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Medicine

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

doi: 10.3791/50768 Published: October 16, 2013

Summary

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.

Abstract

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' responses are monitored for 15 min. The assay can be performed with fresh or frozen PBMCs and the procedure is completed within 4 days.

Introduction

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° 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°, while surgery is reserved for curves greater than 45° 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.

Protocol

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

  1. Prepare solutions according to Table 1.
  2. Keep balanced salt solution (BSS) at room temperature and all other solutions at 4 °C until the time of use.
  3. Warm cold media to 37 °C in the water bath for a few minutes before using.

2. Preparation and Storage of PBMCs

  1. Collect 10 ml of whole blood in EDTA-treated collection tubes to prepare two aliquots of PBMCs using 5 ml for each aliquot.
  2. Transfer 5 ml of whole blood from the EDTA-treated collection tube to a 50 ml tube.
  3. Add an equal volume of BSS and mix sample by gentle pipetting up and down.
  4. Place 3 ml of Ficoll in two 15 ml Falcon tubes.
  5. Carefully layer 4.5 ml of diluted blood mixture over the Ficoll in each tube.
  6. Let the tubes rest for up to 5 min to favor a clear separation of the blood and Ficoll.
  7. Centrifuge the tubes at 400 x g for 30 min at room temperature with no brake.
  8. Carefully remove the tubes from the centrifuge so as to not disturb the layering. The PBMCs are visible at the BSS/Ficoll interface.
  9. Harvest the cloudy layer of PBMCs at the interface of both tubes with a pipette and transfer to a new 50 ml tube.
  10. Add 20 ml of complete media.
  11. Centrifuge the tube at 288 x g for 7 min at room temperature.
  12. Remove the supernatant by aspiration.
  13. Resuspend the cell pellet in 500 μl of supplementary media.
  14. Add an equal volume of freezing media.
  15. Transfer the cell suspension to a cryovial.
  16. Place the cryovial into a cryofreezing container with isopropanol.
  17. Store the freezing container at -80 °C overnight.
  18. Transfer the frozen PBMCs aliquot to liquid nitrogen for long-term storage.

3. Functional Assay

1. Day 1

  1. Place aliquot from liquid nitrogen in water bath at 37 °C for a minute or until defrosted.
  2. Transfer the cell suspension to a 50 ml tube with a sterile pipette.
  3. Add 15 ml of complete media and spin the cells down at 200 x g for 5 min at room temperature.
  4. Remove the supernatant by aspiration.
  5. Gently suspend cell pellet in 1 ml of PHA media.
  6. Complete the volume to 20 ml with the same media.
  7. Cap the tube loosely to allow air to enter.
  8. Leave the tube overnight at 37 °C in a CO2 incubator to allow quiescent lymphocytes to transform into rapidly-proliferating lymphoblasts.

2. Day 2

  1. 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.
  2. Remove the supernatant by aspiration.
  3. Gently suspend cell pellet in 1 ml of complete media.
  4. Complete the volume to 20 ml with the same media.
  5. Cap the tube loosely to allow air to enter.
  6. Leave the tube overnight at 37 °C in a CO2 incubator to expand cell numbers.

3. Day 3

  1. 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.
  2. Remove the supernatant by aspiration.
  3. Wash cells twice with 10 ml of RPMI-1640 by centrifugation at 200 x g for 5 min at room temperature.
  4. Gently resuspend the cell pellet in 600 μl of RPMI-1640.
  5. Measure the cell concentration and viability, using an automated cell counter and viability analyzer.
  6. Add appropriate volume of RPMI-1640 to adjust to a cell concentration of 1.5 x 105 cells/20 μl.
  7. Treat cells with recombinant OPN (rOPN) or vehicle (PBS) in 1.5 ml of Eppendorf tubes.
    1. Transfer 100 μl of cell suspension to two sterile 1.5 ml Eppendorf tubes.
    2. Add rOPN in one tube to a final concentration of 0.5 μg/ml.
    3. Add an equal volume of PBS in the second tube.
    4. Gently mix each condition by pipetting up and down twice using a sterile pipette set at 100 μl.
  8. Prepare the small sample 96-well microplate.
    1. Add 5 μl of RPMI-1640 to each well.
    2. Centrifuge the plate at 200 x g for 3 min to remove any air bubbles.
  9. Seed the untreated cells as well as cells treated with rOPN or PBS.
    1. Before transferring cells from tube to microplate, gently pipette up and down once to ensure a uniform suspension of cells.
    2. Add 40 μl 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.
    3. 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.
  10. Incubate the plate for 18 hr at 37 °C in a CO2 incubator to optimize the effect of OPN.

4. Day 4

  1. Run the plate with compounds.
    1. Take the plate out of the incubator and leave it at RT for around 30 min.
    2. Prepare 1 ml of 100 μM of somatostatin and isoproterenol in RPMI-1640 by adding 10 μl of stock solution (10 mM) in 990 μl of RPMI-1640.
    3. Fill the compound plate by dispensing 20 μl in appropriate wells as indicated in Figure 2.
    4. 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.
    5. Load cell plate, pipette tips, and compound plate into the CDS-based system.
    6. Name the plate in the CDS-based instrument software.
    7. Select the appropriate protocol. The protocol edited for the classification with PBMCs is called 'Agonist Non-adherent cells Small Sample Plate RT 15 min'. Go to the protocol box and select this protocol in the list of protocols
    8. Initiate the protocol by clicking on 'Start'.
    9. The integrated fluidics system simultaneously adds the compounds to all wells by injecting 5 μl per well to achieve a final concentration of 10 μM in a total volume of 50 μl.
    10. The CDS-based system automatically collects the data for 15 min after compound addition.
  2. Data analysis
    1. Select low and high ranges of frequencies to use when calculating extracted values for the nonadherent cells.
    2. Select drift correction to correct the linear change in baseline impedance measurements over time.
    3. Select data filtering to reduce variations in the kinetic response measurement due to electronic noise and compound addition.
    4. Select the Max-Min method for the full analysis time.
    5. Export data to Excel under the plate format option.
    6. Calculate delta G (ΔG) 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:
      ΔG = RmGi - RmGs
    7. 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)
    8. Refer to Table 2 to classify patients.

Representative Results

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 > +10 for FG3, between +10 and -10 for FG2, and finally < -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.

Solution A Anhydrous D-glucose 0.1%
CaCl2H2O 0.05 mM
MgCl2 0.98 mM
KCl 5.4 mM
Tris 145 mM
Solution B NaCl 140 mM
Balanced Salt Solution (BSS) Solution A 1 volume
Solution B 9 volume
Complete media RPMI-1640 500 ml
Antibiotic-antimycotic 1%
FBS 10%
Supplementary media RPMI-1640 50 ml
Antibiotic-antimycotic 1%
FBS 40%
Freezing media RPMI-1640 50 ml
Antibiotic-antimycotic 1%
FBS 40%
DMSO 20%
PHA media RPMI-1640 500 ml
Antibiotic-antimycotic 1%
FBS 10%
Phytohemaglutinin 1%

Table 1. Essential solutions.

Dynamic ranges with ΔG Functional Groups Dynamic ranges with Fe
ΔG< -10 FG1 Fe>100%
-10 <ΔG< +10 FG2 Fe<50%
ΔG> +10 FG3 50%<Fe<95%

Table 2. Categorization of functional groups according to dynamic ranges established with ΔG and Fe.

Patients Viability (%) Cell concentration (×106/ml) Comments
343 88.7 11.64
344 90.5 13.6
345 94.4 8.54
346 94.3 25.79
347 94.2 27.36
348 94.6 8.52
349 91.2 0.82 Insufficient number of cells
350 90.3 8.92
352 92.6 8.28
353 91.3 12.75
354 86.9 7.62
355 91.2 7.51
356 90.3 9.36
358 95.1 16.94
359 92.3 13.89
360 89.4 7.67
361 93.5 7.84
365 86.5 2.2 Insufficient number of cells
368 92.6 15.69
369 93.4 10.9
370 92.5 19.93
371 88.8 10.68
374 93.9 16.86
376 92.9 15.67
377 93.1 9.99
378 93.6 13.57
379 92.6 19.86
380 91.1 8.46
381 93.9 14.82
382 92.1 23.06
383 92.9 11.82
384 89.1 7.73

Table 3. Percent viability and cell concentration as determined using an automated cell counter and viability analyzer.

Figure 1
Figure 1. Design for cell seeding.

Figure 2
Figure 2. Design for dispensing compounds.

Figure 3
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 μM of somatostatin and isoproterenol. Each point represents the ΔG of both responses in duplicate.

Figure 4
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 μg/ml rOPN and then stimulated with 10 μM 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.

Figure 5
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. Click here to view larger figure.

Figure 6
Figure 6. Distribution of functional groups among different phases of scoliosis. A large cohort of scoliotic patients with 794 moderate (curvatures between 10-44°) and 162 severe (curvature greater than 45°) 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 μM of somatostatin and isoproterenol.

Discussion

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' 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.

Disclosures

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.

Acknowledgments

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).

Materials

Name Company Catalog Number Comments
Materials
RPMI Wisent, Inc 350-005-CL
FBS Therno Scientific Hyclone SH3007103
DMSO Sigma Aldrich D2650
Ficoll-Plaque Plus GE Healthcare 17144003
Antibiotic-Antimycotic Invitrogen 15240-062
Phytohemagglutinin Invitrogen (Gibco) 10576-015
Recombinant Human Osteopontin R&D Systems, Inc 1433-OP/CF
Somatostatin Tocris 1157
Isoproterenol Tocris 1743
PBS Wisent, Inc 311-010-CL
Sterile pipette tips Axygen Scientific 301-06-451
Sterile Eppendorf tubes Ultident 24-MCT-150-C
50 ml conical tubes VWR International 89039-658
Cellkey small sample 96W microplate Molecular Devices 1026496
Cellkey tips Cybio OL3800-25-559N
Precut pierceable seals Excel Scientific, Inc XP-100
Equipment
Vicell XR Beckman Coulter 731050 Automated cell counter
Cell culture hood Forma Scientific 1284 Class II
Liquid nitrogen storage Thermo Scientific CY5093570
Water bath VWR International 89032-204
Standard light microscope Leica Microsystems DMIL LED
Cell culture incubator Thermo Scientific 51019557 5% CO2 at 37 °C
Low speed centrifuge Thermo Scientific 75004364
Cellkey system Molecular Devices 1019185 CDS-based instrument

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References

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  4. Fong, D. Y., et al. A meta-analysis of the clinical effectiveness of school scoliosis screening. Spine (Phila Pa 1976). 35, (10), 1061-1071 (2010).
  5. Chowanska, J., Kotwicki, T., Rosadzinski, K., Sliwinski, Z. School screening for scoliosis: can surface topography replace examination with scoliometer? Scoliosis. 7, (9), 1748-7161 (2012).
  6. Kim, H., et al. Scoliosis imaging: what radiologists should know. Radiographics. 30, (7), 1823-1842 (2010).
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  9. Enneking, W. F., Harrington, P. Pathological changes in scoliosis. J. Joint Surg. 51, (1), 165-184 (1969).
  10. Miller, N. H. Cause and natural history of adolescent idiopathic scoliosis. Orthop. Clin. North Am. 30, (3), 343-3452 (1999).
  11. Nash, C. L. Jr, Gregg, E. C., Brown, R. H., Pillai, K. Risks of exposure to X-rays in patients undergoing long-term treatment for scoliosis. J. Bone Joint Surg. Am. 61, (3), 371-400 (1979).
  12. Akoume, M. Y., et al. Cell-based screening test for idiopathic scoliosis using cellular dielectric spectroscopy. Spine. 35, (13), 601-608 (2010).
  13. Verdonk, E., et al. Cellular dielectric spectroscopy: a label-free comprehensive platform for functional evaluation of endogenous receptors. Assay Drug Dev. Technol. 4, (5), 609-6019 (2006).
  14. Peters, M. F., et al. Evaluation of cellular dielectric spectroscopy, a whole-cell, label-free technology for drug discovery on Gi-coupled GPCRs. J. Biomol. Screen. 12, (3), 312-319 (2007).
  15. Peters, M. F., Scott, C. W. Evaluating cellular impedance assays for detection of GPCR pleiotropic signaling and functional selectivity. J. Biomol. Screen. 14, (3), 246-255 (2009).
  16. Peters, M. F., Vaillancourt, F., Heroux, M., Valiquette, M., Scott, C. W. Comparing label-free biosensors for pharmacological screening with cell-based functional assays. Assay Drug Dev. Technol. 8, (2), 219-227 (2010).
  17. Akoume, M. Y., et al. Disrupted Gi-coupled receptor signaling occurs in adolescent idiopathic scoliosis. J. Clin. Invest. Submitted (2013).
Cell-based Assay Protocol for the Prognostic Prediction of Idiopathic Scoliosis Using Cellular Dielectric Spectroscopy
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Cite this Article

Akoume, M. Y., Franco, A., Moreau, A. Cell-based Assay Protocol for the Prognostic Prediction of Idiopathic Scoliosis Using Cellular Dielectric Spectroscopy. J. Vis. Exp. (80), e50768, doi:10.3791/50768 (2013).More

Akoume, M. Y., Franco, A., Moreau, A. Cell-based Assay Protocol for the Prognostic Prediction of Idiopathic Scoliosis Using Cellular Dielectric Spectroscopy. J. Vis. Exp. (80), e50768, doi:10.3791/50768 (2013).

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