Name: cell-based assay protocol for the prognostic prediction of idiopathic scoliosis using cellular dielectric spectroscopy
Uploaded: 2013-10-16T20:00:00
Duration: 8 min 8 s
Description: Watch this Scientific Journal Video about Cell-based Assay Protocol for the Prognostic Prediction of Idiopathic Scoliosis Using Cellular Dielectric Spectroscopy at JoVE.com

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 border="1">
	<tbody>
		<tr>
			<td></td>
			<td></td>
			<td></td>
			<td>Materials</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&#38;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></td>
			<td></td>
			<td></td>
			<td>Equipment</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% CO2 at 37 &#176;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 ...

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Medicine

An Experimental Paradigm for the Prediction of Post-Operative Pain (PPOP)

Many women undergo cesarean delivery without problems, however some experience significant pain after cesarean section. Pain is associated with negative short-term and long-term effects on the mother. Prior to women undergoing surgery, can we predict who is at risk for developing significant postoperative pain and potentially prevent or minimize its negative consequences? These are the fundamental questions that a team from the University of Washington, Stanford University, the Catholic University in Brussels, Belgium, Santa Joana Women's Hospital in S&atilde;o Paulo, Brazil, and Rambam Medical Center in Israel is currently evaluating in an international research collaboration. The ultimate goal of this project is to provide optimal pain relief during and after cesarean section by offering individualized anesthetic care to women who appear to be more 'susceptible' to pain after surgery.
A significant number of women experience moderate or severe acute post-partum pain after vaginal and cesarean deliveries. 1 Furthermore, 10-15% of women suffer chronic persistent pain after cesarean section. 2 With constant increase in cesarean rates in the US 3 and the already high rate in Brazil, this is bound to create a significant public health problem. When questioning women's fears and expectations from cesarean section, pain during and after it is their greatest concern. 4 Individual variability in severity of pain after vaginal or operative delivery is influenced by multiple factors including sensitivity to pain, psychological factors, age, and genetics. The unique birth experience leads to unpredictable requirements for analgesics, from 'none at all' to 'very high' doses of pain medication. Pain after cesarean section is an excellent model to study post-operative pain because it is performed on otherwise young and healthy women. Therefore, it is recommended to attenuate the pain during the acute phase because this may lead to chronic pain disorders. The impact of developing persistent pain is immense, since it may impair not only the ability of women to care for their child in the immediate postpartum period, but also their own well being for a long period of time.
In a series of projects, an international research network is currently investigating the effect of pregnancy on pain modulation and ways to predict who will suffer acute severe pain and potentially chronic pain, by using simple pain tests and questionnaires in combination with genetic analysis. A relatively recent approach to investigate pain modulation is via the psychophysical measure of Diffuse Noxious Inhibitory Control (DNIC). This pain-modulating process is the neurophysiological basis for the well-known phenomenon of 'pain inhibits pain' from remote areas of the body. The DNIC paradigm has evolved recently into a clinical tool and simple test and has been shown to be a predictor of post-operative pain.5 Since pregnancy is associated with decreased pain sensitivity and/or enhanced processes of pain modulation, using tests that investigate pain modulation should provide a better understanding of the pathways involved with pregnancy-induced analgesia and may help predict pain outcomes during labor and delivery. For those women delivering by cesarean section, a DNIC test performed prior to surgery along with psychosocial questionnaires and genetic tests should enable one to identify women prone to suffer severe post-cesarean pain and persistent pain. These clinical tests should allow anesthesiologists to offer not only personalized medicine to women with the promise to improve well-being and satisfaction, but also a reduction in the overall cost of perioperative and long term care due to pain and suffering. On a larger scale, these tests that explore pain modulation may become bedside screening tests to predict the development of pain disorders following surgery.

An Experimental Paradigm for the Prediction of Post-Operative Pain PPOP

Diffuse noxious inhibitory control, temporal summation and wound hyperalgesia testing are demonstrated in the obstetric patient. These tests evaluate inhibitory and excitatory mechanisms of pain processing and are here utilized to evaluate endogenous analgesia at different time-points during pregnancy and the peripartum period to help reveal individual s risk for persistent pain.

Many women undergo cesarean delivery without problems, however some experience significant pain after cesarean section. Pain is associated with negative ...

A Method for Murine Islet Isolation and Subcapsular Kidney Transplantation

Since the early pioneering work of Ballinger and Reckard demonstrating that transplantation of islets of Langerhans into diabetic rodents could normalize their blood glucose levels, islet transplantation has been proposed to be a potential treatment for type 1 diabetes 1,2. More recently, advances in human islet transplantation have further strengthened this view 1,3. However, two major limitations prevent islet transplantation from being a widespread clinical reality: (a) the requirement for large numbers of islets per patient, which severely reduces the number of potential recipients, and (b) the need for heavy immunosuppression, which significantly affects the pediatric population of patients due to their vulnerability to long-term immunosuppression. Strategies that can overcome these limitations have the potential to enhance the therapeutic utility of islet transplantation.
Islet transplantation under the mouse kidney capsule is a widely accepted model to investigate various strategies to improve islet transplantation. This experiment requires the isolation of high quality islets and implantation of islets to the diabetic recipients. Both procedures require surgical steps that can be better demonstrated by video than by text. Here, we document the detailed steps for these procedures by both video and written protocol. We also briefly discuss different transplantation models: syngeneic, allogeneic, syngeneic autoimmune, and allogeneic autoimmune.

Transplantation of isolated islets has been proposed to be a potential treatment for type 1 diabetes. Here we describe a method to isolate islets from mouse pancreata and transplant them to the subcapsular space of the kidney.

Since the early pioneering work of Ballinger and Reckard demonstrating that transplantation of islets of Langerhans into diabetic rodents could normalize ...

The Trier Social Stress Test Protocol for Inducing Psychological Stress

This article demonstrates a psychological stress protocol for use in a laboratory setting. Protocols that allow researchers to study the biological pathways of the stress response in health and disease are fundamental to the progress of research in stress and anxiety.1 Although numerous protocols exist for inducing stress response in the laboratory, many neglect to provide a naturalistic context or to incorporate aspects of social and psychological stress. Of psychological stress protocols, meta-analysis suggests that the Trier Social Stress Test (TSST) is the most useful and appropriate standardized protocol for studies of stress hormone reactivity.2 In the original description of the TSST, researchers sought to design and evaluate a procedure capable of inducing a reliable stress response in the majority of healthy volunteers.3 These researchers found elevations in heart rate, blood pressure and several endocrine stress markers in response to the TSST (a psychological stressor) compared to a saline injection (a physical stressor).3 Although the TSST has been modified to meet the needs of various research groups, it generally consists of a waiting period upon arrival, anticipatory speech preparation, speech performance, and verbal arithmetic performance periods, followed by one or more recovery periods. The TSST requires participants to prepare and deliver a speech, and verbally respond to a challenging arithmetic problem in the presence of a socially evaluative audience.3 Social evaluation and uncontrollability have been identified as key components of stress induction by the TSST.4 In use for over a decade, the goal of the TSST is to systematically induce a stress response in order to measure differences in reactivity, anxiety and activation of the hypothalamic-pituitary-adrenal (HPA) or sympathetic-adrenal-medullary (SAM) axis during the task.1 Researchers generally assess changes in self-reported anxiety, physiological measures (e.g. heart rate), and/or neuroendocrine indices (e.g. the stress hormone cortisol) in response to the TSST. Many investigators have adopted salivary sampling for stress markers such as cortisol and alpha-amylase (a marker of autonomic nervous system activation) as an alternative to blood sampling to reduce the confounding stress of blood-collection techniques. In addition to changes experienced by an individual completing the TSST, researchers can compare changes between different treatment groups (e.g. clinical versus healthy control samples) or the effectiveness of stress-reducing interventions.1

This article describes a protocol for inducing psychological stress in participants, which enables researchers to measure psychological, physiological and neuroendocrine responses to stress within single participants or between groups.

This article demonstrates a psychological stress protocol for use in a laboratory setting.  Protocols that allow researchers to study the biological ...

High-throughput Flow Cytometry Cell-based Assay to Detect Antibodies to N-Methyl-D-aspartate Receptor or Dopamine-2 Receptor in Human Serum

Over the recent years, antibodies against surface and conformational proteins involved in neurotransmission have been detected in autoimmune CNS diseases in children and adults. These antibodies have been used to guide diagnosis and treatment. Cell-based assays have improved the detection of antibodies in patient serum. They are based on the surface expression of brain antigens on eukaryotic cells, which are then incubated with diluted patient sera followed by fluorochrome-conjugated secondary antibodies. After washing, secondary antibody binding is then analyzed by flow cytometry. Our group has developed a high-throughput flow cytometry live cell-based assay to reliably detect antibodies against specific neurotransmitter receptors. This flow cytometry method is straight forward, quantitative, efficient, and the use of a high-throughput sampler system allows for large patient cohorts to be easily assayed in a short space of time. Additionally, this cell-based assay can be easily adapted to detect antibodies to many different antigenic targets, both from the central nervous system and periphery. Discovering additional novel antibody biomarkers will enable prompt and accurate diagnosis and improve treatment of immune-mediated disorders.

Over the recent years, live cell-based assays have been used successfully to detect antibodies against surface and conformational antigens. Here, we describe a method using high-throughput flow cytometry enabling the analysis of large cohorts of patients. Detection of novel antibodies will improve diagnosis and treatment of immune-mediated disorders.

Over the recent years, antibodies against surface and conformational proteins involved in neurotransmission have been detected in autoimmune CNS diseases ...

Focus Formation: A Cell-based Assay to Determine the Oncogenic Potential of a Gene

Malignant transformation of cells is typically associated with increased proliferation, loss of contact inhibition, acquisition of anchorage-independent growth potential, and the ability to form tumors in experimental animals1. In NIH 3T3 cells, the Ras signal transduction pathway is known to trigger many of these events, what is known as Ras transformation. The introduction of an overexpressed gene in NIH 3T3 cells may promote morphological transformation and loss of contact inhibition, which can help determine the oncogenic potential of that gene of interest. An assay that provides a straightforward method to assess one aspect of the transforming potential of an oncogene is the Focus Formation Assay (FFA)2. When NIH 3T3 cells divide normally in culture, they do so until they reach a confluent monolayer. However, in the presence of an overexpressed oncogene, these cells can begin to grow in dense, multilayered foci1 that can be visualized and quantified by crystal violet or Hema 3 staining. In this article we describe the FFA protocol with retroviral transduction of the gene of interest into NIH 3T3 cells, and how to quantify the number of foci through staining. Retroviral transduction offers a more efficient method of gene delivery than transfection, and the use of an ecotropic murine retrovirus provides a biosafety control when working with potential human oncogenes.

The Focus Formation Assay provides a straightforward method to assess the transforming potential of a candidate oncogene.

Malignant transformation of cells is typically associated with increased proliferation, loss of contact inhibition, acquisition of anchorage-independent ...

Diffuse Optical Spectroscopy for the Quantitative Assessment of Acute Ionizing Radiation Induced Skin Toxicity Using a Mouse Model

Acute skin toxicities from ionizing radiation (IR) are a common side effect from therapeutic courses of external beam radiation therapy (RT) and negatively impact patient quality of life and long term survival. Advances in the understanding of the biological pathways associated with normal tissue toxicities have allowed for the development of interventional drugs, however, current response studies are limited by a lack of quantitative metrics for assessing the severity of skin reactions. Here we present a diffuse optical spectroscopic (DOS) approach that provides quantitative optical biomarkers of skin response to radiation. We describe the instrumentation design of the DOS system as well as the inversion algorithm for extracting the optical parameters. Finally, to demonstrate clinical utility, we present representative data from a pre-clinical mouse model of radiation induced erythema and compare the results with a commonly employed visual scoring. The described DOS method offers an objective, high through-put evaluation of skin toxicity via functional response that is translatable to the clinical setting.

We present a diffuse optical spectroscopic (DOS) approach that provides quantitative optical biomarkers of skin response to radiation. We describe DOS instrumentation design, optical parameters extraction algorithms and the animal handling procedures required to yield representative data from a pre-clinical mouse model of radiation induced erythema.

Acute skin toxicities from ionizing radiation (IR) are a common side effect from therapeutic courses of external beam radiation therapy (RT) and ...

Identifying Inhibitors of the HBx-DDB1 Interaction Using a Split Luciferase Assay System

There is an urgent need for novel therapeutic agents for hepatitis B virus (HBV) infection. Although currently available nucleos(t)ide analogs potently inhibit viral replication, they have no direct effect on the expression of viral proteins transcribed from a viral covalently closed circular DNA (cccDNA). As high viral antigen load may play a role in this chronic and HBV-related carcinogenesis, the goal of HBV treatment is to eradicate viral proteins. HBV regulatory protein X (HBx) binds to the host DNA damage-binding protein 1 (DDB1) protein to degrade structural maintenance of chromosomes 5/6 (Smc5/6), resulting in activation of viral transcription from cccDNA. Here, using a split luciferase complementation assay system, we present a comprehensive compound screening system to identify inhibitors of the HBx-DDB1 interaction. Our protocol enables easy detection of interaction dynamics in real time within living cells. This technique may become a key assay to discover novel therapeutic agents for treatment of HBV infection.

Here, we present a method for screening anti-hepatitis B viral agents that inhibit the HBx-DDB1 interaction using a split luciferase assay system. This system allows easy detection of protein-protein interactions and is suitable for identifying inhibitors of such interactions.

There is an urgent need for novel therapeutic agents for hepatitis B virus (HBV) infection. Although currently available nucleos(t)ide analogs potently ...

Quantification of Optic Nerve Cross Sectional Area on MRI: A Novel Protocol using Fiji Software

Optic nerve assessment is an important aspect of glaucoma diagnosis and follow-up. This project describes a protocol for a unified methodology of optic nerve cross-sectional assessment and quantification using 3 T MRI for image acquisition and ImageJ's Fiji software for image processing quantification. Image acquisition was performed using 3 T MRI, with proper instructions for the patient to ensure straight fixation during imaging. A T2-weighted fat suppressed sequence was used. A coronal cut taken 3 mm behind the globe and perpendicular to the optic nerve axis should be uploaded to the software. Using the threshold function, the white matter area of the optic nerve is selected and quantified, thus, eliminating inter-individual measurement bias. We also described the normal limits for the optic nerve cross-sectional area according to age, based on previously published literature. We used the described protocol to assess optic nerve of a suspected glaucoma patient. The optic nerve cross-sectional area was found to be within the normal limits, a finding further confirmed via optical coherence tomography of the optic nerve.

We provided a detailed protocol for a standardized method of optic nerve assessment and quantification using MRI, utilizing a widely available imaging sequence, and open access software for image analysis. Following this standardized protocol would provide meaningful data for comparison between different patients and different studies.

Optic nerve assessment is an important aspect of glaucoma diagnosis and follow-up. This project describes a protocol for a unified methodology of optic ...

A Real-World High-Intensity Interval Training Protocol for Cardiorespiratory Fitness Improvement

High-Intensity Interval Training (HIIT) has emerged as an interesting time-efficient approach to increase exercise adherence and improve health. However, few studies have tested the efficiency of HIIT protocols in a &#34;real world&#34; setting, e.g., HIIT protocols designed for outdoor spaces without specialized equipment. This study presents a &#34;real world&#34; training protocol, named &#34;beep training&#34;, and compares the efficiency of a HIIT regiment versus a traditional long-duration Moderate-Intensity Continuous Training (MICT) regiment using this beep training protocol on VO2 max of overweight untrained men. Twenty-two subjects performed outdoor running with MICT (n = 11) or HIIT (n = 11). Cardiorespiratory fitness was assessed before and after training protocols using a metabolic analyzer. Both training protocols were performed 3 days a week for 8 weeks using the Beep Test results. The MICT group performed the exercise program at 60%-75% of the maximum speed of the 20 m shuttle test (Vmax) and with a progression of the distance of 3,500-5,000 m. The HIIT group performed the interval exercise with 7-10 bouts of 200 m at 85%-100% of the maximum speed of the 20 m shuttle test (Vmax), interspersed with 1 min of passive recovery. Although the HIIT group presented a significantly lower training volume than the MICT group (p &#60; 0.05) after 8 weeks of beep training, HIIT was superior to MICT in improving VO2 max (MICT: ~4.1%; HIIT: ~7.3%; p &#60; 0.05). The &#34;real world&#34; HIIT regiment based on beep training protocol is a time-efficient, low-cost, and easy-to-implement protocol for overweight untrained men.

This study presents a low-cost and easy-to-implement "real world" high-intensity interval training (HIIT) protocol for scientific research and discusses its efficiency for cardiorespiratory fitness.

High-Intensity Interval Training (HIIT) has emerged as an interesting time-efficient approach to increase exercise adherence and improve health. However, ...

Network Pharmacology Prediction and Metabolomics Validation of the Mechanism of Fructus Phyllanthi against Hyperlipidemia

Hyperlipidemia has become a leading risk factor for cardiovascular diseases and liver injury worldwide. Fructus Phyllanthi (FP) is an effective drug against hyperlipidemia in Traditional Chinese Medicine (TCM) and Indian Medicine theories, however the potential mechanism requires further exploration. The present research aims to reveal the mechanism of FP against hyperlipidemia based on an integrated strategy combining network pharmacology prediction with metabolomics validation. A high-fat diet (HFD)-induced mice model was established by evaluating the plasma lipid levels, including total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C). Network pharmacology was applied to find out the active ingredients of FP and potential targets against hyperlipidemia. Metabolomics of plasma and liver were performed to identify differential metabolites and their corresponding pathways among the normal group, model group, and intervention group. The relationship between network pharmacology and metabolomics was further constructed to obtain a comprehensive view of the process of FP against hyperlipidemia. The obtained key target proteins were verified by molecular docking. These results reflected that FP improved the plasma lipid levels and liver injury of hyperlipidemia induced by a HFD. Gallic acid, quercetin, and beta-sitosterol in FP were demonstrated as the key active compounds. A total of 16 and six potential differential metabolites in plasma and liver, respectively, were found to be involved in the therapeutic effects of FP against hyperlipidemia by metabolomics. Further, integration analysis indicated that the intervention effects were associated with CYP1A1, AChE, and MGAM, as well as the adjustment of L-kynurenine, corticosterone, acetylcholine, and raffinose, mainly involving tryptophan metabolism pathway. Molecular docking ensured that the above ingredients acting on hyperlipidemia-related protein targets played a key role in lowering lipids. In summary, this research provided a new possibility for preventing and treating hyperlipidemia.

The present protocol describes an integrated strategy for exploring the key targets and mechanisms of Fructus Phyllanthi against hyperlipidemia based on network pharmacology prediction and metabolomics verification.

Hyperlipidemia has become a leading risk factor for cardiovascular diseases and liver injury worldwide. Fructus Phyllanthi (FP) is an effective drug ...