Microvascular dysfunction is associated with myriad conditions including long-term cardiovascular morbidity and mortality, development of dementia, and disease of both liver and kidney and thus is a key factor of interest in a broad range of biomedical investigations1,2,3,4,5. While multiple techniques have been used to evaluate tissue perfusion, only intravital microscopy enables data collection at the temporal and spatial resolution necessary to characterize blood flow at the level of individual capillaries.
Microvascular flow can be visualized in fluorescence microscopy either by the movement of fluorescent microspheres or by the movement of red blood cells against the background of membrane-impermeant fluorescent markers (e.g., fluorescently-labeled dextran or albumin)6,7. Microvascular flow can be imaged in superficial cell layers using widefield microscopy, or at depth using either confocal or multiphoton microscopy. However, capillary flow rates are such that the passage of red blood cells cannot generally be captured at speeds less than 60 frames/s. Since most laser scanning confocal and multiphoton microscopes require 1&#8211;5 s to scan a full image field, this speed can generally be accomplished only by limiting the field of view, sometimes to a single scan line8. The process of limiting measurements to selected capillary segments (1) has the potential to introduce selection bias and (2) makes it impossible to capture spatial and temporal heterogeneity in the rates of capillary blood flow. In contrast, images of capillary networks can be collected at speeds exceeding 100 fps using widefield digital microscopes equipped with scientific complementary metal oxide semiconductor (sCMOS) cameras9,10. These inexpensive systems, common in typical biomedical laboratories make it possible to image microvascular flow across entire two-dimensional networks, essentially continuously. The problem then becomes one of finding an analysis approach that is capable of extracting meaningful quantitative data from the massive and complex image datasets generated by high-speed video microscopy.
To enable analysis of full-field flow data we have developed STAFF, novel image analysis software that can continuously measure microvascular flow throughout entire microscope fields of image series collected at high speed11. The approach is compatible with a variety of different experimental systems and imaging modalities and the STAFF image analysis software is implemented as a macro toolset for the FIJI implementation of ImageJ12. The underlying principle used here to visualize microvascular flow is that first, some contrast must be provided to be able to image the red blood cells within capillaries. In our studies, contrast is provided by a bulk fluorescent probe that is excluded by the red blood cells. The velocity of flow can then be quantified from the displacement of the red blood cells that appear as a negative stain within the fluorescently labeled plasma in images collected at high speed from a living animal8. We then use STAFF to make plots of distance along each capillary segment over multiple intervals of time called kymographs, then detect the slopes present in the kymographs13, and from those slopes calculate the rates of microvascular flow. The approach can be applied to images collected from any capillary bed that can be accessed for imaging. Here we describe the application of IVM and STAFF to studies of blood flow in the liver.

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			<td height="21" style="height:21px;width:259px;">#5 forceps</td>
			<td style="width:211px;">Fine Science Tools</td>
			<td style="width:120px;">11251-20</td>
			<td style="width:431px;">Dumont #5 Inox Forceps</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">C57BL/6 mice</td>
			<td style="width:211px;">Jackson Labs</td>
			<td style="width:120px;"></td>
			<td>male 9-12 weeks old</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">Cannula</td>
			<td style="width:211px;">Instech</td>
			<td style="width:120px;">BTPE-10</td>
			<td>Polyethylene Tubing .011x.024in</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">CMOS camera</td>
			<td style="width:211px;">Hamamatsu</td>
			<td style="width:120px;">C11440-42U30</td>
			<td>4.0LT Scientific CMOS</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">Coverslip-bottomed dish</td>
			<td style="width:211px;">Electron Microscopy Sciences</td>
			<td style="width:120px;"></td>
			<td>WillCo Dish glass bottom GWST5040</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">Dissecting scissors</td>
			<td style="width:211px;">Fine Science Tools</td>
			<td style="width:120px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">Fiji ImageJ Image analysis software</td>
			<td style="width:211px;"></td>
			<td style="width:120px;"></td>
			<td>https://fiji.sc/ ; https://downloads.imagej.net/fiji/Life-Line/fiji-win64-20170530.zip</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">Fluorescein dextran</td>
			<td style="width:211px;">Thermo Fisher, Invitrogen</td>
			<td style="width:120px;">D1822</td>
			<td>Dextran, Fluorescein, 70,000 MW, Anionic, Lysine Fixable</td>
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		<tr height="21">
			<td height="21" style="height:21px;width:259px;">Gauze sponge</td>
			<td style="width:211px;">Fisher</td>
			<td>22-415-504</td>
			<td>2x2 inch Dukal sterile gauze sponges</td>
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		<tr height="21">
			<td height="21" style="height:21px;width:259px;">Heating pad</td>
			<td style="width:211px;">Reptitherm</td>
			<td style="width:120px;">RH-4</td>
			<td>between mouse and stage</td>
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		<tr height="21">
			<td height="21" style="height:21px;width:259px;">Heating pad</td>
			<td style="width:211px;">Sunbeam</td>
			<td>000732-500-000U</td>
			<td>over mouse</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">Inverted epifluorescence microscope</td>
			<td style="width:211px;">Nikon</td>
			<td style="width:120px;"></td>
			<td>Nikon TiE inverted microscope</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">Isis Rodent electric shaver</td>
			<td style="width:211px;">Braun Aesculap</td>
			<td style="width:120px;">GT420</td>
			<td></td>
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		<tr height="21">
			<td height="21" style="height:21px;width:259px;">Isofluorane</td>
			<td style="width:211px;">Abbott GmbH</td>
			<td style="width:120px;">PZN4831850</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">Luer stub adapter</td>
			<td style="width:211px;">Fisher</td>
			<td>14-826-19E</td>
			<td>Catheter adapter</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">Micro scissors</td>
			<td>Castro Viejo</td>
			<td style="width:120px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">Microscope objective</td>
			<td style="width:211px;">Nikon</td>
			<td style="width:120px;"></td>
			<td>Plan Fluor 20x, NA 0.75 water immersion</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">Needle</td>
			<td style="width:211px;">Fisher</td>
			<td></td>
			<td>30 Ga.x1/2&#34;</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">Needle holder</td>
			<td style="width:211px;">Olsen-Hegar</td>
			<td></td>
			<td></td>
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		<tr height="21">
			<td height="21" style="height:21px;width:259px;">Objective heater</td>
			<td style="width:211px;">BioScience Tools</td>
			<td style="width:120px;">MTC-HLS-025</td>
			<td>Temperature controller with objective heater</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">Rectal thermometer</td>
			<td style="width:211px;">Braintree Scientific, INC</td>
			<td style="width:120px;">TH-5A</td>
			<td>Mouse Body Temperature monitoring</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">STAFF macros</td>
			<td style="width:211px;"></td>
			<td style="width:120px;"></td>
			<td>https://github.com/icbm-iupui/STAFF</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">Suture string</td>
			<td>Harvard Bioscience</td>
			<td style="width:120px;">723288</td>
			<td>silk black suture, 6-0, spool</td>
		</tr>
	</tbody>
</table>

spatial temporal analysis of fieldwise flow in microvasculature

Changes in blood flow velocity and distribution are vital in maintaining tissue and organ perfusion in response to varying cellular needs. Further, appearance of defects in microcirculation can be a primary indicator in the development of multiple pathologies. Advances in optical imaging have made intravital microscopy (IVM) a practical approach, permitting imaging at the cellular and subcellular level in live animals at high-speed over time. Yet, despite the importance of maintaining adequate tissue perfusion, spatial and temporal variability in capillary flow is seldom documented. In the standard approach, a small number of capillary segments are chosen for imaging over a limited time. To comprehensively quantify capillary flow in an unbiased way we developed Spatial Temporal Analysis of Fieldwise Flow (STAFF), a macro for FIJI open-source&#160;image analysis software. Using high-speed image sequences of full fields of blood flow within capillaries, STAFF produces&#160;images that represent motion over time called kymographs for every time interval for every vascular segment. From the kymographs STAFF calculates velocities from the distance that red blood cells move over time, and outputs the velocity data as a sequence of color-coded spatial maps for visualization and tabular output for quantitative analyses. In normal mouse livers, STAFF analyses quantified profound differences in flow velocity between pericentral and periportal regions within lobules. Even more unexpected are the differences in flow velocity seen between sinusoids&#160;that are side by side and fluctuations seen within individual vascular segments over seconds. STAFF is a powerful new tool capable of providing novel insights by enabling measurement of the complex spatiotemporal dynamics of capillary flow.

STAFF analysis generates a complete census of microvascular velocities across entire microscope fields over periods of time extending from seconds to minutes. Representative results are presented in Figure 1, Figure 2, Figure 3, and Figure 4. Figure 1 shows an example of a time series of the microvascular network in the liver of a mouse, the generation of the skeletonized i...

Watch this Scientific Journal Video about Spatial Temporal Analysis of Fieldwise Flow in Microvasculature at JoVE.com

Spatial Temporal Analysis of Fieldwise Flow in Microvasculature

To quantify microvascular flow from high speed capillary flow image sequences, we developed STAFF (Spatial Temporal Analysis of Fieldwise Flow) software. Across the full image field and over time, STAFF evaluates flow velocities and generates a sequence of color-coded spatial maps for visualization and tabular output for quantitative analyses.

Changes in blood flow velocity and distribution are vital in maintaining tissue and organ perfusion in response to varying cellular needs. Further, ...

Since microvascular flow varies between capillaries and changes over a time course of seconds, a method for the continuous quantification of flow across entire fields is needed. Staff enables a nearly continuous measurement of flow velocities across entire microscope fields, within hours, that would otherwise take months to obtain manually. Although these procedures are straightforward, visual demonstration will significantly help new users navigate staff for the first time.To use TrakEM2 to define the vascular network, first select File, New, and TrakEM2 Blank to setup a new blank TrakEM2 project, and select the new folder containing the single image from the movie as the project folder. The TrakEM2 windows will open. Right-click in the main work area and select Import and Import Image.Navigate to the single saved image and select the image. Right-click in the main work area again and select Display and Auto Resize Canvas/LayerSet. Then, left-click in the main work window.The image will fill the work area. To select the areas in the image that contain the vascular network, in the smaller TrakEM2 window, right-click on template Anything, and select Add New Child and Area List. In the smaller TrakEM2 window, drag template Anything onto Project Objects, untitled project.Then drag template Anything, area list, onto Project Objects, untitled projects, Anything. Under Project Objects, untitled project, the Anything area list will now be present. In the main TrakEM2 window under the Z Space tab, a bar labeled Area List will have been created.Click to select the list. In the main TrakEM2 window, select the paintbrush tool and click Shift while rolling the mouse wheel to select a paintbrush size that is smaller than the diameter of the vasculature of interest. Press Control S to save the project.Using the paintbrush tool, paint the vascular network, excluding any out of focus regions. When the labeling is complete, right-click in the main TrakEM2 window and select Export and Area Lists as Labels. In the pop-up window, select Scale, 100%and export all Area List.Close the TrakEM2 windows and select Yes to save the project. The image of Area List will open and may appear as a blank, black image. In the the main Fiji menu, select Image, Adjust, and Brightness/Contrast.In the Brightness and Contrast window, click Auto and the Area List will become visible. In the main Fiji menu, select Image, Lookup Tables, and Invert Lookup Table. Save this image of black labels on white background as a t-i-f file and close the image.Open the Labels file in Fiji and select Plugins, Skeleton, and Skeleton Eyes. Then, save the Skeleton Eyes image as a t-i-f file. To create a new staff project, select Plugins, Macros, and Open/Create Project and follow the prompts to create or update a configuration file.From the Open/Create project menu, navigate to and select the project directory Input File folder and the Input Movie and Skeleton files. Input the values for the Maximum Measured Speed, the Maximum Speed Mapped, the Minimum Segment Length, the Pixel Size, and the Frame Rate. Check the Flicker correction box if the images have periodic background intensity flicker and click OK.Adjust the parameters for the best visualization of the data.Set the Maximum Speed Mapped to include about 95 percent of the data, so that the data is mapped across the full range of the color scale. To analyze the skeleton, select Plugins, Macros, and Analyze Skeleton. The skeleton file will open and the Region of Interest manager will open and run.In the Region of Interest manager, click Show All and Label and click OK.To select the time intervals, select Plugins, Macros, and Edit Time Intervals and wait for the macro to generate a kymograph from a single segment over the total time for the movie. Use the Control plus and minus keys to increase the size of the kymograph as needed and use the Rectangle selection tool to draw a rectangle around each time interval. Press the T key or click the Add button to record a Time Interval selection and repeat the selection for as many time intervals as desired.To evaluate the parameter choices, select three to four time intervals and complete the analysis for just those intervals. Click OK when the time interval selection has been completed. A pop-up window will appear when the selected intervals have been saved in the project folder.Click OK.To analyze the flow, select Plugins, Macros, and Analyze Flow. The Analyze Flow Parameters dialogue box will open and display the values entered in the Open/Create Project step. Edit these values if necessary and click OK.The Output File Names dialogue box will open and display the names entered in the Open/Create Project step.Edit these names as necessary and click OK to begin the Flow Analysis. When a dialogue box appears indicating that the flow has been analyzed, click OK to store the analysis results in CSV Spreadsheet files. To produce spatial maps, select Plugins, Macros, and Produce Spatial Map.The Spatial Map Parameters window will open displaying the values entered in the Open/Create Project step. Edit these values as necessary and click OK.A temporal sequence of Spatial Maps of Flow Velocities will be generated with each color indicating a flow speed. Scroll through the generated stack of one image per interval to visualize the spatial and temporal variations in flow and save the stack as an a-v-i file to share the file as a movie.Staff Analysis generates the complete census of the microvascular velocities across entire microscope fields, over periods of time extending from seconds to minutes. For example, using a single image in this time series of the microvascular network in the liver of a mouse, the generated skeletonized image was used to define the axis of the microvascular flow, allowing the Staff generated map of individual vascular segments to be identified for subsequent flow quantification. From the individual vascular segments generated from the skeletonized image, kymographs can be generated representing the intensity along each line segment over time.The Skeleton and User Supply time intervals can be used to break the kymograph of each segment into individual segment time intervals. Staff then identifies the predominant angle in the kymograph from each segment time interval and provides the calculated velocity measurements as CSV data files. Staff CSV output can be used to analyze the overall velocity distribution to enable plotting of the velocity in the individual vascular segments over time.And can be visualized as stacks of color-coded velocity map images. Note that the results that came from Staff depend upon the quality of the image series, with respect to the sample stability, frame rate, resolution, and signal-to-noise ratio. The Staff Velocity Map Outputs allow an intuitive exploration of spatial flow patterning while Staff CSV outputs enable the statistical analysis of flow velocities, both within and between treatment groups.

spatial-temporal-analysis-of-fieldwise-flow-in-microvasculature

Research

JoVE Journal

Bioengineering

Spatio-Temporal Manipulation of Small GTPase Activity at Subcellular Level and on Timescale of Seconds in Living Cells

Dynamic regulation of the Rho family of small guanosine triphosphatases (GTPases) with great spatiotemporal precision is essential for various cellular functions and events1, 2. Their spatiotemporally dynamic nature has been revealed by visualization of their activity and localization in real time3. In order to gain deeper understanding of their roles in diverse cellular functions at the molecular level, the next step should be perturbation of protein activities at a precise subcellular location and timing. 
To achieve this goal, we have developed a method for light-induced, spatio-temporally controlled activation of small GTPases by combining two techniques: (1) rapamycin-induced FKBP-FRB heterodimerization and (2) a photo-caging method of rapamycin. With the use of rapamycin-mediated FKBP-FRB heterodimerization, we have developed a method for rapidly inducible activation or inactivation of small GTPases including Rac4, Cdc424, RhoA4 and Ras5, in which rapamycin induces translocation of FKBP-fused GTPases, or their activators, to the plasma membrane where FRB is anchored. For coupling with this heterodimerization system, we have also developed a photo-caging system of rapamycin analogs. A photo-caged compound is a small molecule whose activity is suppressed with a photocleavable protecting group known as a caging group. To suppress heterodimerization activity completely, we designed a caged rapamycin that is tethered to a macromolecule such that the resulting large complex cannot cross the plasma membrane, leading to virtually no background activity as a chemical dimerizer inside cells6. Figure 1 illustrates a scheme of our system. With the combination of these two systems, we locally recruited a Rac activator to the plasma membrane on a timescale of seconds and achieved light-induced Rac activation at the subcellular level6.

A method for spatio-temporal control of small GTPase activity by light is described. This method is based on rapamycin-induced FKBP-FRB heterodimerization and photo-caging systems. Optimization of light-irradiation enables the spatio-temporally controlled activation of small GTPases at the subcellular level.

Dynamic regulation of the Rho family of small guanosine triphosphatases (GTPases) with great spatiotemporal precision is essential for various cellular ...

Evaluation of Polymeric Gene Delivery Nanoparticles by Nanoparticle Tracking Analysis and High-throughput Flow Cytometry

Non-viral gene delivery using polymeric nanoparticles has emerged as an attractive approach for gene therapy to treat genetic diseases1 and as a technology for regenerative medicine2. Unlike viruses, which have significant safety issues, polymeric nanoparticles can be designed to be non-toxic, non-immunogenic, non-mutagenic, easier to synthesize, chemically versatile, capable of carrying larger nucleic acid cargo and biodegradable and/or environmentally responsive. Cationic polymers self-assemble with negatively charged DNA via electrostatic interaction to form complexes on the order of 100 nm that are commonly termed polymeric nanoparticles. Examples of biomaterials used to form nanoscale polycationic gene delivery nanoparticles include polylysine, polyphosphoesters, poly(amidoamines)s and polyethylenimine (PEI), which is a non-degradable off-the-shelf cationic polymer commonly used for nucleic acid delivery1,3 . Poly(beta-amino ester)s (PBAEs) are a newer class of cationic polymers4 that are hydrolytically degradable5,6 and have been shown to be effective at gene delivery to hard-to-transfect cell types such as human retinal endothelial cells (HRECs)7, mouse mammary epithelial cells8, human brain cancer cells9 and macrovascular (human umbilical vein, HUVECs) endothelial cells10.
A new protocol to characterize polymeric nanoparticles utilizing nanoparticle tracking analysis (NTA) is described. In this approach, both the particle size distribution and the distribution of the number of plasmids per particle are obtained11. In addition, a high-throughput 96-well plate transfection assay for rapid screening of the transfection efficacy of polymeric nanoparticles is presented. In this protocol, poly(beta-amino ester)s (PBAEs) are used as model polymers and human retinal endothelial cells (HRECs) are used as model human cells. This protocol can be easily adapted to evaluate any polymeric nanoparticle and any cell type of interest in a multi-well plate format.

A protocol for nanoparticle tracking analysis (NTA) and high-throughput flow cytometry to evaluate polymeric gene delivery nanoparticles is described. NTA is utilized to characterize the nanoparticle particle size distribution and the plasmid per particle distribution. High-throughput flow cytometry enables quantitative transfection efficacy evaluation for a library of gene delivery biomaterials.

Non-viral gene delivery using polymeric nanoparticles has emerged as an attractive approach for gene therapy to treat genetic diseases1 and as a ...

Quantitative and Temporal Control of Oxygen Microenvironment at the Single Islet Level

Simultaneous oxygenation and monitoring of glucose stimulus-secretion coupling factors in a single technique is critical for modeling pathophysiological states of islet hypoxia, especially in transplant environments. Standard hypoxic chamber techniques cannot modulate both stimulations at the same time nor provide real-time monitoring of glucose stimulus-secretion coupling factors. To address these difficulties, we applied a multilayered microfluidic technique to integrate both aqueous and gas phase modulations via a diffusion membrane. This creates a stimulation sandwich around the microscaled islets within the transparent polydimethylsiloxane (PDMS) device, enabling monitoring of the aforementioned coupling factors via fluorescence microscopy. Additionally, the gas input is controlled by a pair of microdispensers, providing quantitative, sub-minute modulations of oxygen between 0-21%. This intermittent hypoxia is applied to investigate a new phenomenon of islet preconditioning. Moreover, armed with multimodal microscopy, we were able to look at detailed calcium and KATP channel dynamics during these hypoxic events. We envision microfluidic hypoxia, especially this simultaneous dual phase technique, as a valuable tool in studying islets as well as many ex vivo tissues.

Microfluidic oxygen control confers more than just convenience and speed over hypoxic chambers for biological experiments. Especially when implemented via diffusion through a membrane, microfluidic oxygen can provide simultaneous liquid and gas phase modulations at the microscale-level. This technique enables dynamic multi-parametric experiments critical for studying islet pathophysiology.

Simultaneous oxygenation and monitoring of glucose stimulus-secretion coupling factors in a single technique is critical for modeling pathophysiological ...

Quantification of Global Diastolic Function by Kinematic Modeling-based Analysis of Transmitral Flow via the Parametrized Diastolic Filling Formalism

Quantitative cardiac function assessment remains a challenge for physiologists and clinicians.&#160;Although historically invasive methods have comprised the only means available, the development of noninvasive imaging modalities (echocardiography, MRI, CT) having high temporal and spatial resolution provide a new window for quantitative diastolic function assessment. Echocardiography is the agreed upon standard for diastolic function assessment, but indexes in current clinical use merely utilize selected features of chamber dimension (M-mode) or blood/tissue motion (Doppler) waveforms without incorporating the physiologic causal determinants of the motion itself.&#160;The recognition that all left ventricles (LV) initiate filling by serving as mechanical suction pumps allows global diastolic function to be assessed based on laws of motion that apply to all chambers. What differentiates one heart from another are the parameters of the equation of motion that governs filling. Accordingly, development of the Parametrized Diastolic Filling (PDF) formalism&#160;has shown that the entire range of clinically observed early transmitral flow (Doppler E-wave) patterns are extremely well fit by the laws of damped oscillatory motion.&#160;This permits analysis of individual E-waves in accordance with a causal mechanism (recoil-initiated suction) that yields three (numerically) unique lumped parameters whose physiologic analogues are chamber stiffness (k), viscoelasticity/relaxation (c), and load (xo).&#160;The recording of transmitral flow (Doppler E-waves) is standard practice in clinical cardiology and, therefore, the echocardiographic recording method is only briefly reviewed. Our focus is on determination of the PDF parameters from routinely recorded E-wave data.&#160;As the highlighted results indicate, once the PDF parameters have been obtained from a suitable number of load varying E-waves, the investigator is free to use the parameters or construct indexes from the parameters (such as stored energy 1/2kxo2, maximum A-V pressure gradient kxo, load independent index of diastolic function, etc.) and select the aspect of physiology or pathophysiology to be quantified.

Accurate, causality-based quantification of global diastolic function has been achieved by kinematic modeling-based analysis of transmitral flow via the Parametrized Diastolic Filling (PDF) formalism. PDF generates unique stiffness, relaxation,&#160;and load parameters and elucidates &#39;new&#39; physiology while providing sensitive and specific indexes of dysfunction.

Quantitative cardiac function assessment remains a challenge for physiologists and clinicians.&#160;Although historically invasive methods have comprised ...

A Label-free Technique for the Spatio-temporal Imaging of Single Cell Secretions

Inter-cellular communication is an integral part of a complex system that helps in maintaining basic cellular activities. As a result, the malfunctioning of such signaling can lead to many disorders. To understand cell-to-cell signaling, it is essential to study the spatial and temporal nature of the secreted molecules from the cell without disturbing the local environment. Various assays have been developed to study protein secretion, however, these methods are typically based on fluorescent probes which disrupt the relevant signaling pathways. To overcome this limitation, a label-free technique is required.
In this paper, we describe the fabrication and application of a label-free localized surface plasmon resonance imaging (LSPRi) technology capable of detecting protein secretions from a single cell. The plasmonic nanostructures are lithographically patterned onto a standard glass coverslip and can be excited using visible light on commercially available light microscopes. Only a small fraction of the coverslip is covered by the nanostructures and hence this technique is well suited for combining common techniques such as fluorescence and bright-field imaging.
A multidisciplinary approach is used in this protocol which incorporates sensor nanofabrication and subsequent biofunctionalization, binding kinetics characterization of ligand and analyte, the integration of the chip and live cells, and the analysis of the measured signal. As a whole, this technology enables a general label-free approach towards mapping cellular secretions and correlating them with the responses of nearby cells.

Inter-cellular communication is critical for controlling various physiological activities within and outside the cell. This paper describes a protocol for measuring the spatio-temporal nature of single cell secretions. To achieve this, a multidisciplinary approach is used which integrates label-free nanoplasmonic sensing with live cell imaging.

Inter-cellular communication is an integral part of a complex system that helps in maintaining basic cellular activities. As a result, the malfunctioning ...

Photoactivated Localization Microscopy with Bimolecular Fluorescence Complementation (BiFC-PALM)

Protein-protein interactions (PPIs) are key molecular events to biology. However, it remains a challenge to visualize PPIs with sufficient resolution and sensitivity in cells because the resolution of conventional light microscopy is diffraction-limited to ~250 nm. By combining bimolecular fluorescence complementation (BiFC) with photoactivated localization microscopy (PALM), PPIs can be visualized in cells with single molecule sensitivity and nanometer spatial resolution. BiFC is a commonly used technique for visualizing PPIs with fluorescence contrast, which involves splitting of a fluorescent protein into two non-fluorescent fragments. PALM is a recent superresolution microscopy technique for imaging biological samples at the nanometer and single molecule scales, which uses phototransformable fluorescent probes such as photoactivatable fluorescent proteins (PA-FPs). BiFC-PALM was demonstrated by splitting PAmCherry1, a PA-FP compatible with PALM, for its monomeric nature, good single molecule brightness, high contrast ratio, and utility for stoichiometry measurements. When split between amino acids 159 and 160, PAmCherry1 can be made into a BiFC probe that reconstitutes efficiently at 37 &#176;C with high specificity to PPIs and low non-specific reconstitution. Ras-Raf interaction is used as an example to show how BiFC-PALM helps to probe interactions at the nanometer scale and with single molecule resolution. Their diffusion can also be tracked in live cells using single molecule tracking (smt-) PALM. In this protocol, factors to consider when designing the fusion proteins for BiFC-PALM are discussed, sample preparation, image acquisition, and data analysis steps are explained, and a few exemplary results are showcased. Providing high spatial resolution, specificity, and sensitivity, BiFC-PALM is a useful tool for studying PPIs in intact biological samples.

Photoactivated Localization Microscopy with Bimolecular Fluorescence Complementation BiFC-PALM

Protein-protein interactions are visualized in cells with nanometer spatial resolution by combining bimolecular fluorescence complementation (BiFC) with photoactivated localization microscopy (PALM). Described here is the use of BiFC-PALM for imaging Ras-Raf interactions in U2OS cells for visualizing the nanoscale clustering and diffusion of individual Ras-Raf complexes.

Protein-protein interactions (PPIs) are key molecular events to biology. However, it remains a challenge to visualize PPIs with sufficient resolution and ...

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

Microfluidic processing of biological samples typically involves differential manipulations of suspended particles under various force fields in order to spatially fractionate the sample based on a biological property of interest. For the resultant spatial distribution to be used as the assay readout, microfluidic devices are often subjected to microscopic analysis requiring complex instrumentation with higher cost and reduced portability. To address this limitation, we have developed an integrated electronic sensing technology for multiplexed detection of particles at different locations on a microfluidic chip. Our technology, called Microfluidic CODES, combines Resistive Pulse Sensing with Code Division Multiple Access to compress 2D spatial information into a 1D electrical signal. In this paper, we present a practical demonstration of the Microfluidic CODES technology to detect and size cultured cancer cells distributed over multiple microfluidic channels. As validated by the high-speed microscopy, our technology can accurately analyze dense cell populations all electronically without the need for an external instrument. As such, the Microfluidic CODES can potentially enable low-cost integrated lab-on-a-chip devices that are well suited for the point-of-care testing of biological samples.

We demonstrate a microfluidic platform with an integrated surface electrode network that combines resistive pulse sensing (RPS) with code division multiple access (CDMA), to multiplex detection and sizing of particles in multiple microfluidic channels.

Microfluidic processing of biological samples typically involves differential manipulations of suspended particles under various force fields in order to ...

Gene Expression Analysis of Endothelial Cells Exposed to Shear Stress Using Multiple Parallel-plate Flow Chambers

We describe a workflow for the analysis of gene expression from endothelial cells subject to a steady laminar flow using multiple monitored parallel-plate flow chambers. Endothelial cells form the inner cellular lining of blood vessels and are chronically exposed to the frictional force of blood flow called shear stress. Under physiological conditions, endothelial cells function in the presence of various shear stress conditions. Thus, the application of shear stress conditions in in vitro models can provide greater insight into endothelial responses in vivo. The parallel-plate flow chamber previously published by Lane et al.9 is adapted to study endothelial gene regulation in the presence and absence of steady (non-pulsatile) laminar flow. Key adaptations in the set-up for laminar flow as presented here include a large, dedicated environment to house concurrent flow circuits, the monitoring of flow rates in real-time, and the inclusion of an exogenous reference RNA for the normalization of quantitative real-time PCR data. To assess multiple treatments/conditions with the application of shear stress, multiple flow circuits and pumps are used simultaneously within the same heated and humidified incubator. The flow rate of each flow circuit is measured continuously in real-time to standardize shear stress conditions throughout the experiments. Because these experiments have multiple conditions, we also use an exogenous reference RNA that is spiked-in at the time of RNA extraction for the normalization of RNA extraction and first-strand cDNA synthesis efficiencies. These steps minimize the variability between samples. This strategy is employed in our pipeline for the gene expression analysis with shear stress experiments using the parallel-plate flow chamber, but parts of this strategy, such as the exogenous reference RNA spike-in, can easily and cost-effectively be used for other applications.

Here, a workflow for the culture and gene expression analysis of endothelial cells under fluid shear stress is presented. Included is a physical arrangement for simultaneously housing and monitoring multiple flow chambers in a controlled environment and the use of an exogenous reference RNA for quantitative PCR.

We describe a workflow for the analysis of gene expression from endothelial cells subject to a steady laminar flow using multiple monitored parallel-plate ...

Substructure Analyzer: A User-Friendly Workflow for Rapid Exploration and Accurate Analysis of Cellular Bodies in Fluorescence Microscopy Images

The last decade has been characterized by breakthroughs in fluorescence microscopy techniques illustrated by spatial resolution improvement but also in live-cell imaging and high-throughput microscopy techniques. This led to a constant increase in the amount and complexity of the microscopy data for a single experiment. Because manual analysis of microscopy data is very time consuming, subjective, and prohibits quantitative analyses, automation of bioimage analysis is becoming almost unavoidable. We built an informatics workflow called Substructure Analyzer to fully automate signal analysis in bioimages from fluorescent microscopy. This workflow is developed on the user-friendly open-source platform Icy and is completed by functionalities from ImageJ. It includes the pre-processing of images to improve the signal to noise ratio, the individual segmentation of cells (detection of cell boundaries) and the detection/quantification of cell bodies enriched in specific cell compartments. The main advantage of this workflow is to propose complex bio-imaging functionalities to users without image analysis expertise through a user-friendly interface. Moreover, it is highly modular and adapted to several issues from the characterization of nuclear/cytoplasmic translocation to the comparative analysis of different cell bodies in different cellular sub-structures. The functionality of this workflow is illustrated through the study of the Cajal (coiled) Bodies under oxidative stress (OS) conditions. Data from fluorescence microscopy show that their integrity in human cells is impacted a few hours after the induction of OS. This effect is characterized by a decrease of coilin nucleation into characteristic Cajal Bodies, associated with a nucleoplasmic redistribution of coilin into an increased number of smaller foci. The central role of coilin in the exchange between CB components and the surrounding nucleoplasm suggests that OS induced redistribution of coilin could affect the composition and the functionality of Cajal Bodies.

We present a freely available workflow built for rapid exploration and accurate analysis of cellular bodies in specific cell compartments in fluorescence microscopy images. This user-friendly workflow is designed on the open-source software Icy and also uses ImageJ functionalities. The pipeline is affordable without knowledge in image analysis.

The last decade has been characterized by breakthroughs in fluorescence microscopy techniques illustrated by spatial resolution improvement but also in ...

Asymmetrical Flow Field-Flow Fractionation for Sizing of Gold Nanoparticles in Suspension

Particle size is arguably the most important physico-chemical parameter associated with the notion of a nanoparticle. Precise knowledge of the size and size distribution of nanoparticles is of utmost importance for various applications. The size range is also important, as it defines the most &#8220;active&#8221; component of a nanoparticle dose.
Asymmetrical Flow Field-Flow Fractionation (AF4) is a powerful technique for sizing of particles in suspension in the size range of approximately 1&#8211;1000 nm. There are several ways to derive size information from an AF4 experiment. Besides coupling AF4 online with size-sensitive detectors based on the principles of Multi-Angle Light Scattering or Dynamic Light Scattering, there is also the possibility to correlate the size of a sample with its retention time using a well-established theoretical approach (FFF theory) or by comparing it with the retention times of well-defined particle size standards (external size calibration).
We here describe the development and in-house validation of a standard operating procedure (SOP) for sizing of an unknown gold nanoparticle sample by AF4 coupled with UV-vis detection using external size calibration with gold nanoparticle standards in the size range of 20&#8211;100 nm. This procedure provides a detailed description of the developed workflow including sample preparation, AF4 instrument setup and qualification, AF4 method development and fractionation of the unknown gold nanoparticle sample, as well as the correlation of the obtained results with the established external size calibration. The SOP described here was eventually successfully validated in the frame of an interlaboratory comparison study highlighting the excellent robustness and reliability of AF4 for sizing of nanoparticulate samples in suspension.

This protocol describes the use of Asymmetrical Flow Field-Flow Fractionation coupled with UV-vis detection for the determination of the size of an unknown gold nanoparticle sample.

Particle size is arguably the most important physico-chemical parameter associated with the notion of a nanoparticle. Precise knowledge of the size and ...