The laboratory work was conducted with the support of the UCLA Molecular Shared Screening Resource (MSSR) where Forcyte is sponsoring research activities, and the Magnify Incubator at the California NanoSystems Institute (CNSI), where Forcyte Biotechnologies, Inc. is a resident company. The authors will grant access to the Biodock.ai FLECS analysis module to all academic researchers upon request. L.H. and I.P. contributed equally to this work.

1. Day 1: Preparation of the 24 well plate
<ol>
	<li>Begin the procedure by adding 20 mL of the cell culture medium into a 50 mL conical tube. In this experiment, F12 Ham&#39;s based medium supplemented with 10% fetal bovine serum (FBS) is used.</li>
	<li>Obtain a 24 well plate designed to assay cell contractility. Set the pipette to 500 &#181;L and obtain a cell strainer for cell passaging. 
	NOTE: The plate is available from the authors upon request.</li>
	<li>Lift and hold the plate in one hand and proceed to gently peel the plastic film from the top of the plate. Then carefully set the plate back down.</li>
	<li>Turn on a vacuum aspirator and aspirate the top layer of phosphate-buffered saline (PBS) from the wells to prevent spilling. Remove the PBS one row at a time. Once the wells are no longer completely full, hold the plate in one hand and carefully remove the rest of the PBS from the wells. Quickly fill with 500 &#181;L of cell culture medium. Take care to avoid contact between the aspirator and the bottom of the well.</li>
	<li>Shake the plate gently and tap on the side to ensure the entire bottom of the well is covered with solution. Once all wells are filled with medium, set the plate to the side.</li>
</ol>
2. Day 1: Cell seeding
<ol>
	<li>Retrieve the culture flask with passage 7 or lower primary human bladder smooth muscle (BSM) cells from the 37 &#176;C incubator. Under a microscope, check cell morphology and ensure cells have grown to at least 90% confluency but less than 100% confluency.</li>
	<li>Conduct the cell dissociation protocol. Within a sterile biosafety cabinet, trypsinize the cells for 2.5 min until cells are detached before quenching them with serum-supplemented medium (10% FBS).</li>
	<li>Once cells are dissociated, use a hemocytometer to count the cells and dilute the cell suspension to approximately 50,000 cells/mL in serum-supplemented medium. Importantly, cells require at least 2% serum to attach to the micropatterns.</li>
	<li>Prior to seeding, rapidly strain the cell suspension through a 40 or 100 &#181;m cell strainer into a 50 mL conical tube with a serological pipette to break up clumps of cells into single cells.</li>
	<li>Carefully add 500 &#181;L of the 50,000 cells/mL cell suspension into each of the 24 wells on the plate using a P1000 pipette by dispensing the solution dropwise across different positions in the wells.</li>
	<li>After cell seeding, let the plate sit at room temperature for 1 h to let the cells settle directly onto the micropatterns without becoming influenced by microcurrents generated by evaporation. After 1 h, place the plate into a 37 &#176;C incubator overnight. The cells will self-assemble and spread over the adhesive micropatterns during this time and begin exerting basal contraction levels.</li>
</ol>
3. Day 2: Addition of test drug
NOTE: The final concentration of dimethyl sulfoxide (DMSO) in the wells containing adhered cells cannot exceed 1% and drug/DMSO cannot be added directly to the cells but should first be diluted and mixed into an intermediate solution of cell medium.
<ol>
	<li>Create a six-step, eight-fold drug dilution series by transferring 30 &#181;L of the stock drug into consecutive 210 &#181;L volumes of DMSO and thoroughly mixing between each transfer step. In this work, a six-step, eight-fold dilution series of blebbistatin is prepared in doses ranging from 40 &#181;M to 1 nM, in DMSO.</li>
	<li>For each stock drug solution (from Step 3.1), mix 30 &#181;L of drug into 470 &#181;L of cell culture medium. The intermediate solution yields a 16.7-fold dilution of DMSO.</li>
	<li>Transfer 200 &#181;L of each intermediate solution to the appropriate well on the 24 well plate (which already contains 100 &#181;L of medium in each well). This yields an additional six-fold dilution of DMSO.</li>
	<li>Steps 3.2 and 3.3 collectively yield a 1% final concentration of DMSO in the wells.</li>
	<li>Place the treated plate into a 37 &#176;C incubator for the appropriate duration. For this experiment, a 30 min incubation is used.</li>
	<li>Immediately prior to imaging, add Hoechst 33342 live nuclear stain solution to each well (1:10,000 final dilution). Allow it to incubate for an additional 15 min to label the cell nuclei.</li>
</ol>
4. Day 2: Imaging the well-plate
<ol>
	<li>Access a microscope that is equipped to image the channels for both the cell nuclei (DAPI) and the micropatterns (TRITC).</li>
	<li>First image the cells with DMSO only.</li>
	<li>Then focus on and image both the micropatterns and the labeled cell nuclei in order to identify single cells and ensure both channels are perfectly aligned to enable automated image analysis.</li>
	<li>Repeat at multiple positions in each of the 24 wells on the plate. Images may be taken with 4x objective (or optionally higher to expedite imaging and acquire maximal data points per image).</li>
	<li>Export the images as TIF files and open them on a web-connected computer with ImageJ to analyze the data.</li>
</ol>
5. Post-experiment: Image analysis
NOTE: Image analysis was performed using Biodock.ai portal and imaging software.
<ol>
	<li>Upload the acquired images to a computer.
	<ol>
		<li>Ensure that corresponding pairs of micropattern and nuclear images are named properly.</li>
		<li>Ensure that micropattern image names all take the form &#34;sharedCoreName_pt.tif&#34;.</li>
		<li>Ensure that nuclei image names all take the form &#34;sharedCoreName_dapi.tif&#34;.</li>
	</ol>
	</li>
	<li>Convert images from TIF to PNG using ImageJ.
	<ol>
		<li>Once ImageJ is opened, load in one channel at a time. For this experiment, first load micropattern images as a stack into ImageJ.</li>
		<li>Using Image &#62; Adjust &#62; Brightness/Contrast,&#160;adjust the image brightness to emphasize the micropatterns and reduce the background to black. In addition to this, smooth out the images.</li>
		<li>Using Image &#62; Type &#62; 8-bit, convert the images to 8-bit.</li>
		<li>Then export the image to PNG type and check the box slice level as file name. Now create a new folder PNGs and save the PNG files there with the same name.</li>
		<li>Repeat this process for nuclei images.</li>
	</ol>
	</li>
	<li>Upload PNG image pairs into the image processing software for the analysis.
	<ol>
		<li>Create and validate the account. The authors have an account to enable open access to academic users.</li>
		<li>Validate the account by contacting the authors.</li>
		<li>Log into the software.</li>
		<li>Under the Data tab on the left, click Upload Batch.</li>
		<li>Import the images by dragging and dropping image pairs into the window that pops up and name the batch. Click OK.</li>
		<li>Check the box next to the batch name and click Analyze.</li>
		<li>On the next screen, scroll down and check the box next to Contractility Analysis and click Select. Lower down the page, select 10x as the magnification that was used for imaging from a drop-down menu.
		<ol>
			<li>Click Submit. Once the data analysis reads Completed, click on the batch name. On the next screen, click Download Data&#160;on the right side of the page. 
			NOTE: The downloaded files will contain images that were analyzed, summary results reporting average contraction in each image, and a detailed analysis of every micropattern that was detected in any image, reporting their sizes, positions, number of cells adhered, and contraction.</li>
			<li>Plot contraction values against drug concentrations to generate a concentration-response curve and determine the relative potencies of different treatments.</li>
		</ol>
		</li>
	</ol>
	</li>
</ol>

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(121), e55362 (2017).</li><li>Huang, Y., 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=Traction+force+microscopy+with+optimized+regularization+and+automated+Bayesian+parameter+selection+for+comparing+cells.">Traction force microscopy with optimized regularization and automated Bayesian parameter selection for comparing cells.</a> Scientific Reports. 9, 539 (2019).</li><li>Franck, C., Maskarinec, S. A., Tirrell, D. 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D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Metallization+and+biopatterning+on+ultra-flexible+substrates+via+dextran+sacrificial+layers.">Metallization and biopatterning on ultra-flexible substrates via dextran sacrificial layers.</a> PLOS ONE. 9, 106091 (2014).</li><li>Yoo, E. 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I.P. is an inventor on an issued patent family protecting the methods and systems of FLECS technology. I.P., Y.W., J.Z., E.C., and R.H. are all employees of Forcyte Biotechnologies, Inc. R.D. is a professor at UCLA and a cofounder of Forcyte Biotechnologies, Inc. I.P., Y.W., J.Z., and R.D. hold financial interests in Forcyte Biotechnologies, Inc., who is the exclusive licensee of the above patents and is commercializing FLECS Technology.

This simplified method to quantitatively measure contraction in hundreds of thousands of cells at a time under different treatment conditions and using only standard microscopy instruments provides an accessible alternative to traditional TFM for researchers to study cellular force biology. Because the presented technology provides a visual display of cell contraction by analyzing changes in regularly shaped fluorescent micropatterns, the magnitude of the contraction produced by any given cell is intuitively understood - the smaller the micropattern, the larger the contractile force exerted by the cell.
Notably, by offering control over factors such as shape, spread-area, and adhesion molecule comprising the micropatterns (all factors known to regulate cell contractility22,23,24), the presented technology systematically eliminates additional variables that may confound interpretations of cell contraction studies.
In this experiment, 10 kPa stiffness was used in the gel and a 70 &#181;m (diagonal length) micropattern was used comprised of type IV collagen. Besides these parameters, the adhesive molecule can be replaced with various collagens, fibronectin, gelatin, and other extracellular matrix (ECM). The stiffness of the gel can be tuned down to 0.1 kPa, and up into the MPa range. The micropattern geometry can be designed de novo to be any shape with minimal feature size of ~5 &#181;m. These parameters are decoupled and can be independently optimized for a particular biological context.
This technology has been extensively validated to be compatible with highly adhesive and contractile cell types of a mesenchymal phenotype including various smooth muscle cell types (primary human bladder, intestinal, tracheal, bronchial, uterine, aortic, and arterial), mesenchymal stem cells and their differentiated progeny, various fibroblasts (pulmonary, dermal, and cardiac), myofibroblasts, and endothelial cells. In addition, monocyte-derived macrophages will also produce large measurable phagocytic force on the micropatterns, particularly if the micropattern consists of a known opsonin. Various cancer lines can also be assayed using the method.
The method may pose some challenges for the use with cells that are either relatively small such as T-cells and neutrophils, or cell types with a predominantly epithelial phenotype. The main reason for this is that the method relies on strong adhesion and&#160;complete spreading of cells over the micropattern in order to generate the measurable contractile signal. Cells that bind weakly, bind to each other, or do not completely spread will not produce measurable contractile signals. These behaviors, which are relatively rare, can be mitigated by adjusting the micropattern size to be smaller, or by using alternative adhesive molecules within the micropatterns that will better promote adhesion and spreading in those cells.
Users of the technology must carefully evaluate different possible cell culture medium formulations for their particular cell type of interest, as different components, growth factors, serum levels, and pH sensitivities may drive variable behaviors in different cells. Optimization of the protocol should precede scaling of any experimental workflows, and media components should always be fresh, sterile, and consistent with prior batches.
Ultimately, if single-cell resolution is not necessary for a user&#39;s goals, or if the target cell type has minimal spreading capacity, then traditional TFM may be equally or more suitable for such experiments. The authors&#39; aim and hope is that this tool provides an additional avenue for cell biologists to study cellular contraction, particularly in the context of automated high-throughput phenotypic drug screens.
Specific to future uses in drug screens, higher throughput plates such as a 384-well FLECS plate may be used. In such plates, 4x objectives on many microscopes can capture an entire single well in their field of view, ensuring that all cellular contractile responses are captured. By using a high-throughput imaging system, an entire 384-well plate can be imaged in approximately 5 min, making this system dramatically faster than other options, and, therefore, suitable for high-throughput phenotypic drug discovery. Indeed, the authors routinely run weekly drug screens on ~50 384-wellplates (totaling more than 19,000 wells) using automation.

Cell-generated mechanical forces are essential to proper function in various organs throughout the body such as the intestines, bladder, heart, and others. These organs must generate stable patterns of cell contraction and relaxation to maintain the internal homeostatic state. Abnormal smooth muscle cell (SMC) contraction can lead to the onset of various disorders, including, for example, intestinal dysmotility, characterized by abnormal patterns of intestinal smooth muscle contraction1, as well as the urologic conditions of overactive2 or underactive bladder3. Within the airways, SMCs that exhibit irregular contraction patterns can trigger asthmatic hyperresponsiveness4, potentially tightening the airways and decreasing airflow of oxygen into the lungs. Another widespread physical condition, hypertension, is caused by fluctuations in the smooth muscle contraction within blood vessels5. Clearly, contractile mechanisms within cells and tissues can lead to diseases that require treatment options. As these conditions unmistakably stem from the dysfunctional contractile behaviors of cells, it becomes logical and necessary to measure the cell contractile function itself, when screening potential drug candidates.
Recognizing the need for tools to study cellular contractile force, several quantitative contraction assay methods have been developed by academic researchers including traction force microscopy (TFM)6, micropatterned TFM7, floating gel assays8, and elastomeric micropost assays9. These technologies have been utilized in single-dish format as well as multi-well-plate format in numerous studies and have even been proposed for three-dimensional force measurements10,11,12,13,14. While these technologies have enabled pioneering research within the expansive field of cell force biology, they have all been largely limited to labs possessing specific capabilities and resources, in particular: ability to fabricate TFM substrates, ability to properly apply complex and non-intuitive algorithms to solve TFM displacement maps, and relatively precise microscopy systems that can register images taken before and after sample removal from the stage (for cell dissociation). Thus, for an untrained researcher, the entry barrier to use these methods can be quite high given the extensive set of requirements to apply these technologies. In addition, the imaging resolution required for many existing technologies (40x objectives or greater) can significantly limit experimental throughput, while bulk measurement technologies could mask contributions from outlier cells and prevent discovery of milder contractile differences. Of note, as far as the authors are aware, only the low-throughput and semi-quantitative floating gel assay approach has matured sufficiently to become available to researchers (see Figure 1).
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/63211/63211fig01.jpg" /> 
Figure 1: Overall schematic of the FLECS Technology method. (A) Cells are adhered to adhesive protein micropatterns that are covalently embedded into a thin elastomeric layer supported by glass. (B) Top-view of various possible micropattern shapes and a blow-up of a cell contracting an &#39;X&#39;-shaped micropattern. (C) Overlay of fluorescent micropatterns and phase contrast images of a contracting cell. (D) Time-course images of a single contracting cell. Scale bars = 25 &#181;m. This figure was adapted with permission from Pushkarsky et al15. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/63211/63211fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Following recent advances in microtechnology, the authors developed a microplate-based technology enabling quantitative measurements of single-cell contraction in hundreds of thousands of cells called FLECS (fluorescently labelled elastomeric contractible surfaces)15,16,17,18,19,20,&#160;as an alternative to TFM. In this approach, fluorescent protein micropatterns are embedded into soft films which deform and shrink when cells apply traction forces to them, in an intuitive and measurable manner. Importantly, the protein micropatterns constrain cell position, shape, and spread area, leading to uniform test conditions. These allow simple measurements based only on their dimensional changes, which are highly resolved spatially even in 4x magnification images. The method includes a browser-based image analysis module and enables straightforward analysis of contractile cell force without requiring delicate handling procedures or registration of fiduciary markers, such that it should be operable by any researcher with a basic cell culture facility and simple fluorescent microscope with low magnification (Figure 2). This technology, which is shelf-ready and commercially available, was designed with the end-user in mind and aims to reduce the entry barrier for any laboratory scientist to study cellular force biology.
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/63211/63211fig02.jpg" /> 
Figure 2: Schematic of the 24-well plate format for the single-cell contractility assay. This format was used in the experiments described herein and depicted in the video portion of the article. Scale bars = 25 &#181;m. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/63211/63211fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
In this work, we present a protocol for applying the 24 well plate format of the FLECS Technology platform to quantify the effects of force-modulating drugs on cellular contractility in primary bladder smooth muscle cells. This general-purpose protocol can be adapted and modified as needed to account for various other timescales, cell-types, and treatment conditions of interest, and scaled to answer other questions in force biology.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Bladder smooth muscle cell culture</td>
			<td>Sciencell</td>
			<td>#4310</td>
			<td></td>
		</tr>
		<tr>
			<td>Blebbistatin</td>
			<td>Sigma-Aldrich</td>
			<td>B0560</td>
			<td></td>
		</tr>
		<tr>
			<td>Cell culture media</td>
			<td>Thermofisher</td>
			<td>11765054</td>
			<td>Ham&#39;s F12 medium supplemented with 10% FBS and 1% p/s</td>
		</tr>
		<tr>
			<td>Cell strainer</td>
			<td>Fisher Scientific</td>
			<td>7201432</td>
			<td></td>
		</tr>
		<tr>
			<td>Conical Tube</td>
			<td>Fisher Scientific</td>
			<td>05-539-13</td>
			<td></td>
		</tr>
		<tr>
			<td>Culture flask</td>
			<td>Fisher Scientific</td>
			<td>&#160;FB012941</td>
			<td></td>
		</tr>
		<tr>
			<td>Cytochalasin D</td>
			<td>Sigma-Aldrich</td>
			<td>C8273</td>
			<td></td>
		</tr>
		<tr>
			<td>DMSO (Dimethyl sulfoxide)</td>
			<td>Fisher Scientific</td>
			<td>D1284</td>
			<td></td>
		</tr>
		<tr>
			<td>Eppendorf tubes</td>
			<td>Fisher Scientific</td>
			<td>05-402-31</td>
			<td></td>
		</tr>
		<tr>
			<td>Fluorescent microscope</td>
			<td>Molecular Devices</td>
			<td>ImageXpress Confocal</td>
			<td></td>
		</tr>
		<tr>
			<td>Forcyte-manufactured 24-well plate</td>
			<td>Forcyte Biotechnologies</td>
			<td>24-HC4R-X1-QB12</td>
			<td></td>
		</tr>
		<tr>
			<td>Hoescht 3342 Live Nuclear Stain</td>
			<td>Thermofisher</td>
			<td>62249</td>
			<td></td>
		</tr>
		<tr>
			<td>Phosphate Buffered Saline (PBS)</td>
			<td>Fisher Scientific</td>
			<td>BP39920</td>
			<td></td>
		</tr>
	</tbody>
</table>

simplified, high-throughput analysis of single-cell contractility using micropatterned elastomers

Cellular contractile force generation is a fundamental trait shared by virtually all cells. These contractile forces are crucial to proper development, function at both the cellular and tissue levels,and regulate the mechanical systems in the body. Numerous biological processes are force-dependent, including motility, adhesion, and division of single-cells, as well as contraction and relaxation of organs such as the heart, bladder, lungs, intestines, and uterus. Given its importance in maintaining proper physiological function, cellular contractility can also drive disease processes when exaggerated or disrupted. Asthma, hypertension, preterm labor, fibrotic scarring, and underactive bladder are all examples of mechanically driven disease processes that could potentially be alleviated with proper control of cellular contractile force. Here, we present a comprehensive protocol for utilizing a novel microplate-based contractility assay technology known as fluorescently labeled elastomeric contractible surfaces (FLECS), that provides simplified and intuitive analysis of single-cell contractility in a massively scaled manner. Herein, we provide a step-wise protocol for obtaining two six-point dose-response curves describing the effects of two contractile inhibitors on the contraction of primary human bladder smooth muscle cells in a simple procedure utilizing just a single FLECS assay microplate, to demonstrate proper technique to users of the method. Using FLECS Technology, all researchers with basic biological laboratories and fluorescent microscopy systems gain access to studying this fundamental but difficult-to-quantify functional cell phenotype, effectively lowering the entry barrier into the field of force biology and phenotypic screening of contractile cell force.

Regions of the images acquired from wells that were treated with DMSO only and those that were treated with 40 &#181;M blebbistatin are shown side-by-side in Figure 3. It can be clearly observed that DMSO-only treated cells exhibit a significant level of contraction based on the very prominent deformations of the micropatterns adhered to by bladder smooth muscle cells (BSMCs) in that well. Conversely, in the image of the well treated with 40 &#181;M blebbistatin, significant cell relaxation is observed7 as the micropatterns adhered to by BSMCs are nearly indistinguishable in size from the micropatterns that are not adhered to by cells, indicating minimal contraction. These images demonstrate the intuitive and clear visual representation of single-cell contractility offered by the fluorescent micropatterning method. Unlike TFM-based methods, where the omnidirectional movement of numerous fluorescent particles randomly distributed beneath a dense cell monolayer is meant to convey relative contractile force, here, the uniform and marked contracted geometries of the micropatterns provide immediate and easily interpretable qualitative information about contraction of individual cells. These can be directly quantified by applying standard binary object operations on the images.
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/63211/63211fig03.jpg" /> 
Figure 3: Side-by-side comparisons of images taken of wells containing either only 1% DMSO treatment (left) or containing 40 &#181;M of blebbistatin (right). It can be clearly observed that treatment with blebbistatin significantly reduces the contractility of the single cells as indicated by the larger, un-contracted micropatterns. Blue nuclei indicate which micropatterns are bound by cells. Scale bar = 25 &#181;m. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/63211/63211fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
By applying the browser-based analysis module to analyze the acquired image pairs of micropatterns and cell nuclei, single-cell contractility distributions are obtained for each population as shown in Figure 4. Described in detail in a prior report on the FLECS methodology15, the analysis works by locating the positions and orientations of each &#34;X&#34; shaped micropattern, counting the number of nuclei adhered directly over the center of each micropattern, computing the mean length of each micropattern, and calculating the pixel distance of the contraction of each micropattern with respect to the mean length of empty micropatterns (zero contraction reference). Therefore, the empty micropatterns serve an important purpose for normalizing the contraction data. Importantly, cells that do not bind to the micropatterns will accumulate on the well boundaries due to microcurrents where they will not affect image analysis. As seen in these plots, the unperturbed contractility of the cell population treated only with DMSO controls spans a large range as high as 20 pixels, with a center found at around 10 pixels. Meanwhile, cells treated with blebbistatin contract significantly less and their distribution is pushed down to a center of just over 6 pixels. Importantly, every single micropattern found in the image that binds exactly on cell is represented in these distributions. This demonstrates the ability of the method to convey differential cellular responses to drug treatments.
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/63211/63211fig04.jpg" /> 
Figure 4: Histograms depicting single-cell contractility data obtained from the analysis of images taken of wells containing 1% DMSO only (blue) or 40&#181;M blebbistatin. The distribution of DMSO-treated cells is broad and centered at a much larger contraction value (~10 pixels) than the blebbistatin treated distribution, demonstrating the quantitative effects of treatment of cells with blebbistatin. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/63211/63211fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
By utilizing all of the wells on a single 24-well plate and imaging at least 3 sites per well, six-point dose-response curves are simultaneously generated for two drug compounds. Figure 5 shows the concentration-response data for BSMCs treated with the same range of doses of blebbistatin or cytochalasin D (both known contractility inhibitors). As evident from the concentration-response profiles, cytochalasin D is the more potent inhibitor of tonic contraction in these cells. By fitting a sigmoidal curve to the data points, IC50 values can be calculated for each drug. Our experiments indicate that the IC50 are 7.9 &#181;M and 100 nM for blebbistatin and cytochalasin D, respectively, following ~30 min of exposure to the drugs. Importantly, overall, these values are consistent with prior reports, validating the quantitative accuracy of the method to determine potency of contraction inhibitors7,21.
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/63211/63211fig05.jpg" /> 
Figure 5: Concentration-response curves depicting the effects of blebbistatin and cytochalasin D on cellular contractility in single-cells. Each data point comprises three images for that condition. A sigmoidal curve was fit to each set of data. The results indicate that cytochalasin D is more potent, having a lower IC50 value. This data is collectible from a single 24-well FLECS plate. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/63211/63211fig05large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Simplified, High-throughput Analysis of Single-cell Contractility using Micropatterned Elastomers at JoVE.com

Simplified, High-throughput Analysis of Single-cell Contractility using Micropatterned Elastomers

This work presents a flexible protocol for utilizing fluorescently labeled elastomeric contractible surfaces (FLECS) Technology in microwell format for simplified, hands-off quantification of single-cell contractile forces based on visualized displacements of fluorescent protein micropatterns.

Cellular contractile force generation is a fundamental trait shared by virtually all cells. These contractile forces are crucial to proper development, ...

simplified-high-throughput-analysis-single-cell-contractility-using

Nanyang Technological University

Research

JoVE Journal

Bioengineering

3.5K Views.  Forcyte Biotechnologies. This work presents a flexible protocol for utilizing fluorescently labeled elastomeric contractible surfaces (FLECS) Technology in microwell format for simplified, hands-off quantification of single-cell contractile forces based on visualized displacements of fluorescent protein micropatterns.

Video: Simplified, High-throughput Analysis of Single-cell Contractility using Micropatterned Elastomers

Improved Visualization and Quantitative Analysis of Drug Effects Using Micropatterned Cells

To date, most HCA (High Content Analysis) studies are carried out with adherent cell lines grown on a homogenous substrate in tissue-culture treated micro-plates. Under these conditions, cells spread and divide in all directions resulting in an inherent variability in cell shape, morphology and behavior. The high cell-to-cell variance of the overall population impedes the success of HCA, especially for drug development. The ability of micropatterns to normalize the shape and internal polarity of every individual cell provides a tremendous opportunity for solving this critical bottleneck 1-2.
To facilitate access and use of the micropatterning technology, CYTOO has developed a range of ready to use micropatterns, available in coverslip and microwell formats. In this video article, we provide detailed protocols of all the procedures from cell seeding on CYTOOchip micropatterns, drug treatment, fixation and staining to automated acquisition, automated image processing and final data analysis. With this example, we illustrate how micropatterns can facilitate cell-based assays. Alterations of the cell cytoskeleton are difficult to quantify in cells cultured on homogenous substrates, but culturing cells on micropatterns results in a reproducible organization of the actin meshwork due to systematic positioning of the cell adhesion contacts in every cell. Such normalization of the intracellular architecture allows quantification of even small effects on the actin cytoskeleton as demonstrated in these set of protocols using blebbistatin, an inhibitor of the actin-myosin interaction.

Adhesive micropatterns that normalize cellular architecture can be used to increase sensitivity in the detection of drug effects, improve reproducibility and simplify automated image acquisition and analysis. Such technology will benefit drug/siRNA screening assays, performed on conventional cell culture supports and consequently suffering from excessive cell-to-cell variability.

To date, most HCA (High Content Analysis) studies are carried out with adherent cell lines grown on a homogenous substrate in tissue-culture treated ...

Fabrication of Micropatterned Hydrogels for Neural Culture Systems using Dynamic Mask Projection Photolithography

Increasingly, patterned cell culture environments are becoming a relevant technique to study cellular characteristics, and many researchers believe in the need for 3D environments to represent in vitro experiments which better mimic in vivo qualities 1-3. Studies in fields such as cancer research 4, neural engineering 5, cardiac physiology 6, and cell-matrix interaction7,8have shown cell behavior differs substantially between traditional monolayer cultures and 3D constructs.
Hydrogels are used as 3D environments because of their variety, versatility and ability to tailor molecular composition through functionalization 9-12. Numerous techniques exist for creation of constructs as cell-supportive matrices, including electrospinning13, elastomer stamps14, inkjet printing15, additive photopatterning16, static photomask projection-lithography17, and dynamic mask microstereolithography18. Unfortunately, these methods involve multiple production steps and/or equipment not readily adaptable to conventional cell and tissue culture methods. The technique employed in this protocol adapts the latter two methods, using a digital micromirror device (DMD) to create dynamic photomasks for crosslinking geometrically specific poly-(ethylene glycol) (PEG) hydrogels, induced through UV initiated free radical polymerization. The resulting "2.5D" structures provide a constrained 3D environment for neural growth. We employ a dual-hydrogel approach, where PEG serves as a cell-restrictive region supplying structure to an otherwise shapeless but cell-permissive self-assembling gel made from either Puramatrix or agarose. The process is a quick simple one step fabrication which is highly reproducible and easily adapted for use with conventional cell culture methods and substrates.
Whole tissue explants, such as embryonic dorsal root ganglia (DRG), can be incorporated into the dual hydrogel constructs for experimental assays such as neurite outgrowth. Additionally, dissociated cells can be encapsulated in the photocrosslinkable or self polymerizing hydrogel, or selectively adhered to the permeable support membrane using cell-restrictive photopatterning. Using the DMD, we created hydrogel constructs up to ~1mm thick, but thin film (&lt;200 &mu;m) PEG structures were limited by oxygen quenching of the free radical polymerization reaction. We subsequently developed a technique utilizing a layer of oil above the polymerization liquid which allowed thin PEG structure polymerization.
In this protocol, we describe the expeditious creation of 3D hydrogel systems for production of microfabricated neural cell and tissue cultures. The dual hydrogel constructs demonstrated herein represent versatile in vitro models that may prove useful for studies in neuroscience involving cell survival, migration, and/or neurite growth and guidance. Moreover, as the protocol can work for many types of hydrogels and cells, the potential applications are both varied and vast.

Simple techniques are described for the rapid production of microfabricated neural culture systems using a digital micromirror device for dynamic mask projection lithography on regular cell culture substrates. These culture systems may be more representative of natural biological architecture, and the techniques described could be adapted for numerous applications.

Increasingly, patterned cell culture environments are becoming a relevant technique to study cellular characteristics, and many researchers believe in the ...

Polymer Microarrays for High Throughput Discovery of Biomaterials

The discovery of novel biomaterials that are optimized for a specific biological application is readily achieved using polymer microarrays, which allows a combinatorial library of materials to be screened in a parallel, high throughput format1. Herein is described the formation and characterization of a polymer microarray using an on-chip photopolymerization technique 2. This involves mixing monomers at varied ratios to produce a library of monomer solutions, transferring the solution to a glass slide format using a robotic printing device and curing with UV irradiation. This format is readily amenable to many biological assays, including stem cell attachment and proliferation, cell sorting and low bacterial adhesion, allowing the ready identification of 'hit' materials that fulfill a specific biological criterion3-5. Furthermore, the use of high throughput surface characterization (HTSC) allows the biological performance to be correlated with physio-chemical properties, hence elucidating the biological-material interaction6. HTSC makes use of water contact angle (WCA) measurements, atomic force microscopy (AFM), X-ray photoelectron spectroscopy (XPS) and time-of-flight secondary ion mass spectrometry (ToF-SIMS). In particular, ToF-SIMS provides a chemically rich analysis of the sample that can be used to correlate the cell response with a molecular moiety. In some cases, the biological performance can be predicted from the ToF-SIMS spectra, demonstrating the chemical dependence of a biological-material interaction, and informing the development of hit materials5,3.

A description of the formation of a polymer microarray using an on-chip photopolymerization technique. The high throughput surface characterization using atomic force microscopy, water contact angle measurements, X-ray photoelectron spectroscopy and time of flight secondary ion mass spectrometry and a cell attachment assay is also described.

The discovery of novel biomaterials that are optimized for a specific biological application is readily achieved using polymer microarrays, which allows a ...

High-throughput Protein Expression Generator Using a Microfluidic Platform

Rapidly increasing fields, such as systems biology, require the development and implementation of new technologies, enabling high-throughput and high-fidelity measurements of large systems. Microfluidics promises to fulfill many of these requirements, such as performing high-throughput screening experiments on-chip, encompassing biochemical, biophysical, and cell-based assays1. Since the early days of microfluidics devices, this field has drastically evolved, leading to the development of microfluidic large-scale integration2,3. This technology allows for the integration of thousands of micromechanical valves on a single device with a postage-sized footprint (Figure 1). We have developed a high-throughput microfluidic platform for generating in vitro expression of protein arrays (Figure 2) named PING (Protein Interaction Network Generator). These arrays can serve as a template for many experiments such as protein-protein 4, protein-RNA5 or protein-DNA6 interactions.
The device consist of thousands of reaction chambers, which are individually programmed using a microarrayer. Aligning of these printed microarrays to microfluidics devices programs each chamber with a single spot eliminating potential contamination or cross-reactivity Moreover, generating microarrays using standard microarray spotting techniques is also very modular, allowing for the arraying of proteins7, DNA8, small molecules, and even colloidal suspensions. The potential impact of microfluidics on biological sciences is significant. A number of microfluidics based assays have already provided novel insights into the structure and function of biological systems, and the field of microfluidics will continue to impact biology.

We present a microfluidic approach for the expression of protein arrays. The device consists of thousands of reaction chambers controlled by micro-mechanical valves. The microfluidic device is mated to a microarray-printed gene library. These genes are then transcribed and translated on-chip, resulting in a protein array ready for experimental use.

Rapidly increasing fields, such as systems biology, require the development and implementation of new technologies, enabling high-throughput and ...

High Throughput Single-cell and Multiple-cell Micro-encapsulation

Microfluidic encapsulation methods have been previously utilized to capture cells in picoliter-scale aqueous, monodisperse drops, providing confinement from a bulk fluid environment with applications in high throughput screening, cytometry, and mass spectrometry. We describe a method to not only encapsulate single cells, but to repeatedly capture a set number of cells (here we demonstrate one- and two-cell encapsulation) to study both isolation and the interactions between cells in groups of controlled sizes. By combining drop generation techniques with cell and particle ordering, we demonstrate controlled encapsulation of cell-sized particles for efficient, continuous encapsulation. Using an aqueous particle suspension and immiscible fluorocarbon oil, we generate aqueous drops in oil with a flow focusing nozzle. The aqueous flow rate is sufficiently high to create ordering of particles which reach the nozzle at integer multiple frequencies of the drop generation frequency, encapsulating a controlled number of cells in each drop. For representative results, 9.9 &mu;m polystyrene particles are used as cell surrogates. This study shows a single-particle encapsulation efficiency Pk=1 of 83.7% and a double-particle encapsulation efficiency Pk=2 of 79.5% as compared to their respective Poisson efficiencies of 39.3% and 33.3%, respectively. The effect of consistent cell and particle concentration is demonstrated to be of major importance for efficient encapsulation, and dripping to jetting transitions are also addressed. 
Introduction 
Continuous media aqueous cell suspensions share a common fluid environment which allows cells to interact in parallel and also homogenizes the effects of specific cells in measurements from the media. High-throughput encapsulation of cells into picoliter-scale drops confines the samples to protect drops from cross-contamination, enable a measure of cellular diversity within samples, prevent dilution of reagents and expressed biomarkers, and amplify signals from bioreactor products. Drops also provide the ability to re-merge drops into larger aqueous samples or with other drops for intercellular signaling studies.1,2 The reduction in dilution implies stronger detection signals for higher accuracy measurements as well as the ability to reduce potentially costly sample and reagent volumes.3 Encapsulation of cells in drops has been utilized to improve detection of protein expression,4 antibodies,5,6 enzymes,7 and metabolic activity8 for high throughput screening, and could be used to improve high throughput cytometry.9 Additional studies present applications in bio-electrospraying of cell containing drops for mass spectrometry10 and targeted surface cell coatings.11 Some applications, however, have been limited by the lack of ability to control the number of cells encapsulated in drops. Here we present a method of ordered encapsulation12 which increases the demonstrated encapsulation efficiencies for one and two cells and may be extrapolated for encapsulation of a larger number of cells.
To achieve monodisperse drop generation, microfluidic "flow focusing" enables the creation of controllable-size drops of one fluid (an aqueous cell mixture) within another (a continuous oil phase) by using a nozzle at which the streams converge.13 For a given nozzle geometry, the drop generation frequency f and drop size can be altered by adjusting oil and aqueous flow rates Qoil and Qaq. As the flow rates increase, the flows may transition from drop generation to unstable jetting of aqueous fluid from the nozzle.14 
When the aqueous solution contains suspended particles, particles become encapsulated and isolated from one another at the nozzle. For drop generation using a randomly distributed aqueous cell suspension, the average fraction of drops Dk containing k cells is dictated by Poisson statistics, where Dk = &lambda;k exp(-&lambda;)/(k!) and &lambda; is the average number of cells per drop. The fraction of cells which end up in the "correctly" encapsulated drops is calculated using Pk = (k x Dk)/&Sigma;(k' x Dk'). The subtle difference between the two metrics is that Dk relates to the utilization of aqueous fluid and the amount of drop sorting that must be completed following encapsulation, and Pk relates to the utilization of the cell sample. As an example, one could use a dilute cell suspension (low &lambda;) to encapsulate drops where most drops containing cells would contain just one cell. While the efficiency metric Pk would be high, the majority of drops would be empty (low Dk), thus requiring a sorting mechanism to remove empty drops, also reducing throughput.15
Combining drop generation with inertial ordering provides the ability to encapsulate drops with more predictable numbers of cells per drop and higher throughputs than random encapsulation. Inertial focusing was first discovered by Segre and Silberberg16 and refers to the tendency of finite-sized particles to migrate to lateral equilibrium positions in channel flow. Inertial ordering refers to the tendency of the particles and cells to passively organize into equally spaced, staggered, constant velocity trains. Both focusing and ordering require sufficiently high flow rates (high Reynolds number) and particle sizes (high Particle Reynolds number).17,18 Here, the Reynolds number Re =uDh/&nu; and particle Reynolds number Rep =Re(a/Dh)2, where u is a characteristic flow velocity, Dh [=2wh/(w+h)] is the hydraulic diameter, &nu; is the kinematic viscosity, a is the particle diameter, w is the channel width, and h is the channel height. Empirically, the length required to achieve fully ordered trains decreases as Re and Rep increase. Note that the high Re and Rep requirements (for this study on the order of 5 and 0.5, respectively) may conflict with the need to keep aqueous flow rates low to avoid jetting at the drop generation nozzle. Additionally, high flow rates lead to higher shear stresses on cells, which are not addressed in this protocol. The previous ordered encapsulation study demonstrated that over 90% of singly encapsulated HL60 cells under similar flow conditions to those in this study maintained cell membrane integrity.12 However, the effect of the magnitude and time scales of shear stresses will need to be carefully considered when extrapolating to different cell types and flow parameters. The overlapping of the cell ordering, drop generation, and cell viability aqueous flow rate constraints provides an ideal operational regime for controlled encapsulation of single and multiple cells.
Because very few studies address inter-particle train spacing,19,20 determining the spacing is most easily done empirically and will depend on channel geometry, flow rate, particle size, and particle concentration. Nonetheless, the equal lateral spacing between trains implies that cells arrive at predictable, consistent time intervals. When drop generation occurs at the same rate at which ordered cells arrive at the nozzle, the cells become encapsulated within the drop in a controlled manner. This technique has been utilized to encapsulate single cells with throughputs on the order of 15 kHz,12 a significant improvement over previous studies reporting encapsulation rates on the order of 60-160 Hz.4,15 In the controlled encapsulation work, over 80% of drops contained one and only one cell, a significant efficiency improvement over Poisson (random) statistics, which predicts less than 40% efficiency on average.12
In previous controlled encapsulation work,12 the average number of particles per drop &lambda; was tuned to provide single-cell encapsulation. We hypothesize that through tuning of flow rates, we can efficiently encapsulate any number of cells per drop when &lambda; is equal or close to the number of desired cells per drop. While single-cell encapsulation is valuable in determining individual cell responses from stimuli, multiple-cell encapsulation provides information relating to the interaction of controlled numbers and types of cells. Here we present a protocol, representative results using polystyrene microspheres, and discussion for controlled encapsulation of multiple cells using a passive inertial ordering channel and drop generation nozzle.

Combining monodisperse drop generation with inertial ordering of cells and particles, we describe a method to encapsulate a desired number of cells or particles in a single drop at kHz rates. We demonstrate efficiencies twice exceeding those of unordered encapsulation for single- and double-particle drops.

Microfluidic encapsulation methods have been previously utilized to capture cells in picoliter-scale aqueous, monodisperse drops, providing confinement ...

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 ...

Using Tomoauto: A Protocol for High-throughput Automated Cryo-electron Tomography

Cryo-electron tomography (Cryo-ET) is a powerful three-dimensional (3-D) imaging technique for visualizing macromolecular complexes in their native context at a molecular level. The technique involves initially preserving the sample in its native state by rapidly freezing the specimen in vitreous ice, then collecting a series of micrographs from different angles at high magnification, and finally computationally reconstructing a 3-D density map. The frozen-hydrated specimen is extremely sensitive to the electron beam and so micrographs are collected at very low electron doses to limit the radiation damage. As a result, the raw cryo-tomogram has a very low signal to noise ratio characterized by an intrinsically noisy image. To better visualize subjects of interest, conventional imaging analysis and sub-tomogram averaging in which sub-tomograms of the subject are extracted from the initial tomogram and aligned and averaged are utilized to improve both contrast and resolution. Large datasets of tilt-series are essential to understanding and resolving the complexes at different states, conditions, or mutations as well as obtaining a large enough collection of sub-tomograms for averaging and classification. Collecting and processing this data can be a major obstacle preventing further analysis. Here we describe a high-throughput cryo-ET protocol based on a computer-controlled 300kV cryo-electron microscope, a direct detection device (DDD) camera and a highly effective, semi-automated image-processing pipeline software wrapper library tomoauto developed in-house. This protocol has been effectively utilized to visualize the intact type III secretion system (T3SS) in Shigella flexneri minicells. It can be applicable to any project suitable for cryo-ET.

We present a protocol on how to utilize high-throughput cryo-electron tomography to determine high resolution in situ structures of molecular machines. The protocol permits large amounts of data to be processed, avoids common bottlenecks and reduces resource downtime, allowing the user to focus on important biological questions.

Cryo-electron tomography (Cryo-ET) is a powerful three-dimensional (3-D) imaging technique for visualizing macromolecular complexes in their native ...

A Microfluidic Platform for High-throughput Single-cell Isolation and Culture

Studying the heterogeneity of single cells is crucial for many biological questions, but is technically difficult. Thus, there is a need for a simple, yet high-throughput, method to perform single-cell culture experiments. Here, we report a microfluidic chip-based strategy for high-efficiency single-cell isolation (~77%) and demonstrate its capability of performing long-term single-cell culture (up to 7 d) and cellular heterogeneity analysis using clonogenic assay. These applications were demonstrated with KT98 mouse neural stem cells, and A549 and MDA-MB-435 human cancer cells. High single-cell isolation efficiency and long-term culture capability are achieved by using different sizes of microwells on the top and bottom of the microfluidic channel. The small microwell array is designed for precisely isolating single-cells, and the large microwell array is used for single-cell clonal culture in the microfluidic chip. This microfluidic platform constitutes an attractive approach for single-cell culture applications, due to its flexibility of adjustable cell culture spaces for different culture strategies, without decreasing isolation efficiency.

Here, we present a protocol for isolating and culturing single cells with a microfluidic platform, which utilizes a new microwell design concept to allow for high-efficiency single cell isolation and long-term clonal culture.

Studying the heterogeneity of single cells is crucial for many biological questions, but is technically difficult. Thus, there is a need for a simple, yet ...

High-throughput Identification of Bacteria Repellent Polymers for Medical Devices

Medical devices are often associated with hospital-acquired infections, which place enormous strain on patients and the healthcare system as well as contributing to antimicrobial resistance. One possible avenue for the reduction of device-associated infections is the identification of bacteria-repellent polymer coatings for these devices, which would prevent bacterial binding at the initial attachment step. A method for the identification of such repellent polymers, based on the parallel screening of hundreds of polymers using a microarray, is described here. This high-throughput method resulted in the identification of a range of promising polymers that resisted binding of various clinically relevant bacterial species individually and also as multi-species communities. One polymer, PA13 (poly(methylmethacrylate-co-dimethylacrylamide)), demonstrated significant reduction in attachment of a number of hospital isolates when coated onto two commercially available central venous catheters. The method described could be applied to identify polymers for a wide range of applications in which modification of bacterial attachment is important.

A high-throughput microarray method for the identification of polymers which reduce bacterial surface binding on medical devices is described.

Medical devices are often associated with hospital-acquired infections, which place enormous strain on patients and the healthcare system as well as ...

A High-throughput Cell Microarray Platform for Correlative Analysis of Cell Differentiation and Traction Forces

Microfabricated cellular microarrays, which consist of contact-printed combinations of biomolecules on an elastic hydrogel surface, provide a tightly controlled, high-throughput engineered system for measuring the impact of arrayed biochemical signals on cell differentiation. Recent efforts using cell microarrays have demonstrated their utility for combinatorial studies in which many microenvironmental factors are presented in parallel. However, these efforts have focused primarily on investigating the effects of biochemical cues on cell responses. Here, we present a cell microarray platform with tunable material properties for evaluating both cell differentiation by immunofluorescence and biomechanical cell&#8211;substrate interactions by traction force microscopy. To do so, we have developed two different formats utilizing polyacrylamide hydrogels of varying Young&#39;s modulus fabricated on either microscope slides or glass-bottom Petri dishes. We provide best practices and troubleshooting for the fabrication of microarrays on these hydrogel substrates, the subsequent cell culture on microarrays, and the acquisition of data. This platform is well-suited for use in investigations of biological processes for which both biochemical (e.g., extracellular matrix composition) and biophysical (e.g., substrate stiffness) cues may play significant, intersecting roles.

Cell differentiation is regulated by a host of microenvironmental factors, including both matrix composition and substrate material properties. We describe here a technique utilizing cell microarrays in conjunction with traction force microscopy to evaluate both cell differentiation and biomechanical cell&#8211;substrate interactions as a function of microenvironmental context.

Microfabricated cellular microarrays, which consist of contact-printed combinations of biomolecules on an elastic hydrogel surface, provide a tightly ...