This study was supported by the Higher Education Commission of Pakistan.

NOTE: The protocol here uses COMSOL, a multiphysics simulation software, to simulate the controlled sorting of non-metastatic breast cancer cells (MCF-7) and non-tumor breast epithelial cells (MCF-10A) using AC dielectrophoresis.
1. Chip design and parameter selection
<ol>
	<li>Open multiphysics software and select Blank Model. Right-click on the Global Definitions and select Parameters. Import the parameters given in Table 1 into global definitions as a text file or enter the values individually.</li>
	<li>Select Add Component from the home tab and add a 2D Component. Right-click on geometry and import the model file by double-clicking on the file.</li>
	<li>Choose a blank material and use the material properties from Table 1.</li>
	<li>Select Add Physics from the home tab, and type AC/DC. Under the AC/DC node, choose electric currents as Physics under the sub-node of electric fields and currents.</li>
	<li>Right-click on the Electric Current and choose the Current Conservation, Insulate, and Electric Potential sub-nodes to insulate the channel walls to assign potential to the electrodes.</li>
	<li>Select Add Physics from the home tab, and under the Fluid Flow node, choose Creeping Flow Physics under the sub-node of Single-Phase Flow. Right-click on Single-Phase Flow and render the chip boundaries as walls by using the Wall sub-node.</li>
	<li>Right click on Single-Phase Flow and add two inlet sub-nodes and one outlet sub-node.</li>
	<li>Assign the inlets using the inlet sub-node and use normal in Flow Velocity as the Boundary Condition. Assign the outlet using the outlet sub-node.</li>
	<li>Select Add Physics from the home tab, and under the Fluid Flow node, choose Particle Tracing Flow Physics under the sub node of Particle Tracing.</li>
	<li>Right-click on the Particle Tracing node and add the sub-nodes wall, two-particle property sub-nodes, two inlet sub-nodes, one outlet sub-node, two dielectrophoresis force sub-nodes, and one drag force sub-node.
	<ol>
		<li>Set Particle Properties for both MCF-7 and MCF-10A cells using the Particle Properties sub-node. Choose the particle properties from parameters under the Global Definition section.</li>
		<li>Add the Drag Force sub-node to assign the dielectrophoretic force to both types of cells.</li>
		<li>Add Particle Properties in this case from the parameter section. Add the Shell sub-node to model mammalian cells.</li>
	</ol>
	</li>
	<li>From the home tab, choose Add Mesh and select Fine Mesh. Choose Build Mesh from the home tab to build a mesh.</li>
	<li>From the home tab, click on Add Study to add three study steps. Study Step 1 is for simulating a frequency response; use a Frequency Domain sub-node.
	<ol>
		<li>To simulate creeping flow, choose a Stationary Study node. Add two time-dependent steps to simulate conditions with dielectrophoretic force and without dielectrophoretic force.</li>
		<li>For the no dielectrophoretic condition, choose Physics and Variables Selection, check the box titled Modify Model Configuration for the study step, and disable the Dielectrophoretic Step. For dielectrophoretic conditions, do not disable. Save the file and press Compute for the simulation to run. 
		NOTE: The microfluidic chip designed for the sorting of non-metastatic breast cancer cells (MCF-7) and non-tumor breast epithelial cells (MCF-10A) has two separate inlets for cell mixture flow and for hydrodynamic flow focusing, respectively, with widths of 20 &#181;m and 40 &#181;m, respectively, as shown in Supplementary Figure 1 and Supplementary Figure 2.</li>
		<li>Assign frequency (f0) under the Frequency Domain sub-node and voltage using the Electric Potential sub-node to the planer electrodes (295 &#181;m in width) placed along the top side wall of the sorting chamber. At the outlet, use the &#34;freeze&#34; wall condition to visualize the sorted particles.</li>
	</ol>
	</li>
</ol>
2. Mathematical model and computational analysis
<ol>
	<li>Verify the operating parameters for separating non-metastatic breast cancer cells and non-tumor breast epithelial cells inside the microfluidic device by setting up a computational fluid dynamic (CFD) study. 
	NOTE: Multiphysics software (AC/DC, Microfluidics, and Particle Tracking modules) was used for this purpose. The governing equations and theoretical background are given in detail in Supplementary File 1. The model was tested by using the dielectric properties of non-metastatic breast cancer cells (MCF7) and non-tumor breast epithelial cells (MCF-10A) reported in literature31,32, which are summarized in Table 1.</li>
	<li>Perform the CFD simulations by introducing non-metastatic breast cancer (MCF7) and non-tumor breast epithelial (MCF-10A) cell lines with a ratio of 1:1 at the cell mixture inlet.
	<ol>
		<li>Initially, perform a mesh independence study to optimize the mesh size for the simulations33. 
		NOTE: A mesh independence study was performed to find the best solution for the operating parameters. A set of five different mesh sizes was chosen to quantify the best possible element size for the convergence of the solution. It was observed that, when the total number of elements defining a mesh was 635 (coarser mesh), as shown in Supplementary Figure 3A, the sorting efficiency was at its lowest, with some of the MCF7 cells moving to the bottom outlet, as depicted in Supplementary Figure 3B. When the mesh size was increased to fine, the number of elements defining the mesh also increased to 2,288. The sorting efficiency was at its maximum in this case, with both MCF7 and MCF-10A cells moving toward their respective outlets. The finer mesh was also simulated, with the number of elements defining the mesh increasing to 3,188. The sorting efficiency remained unaffected beyond this point. Hence, we can safely say that fine mesh size works the best in our case.</li>
		<li>Solve two sets of CFD studies.</li>
		<li>For the first set, right -click on Study 1 and add the Parametric Sweep sub-node. Press the + sign to add fluid medium conductivity &#34;&#963;m&#34;&#160;as the sweep variable. Perform a parametric sweep study for the fluid medium conductivity &#963;m ranging from 0.01 S/m to 2.5 S/m, keeping the applied frequency, f (Hz), constant at a value of 800 kHz.</li>
		<li>For the second set, conduct a Parametric Sweep study by varying the applied AC frequency from 100 kHz to 100 MHz while keeping the conductivity of the fluid medium, &#963;m, fixed at 0.4 S/m for each case. This &#963;m value was chosen based on the results of the first CFD study as a maximum separation between MCF-7 and MCF-10A was observed at this value.</li>
		<li>The strength of the dielectrophoresis (DEP) force, FDEP (-), exerted on a dielectric spherical particle in a conductive medium is given by Equation 1T34: 
		FDEP&#160;<img alt="Equation 1" src="/files/ftp_upload/63850/63850eq01.jpg" style="margin: auto;" />&#160; [1] 
		Use Equation 1 under the dielectrophoretic force sub-node. In equation 1, r shows the radius of the particle on which FDEP is applied; K (-) is known as the Clausius-Mossotti factor; &#949;m (-) shows the dielectric permittivity of the medium; and E(V/m) is the root mean square value of the electric field.</li>
		<li>Use Equation 2 for a spherical particle under the dielectrophoretic force sub-node. 
		<img alt="Equation 2" src="/files/ftp_upload/63850/63850eq02.jpg" style="margin: auto;" />&#160; &#160; &#160;[2] 
		In Equation 2, <img alt="Equation 3" src="/files/ftp_upload/63850/63850eq03.jpg" style="margin: auto;" /> (-) shows the complex permittivity of the particle on which the DEP force is applied; <img alt="Equation 4" src="/files/ftp_upload/63850/63850eq04.jpg" style="margin: auto;" /> (-) shows the complex permittivity of the fluid surrounding the particle. The complex permittivity <img alt="Equation 3" src="/files/ftp_upload/63850/63850eq03.jpg" style="margin: auto;" /> and <img alt="Equation 4" src="/files/ftp_upload/63850/63850eq04.jpg" style="margin: auto;" /> are defined as follows35:</li>
		<li>Use Equation 3 for a spherical particle under the dielectrophoretic force sub-node: 
		<img alt="Equation 6" src="/files/ftp_upload/63850/63850eq06.jpg" style="margin: auto;" />&#160; &#160; &#160;[3] 
		In Equation 3, &#949;p (-) shows the real part of the complex permittivity of the particle; &#949;m (-) shows the&#160;real part of the complex permittivity of the fluid surrounding the particle; &#963;p (S/m) shows the particle conductivity; &#963;m (S/m) shows the conductivity of the medium surrounding the particle; and &#969; (Hz) is the frequency of the applied electric field. 
		NOTE: The sign of Re(K) determines the polarity of the FDEP. If the sign of Re(K) is negative, then the particle experiences a negative dielectrophoretic force (nDEP); contrary to this, if the sign of Re(K) is positive, it implies a positive dielectrophoretic force (pDEP). For the Clausius-Mossotti factor (K), the variation lies within the range of -1 to 1.</li>
	</ol>
	</li>
	<li>Use a modified form of Equation 3 to model biological cells such as mammalian cells, which are more complex and have a multilayered structure. 
	K (<img alt="Equation 7" src="/files/ftp_upload/63850/63850eq07.jpg" style="margin: auto;" />) = <img alt="Equation 8" src="/files/ftp_upload/63850/63850eq08.jpg" style="margin: auto;" />&#160; &#160; &#160;[4] 
	In Equation 4, <img alt="Equation 9" src="/files/ftp_upload/63850/63850eq09.jpg" style="margin: auto;" /> (-) incorporates both the complex permittivity of the cytoplasm, <img alt="Equation 10" src="/files/ftp_upload/63850/63850eq10.jpg" style="margin: auto;" /> (-), and the complex permittivity of the cell membrane, <img alt="Equation 11" src="/files/ftp_upload/63850/63850eq11.jpg" style="margin: auto;" /> (-), and is given as follows:36</li>
	<li>Use Equation 5 to solve &#34;<img alt="Equation 12" src="/files/ftp_upload/63850/63850eq12.jpg" style="margin: auto;" />&#34;: 
	<img alt="Equation 13" src="/files/ftp_upload/63850/63850eq13.jpg" style="margin: auto;" />&#160; &#160;&#160; [5] 
	In Equation 5, Rcyto (m) and Rmem (m) show the radius of the cell cytoplasm and cell membrane, respectively.</li>
	<li>Then, use Equation 4 to plot Re(K) as a function of the applied electric field for both cancer and healthy cells. Calculate the real part of the Clausius-Mossotti (CM) factor, Re(K), to quantify the dielectrophoretic force (DEP) that the particle experiences.</li>
	<li>Right-click on the Results node, add the Particle Evaluation sub-node, and in the expression section, type fpt.deff1.K to plot the CM factor for particle 1 and fpt.deff2.K for particle 2. 
	NOTE: All the protocol steps listed in the main text can be viewed in the protocol video (Video 1).</li>
</ol>

The authors declare no potential conflicts of interest.

Microfluidic devices have been reported previously for cell culture, trapping, and sorting47,52,53. The fabrication of these devices in the cleanroom is an expensive process, and it is imperative to quantify the output and efficiency of a proposed microfluidic device through CFD simulations. This study presents the design and simulations of an AC-dielectrophoretic microfluidic device for the continuous separation of non-metastat...

A malignant tumor that develops in and around the breast tissue is a frequent cause of breast cancer in women worldwide, causing a critical health problem1. Breast tumors before metastasis can be treated through surgery if detected at an early stage, but if ignored, they can have severe implications on the patient&#39;s life by spreading to their lungs, brain, and bones. The treatments offered at later stages, such as radiation and chemical-based therapies, have severe side effects2. Recent studies have reported that an early diagnosis of breast cancer reduces the mortality rate by 60%3. Hence, it is imperative to work toward personalized early detection methods. To this end, researchers working in different fields of science and technology have used microfluidics to develop devices for the early diagnosis of breast cancer4. These methods include cell affinity micro-chromatography, magnetic-activated micro-cell sorters, size-based cancer cell capture and separation, and on-chip dielectrophoresis (DEP)5,6. These microfluidic techniques reported in the literature enable precise cell manipulation, real-time monitoring, and sorting of well-defined samples, which serve as an intermediate step in many diagnostic and therapeutic applications5. The integration of these sorting mechanisms with microfluidics offers flexible and reliable manipulation of the target cells7,8,9,10. One of the main advantages of such an integration is the ability to work with fluid samples in nano to microliter volumes and also being able to manipulate the electrical properties of the sample fluid. By adjusting the conductivity of the suspending fluid inside microfluidic devices, the biological cells can be sorted based on their sizes and differences in their dielectric properties11,12.
Among these techniques, on-chip DEP is often preferred as it is a label-free cell sorting technique that exploits the electric properties of the biological samples. DEP has been reported to manipulate bio-samples such as DNA13, RNA14, proteins15, bacteria16, blood cells17, circulating tumor cells (CTCs)18, and stem cells19. Microfluidic devices that employ DEP for sorting biological samples have been reported extensively in literature20. Reservoir-based DEP microfluidic (rDEP) devices for sorting viable and non-viable yeast cells have been reported that protect the cells from the adverse effects of electrochemical reactions21,22. Piacentini et al. reported a castellated microfluidic cell sorter that separated red blood cells from platelets with an efficiency of 97%23. On-chip DEP devices with asymmetric orifices and embedded electrodes have also been reported to sort viable and non-viable cells24. Valero and Demierre et al. modified the castellated microfluidic cell sorter by introducing two arrays of microelectrodes on both sides of the channel25,26. This helped in focusing the cells in the center of the channel. Zeynep et al. presented a DEP-based microfluidic device to separate and concentrate MCF7 breast cancer cells from leukocytes27. They reported an efficiency of extracting MCF7 cells from leukocytes between 74%-98% with a frequency of 1 MHz and an applied voltage ranging from 10-12 Vpp. Supplementary Table 1 represents a qualitative and quantitative comparison between the DEP-based microfluidic sorting devices based on their design, electrode configuration, and operating parameters (applied frequency and voltage).
More recently, researchers have tried to measure the differences in the dielectric behavior of breast epithelial cells (MCF-10A) and non-metastatic breast cancer cells (MCF-7) inside a microfluidic chip28,29. Jithin et al. also characterized the dielectric responses of different cancer cell lines using an open-ended coaxial probe technique with frequencies between 200 MHz and 13.6 GHz30. These differences in the dielectric responses of MCF-7 and MCF-10A cell lines can be exploited to separate them in runtime and can lead to the development of personalized early-stage diagnosis devices.
In this article, we simulate the controlled sorting of non-metastatic breast cancer cells (MCF-7) and non-tumor breast epithelial cells (MCF-10A) using AC dielectrophoresis. The region of change in the electric field influences the sorting inside the microfluidic chip. The proposed technique is easy to implement and allows for the integration of the sorting technique into various microfluidic chip layouts. Computational fluid dynamics (CFD) simulations were carried out to study the separation of non-metastatic breast cancer cells and non-tumor breast epithelial cells by varying the conductivity of the fluid medium in which cells were suspended. In these simulations, it is shown that, by keeping the conductivity constant and by changing the applied frequency, the separation of cancer cells and healthy cells can be controlled.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>COMSOL</td>
			<td>COMSOL</td>
			<td></td>
			<td>multiphysics simulation software</td>
		</tr>
	</tbody>
</table>

microfluidic device for the separation of non-metastatic (mcf-7) and non-tumor (mcf-10a) breast cancer cells using ac dielectrophoresis

Dielectrophoretic devices are capable of the detection and manipulation of cancer cells in a label-free, cost-effective, robust, and accurate manner using the principle of the polarization of the cancer cells in the sample volume by applying an external electric field. This article demonstrates how a microfluidic platform can be utilized for high-throughput continuous sorting of non-metastatic breast cancer cells (MCF-7) and non-tumor breast epithelial cells (MCF-10A) using hydrodynamic dielectrophoresis (HDEP) from the cell mixture. By generating an electric field between two electrodes placed side-by-side with a micron-sized gap between them in an HDEP microfluidic chip, non-tumor breast epithelial cells (MCF-10A) can be pushed away, exhibiting negative DEP inside the main channel, while the non-metastatic breast cancer cells follow their course unaffected when suspended in cell medium due to having conductivity higher than the membrane conductivity. To demonstrate this concept, simulations were performed for different values of medium conductivity, and the sorting of cells was studied. A parametric study was carried out, and a suitable cell mixture conductivity was found to be 0.4 S/m. By keeping the medium conductivity fixed, an adequate AC frequency of 0.8 MHz was established, giving maximum sorting efficiency, by varying the electric field frequency. Using the demonstrated method, after choosing the appropriate cell mixture suspension medium conductivity and frequency of the applied AC, maximum sorting efficiency can be achieved.

Investigating the optimal operational parameters for effective DEP-based sorting of non-metastatic breast cancer (MCF-7) and non-tumor breast epithelial (MCF-10A) cells 
To achieve a successful separation of non-metastatic breast cancer (MCF-7) and non-tumor breast epithelial (MCF-10A) cells with divergent dielectric properties when undergoing dielectrophoresis, their K factors should be distinct by keeping the applied frequency fixed37,38. ...

Watch this Scientific Journal Video about Microfluidic Device for the Separation of Non-Metastatic MCF-7 and Non-Tumor MCF-10A Breast Cancer Cells Using AC Dielectrophoresis at JoVE.com

Microfluidic Device for the Separation of Non-Metastatic MCF-7 and Non-Tumor MCF-10A Breast Cancer Cells Using AC Dielectrophoresis

Breast cancer cells exhibit different dielectric properties compared to non-tumor breast epithelial cells. It has been hypothesized that, based on this difference in dielectric properties, the two populations can be separated for immunotherapy purposes. To support this, we model a microfluidic device to sort MCF-7 and MCF-10A cells.

Microfluidic Device for the Separation of Non-Metastatic (MCF-7) and Non-Tumor (MCF-10A) Breast Cancer Cells Using AC Dielectrophoresis

Dielectrophoretic devices are capable of the detection and manipulation of cancer cells in a label-free, cost-effective, robust, and accurate manner using ...

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2.2K Views.  Foundation University Islamabad. Breast cancer cells exhibit different dielectric properties compared to non-tumor breast epithelial cells. It has been hypothesized that, based on this difference in dielectric properties, the two populations can be separated for immunotherapy purposes. To support this, we model a microfluidic device to sort MCF-7 and MCF-10A cells. 

Video: Microfluidic Device for the Separation of Non-Metastatic MCF-7 and Non-Tumor MCF-10A Breast Cancer Cells Using AC Dielectrophoresis

Terahertz Microfluidic Sensing Using a Parallel-plate Waveguide Sensor

Refractive index (RI) sensing is a powerful noninvasive and label-free sensing technique for the identification, detection and monitoring of microfluidic samples with a wide range of possible sensor designs such as interferometers and resonators 1,2. Most of the existing RI sensing applications focus on biological materials in aqueous solutions in visible and IR frequencies, such as DNA hybridization and genome sequencing. At terahertz frequencies, applications include quality control, monitoring of industrial processes and sensing and detection applications involving nonpolar materials.
Several potential designs for refractive index sensors in the terahertz regime exist, including photonic crystal waveguides 3, asymmetric split-ring resonators 4, and photonic band gap structures integrated into parallel-plate waveguides 5. Many of these designs are based on optical resonators such as rings or cavities. The resonant frequencies of these structures are dependent on the refractive index of the material in or around the resonator. By monitoring the shifts in resonant frequency the refractive index of a sample can be accurately measured and this in turn can be used to identify a material, monitor contamination or dilution, etc.
The sensor design we use here is based on a simple parallel-plate waveguide 6,7. A rectangular groove machined into one face acts as a resonant cavity (Figures 1 and 2). When terahertz radiation is coupled into the waveguide and propagates in the lowest-order transverse-electric (TE1) mode, the result is a single strong resonant feature with a tunable resonant frequency that is dependent on the geometry of the groove 6,8. This groove can be filled with nonpolar liquid microfluidic samples which cause a shift in the observed resonant frequency that depends on the amount of liquid in the groove and its refractive index 9.
Our technique has an advantage over other terahertz techniques in its simplicity, both in fabrication and implementation, since the procedure can be accomplished with standard laboratory equipment without the need for a clean room or any special fabrication or experimental techniques. It can also be easily expanded to multichannel operation by the incorporation of multiple grooves 10. In this video we will describe our complete experimental procedure, from the design of the sensor to the data analysis and determination of the sample refractive index.

The procedure for implementing a refractive index sensor for terahertz frequencies based on a grooved parallel-plate waveguide geometry is described here. The method yields a measurement of the refractive index of a small volume of liquid through monitoring of the shift in the resonant frequency of the waveguide structure

Refractive index (RI) sensing is a powerful noninvasive and label-free sensing technique for the identification, detection and monitoring of microfluidic ...

Spatial Separation of Molecular Conformers and Clusters

Gas-phase molecular physics and physical chemistry experiments commonly use supersonic expansions through pulsed valves for the production of cold molecular beams. However, these beams often contain multiple conformers and clusters, even at low rotational temperatures. We present an experimental methodology that allows the spatial separation of these constituent parts of a molecular beam expansion. Using an electric deflector the beam is separated by its mass-to-dipole moment ratio, analogous to a bender or an electric sector mass spectrometer spatially dispersing charged molecules on the basis of their mass-to-charge ratio. This deflector exploits the Stark effect in an inhomogeneous electric field and allows the separation of individual species of polar neutral molecules and clusters. It furthermore allows the selection of the coldest part of a molecular beam, as low-energy rotational quantum states generally experience the largest deflection. Different structural isomers (conformers) of a species can be separated due to the different arrangement of functional groups, which leads to distinct dipole moments. These are exploited by the electrostatic deflector for the production of a conformationally pure sample from a molecular beam. Similarly, specific cluster stoichiometries can be selected, as the mass and dipole moment of a given cluster depends on the degree of solvation around the parent molecule. This allows experiments on specific cluster sizes and structures, enabling the systematic study of solvation of neutral molecules.

We present a technique that allows the spatial separation of different conformers or clusters present in a molecular beam. An electrostatic deflector is used to separate species by their mass-to-dipole moment ratio, leading to the production of gas-phase ensembles of a single conformer or cluster stoichiometry.

Gas-phase molecular physics and physical chemistry experiments commonly use supersonic expansions through pulsed valves for the production of cold ...

Capillary-based Centrifugal Microfluidic Device for Size-controllable Formation of Monodisperse Microdroplets

Here, we demonstrate a simple method for the rapid production of size-controllable, monodisperse, W/O microdroplets using a capillary-based centrifugal microfluidic device. W/O microdroplets have recently been used in powerful methods that enable miniaturized chemical experiments. Therefore, developing a versatile method to yield monodisperse W/O microdroplets is needed. We have developed a method for generating monodisperse W/O microdroplets based on a capillary-based centrifugal axisymmetric co-flowing microfluidic device. We succeeded in controlling the size of microdroplets by adjusting the capillary orifice. Our method requires equipment that is easier-to-use than with other microfluidic techniques, requires only a small volume (0.1-1 &#181;l) of sample solution for encapsulation, and enables the production of hundreds of thousands number of W/O microdroplets per second. We expect this method will assist biological studies that require precious biological samples by conserving the volume of the samples for rapid quantitative analysis biochemical and biological studies.

Here, we demonstrate a simple production method for size-controllable, monodisperse, water-in-oil (W/O) microdroplets using a capillary-based centrifugal microfluidic device. This method requires only a small sample volume and enables high-yield production. We expect this method will be useful for rapid biochemical and cellular analyses.

Here, we demonstrate a simple method for the rapid production of size-controllable, monodisperse, W/O microdroplets using a capillary-based centrifugal ...

Scanning Light Scattering Profiler (SLPS) Based Methodology to Quantitatively Evaluate Forward and Backward Light Scattering from Intraocular Lenses

The scanning light scattering profiler (SLSP) methodology has been developed for the full-angle quantitative evaluation of forward and backward light scattering from intraocular lenses (IOLs) using goniophotometer principles. This protocol describes the SLSP platform and how it employs a 360&#176; rotational photodetector sensor that is scanned around an IOL sample while recording the intensity and location of scattered light as it passes through the IOL medium. The SLSP platform can be used to predict, non-clinically, the propensity for current and novel IOL designs and materials to induce light scatter. Non-clinical evaluation of light scattering properties of IOLs can significantly reduce the number of patient complaints related to unwanted glare, glistening, optical defects, poor image quality, and other phenomena associated with the unintended light scattering. Future studies should be conducted to correlate SLSP data with clinical results to help identify which measured light scatter is most problematic for patients that have undergone cataract surgery subsequent to IOL implantation.

Scanning Light Scattering Profiler SLPS Based Methodology to Quantitatively Evaluate Forward and Backward Light Scattering from Intraocular Lenses

This protocol describes the scanning light scattering profiler (SLSP) that enables the full-angle quantitative evaluation of forward and backward scattering of light from intraocular lenses (IOLs) using goniophotometer principles.

The scanning light scattering profiler (SLSP) methodology has been developed for the full-angle quantitative evaluation of forward and backward light ...

Flow-assisted Dielectrophoresis: A Low Cost Method for the Fabrication of High Performance Solution-processable Nanowire Devices

Flow-assisted dielectrophoresis (DEP) is an efficient self-assembly method for the controllable and reproducible positioning, alignment, and selection of nanowires. DEP is used for nanowire analysis, characterization, and for solution-based fabrication of semiconducting devices. The method works by applying an alternating electric field between metallic electrodes. The nanowire formulation is then dropped onto the electrodes which are on an inclined surface to create a flow of the formulation using gravity. The nanowires then align along the gradient of the electric field and in the direction of the liquid flow. The frequency of the field can be adjusted to select nanowires with superior conductivity and lower trap density. 
In this work, flow-assisted DEP is used to create nanowire field effect transistors. Flow-assisted DEP has several advantages: it allows selection of nanowire electrical properties; control of nanowire length; placement of nanowires in specific areas; control of orientation of nanowires; and control of nanowire density in the device. 
The technique can be expanded to many other applications such as gas sensors and microwave switches. The technique is efficient, quick, reproducible, and it uses a minimal amount of dilute solution making it ideal for the testing of novel nanomaterials. Wafer scale assembly of nanowire devices can also be achieved using this technique, allowing large numbers of samples for testing and large-area electronic applications.

In this paper, flow assisted dielectrophoresis is demonstrated for the self-assembly of nanowire devices. The fabrication of a silicon nanowire field effect transistor is shown as an example.

Flow-assisted dielectrophoresis (DEP) is an efficient self-assembly method for the controllable and reproducible positioning, alignment, and selection of ...

Guidelines and Experience Using Imaging Biomarker Explorer (IBEX) for Radiomics

Imaging Biomarker Explorer (IBEX) is an open-source tool for medical imaging radiomics work. The purpose of this paper is to describe how to use IBEX's graphical user interface (GUI) and to demonstrate how IBEX calculated features have been used in clinical studies. IBEX allows for the import of DICOM images with DICOM radiation therapy structure files or Pinnacle files. Once the images are imported, IBEX has tools within the Data Selection GUI to manipulate the viewing of the images, measure voxel values and distances, and create and edit contours. IBEX comes with 27 preprocessing and 132 feature choices to design feature sets. Each preprocessing and feature category has parameters that can be altered. The output from IBEX is a spreadsheet that contains: 1) each feature from the feature set calculated for each contour in a data set, 2) image information about each contour in a data set, and 3) a summary of the preprocessing and features used with their selected parameters. Features calculated from IBEX have been used in studies to test the variability of features under different imaging conditions and in survival models to improve current clinical models.

Guidelines and Experience Using Imaging Biomarker Explorer IBEX for Radiomics

We describe IBEX, an open-source tool designed for medical imaging radiomics studies, and how to use this tool. In addition, some published works that have used IBEX for uncertainty analysis and model building are showcased.

Imaging Biomarker Explorer (IBEX) is an open-source tool for medical imaging radiomics work. The purpose of this paper is to describe how to use IBEX's ...

A Pipette-Tip Based Method for Seeding Cells to Droplet Microfluidic Platforms

Amongst various microfluidic platform designs frequently used for cellular analysis, droplet-microfluidics provides a robust tool for isolating and analyzing cells at the single-cell level by eliminating the influence of external factors on the cellular microenvironment. Encapsulation of cells in droplets is dictated by the Poisson distribution as a function of the number of cells present in each droplet and the average number of cells per volume of droplet. Primary cells, especially immune cells, or clinical specimens can be scarce and loss-less encapsulation of cells remains challenging. In this paper, we present a new methodology that uses pipette-tips to load cells to droplet-based microfluidic devices without the significant loss of cells. With various cell types , we demonstrate efficient cell encapsulation in droplets that closely corresponds to the encapsulation efficiency predicted by the Poisson distribution. Our method ensures loss-less loading of cells to microfluidic platforms and can be easily adapted for downstream single cell analysis, e.g., to decode cellular interactions between different cell types.

This article presents a protocol for seeding scarce population of cells using pipette-tips to droplet microfluidic devices in order to provide higher encapsulation efficiency of cells in droplets.

Amongst various microfluidic platform designs frequently used for cellular analysis, droplet-microfluidics provides a robust tool for isolating and ...

Terahertz Imaging and Characterization Protocol for Freshly Excised Breast Cancer Tumors

This manuscript presents a protocol to handle, characterize, and image freshly excised human breast tumors using pulsed terahertz imaging and spectroscopy techniques. The protocol involves terahertz transmission mode at normal incidence and terahertz reflection mode at an oblique angle of 30&#176;. The collected experimental data represent time domain pulses of the electric field. The terahertz electric field signal transmitted through a fixed point on the excised tissue is processed, through an analytical model, to extract the refractive index and absorption coefficient of the tissue. Utilizing a stepper motor scanner, the terahertz emitted pulse is reflected from each pixel on the tumor providing a planar image of different tissue regions. The image can be presented in time or frequency domain. Furthermore, the extracted data of the refractive index and absorption coefficient at each pixel are utilized to provide a tomographic terahertz image of the tumor. The protocol demonstrates clear differentiation between cancerous and healthy tissues. On the other hand, not adhering to the protocol can result in noisy or inaccurate images due to the presence of air bubbles and fluid remains on the tumor surface. The protocol provides a method for surgical margins assessment of breast tumors.

Freshly excised human breast cancer tumors are characterized with terahertz spectroscopy and imaging following fresh tissue handling protocols. Tissue positioning is taken into consideration to enable effective characterization while providing analysis in a timely manner for future intraoperative applications.

This manuscript presents a protocol to handle, characterize, and image freshly excised human breast tumors using pulsed terahertz imaging and spectroscopy ...

Ion-Exchange Membranes for the Fabrication of Reverse Electrodialysis Device

Reverse electrodialysis (RED) is an effective way to generate power by mixing two different salt concentrations in water using cation-exchange membranes (CEM) and anion-exchange membranes (AEM). The RED stack is composed of an alternating arrangement of the cation-exchange membrane and anion-exchange membrane. The RED device acts as a potential candidate for fulfilling the universal demand for future energy crises. Here, in this article, we demonstrate a procedure to fabricate a reverse electrodialysis device using laboratory-scale CEM and AEM for power production. The active area of the ion-exchange membrane is 49 cm2. In this article, we provide a step-by-step procedure for synthesizing the membrane, followed by the stack&#39;s assembly and power measurement. The measurement conditions and net power output calculation have also been explained. Furthermore, we describe the fundamental parameters that are taken into consideration for obtaining a reliable outcome. We also provide a theoretical parameter that affects the overall cell performance relating to the membrane and the feed solution. In short, this experiment describes how to assemble and measure RED cells on the same platform. It also contains the working principle and calculation used for estimating the net power output of the RED stack using CEM and AEM membranes.

We demonstrate the fabrication of a reverse electrodialysis device using a cation-exchange membrane (CEM) and anion-exchange membrane (AEM) for power generation.

Reverse electrodialysis (RED) is an effective way to generate power by mixing two different salt concentrations in water using cation-exchange membranes ...

Pneumatically Driven Microfluidic Platform for Micro-Particle Concentration

The present article introduces a method for fabricating and operating a pneumatic valve to control particle concentration using a microfluidic platform. This platform has a three-dimensional (3D) network with curved fluid channels and three pneumatic valves, which create networks, channels, and spaces through duplex replication with polydimethylsiloxane (PDMS). The device operates based on the transient response of a fluid flow rate controlled by a pneumatic valve in the following order: (1) sample loading, (2) sample blocking, (3) sample concentration, and (4) sample release. The particles are blocked by thin diaphragm layer deformation of the sieve valve (Vs) plate and accumulate in the curved microfluidic channel. The working fluid is discharged by the actuation of two on/off valves. As a result of the operation, all particles of various magnifications were successfully intercepted and disengaged. When this technology is applied, the operating pressure, the time required for concentration, and the concentration rate may vary depending on the device dimensions and particle size magnification.

The present protocol describes a pneumatic microfluidic platform that can be used for efficient microparticle concentration.

The present article introduces a method for fabricating and operating a pneumatic valve to control particle concentration using a microfluidic platform. ...