This work was supported by grants from La Fondation Yves Cotrel de l'Institut de France, Paris, France (to Dr. Moreau), The Canadian Institutes of Health Research (grant PP2-99466 to Dr. Moreau) and from Fourth Dimension Spine LLC, New York, USA (Research grant to Dr. Moreau).

The entire procedure is carried out under the sterile biological hood and all solutions and equipment coming into contact with cells must be sterile.
1. Preparation of Essential Solutions
<ol>
	<li>Prepare solutions according to Table 1. </li>
	<li>Keep balanced salt solution (BSS) at room temperature and all other solutions at 4 &#176;C until the time of use.</li>
	<li>Warm cold media to 37 &#176;C in the water bath for a few minutes before using.</li>
</ol>
2. Preparation and Storage of PBMCs
<ol>
	<li>Collect 10 ml of whole blood in EDTA-treated collection tubes to prepare two aliquots of PBMCs using 5 ml for each aliquot.</li>
	<li>Transfer 5 ml of whole blood from the EDTA-treated collection tube to a 50 ml tube.</li>
	<li>Add an equal volume of BSS and mix sample by gentle pipetting up and down.</li>
	<li>Place 3 ml of Ficoll in two 15 ml Falcon tubes.</li>
	<li>Carefully layer 4.5 ml of diluted blood mixture over the Ficoll in each tube.</li>
	<li>Let the tubes rest for up to 5 min to favor a clear separation of the blood and Ficoll.</li>
	<li>Centrifuge the tubes at 400 x g for 30 min at room temperature with no brake.</li>
	<li>Carefully remove the tubes from the centrifuge so as to not disturb the layering. The PBMCs are visible at the BSS/Ficoll interface.</li>
	<li>Harvest the cloudy layer of PBMCs at the interface of both tubes with a pipette and transfer to a new 50 ml tube.</li>
	<li>Add 20 ml of complete media.</li>
	<li>Centrifuge the tube at 288 x g for 7 min at room temperature.</li>
	<li>Remove the supernatant by aspiration.</li>
	<li>Resuspend the cell pellet in 500 &#956;l of supplementary media.</li>
	<li>Add an equal volume of freezing media.</li>
	<li>Transfer the cell suspension to a cryovial.</li>
	<li>Place the cryovial into a cryofreezing container with isopropanol.</li>
	<li>Store the freezing container at -80 &#176;C overnight.</li>
	<li>Transfer the frozen PBMCs aliquot to liquid nitrogen for long-term storage.</li>
</ol>
3. Functional Assay
1. Day 1
<ol>
	<li>Place aliquot from liquid nitrogen in water bath at 37 &#176;C for a minute or until defrosted.</li>
	<li>Transfer the cell suspension to a 50 ml tube with a sterile pipette.</li>
	<li>Add 15 ml of complete media and spin the cells down at 200 x g for 5 min at room temperature.</li>
	<li>Remove the supernatant by aspiration.</li>
	<li>Gently suspend cell pellet in 1 ml of PHA media.</li>
	<li>Complete the volume to 20 ml with the same media.</li>
	<li>Cap the tube loosely to allow air to enter.</li>
	<li>Leave the tube overnight at 37 &#176;C in a CO2 incubator to allow quiescent lymphocytes to transform into rapidly-proliferating lymphoblasts.</li>
</ol>
2. Day 2
<ol>
	<li>Take the tube out of the incubator, screw the caps completely and spin the cells down at 200 x g for 5 min at room temperature.</li>
	<li>Remove the supernatant by aspiration.</li>
	<li>Gently suspend cell pellet in 1 ml of complete media.</li>
	<li>Complete the volume to 20 ml with the same media.</li>
	<li>Cap the tube loosely to allow air to enter.</li>
	<li>Leave the tube overnight at 37 &#176;C in a CO2 incubator to expand cell numbers.</li>
</ol>
3. Day 3
<ol>
	<li>Get the tube out of the incubator, screw the caps completely and spin the cells down at 200 x g for 5 min at room temperature.</li>
	<li>Remove the supernatant by aspiration.</li>
	<li>Wash cells twice with 10 ml of RPMI-1640 by centrifugation at 200 x g for 5 min at room temperature.</li>
	<li>Gently resuspend the cell pellet in 600 &#956;l of RPMI-1640.</li>
	<li>Measure the cell concentration and viability, using an automated cell counter and viability analyzer.</li>
	<li>Add appropriate volume of RPMI-1640 to adjust to a cell concentration of 1.5 x 105 cells/20 &#956;l.</li>
	<li>Treat cells with recombinant OPN (rOPN) or vehicle (PBS) in 1.5 ml of Eppendorf tubes.
	<ol>
		<li>Transfer 100 &#956;l of cell suspension to two sterile 1.5 ml Eppendorf tubes.</li>
		<li>Add rOPN in one tube to a final concentration of 0.5 &#956;g/ml.</li>
		<li>Add an equal volume of PBS in the second tube.</li>
		<li>Gently mix each condition by pipetting up and down twice using a sterile pipette set at 100 &#956;l.</li>
	</ol>
	</li>
	<li>Prepare the small sample 96-well microplate.
	<ol>
		<li>Add 5 &#956;l of RPMI-1640 to each well.</li>
		<li>Centrifuge the plate at 200 x g for 3 min to remove any air bubbles.</li>
	</ol>
	</li>
	<li>Seed the untreated cells as well as cells treated with rOPN or PBS.
	<ol>
		<li>Before transferring cells from tube to microplate, gently pipette up and down once to ensure a uniform suspension of cells.</li>
		<li>Add 40 &#956;l of cell suspension per well in quadruplicate for untreated cells, in duplicate for rOPN or PBS treated cells. Refer to Figure 1 for the design. This design allows 12 patients to be tested on the same microplate.</li>
		<li>Leave the cell plate under the sterile hood for 5 min to allow cells to rest and settle evenly to the bottom of the well before placing in the incubator.</li>
	</ol>
	</li>
	<li>Incubate the plate for 18 hr at 37 &#176;C in a CO2 incubator to optimize the effect of OPN.</li>
</ol>
4. Day 4
<ol>
	<li>Run the plate with compounds.
	<ol>
		<li>Take the plate out of the incubator and leave it at RT for around 30 min.</li>
		<li>Prepare 1 ml of 100 &#956;M of somatostatin and isoproterenol in RPMI-1640 by adding 10 &#956;l of stock solution (10 mM) in 990 &#956;l of RPMI-1640.</li>
		<li>Fill the compound plate by dispensing 20 &#956;l in appropriate wells as indicated in Figure 2.</li>
		<li>Cover the compound plate with a precut pierceable seal to avoid change in compound concentration due to evaporation before or during incubation in the CDS-based system.</li>
		<li>Load cell plate, pipette tips, and compound plate into the CDS-based system.</li>
		<li>Name the plate in the CDS-based instrument software.</li>
		<li>Select the appropriate protocol. The protocol edited for the classification with PBMCs is called &#39;Agonist Non-adherent cells Small Sample Plate RT 15 min&#39;. Go to the protocol box and select this protocol in the list of protocols</li>
		<li>Initiate the protocol by clicking on &#39;Start&#39;.</li>
		<li>The integrated fluidics system simultaneously adds the compounds to all wells by injecting 5 &#956;l per well to achieve a final concentration of 10 &#956;M in a total volume of 50 &#956;l.</li>
		<li>The CDS-based system automatically collects the data for 15 min after compound addition.</li>
	</ol>
	</li>
	<li>Data analysis
	<ol>
		<li>Select low and high ranges of frequencies to use when calculating extracted values for the nonadherent cells.</li>
		<li>Select drift correction to correct the linear change in baseline impedance measurements over time.</li>
		<li>Select data filtering to reduce variations in the kinetic response measurement due to electronic noise and compound addition.</li>
		<li>Select the Max-Min method for the full analysis time.</li>
		<li>Export data to Excel under the plate format option.</li>
		<li>Calculate delta G (&#916;G) by subtracting the average of response magnitude to Gi stimulation (RmGi) from the average of response magnitude to Gs stimulation (RmGs) using the following formula: 
		&#916;G = RmGi - RmGs</li>
		<li>Calculate the percentage of the fold effect (Fe) of OPN on Gi-mediated response by dividing the average of response magnitude to Gi stimulation in the presence of OPN (RmGiOPN) with the average of response magnitude to Gi stimulation in the presence of PBS (RmGiPBS) using the following formula: 
		Fe = 100 x (RmGiOPN/RmGiPBS)</li>
		<li>Refer to Table 2 to classify patients.</li>
	</ol>
	</li>
</ol>

<ol>
	<li>Kane, W. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Prevalence:+a+call+for+a+statement+of+terms.">Prevalence: a call for a statement of terms.</a> Clin Orthop. Relat Res. 126, 43-46 (1977).</li><li>Bunnell, W. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Selective+screening+for+scoliosis.">Selective screening for scoliosis.</a> Clin Orthop Relat Res. 434, 40-45 (2005).</li><li>Asher, M. A., Burton, D. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Adolescent+idiopathic+scoliosis:+natural+history+and+long+term+treatment+effects.">Adolescent idiopathic scoliosis: natural history and long term treatment effects.</a> Scoliosis. 1 (1), 2 (2006).</li><li>Fong, D. 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=A+meta-analysis+of+the+clinical+effectiveness+of+school+scoliosis+screening.">A meta-analysis of the clinical effectiveness of school scoliosis screening.</a> Spine (Phila Pa 1976). 35 (10), 1061-1071 (2010).</li><li>Chowanska, J., Kotwicki, T., Rosadzinski, K., Sliwinski, Z. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=School+screening+for+scoliosis:+can+surface+topography+replace+examination+with+scoliometer?.">School screening for scoliosis: can surface topography replace examination with scoliometer?.</a> Scoliosis. 7 (9), 1748-7161 (2012).</li><li>Kim, H., 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=Scoliosis+imaging:+what+radiologists+should+know.">Scoliosis imaging: what radiologists should know.</a> Radiographics. 30 (7), 1823-1842 (2010).</li><li>Wong, H. K., Hui, J. H., Rajan, U., Chia, H. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Idiopathic+scoliosis+in+Singapore+schoolchildren:+a+prevalence+study+15+years+into+the+screening+program.">Idiopathic scoliosis in Singapore schoolchildren: a prevalence study 15 years into the screening program.</a> Spine. 30 (10), 1188-1196 (2005).</li><li>Nachemson, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+long+term+follow-up+study+of+non-treated+scoliosis.">A long term follow-up study of non-treated scoliosis.</a> Acta Scand. 39 (4), 466-476 (1968).</li><li>Enneking, W. F., Harrington, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Pathological+changes+in+scoliosis.">Pathological changes in scoliosis.</a> J. Joint Surg. 51 (1), 165-184 (1969).</li><li>Miller, N. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cause+and+natural+history+of+adolescent+idiopathic+scoliosis.">Cause and natural history of adolescent idiopathic scoliosis.</a> Orthop. Clin. North Am. 30 (3), 343-3452 (1999).</li><li>Nash, C. L., Gregg, E. C., Brown, R. H., Pillai, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Risks+of+exposure+to+X-rays+in+patients+undergoing+long-term+treatment+for+scoliosis.">Risks of exposure to X-rays in patients undergoing long-term treatment for scoliosis.</a> J. Bone Joint Surg. Am. 61 (3), 371-400 (1979).</li><li>Akoume, M. 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=Cell-based+screening+test+for+idiopathic+scoliosis+using+cellular+dielectric+spectroscopy.">Cell-based screening test for idiopathic scoliosis using cellular dielectric spectroscopy.</a> Spine. 35 (13), 601-608 (2010).</li><li>Verdonk, E., 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=Cellular+dielectric+spectroscopy:+a+label-free+comprehensive+platform+for+functional+evaluation+of+endogenous+receptors.">Cellular dielectric spectroscopy: a label-free comprehensive platform for functional evaluation of endogenous receptors.</a> Assay Drug Dev. Technol. 4 (5), 609-6019 (2006).</li><li>Peters, M. F., 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=Evaluation+of+cellular+dielectric+spectroscopy,+a+whole-cell,+label-free+technology+for+drug+discovery+on+Gi-coupled+GPCRs.">Evaluation of cellular dielectric spectroscopy, a whole-cell, label-free technology for drug discovery on Gi-coupled GPCRs.</a> J. Biomol. Screen. 12 (3), 312-319 (2007).</li><li>Peters, M. F., Scott, C. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Evaluating+cellular+impedance+assays+for+detection+of+GPCR+pleiotropic+signaling+and+functional+selectivity.">Evaluating cellular impedance assays for detection of GPCR pleiotropic signaling and functional selectivity.</a> J. Biomol. Screen. 14 (3), 246-255 (2009).</li><li>Peters, M. F., Vaillancourt, F., Heroux, M., Valiquette, M., Scott, C. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparing+label-free+biosensors+for+pharmacological+screening+with+cell-based+functional+assays.">Comparing label-free biosensors for pharmacological screening with cell-based functional assays.</a> Assay Drug Dev. Technol. 8 (2), 219-227 (2010).</li><li>Akoume, M. 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=Disrupted+Gi-coupled+receptor+signaling+occurs+in+adolescent+idiopathic+scoliosis.">Disrupted Gi-coupled receptor signaling occurs in adolescent idiopathic scoliosis.</a> J. Clin. Invest. , (2013).</li></ol>

This work led to several patents hold by Sainte-Justine University Hospital and many others are pending in several countries. Fourth Dimension Spine LLC is the exclusive licensee of Sainte-Justine University Hospital.

We have described a detailed procedure of a cell-based prognostic test for idiopathic scoliosis that is applicable to peripheral blood mononuclear cells (PBMCs) freshly isolated or conserved frozen for up to one year in liquid nitrogen. Since using freshly isolated PBMCs is cumbersome when testing large number of individuals, the procedure was presented with frozen PBMCs that offer a more practical alternative in clinical setting. However, problems with cell clumping upon thawing were encountered when frozen PBMCs were initially used, leading sometimes to inter-assay variability. To maximize assay reproducibility, we recommend avoiding freeze-thaw cycle and using the frozen sample only once. The procedure is very simple, allowing for accurate detection of defective Gi protein function in a short time. Using this procedure, asymptomatic and scoliotic children can be easily classified to better predict their clinical outcome without any danger for their health. However, when performing classification according to the degree of maximum response to Gi stimulation relative to the healthy control subjects 12, several requirements for the control subjects should be met. Indeed, in order to have a proper comparison cohort, the control subjects must be age and gender matched, not be on any kind of medication, and provide private information, such as past individual/familial medical history. These requirements may constitute an important obstacle for the recruitment of control subjects. Therefore, performing classification by examining the degree of imbalance between response to Gi and Gs protein stimulation in the same individual is ideal to eliminate the necessity of using control subjects.
The use of the CDS-based system to perform this prognostic test is significant in terms of simultaneously providing Gi- and Gs-mediated cellular responses in the same assay. Although many patients can be classified with no ambiguity using the dynamic range fixed for this assay, a small number of patients will exhibit values at the borderline of ranges, as illustrated by the results of the present report. To discriminate these individuals, we have introduced the evaluation of the effect of OPN on response to Gi stimulation by demonstrating that OPN induces a differential effect on Gi-mediated cellular response among the three functional groups. Indeed, we found that in presence of OPN, response to Gi stimulation increases in FG1, while it decreases in FG2 and FG3, to a higher extent in FG2. Despite the high cost of OPN, the use of this chemokine is essential to distinguish ambiguous cases, and therefore improve the accuracy of our classification assay. However, this assay has a disadvantage in that a minimum of 1.5 x 105 cells per well is required to observe cellular response with the CDS-based system under our experimental conditions. Certain patient samples will not have a sufficient number of cells to be tested. In this case, it is necessary to recall the patients for additional blood collection, which can be worrisome for families and frustrating for the medical and laboratory staff. Prospective studies are planned in our laboratory to address this issue.
Nevertheless, the current protocol relies on simple and proven methods to prepare cells while the testing is automated using a validated label-free system 13, 14 to monitor the cells&#39; responses. The testing platform is relatively inexpensive when compared with genetic platform available for the prognosis of other diseases. Also, the cost of all the disposable materials, including the blood collection tubes, tips, the special electrode microplates, and conical and Eppendorf tubes, is not very expensive and is estimated at less than $3,000 to complete a testing for approximately one thousand patients. Though this estimate does not include labor costs for the preparation of samples and performing the test, this test remains considerably more affordable than next-generation sequencing platforms. Noteworthy, is not only the cost comparison to genetic platforms, but more specifically related to the field of AIS, is the costs associated to radiological imaging. Today, more than one million children in the USA and about 100,000 children in Canada are diagnosed with idiopathic scoliosis, and the total cost of diagnosis and monitoring of the scoliotic children by X-ray exposure is over 2.5 billion dollars annually in North America. Thus, our cell-based assay procedure would be expected to be suitable for routine screening and monitoring of children with idiopathic scoliosis without health risk and at lower cost.

Idiopathic scoliosis is a spine deformity of unknown cause generally defined as a lateral curvature greater than 10 degrees accompanied by a vertebral rotation1. The condition affects 4% of the pediatric population and is most commonly diagnosed between the ages of 9 to 13 years2,3,4. The diagnosis is primarily of exclusion and is made only after ruling out other causes of spinal deformity such as vertebral malformation, neuromuscular or syndromic disorders. Traditionally, the trunkal asymmetry is revealed by Adams forward bending test and measured with scoliometer during physical examination5. The diagnosis can then be confirmed by radiographic observation of the curve and the angle measurement using the Cobb method6.
Once diagnosed, the primary concern for physicians in managing scoliotic children is whether the curve will progress. Indeed, the curve progression is often unpredictable and is more frequently observed among girls than in boys7. If untreated, the curve can progress dramatically, creating significant physical deformity and even cardiopulmonary problems. These manifestations become life threatening when the curve exceeds 70&#176;&#160;8,9. The current treatment options to prevent or stop curve progression include bracing and surgery. In general, bracing is recommended for curves between 25-40&#176;, while surgery is reserved for curves greater than 45&#176; or unresponsive to bracing.
Approximately, 10% of children diagnosed with idiopathic scoliosis have curve progression requiring corrective surgery10. Currently, there is no proven method or test available to identify this category of patients. Consequently, all diagnosed children are subjected to multiple radiographs over several years, usually until they reach skeletal maturity. It is estimated that the typical patients with scoliosis will have approximately 22 radiological examinations over a 3-year period11. Because of the potential risk of multiple radiographic examinations, the alternative approaches that could allow performing the prognosis of idiopathic scoliosis without exposing children to ionizing radiation are strongly desirable. With the intention of meeting this need, we have previously developed a cell-based screening assay as a prognostic test to sooner identify the asymptomatic children at risk of developing idiopathic scoliosis. The test predicts the clinical outcome in both asymptomatic and affected children by examining the functional status of Gi proteins and classifying children into three functional groups (FG1, FG2 and FG3) according to the degree of maximum response to Gi protein stimulation12 as measured by CDS-based system. This system is largely used to assess signal transduction through G proteins in various cell types13,14,15,16. It yields information regarding the total integrated response of the cells to the external stimuli by measuring changes in impedance following the activation of cell surface receptors. Cells are seeded into microplates that contain electrodes at the bottom of the wells and the system applies a small voltage that induce extracellular and transcellular currents. Following compound injection into the well, cell surface receptors are stimulated and signal transduction events occur, leading to cellular changes that affect the flow of extracellular and transcellular currents, and thereby affect the measured magnitude. With this approach, the scoliotic patients and children more at risk of developing scoliosis are less responsive to Gi protein stimulation when compared with healthy control subjects, and the classification is based on the percentage of degree of reduction relative to control group. The classification ranges are fixed between 10 and 40% for FG3, 40 and 60% for FG2, and 60 and 90% for FG112.
More recently, we have modified this approach by demonstrating that the three functional groups can clearly be distinguished according to the profile of imbalance between response to Gi and Gs stimulation. Indeed, we found that response to Gi stimulation predominated in FG3, while no apparent imbalance was observed in FG2. In contrast, FG1 exhibited predominance for response to Gs stimulation. In addition, we have provided the evidence that patients belonging to FG2 are more at risk of progressing to the point of needing surgery17. The precision of this classification test has further been improved by demonstrating a differential effect of osteopontin (OPN) on response to Gi stimulation among functional groups.
Here we document the detailed steps of experimental and analytical procedures of this functional test as currently performed in our laboratory.

<table><tbody><tr><td colspan="4">&lt;strong&gt;Materials&lt;/strong&gt;</td></tr><tr><td>RPMI</td><td>Wisent, Inc</td><td>350-005-CL</td><td></td></tr><tr><td>FBS</td><td>Therno Scientific Hyclone</td><td>SH3007103</td><td></td></tr><tr><td>DMSO</td><td>Sigma Aldrich</td><td>D2650</td><td></td></tr><tr><td>Ficoll-Plaque Plus</td><td>GE Healthcare</td><td>17144003</td><td></td></tr><tr><td>Antibiotic-Antimycotic</td><td>Invitrogen</td><td>15240-062</td><td></td></tr><tr><td>Phytohemagglutinin</td><td>Invitrogen (Gibco)</td><td>10576-015</td><td></td></tr><tr><td>Recombinant Human Osteopontin</td><td>R&amp;amp;D Systems, Inc</td><td>1433-OP/CF</td><td></td></tr><tr><td>Somatostatin</td><td>Tocris</td><td>1157</td><td></td></tr><tr><td>Isoproterenol</td><td>Tocris</td><td>1743</td><td></td></tr><tr><td>PBS</td><td>Wisent, Inc</td><td>311-010-CL</td><td></td></tr><tr><td>Sterile pipette tips</td><td>Axygen Scientific</td><td>301-06-451</td><td></td></tr><tr><td>Sterile Eppendorf tubes</td><td>Ultident</td><td>24-MCT-150-C</td><td></td></tr><tr><td>50 ml conical tubes</td><td>VWR International</td><td>89039-658</td><td></td></tr><tr><td>Cellkey small sample 96W microplate</td><td>Molecular Devices</td><td>1026496</td><td></td></tr><tr><td>Cellkey tips</td><td>Cybio</td><td>OL3800-25-559N</td><td></td></tr><tr><td>Precut pierceable seals</td><td>Excel Scientific, Inc</td><td>XP-100</td><td></td></tr><tr><td colspan="4">&lt;strong&gt;Equipment&lt;/strong&gt;</td></tr><tr><td>Vicell XR</td><td>Beckman Coulter</td><td>731050</td><td>Automated cell counter</td></tr><tr><td>Cell culture hood</td><td>Forma Scientific</td><td>1284</td><td>Class II</td></tr><tr><td>Liquid nitrogen storage</td><td>Thermo Scientific</td><td>CY5093570</td><td></td></tr><tr><td>Water bath</td><td>VWR International</td><td>89032-204</td><td></td></tr><tr><td>Standard light microscope</td><td>Leica Microsystems</td><td>DMIL LED</td><td></td></tr><tr><td>Cell culture incubator</td><td>Thermo Scientific</td><td>51019557</td><td>5% CO&lt;sub&gt;2&lt;/sub&gt; at 37 &amp;deg;C</td></tr><tr><td>Low speed centrifuge</td><td>Thermo Scientific</td><td>75004364</td><td></td></tr><tr><td>Cellkey system</td><td>Molecular Devices</td><td>1019185</td><td>CDS-based instrument</td></tr></tbody></table>

cell-based assay protocol for the prognostic prediction of idiopathic scoliosis using cellular dielectric spectroscopy

This protocol details the experimental and analytical procedure for a cell-based assay developed in our laboratory as a functional test to predict the prognosis of idiopathic scoliosis in asymptomatic and affected children. The assay consists of the evaluation of the functional status of Gi and Gs proteins in peripheral blood mononuclear cells (PBMCs) by cellular dielectric spectroscopy (CDS), using an automated CDS-based instrument, and the classification of children into three functional groups (FG1, FG2, FG3) with respect to the profile of imbalance between the degree of response to Gi and Gs proteins stimulation. The classification is further confirmed by the differential effect of osteopontin (OPN) on response to Gi stimulation among groups and the severe progression of disease is referenced by FG2. Approximately, a volume of 10 ml of blood is required to extract PBMCs by Ficoll-gradient and cells are then stored in liquid nitrogen. The adequate number of PBMCs to perform the assay is obtained after two days of cell culture. Essentially, cells are first incubated with phytohemmaglutinin (PHA). After 24 hr incubation, medium is replaced by a PHA-free culture medium for an additional 24 hr prior to cell seeding and OPN treatment. Cells are then spectroscopically screened for their responses to somatostatin and isoproterenol, which respectively activate Gi and Gs proteins through their cognate receptors. Both somatostatin and isoproterenol are simultaneously injected with an integrated fluidics system and the cells&#39; responses are monitored for 15 min. The assay can be performed with fresh or frozen PBMCs and the procedure is completed within 4 days.

Cell viability was comparable among all samples with values consistent in the range of 86 and 96%. In contrast, high variations were noted in cell numbers among samples (Table 3). Of the 32 samples used, two had insufficient number of cells and have not been classified. An example of results of the functional classification according to the degree of imbalance between Gi and Gs signaling is showed in Figure 3. The vertical axis of this figure is divided into three sections delineating the functional groups with dynamic ranges established as &#62; +10 for FG3, between +10 and -10 for FG2, and finally &#60; -10 for FG1. Among 30 patients tested here, 14, 6, and 5 patients were clearly classified into FG3, FG2, and FG1, respectively, while five patients, notably 345, 353, 370, 371, and 382, were at borderline of ranges. The evaluation of the OPN effect on response to Gi stimulation had revealed that OPN increased the response in patients 353 and 371. In contrast, response was reduced by more than 50% in patients 345 and 382 and by less than 50% in patient 370 following rOPN treatment. So, according to our classification criteria (Table 2), we were able to categorize patients 353 and 371 in FG1, patients 345 and 382 in FG2, and patient 370 in FG3. In parallel, all patients were screened for their response to Gi protein stimulation and compared to control subjects. As expected, all patients were less responsive than control subjects, and patients classified in the same functional group by our new procedure exhibited similar levels of the maximum response (Figure 5). Moreover, disparity between patients of each functional group was consistent with our classical range of classification 12, validating our new procedure. The classification of a large cohort of scoliotic patients regularly followed in our special clinic at Sainte-Justine Hospital has revealed that the three functional groups were similarly distributed among moderate cases, while the FG2 was predominant among severe cases (Figure 6), identifying patients categorized into this functional group as more at risk for severe progression of the disease and indicating that this classification test can be useful in the prognosis of idiopathic scoliosis.
<table border="1">
	<tbody>
		<tr>
			<td rowspan="5">Solution A</td>
			<td>Anhydrous D-glucose</td>
			<td>0.1%</td>
		</tr>
		<tr>
			<td>CaCl2&#160;2H2O</td>
			<td>0.05 mM</td>
		</tr>
		<tr>
			<td>MgCl2</td>
			<td>0.98 mM</td>
		</tr>
		<tr>
			<td>KCl</td>
			<td>5.4 mM</td>
		</tr>
		<tr>
			<td>Tris</td>
			<td>145 mM</td>
		</tr>
		<tr>
			<td>Solution B</td>
			<td>NaCl</td>
			<td>140 mM</td>
		</tr>
		<tr>
			<td rowspan="2">Balanced Salt Solution (BSS)</td>
			<td>Solution A</td>
			<td>1 volume</td>
		</tr>
		<tr>
			<td>Solution B</td>
			<td>9 volume</td>
		</tr>
		<tr>
			<td rowspan="3">Complete media</td>
			<td>RPMI-1640</td>
			<td>500 ml</td>
		</tr>
		<tr>
			<td>Antibiotic-antimycotic</td>
			<td>1%</td>
		</tr>
		<tr>
			<td>FBS</td>
			<td>10%</td>
		</tr>
		<tr>
			<td rowspan="3">Supplementary media</td>
			<td>RPMI-1640</td>
			<td>50 ml</td>
		</tr>
		<tr>
			<td>Antibiotic-antimycotic</td>
			<td>1%</td>
		</tr>
		<tr>
			<td>FBS</td>
			<td>40%</td>
		</tr>
		<tr>
			<td rowspan="4">Freezing media</td>
			<td>RPMI-1640</td>
			<td>50 ml</td>
		</tr>
		<tr>
			<td>Antibiotic-antimycotic</td>
			<td>1%</td>
		</tr>
		<tr>
			<td>FBS</td>
			<td>40%</td>
		</tr>
		<tr>
			<td>DMSO</td>
			<td>20%</td>
		</tr>
		<tr>
			<td rowspan="4">PHA media</td>
			<td>RPMI-1640</td>
			<td>500 ml</td>
		</tr>
		<tr>
			<td>Antibiotic-antimycotic</td>
			<td>1%</td>
		</tr>
		<tr>
			<td>FBS</td>
			<td>10%</td>
		</tr>
		<tr>
			<td>Phytohemaglutinin</td>
			<td>1%</td>
		</tr>
	</tbody>
</table>
Table 1. Essential solutions.
<table border="1">
	<tbody>
		<tr>
			<td>Dynamic ranges with &#916;G</td>
			<td>Functional Groups</td>
			<td>Dynamic ranges with Fe</td>
		</tr>
		<tr>
			<td>&#916;G&#60; -10</td>
			<td>FG1</td>
			<td>Fe&#62;100%</td>
		</tr>
		<tr>
			<td>-10 &#60;&#916;G&#60; +10</td>
			<td>FG2</td>
			<td>Fe&#60;50%</td>
		</tr>
		<tr>
			<td>&#916;G&#62; +10</td>
			<td>FG3</td>
			<td>50%&#60;Fe&#60;95%</td>
		</tr>
	</tbody>
</table>
Table 2. Categorization of functional groups according to dynamic ranges established with &#916;G and Fe.
<table border="1">
	<tbody>
		<tr>
			<td>Patients</td>
			<td>Viability (%)</td>
			<td>Cell concentration (&#215;106/ml)</td>
			<td>Comments</td>
		</tr>
		<tr>
			<td>343</td>
			<td>88.7</td>
			<td>11.64</td>
			<td></td>
		</tr>
		<tr>
			<td>344</td>
			<td>90.5</td>
			<td>13.6</td>
			<td></td>
		</tr>
		<tr>
			<td>345</td>
			<td>94.4</td>
			<td>8.54</td>
			<td></td>
		</tr>
		<tr>
			<td>346</td>
			<td>94.3</td>
			<td>25.79</td>
			<td></td>
		</tr>
		<tr>
			<td>347</td>
			<td>94.2</td>
			<td>27.36</td>
			<td></td>
		</tr>
		<tr>
			<td>348</td>
			<td>94.6</td>
			<td>8.52</td>
			<td></td>
		</tr>
		<tr>
			<td>349</td>
			<td>91.2</td>
			<td>0.82</td>
			<td>Insufficient number of cells</td>
		</tr>
		<tr>
			<td>350</td>
			<td>90.3</td>
			<td>8.92</td>
			<td></td>
		</tr>
		<tr>
			<td>352</td>
			<td>92.6</td>
			<td>8.28</td>
			<td></td>
		</tr>
		<tr>
			<td>353</td>
			<td>91.3</td>
			<td>12.75</td>
			<td></td>
		</tr>
		<tr>
			<td>354</td>
			<td>86.9</td>
			<td>7.62</td>
			<td></td>
		</tr>
		<tr>
			<td>355</td>
			<td>91.2</td>
			<td>7.51</td>
			<td></td>
		</tr>
		<tr>
			<td>356</td>
			<td>90.3</td>
			<td>9.36</td>
			<td></td>
		</tr>
		<tr>
			<td>358</td>
			<td>95.1</td>
			<td>16.94</td>
			<td></td>
		</tr>
		<tr>
			<td>359</td>
			<td>92.3</td>
			<td>13.89</td>
			<td></td>
		</tr>
		<tr>
			<td>360</td>
			<td>89.4</td>
			<td>7.67</td>
			<td></td>
		</tr>
		<tr>
			<td>361</td>
			<td>93.5</td>
			<td>7.84</td>
			<td></td>
		</tr>
		<tr>
			<td>365</td>
			<td>86.5</td>
			<td>2.2</td>
			<td>Insufficient number of cells</td>
		</tr>
		<tr>
			<td>368</td>
			<td>92.6</td>
			<td>15.69</td>
			<td></td>
		</tr>
		<tr>
			<td>369</td>
			<td>93.4</td>
			<td>10.9</td>
			<td></td>
		</tr>
		<tr>
			<td>370</td>
			<td>92.5</td>
			<td>19.93</td>
			<td></td>
		</tr>
		<tr>
			<td>371</td>
			<td>88.8</td>
			<td>10.68</td>
			<td></td>
		</tr>
		<tr>
			<td>374</td>
			<td>93.9</td>
			<td>16.86</td>
			<td></td>
		</tr>
		<tr>
			<td>376</td>
			<td>92.9</td>
			<td>15.67</td>
			<td></td>
		</tr>
		<tr>
			<td>377</td>
			<td>93.1</td>
			<td>9.99</td>
			<td></td>
		</tr>
		<tr>
			<td>378</td>
			<td>93.6</td>
			<td>13.57</td>
			<td></td>
		</tr>
		<tr>
			<td>379</td>
			<td>92.6</td>
			<td>19.86</td>
			<td></td>
		</tr>
		<tr>
			<td>380</td>
			<td>91.1</td>
			<td>8.46</td>
			<td></td>
		</tr>
		<tr>
			<td>381</td>
			<td>93.9</td>
			<td>14.82</td>
			<td></td>
		</tr>
		<tr>
			<td>382</td>
			<td>92.1</td>
			<td>23.06</td>
			<td></td>
		</tr>
		<tr>
			<td>383</td>
			<td>92.9</td>
			<td>11.82</td>
			<td></td>
		</tr>
		<tr>
			<td>384</td>
			<td>89.1</td>
			<td>7.73</td>
			<td></td>
		</tr>
	</tbody>
</table>
Table 3. Percent viability and cell concentration as determined using an automated cell counter and viability analyzer.
<img alt="Figure 1" src="/files/ftp_upload/50768/50768fig1.jpg" /> 
Figure 1. Design for cell seeding.
<img alt="Figure 2" src="/files/ftp_upload/50768/50768fig2.jpg" /> 
Figure 2. Design for dispensing compounds.
<img alt="Figure 3" src="/files/ftp_upload/50768/50768fig3.jpg" /> 
Figure 3. Dynamic range of the functional classification using the CDS-based system. Graph illustrates values of the degree of imbalance between responses to Gi and Gs stimulation obtained in PBMCs from patients with idiopathic scoliosis. Values were measured by the CDS-based system in response to 10 &#956;M of somatostatin and isoproterenol. Each point represents the &#916;G of both responses in duplicate.
<img alt="Figure 4" src="/files/ftp_upload/50768/50768fig4.jpg" /> 
Figure 4. Effect of rOPN on response to Gi stimulation in PBMCs. Cells were serum-starved for 18 hr in the presence or absence of 0.5 &#956;g/ml rOPN and then stimulated with 10 &#956;M of somatostatin to initiate Gi-mediated cellular response. Data in the graph were generated from maximum-minimum impedance and correspond to the average of response in duplicate.
<img alt="Figure 5" src="/files/ftp_upload/50768/50768fig5.jpg" /> 
Figure 5. Functional status of Gi protein in PBMCs from control and scoliostic subjects. PBMCs from control subjects and scoliotic patients were exposed to increasing concentrations of somatostatin to stimulate Gi proteins via endogenous somatostatin receptor. The cellular response was measured by CDS-based system as described in the procedure section. Curves were generated from maximum-minimum impedance. Each curve represents the nonlinear regression. Data were normalized to maximal response in cells from control subjects and each point corresponds to the average of response in duplicate. <a href="https://www.jove.com/files/ftp_upload/50768/50768fig5large.jpg" target="_blank"> Click here to view larger figure</a>.
<img alt="Figure 6" src="/files/ftp_upload/50768/50768fig6.jpg" /> 
Figure 6. Distribution of functional groups among different phases of scoliosis. A large cohort of scoliotic patients with 794 moderate (curvatures between 10-44&#176;) and 162 severe (curvature greater than 45&#176;) cases regularly followed at Sainte-Justine Hospital, were classified according to their degree of imbalance between response to Gi and Gs stimulation. Responses were measured by the CDS-based system in response to 10 &#956;M of somatostatin and isoproterenol.

Watch this Scientific Journal Video about Cell-based Assay Protocol for the Prognostic Prediction of Idiopathic Scoliosis Using Cellular Dielectric Spectroscopy at JoVE.com

Cell-based Assay Protocol for the Prognostic Prediction of Idiopathic Scoliosis Using Cellular Dielectric Spectroscopy

A structured protocol is presented for a cell-based assay as a functional test to predict the prognosis of idiopathic scoliosis using cellular dielectric spectroscopy (CDS). The assay can be performed with fresh or frozen peripheral blood mononuclear cells (PBMCs) and the procedure is completed within 4 days.

This protocol details the experimental and analytical procedure for a cell-based assay developed in our laboratory as a functional test to predict the ...

cell-based-assay-protocol-for-prognostic-prediction-idiopathic

Research

JoVE Journal

Medicine

10.6K Views.  Sainte-Justine University Hospital Research Center. A structured protocol is presented for a cell-based assay as a functional test to predict the prognosis of idiopathic scoliosis using cellular dielectric spectroscopy (CDS). The assay can be performed with fresh or frozen peripheral blood mononuclear cells (PBMCs) and the procedure is completed within 4 days.

Video: Cell-based Assay Protocol for the Prognostic Prediction of Idiopathic Scoliosis Using Cellular Dielectric Spectroscopy

In Vitro Generation of Somite Derivatives from Human Induced Pluripotent Stem Cells

In response to signals such as WNTs, bone morphogenetic proteins (BMPs), and sonic hedgehog (SHH) secreted from surrounding tissues, somites (SMs) give rise to multiple cell types, including the myotome (MYO), sclerotome (SCL), dermatome (D), and syndetome (SYN), which in turn develop into skeletal muscle, axial skeleton, dorsal dermis, and axial tendon/ligament, respectively. Therefore, the generation of SMs and their derivatives from human induced pluripotent stem cells (iPSCs) is critical to obtain pluripotent stem cells (PSCs) for application in regenerative medicine and for disease research in the field of orthopedic surgery. Although the induction protocols for MYO and SCL from PSCs have been previously reported by several researchers, no study has yet demonstrated the induction of SYN and D from iPSCs. Therefore, efficient induction of fully competent SMs remains a major challenge. Here, we recapitulate human SM patterning with human iPSCs in vitro by mimicking the signaling environment during chick/mouse SM development, and report on methods of systematic induction of SM derivatives (MYO, SCL, D, and SYN) from human iPSCs under chemically defined conditions through the presomitic mesoderm (PSM) and SM states. Knowledge regarding chick/mouse&#160;SM development was successfully applied to the induction of SMs with human iPSCs. This method could be a novel tool for studying human somitogenesis and patterning without the use of embryos and for cell-based therapy and disease modeling.

We present here a protocol for the differentiation of human induced pluripotent stem cells into each somite derivative (myotome, sclerotome, dermatome, and syndetome) in chemically defined conditions, which has applications in future disease modeling and cell-based therapies in orthopedic surgery.

In response to signals such as WNTs, bone morphogenetic proteins (BMPs), and sonic hedgehog (SHH) secreted from surrounding tissues, somites (SMs) give ...

Developmental Biology

Enhancing Targeted Cancer Diagnosis by Quantifying Single-Cell Mechanics

Shear Assay Protocol for the Determination of Single-Cell Material Properties

Irregular biomechanics are a hallmark of cancer biology subject to extensive study. The mechanical properties of a cell are similar to those of a material. A cell's resistance to stress and strain, its relaxation time, and its elasticity are all properties that can be derived and compared to other types of cells. Quantifying the mechanical properties of cancerous (malignant) versus normal (non-malignant) cells allows researchers to further uncover the biophysical fundamentals of this disease. While the mechanical properties of cancer cells are known to consistently differ from the mechanical properties of normal cells, a standard experimental procedure to deduce these properties from cells in culture is lacking. 
This paper outlines a procedure to quantify the mechanical properties of single cells in vitro using a fluid shear assay. The principle behind this assay involves applying fluid shear stress onto a single cell and optically monitoring the resulting cellular deformation over time. Cell mechanical properties are subsequently characterized using digital image correlation (DIC) analysis and fitting an appropriate viscoelastic model to the experimental data generated from the DIC analysis. Overall, the protocol outlined here aims to provide a more effective and targeted method for the diagnosis of difficult-to-treat cancers.

Author Spotlight: Shear Assay Protocol for the Determination of Single-Cell Material Properties  

This protocol outlines the quantification of the mechanical properties of cancerous and non-cancerous cell lines in vitro. Conserved differences in the mechanics of cancerous and normal cells can act as a biomarker that may have implications in prognosis and diagnosis.

Irregular biomechanics are a hallmark of cancer biology subject to extensive study. The mechanical properties of a cell are similar to those of a ...

Cancer Research

Preparation of Tunable Extracellular Matrix Microenvironments to Evaluate Schwann Cell Phenotype Specification

Traumatic peripheral nervous system (PNS) injuries currently lack suitable treatments to regain full functional recovery. Schwann cells (SCs), as the major glial cells of the PNS, play a vital role in promoting PNS regeneration by dedifferentiating into a regenerative cell phenotype following injury. However, the dedifferentiated state of SCs is challenging to maintain through the time-period needed for regeneration and is impacted by changes in the surrounding extracellular matrix (ECM). Therefore, determining the complex interplay between SCs and differing ECM to provide cues of regenerative potential of SCs is essential. To address this, a strategy was created where different ECM proteins were adsorbed onto a tunable polydimethylsiloxane (PDMS) substrate which provided a platform where stiffness and protein composition can be modulated. SCs were seeded onto the tunable substrates and critical cellular functions representing the dynamics of SC phenotype were measured. To illustrate the interplay between SC protein expression and cellular morphology, differing seeding densities of SCs in addition to individual microcontact printed cellular patterns were utilized and characterized by immunofluorescence staining and western blot. Results showed that cells with a smaller spreading area and higher extent of cellular elongation promoted higher levels of SC regenerative phenotypic markers. This methodology not only begins to unravel the significant relationship between the ECM and cellular function of SCs, but also provides guidelines for the future optimization of biomaterials in peripheral nerve repair.

This methodology aims to illustrate the mechanisms by which extracellular matrix cues such as substrate stiffness, protein composition and cell morphology regulate Schwann cell (SC) phenotype.

Traumatic peripheral nervous system (PNS) injuries currently lack suitable treatments to regain full functional recovery. Schwann cells (SCs), as the ...

Bioengineering

Single-Cell Optical Action Potential Measurement in Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes

Conventional intracellular microelectrode techniques to quantify cardiomyocyte electrophysiology are extremely complex, labor intensive, and typically carried out in low throughput. Rapid and ongoing expansion of induced pluripotent stem cell (iPSC) technology presents a new standard in cardiovascular research and alternate methods are now necessary to increase throughput of electrophysiological data at a single cell level. VF2.1Cl is a recently derived voltage sensitive dye which provides a rapid single channel, high magnitude response to fluctuations in membrane potential. It possesses kinetics superior to those of other existing voltage indicators and makes available functional data equivalent to that of traditional microelectrode techniques. Here, we demonstrate simplified, non-invasive action potential characterization in externally paced human iPSC derived cardiomyocytes using a modular and highly affordable photometry system.

Here we describe optical acquisition and characterization of action potentials from induced pluripotent stem cell derived cardiomyocytes using a high-speed modular photometry system.

Conventional intracellular microelectrode techniques to quantify cardiomyocyte electrophysiology are extremely complex, labor intensive, and typically ...

Finite Element Modelling of a Cellular Electric Microenvironment

Clinical studies show electrical stimulation (ES) to be a potential therapy for the healing and regeneration of various tissues. Understanding the mechanisms of cell response when exposed to electrical fields can therefore guide the optimization of clinical applications. In vitro experiments aim to help uncover those, offering the advantage of wider input and output ranges that can be ethically and effectively assessed. However, the advancements in in vitro experiments are difficult to reproduce directly in clinical settings. Mainly, that is because the ES devices used in vitro differ significantly from the ones suitable for patient use, and the path from the electrodes to the targeted cells is different. Translating the in vitro results into in vivo procedures is therefore not straightforward. We emphasize that the cellular microenvironment's structure and physical properties play a determining role in the actual experimental testing conditions and suggest that measures of charge distribution can be used to bridge the gap between in vitro and in vivo. Considering this, we show how in silico finite element modelling (FEM) can be used to describe the cellular microenvironment and the changes generated by electric field (EF) exposure. We highlight how the EF couples with geometric structure to determine charge distribution. We then show the impact of time dependent inputs on charge movement. Finally, we demonstrate the relevance of our new in silico model methodology using two case studies: (i) in vitro fibrous Poly(3,4-ethylenedioxythiophene) poly(styrenesulfonate) (PEDOT-PSS) scaffolds and (ii) in vivo collagen in extracellular matrix (ECM).

This paper presents a strategy for building finite element models of fibrous conductive materials exposed to an electric field (EF). The models can be used to estimate the electrical input that cells seeded in such materials receive and assess the impact of changing the scaffold's constituent material properties, structure or orientation.

Clinical studies show electrical stimulation (ES) to be a potential therapy for the healing and regeneration of various tissues. Understanding the ...

Hybrid Cell Analysis System to Assess Structural and Contractile Changes of Human iPSC-Derived Cardiomyocytes for Preclinical Cardiac Risk Evaluation

Cardiac contractility assessment is of immense importance for the development of new therapeutics and their safe transition into clinical stages. While human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) hold promise to serve as a human-relevant model in preclinical phases of drug discovery and safety pharmacology, their maturity is still controversial in the scientific community and under constant development. We present a hybrid contractility and impedance/extracellular field potential (EFP) technology, adding significant pro-maturation features to an industry-standard 96-well platform.
The impedance/EFP system monitors cellular functionality in real-time. Besides the beat rate of contractile cells, the electrical impedance spectroscopy readouts detect compound-induced morphological changes like cell density and integrity of the cellular monolayer. In the other component of the hybrid cell analysis system, the cells are cultured on bio-compliant membranes that mimic the mechanical environment of real heart tissue. This physiological environment supports the maturation of hiPSC-CMs in vitro, leading to more adult-like contractile responses including positive inotropic effects after treatment with isoproterenol, S-Bay K8644, or omecamtiv mecarbil. Parameters such as the amplitude of contraction force (mN/mm2) and beat duration also reveal downstream effects of compounds with influence on electrophysiological properties and calcium handling.
The hybrid system provides the ideal tool for holistic cell analysis, allowing preclinical cardiac risk assessment beyond the current perspectives of human-relevant cell-based assays.

The analysis of changes in contractile function and cellular integrity of human iPSC-derived cardiomyocytes is of immense importance for nonclinical drug development. A hybrid 96-well cell analysis system addresses both parameters in a real-time and physiological manner for reliable, human-relevant results, necessary for a safe transition into clinical stages.

Cardiac contractility assessment is of immense importance for the development of new therapeutics and their safe transition into clinical stages. While ...

Mechanical Fatigue Testing of RBCs by Amplitude-Modulated Electrodeformation

Amplitude-Modulated Electrodeformation to Evaluate Mechanical Fatigue of Biological Cells

Red blood cells (RBCs) are known for their remarkable deformability. They repeatedly undergo considerable deformation when passing through the microcirculation. Reduced deformability is seen in physiologically aged RBCs. Existing techniques to measure cell deformability cannot easily be used for measuring fatigue, the gradual degradation in cell membranes caused by cyclic loads. We present a protocol to evaluate mechanical degradation in RBCs from cyclic shear stresses using amplitude shift keying (ASK) modulation-based electrodeformation in a microfluidic channel. Briefly, the interdigitated electrodes in the microfluidic channel are excited with a low voltage alternating current at radio frequencies using a signal generator. RBCs in suspension respond to the electric field and exhibit positive dielectrophoresis (DEP), which moves cells to the electrode edges. Cells are then stretched due to the electrical forces exerted on the two cell halves, resulting in uniaxial stretching, known as electrodeformation. The level of shear stress and the resultant deformation can be easily adjusted by changing the amplitude of the excitation wave. This enables quantifications of nonlinear deformability of RBCs in response to small and large deformations at high throughput. Modifying the excitation wave with the ASK strategy induces cyclic electrodeformation with programmable loading rates and frequencies. This provides a convenient way for the characterization of RBC fatigue. Our ASK-modulated electrodeformation approach enables, for the first time, a direct measurement of RBC fatigue from cyclic loads. It can be used as a tool for general biomechanical testing, for analyses of cell deformability and fatigue in other cell types and diseased conditions, and can also be combined with strategies to control the microenvironment of cells, such as oxygen tension and biological and chemical cues.

Author Spotlight: Studying Biomechanics of Circulating Cells by Modulating Their Electrodeformation Behavior 

Presented here is a protocol for mechanical fatigue testing in the case of human red blood cells using an amplitude-modulated electrodeformation approach. This general approach can be used to measure the systematic changes in morphological and biomechanical characteristics of biological cells in a suspension from cyclic deformation.

Red blood cells (RBCs) are known for their remarkable deformability. They repeatedly undergo considerable deformation when passing through the ...

Characterization of Sickling During Controlled Automated Deoxygenation with Oxygen Gradient Ektacytometry

In sickle cell disease (SCD), a single point mutation in the gene coding for beta-globin causes the production of abnormal hemoglobin S (HbS). When deoxygenated, HbS can polymerize, forming rigid rods of hemoglobin, resulting in the sickling of red blood cells (RBCs). These sickled RBCs have significantly reduced deformability, causing vaso-occlusion, which leads to numerous SCD-related clinical complications, including pain, stroke, and organ damage. RBC deformability is also reduced by RBC dehydration, resulting in dense red blood cells that are more likely to sickle. To date, there is not a single widely available, rapid, and reproducible laboratory assay capable of predicting the disease severity or directly monitoring the treatment effects for novel, non-fetal hemoglobin inducing therapies. In this study, we describe a protocol to measure RBC deformability as a function of pO2 that allows for the quantitation of sickling behavior in SCD patients. Oxygen gradient ektacytometry measures RBC deformability, expressed as the elongation index (EI), as a function of pO2. RBCs are exposed to a fixed shear stress of 30 Pa during one round of deoxygenation and reoxygenation. Six readout parameters are produced. Of these, the point of sickling (PoS), defined as the pO2 at which maximum EI (EImax) shows a 5% decrease, and minimum EI during deoxygenation (EImin) are the most informative, reflecting an individual patient&#8217;s pO2 at which sickling starts and the minimal deformability of a patient&#8217;s red blood cells, respectively. PoS is associated with an individual patient&#8217;s hemoglobin affinity for oxygen, whereas EImin shows a strong correlation with fetal hemoglobin levels. We conclude that oxygen gradient ektacytometry is a promising technique to monitor the treatment of patients with SCD, as a biomarker for anti-sickling agents in clinical and preclinical trials, and an important tool to study sickling behavior of RBCs from individuals with SCD and sickle cell traits.

Here, we present oxygen gradient ektacytometry, a rapid and reproducible method to measure red blood cell deformability in samples from patients with sickle cell disease under controlled deoxygenation and reoxygenation. This technique provides a way to study red blood cell sickling and to monitor sickle cell disease treatment efficacy.

In sickle cell disease (SCD), a single point mutation in the gene coding for beta-globin causes the production of abnormal hemoglobin S (HbS). When ...

High-Throughput Optical Controlling and Recording Calcium Signal in iPSC-Derived Cardiomyocytes for Toxicity Testing and Phenotypic Drug Screening

Understanding how excitable cells work in health and disease and how that behavior can be altered by small molecules or genetic manipulation is important. Genetically encoded calcium indicators (GECIs) with multiple emission windows can be combined (e.g., for simultaneous observation of distinct subcellular events) or used in extended applications with other light-dependent actuators in excitable cells (e.g., combining genetically encoded optogenetic control with spectrally compatible calcium indicators). Such approaches have been used in primary or stem cell-derived neurons, cardiomyocytes, and pancreatic beta-cells. However, it has been challenging to increase the throughput, or duration of observation, of such approaches due to limitations of the instruments, analysis software, indicator performance, and gene delivery efficiency. Here, a high-performance green GECI, mNeonGreen-GECO (mNG-GECO), and red-shifted GECI, K-GECO, is combined with optogenetic control to achieve all-optical control and visualization of cellular activity in a high-throughput imaging format using a High-Content Imaging System. Applications demonstrating cardiotoxicity testing and phenotypic drug screening with healthy and patient-derived iPSC-CMs are shown. In addition, multi-parametric assessments using combinations of spectral and calcium affinity indicator variants (NIR-GECO, LAR-GECO, and mtGCEPIA or Orai1-G-GECO) are restricted to different cellular compartments are also demonstrated in the iPSC-CM model.

The present protocol describes all-optical control and observation of triggered cellular activity in iPSC-derived cardiomyocytes (iPSC-CMs) for high throughput drug screening and toxicity testing. Multi-parametric quantification of phenotypic patterns in time, and space, are shown. Long-term effects of drugs over hours, or sequential measurements over days, are demonstrated.

Understanding how excitable cells work in health and disease and how that behavior can be altered by small molecules or genetic manipulation is important. ...

Enhancing Peripheral Nerve Regeneration with nsPEF-Stimulated Schwann Cells

Regulating Schwann Cell Growth by Nanosecond Pulsed Electric Field for Peripheral Nerve Regeneration In Vitro

Schwann cells (SCs) are myelinating cells of the peripheral nervous system, playing a crucial role in peripheral nerve regeneration. Nanosecond Pulse Electric Field (nsPEF) is an emerging method applicable in nerve electrical stimulation that has been demonstrated to be effective in stimulating cell proliferation and other biological processes. Aiming to assess whether SCs undergo significant changes under nsPEF and help explore the potential for new peripheral nerve regeneration methods, cultured RSC96 cells were subjected to nsPEF stimulation at 5 kV and 10 kV, followed by continued cultivation for 3-4 days. Subsequently, some relevant factors expressed by SCs were assessed to demonstrate the successful stimulation, including the specific marker protein, neurotrophic factor, transcription factor, and myelination regulator. The representative results showed that nsPEF significantly enhanced the proliferation and migration of SCs and the ability to synthesize relevant factors that contribute positively to the regeneration of peripheral nerves. Simultaneously, lower expression of GFAP indicated the benign prognosis of peripheral nerve injuries. All these outcomes show that nsPEF has great potential as an efficient treatment method for peripheral nerve injuries by stimulating SCs.

Author Spotlight: Innovative Use of nsPEF to Boost Peripheral Nerve Regeneration

Here, we present a protocol for applying nanosecond pulse electric field (nsPEF) to stimulate Schwann cells in vitro. The synthesis and secretion ability of relevant factors and cell behavior changes validated the successful stimulation using nsPEF. The study gives a positive view of the peripheral nerve regeneration method.

Schwann cells (SCs) are myelinating cells of the peripheral nervous system, playing a crucial role in peripheral nerve regeneration. Nanosecond Pulse ...