The authors would like to express their gratitude to Mr. Jeroen van den Berg and Mr. Matthijs Wassink from the development mechanics group at UMC Utrecht for their help in wrapping process of the osteochondral plugs. This work was supported by a Grant from Dutch Arthritis Foundation.

NOTE: The protocol presented here is adopted from the experimental and computational procedures of recent research papers 6,8,9. The protocol is illustrated in Figure 1.
The cadaveric materials were collected with permission from veterinary faculty of Utrecht University.
1. Sample and Bath Preparation
<ol>
	<li>Drill out cylindrical osteochondral plugs (diameter of 8.5 mm) from cadaveric equine femoral condyles using custom-made drill bit (Figure 1) while spraying cool Phosphate-buffered Saline&#160;(PBS) to prevent overheating and subsequent cartilage damage.</li>
	<li>Heat-shrink the osteochondral plugs with a plastic shrinking sleeve to minimize the lateral diffusion of the overlaying bath.
	<ol>
		<li>Mount the osteochondral plug with cartilage at the top initially inside the plastic shrinking sleeve and follow by blowing hot air to it. Add wet cotton pieces on the surface of cartilage to prevent heat-related damage.</li>
	</ol>
	</li>
	<li>Prepare finite-baths of charged (e.g.,&#160;650 &#181;L, 420 mM, ioxaglate, Molecular Weight (MW) = 1,269 Da, charge = -1) and neutral (650 &#181;L, 420 mM, iodixanol, MW = 1,550 Da) solutes separately.</li>
	<li>Load the prepared finite-baths on the surface of cartilage using a syringe and place a cork plug on the wrapped sample to prevent evaporation during experiments at RT (Figure 2A). To study the neutral solute transport, place the iodixanol bath and to study the negatively charged solute transport place ioxaglate bath onto the cartilage surface.</li>
</ol>
2. Imaging and Image Processing
<ol>
	<li>Place the wrapped samples isolated with cork plug on a custom-made holder attached to the motorized stage of a micro-CT. Place the sample so that cartilage surface covered with contrast agent solution is facing upward.</li>
	<li>Scan using the micro-CT (voxel size of 40 &#215; 40 &#215; 40 &#181;m3, scan time of 2 min , tube voltage of 90 kV and tube current of 180 &#181;A) a field of view consisting of cartilage, subchondral plate, and finite-bath in several time points until equilibrium state (48 h) is reached (Figure 2A). The equilibrium state is achieved when concentration values do not change over time.</li>
	<li>Register the 3D images in different time points based on the initial image to facilitate positioning of the Region of Interest (ROI) using manufacturer&#39;s software (e.g., Analyze).</li>
	<li>Convert the 3D reconstructed micro-CT images into 2D Tagged Image File Format (TIFF) stack before processing them using manufacturer&#39;s software.</li>
	<li>Globally segment (ImageJ&#62;Adjust&#62;Threshold) the cartilage from the subchondral bone and overlying bath in the software.</li>
	<li>Obtain the average grey value of cartilage at different time points (ImageJ&#62;Analyze&#62;Measure) using the generated cartilage mask in the previous step.</li>
	<li>Given the initial bath concentration and initial contrast agent concentration in the cartilage, use a linear calibration curve to convert the average grey values to the actual concentration of solutes. Previous data support the fact that grey values maintain a linear relationship with the concentration of contrast agents.</li>
	<li>Plot the solute concentrations versus experimental time points.</li>
</ol>
3. Computational Modeling
NOTE: The diffusion in this problem is assumed to take place in 1D (along the z-axis), which complies with the experimental boundary condition. Therefore, the geometry could be arbitrarily created.
<ol>
	<li>Build finite-bath based cartilage multi-zone models: 1) cartilage consisting of superficial zone (20% of the total cartilage thickness), middle zone (50% of the total cartilage thickness) and deep zone (30% of the total cartilage thickness) 12 and 2) finite-bath in FEBio 13,14 (Figure 2B).</li>
	<li>Assign the mechanical and physical properties of different zones of cartilage and bath in FEBio. Young&#39;s modulus (10 MPa) was assumed to be high enough to resist the osmotic pressure exerted by the overlying bath and therefore protect the cartilage from excessive deformations.
	<ol>
		<li>Use a hydraulic permeability of 10-3 mm4/Ns and Poisson&#39;s ratio of 0. Use actual solute diffusion coefficient of the bath in the simulations 8,9.</li>
	</ol>
	</li>
	<li>Generate mesh (8-node trilinear hexahedral elements) and refine it near the boundaries (Figure 2B) 8,9.</li>
	<li>Biphasic-solute model
	<ol>
		<li>Apply initial solute concentration in the bath and effective pressure corresponding to it. Look at the description of effective pressure in 9,15.</li>
		<li>Run the model in transient mode to obtain solute concentration versus time curves according to the prescribed diffusion coefficients in different cartilage zones.</li>
	</ol>
	</li>
	<li>Multiphasic model 
	NOTE: The electric fluctuation between bath and tissue can be circumvented by adding two monovalent counter-ions to both the bath and the tissue.
	<ol>
		<li>For steady-state models: use the same effective fluid pressures and concentrations in cartilage and overlying bath while increasing FCD to its desired value.</li>
		<li>For transient models: create a well-stirred finite-bath by keeping the solute diffusion coefficient in the bath sufficiently high. Inject the solute from the bath-air interface into the bath to reach its desired concentration value.</li>
		<li>Transient: remove the prescribed solute concentration boundary condition in the previous step and revert the diffusion coefficient of the finite-bath to its actual diffusion coefficient.</li>
		<li>Run the model to obtain solute concentration-time curves based on applied FCDs and diffusion coefficients in different cartilage zones.</li>
	</ol>
	</li>
	<li>FEBio-MATLAB interface
	<ol>
		<li>Develop a MATLAB code to automatically perform simulation in FEBio and plot concentration-time curves (FEBio-MATLAB interface) 8,9.</li>
		<li>Change diffusion coefficients and FCDs in cartilage zones using FEBio-MATLAB interface. Run models in FEBio and extract solute concentration-time curves 8,9.</li>
		<li>Compare the obtained solute concentration-time curves with the experimental data and obtain sets of diffusion coefficients and FCDs in different cartilage zones based on minimum root mean square error (RMSE) 8,9.</li>
	</ol>
	</li>
</ol>
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/54984/54984fig1.jpg" /> 
Figure 1: Experimental Setup. A) Sample extraction procedure using a custom-made drill bit. B) Micro-CT imaging procedure to monitor diffusion process. <a href="http://cloudfront.jove.com/files/ftp_upload/54984/54984fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/54984/54984fig2.jpg" /> 
Figure 2: Schematic. A) Experimental design. B) Multi-zone computational model consisting of the finite bath, superficial, middle and deep zones of cartilage and associated mesh. <a href="http://cloudfront.jove.com/files/ftp_upload/54984/54984fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

<ol>
	<li>Arkill, K. P., Winlove, C. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Solute+transport+in+the+deep+and+calcified+zones+of+articular+cartilage.">Solute transport in the deep and calcified zones of articular cartilage.</a> Osteoarthritis Cartilage. 16 (6), 708-714 (2008).</li><li>Chin, H. C., Moeini, M., Quinn, T. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Solute+transport+across+the+articular+surface+of+injured+cartilage.">Solute transport across the articular surface of injured cartilage.</a> Arch Biochem Biophys. 535 (2), 241-247 (2013).</li><li>Leddy, H. A., Guilak, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Site-specific+effects+of+compression+on+macromolecular+diffusion+in+articular+cartilage.">Site-specific effects of compression on macromolecular diffusion in articular cartilage.</a> Biophys J. 95 (10), 4890-4895 (2008).</li><li>Leddy, H. A., Guilak, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Site-Specific+Molecular+Diffusion+in+Articular+Cartilage+Measured+using+Fluorescence+Recovery+after+Photobleaching.">Site-Specific Molecular Diffusion in Articular Cartilage Measured using Fluorescence Recovery after Photobleaching.</a> Annals of Biomedical Engineering. 31 (7), 753-760 (2003).</li><li>Gu, W. Y., Yao, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effects+of+hydration+and+fixed+charge+density+on+fluid+transport+in+charged+hydrated+soft+tissues.">Effects of hydration and fixed charge density on fluid transport in charged hydrated soft tissues.</a> Ann Biomed Eng. 31 (10), 1162-1170 (2003).</li><li>Pouran, B., Arbabi, V., Zadpoor, A. A., Weinans, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Isolated+effects+of+external+bath+osmolality,+solute+concentration,+and+electrical+charge+on+solute+transport+across+articular+cartilage.">Isolated effects of external bath osmolality, solute concentration, and electrical charge on solute transport across articular cartilage.</a> Medical Engineering and Physics. 38 (12), 1399-1407 (2016).</li><li>Kulmala, K. A. M., 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=Diffusion+coefficients+of+articular+cartilage+for+different+CT+and+MRI+contrast+agents.">Diffusion coefficients of articular cartilage for different CT and MRI contrast agents.</a> Medical Engineering &amp; Physics. 32 (8), 878-882 (2010).</li><li>Arbabi, V., Pouran, B., Weinans, H., Zadpoor, A. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Transport+of+Neutral+Solute+Across+Articular+Cartilage:+The+Role+of+Zonal+Diffusivities.">Transport of Neutral Solute Across Articular Cartilage: The Role of Zonal Diffusivities.</a> Journal of Biomechanical Engineering. 137 (7), 071001-071001 (2015).</li><li>Arbabi, V., Pouran, B., Weinans, H., Zadpoor, A. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multiphasic+modeling+of+charged+solute+transport+across+articular+cartilage:+Application+of+multi-zone+finite-bath+model.">Multiphasic modeling of charged solute transport across articular cartilage: Application of multi-zone finite-bath model.</a> J Biomech. 49 (9), 1510-1517 (2016).</li><li>Arbabi, V., Pouran, B., Weinans, H., Zadpoor, A. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Combined+artificial+neural+networks+for+robust+estimation+of+the+diffusion+coefficients+across+cartilage.">Combined artificial neural networks for robust estimation of the diffusion coefficients across cartilage.</a> , (2016).</li><li>Arbabi, V., Pouran, B., Weinans, H., Zadpoor, A. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Combined+inverse-forward+artificial+neural+networks+for+fast+and+accurate+estimation+of+the+diffusion+coefficients+of+cartilage+based+on+multi-physics+models.">Combined inverse-forward artificial neural networks for fast and accurate estimation of the diffusion coefficients of cartilage based on multi-physics models.</a> Journal of Biomechanics. , (2016).</li><li>Sophia Fox, A. J., Bedi, A., Rodeo, S. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Basic+Science+of+Articular+Cartilage:+Structure,+Composition,+and+Function.">The Basic Science of Articular Cartilage: Structure, Composition, and Function.</a> Sports Health. 1 (6), 461-468 (2009).</li><li>Ateshian, G., Weiss, J., Holzapfel, G. A., Kuhl, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ch.+17.">Ch. 17.</a> Computer Models in Biomechanics. , 231-249 (2013).</li><li>Ateshian, G. A., Maas, S., Weiss, J. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multiphasic+Finite+Element+Framework+for+Modeling+Hydrated+Mixtures+With+Multiple+Neutral+and+Charged+Solutes.">Multiphasic Finite Element Framework for Modeling Hydrated Mixtures With Multiple Neutral and Charged Solutes.</a> Journal of Biomechanical Engineering. 135 (11), 111001-111001 (2013).</li><li>Arbabi, V., Pouran, B., Weinans, H., Zadpoor, A. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Transport+of+neutral+solute+across+articular+cartilage+and+subchondral+plate.">Transport of neutral solute across articular cartilage and subchondral plate.</a> , (2016).</li><li>Pouran, B., Arbabi, V., Weinans, H., Zadpoor, A. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Application+of+multiphysics+models+to+efficient+design+of+experiments+of+solute+transport+across+articular+cartilage.">Application of multiphysics models to efficient design of experiments of solute transport across articular cartilage.</a> Comput Biol Med. 78, 91-96 (2016).</li><li>Hosseini, S. M., Wu, Y., Ito, K., Donkelaar, C. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+importance+of+superficial+collagen+fibrils+for+the+function+of+articular+cartilage.">The importance of superficial collagen fibrils for the function of articular cartilage.</a> Biomechanics and Modeling in Mechanobiology. 13 (1), 41-51 (2013).</li><li>Alexopoulos, L. G., Williams, G. M., Upton, M. L., Setton, L. A., Guilak, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Osteoarthritic+changes+in+the+biphasic+mechanical+properties+of+the+chondrocyte+pericellular+matrix+in+articular+cartilage.">Osteoarthritic changes in the biphasic mechanical properties of the chondrocyte pericellular matrix in articular cartilage.</a> Journal of Biomechanics. 38 (3), 509-517 (2005).</li><li>Felson, D. T., 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=Osteoarthritis:+new+insights.+Part+1:+the+disease+and+its+risk+factors.">Osteoarthritis: new insights. Part 1: the disease and its risk factors.</a> Ann Intern Med. 133 (8), 635-646 (2000).</li><li>Kokkonen, H. T., Jurvelin, J. S., Tiitu, V., Toyras, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Detection+of+mechanical+injury+of+articular+cartilage+using+contrast+enhanced+computed+tomography.">Detection of mechanical injury of articular cartilage using contrast enhanced computed tomography.</a> Osteoarthritis Cartilage. 19 (3), 295-301 (2011).</li><li>Raya, J. G., 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=Diffusion-tensor+imaging+of+human+articular+cartilage+specimens+with+early+signs+of+cartilage+damage.">Diffusion-tensor imaging of human articular cartilage specimens with early signs of cartilage damage.</a> Radiology. 266 (3), 831-841 (2013).</li><li>Tavakoli Nia, 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=Aggrecan+Nanoscale+Solid-Fluid+Interactions+Are+a+Primary+Determinant+of+Cartilage+Dynamic+Mechanical+Properties.">Aggrecan Nanoscale Solid-Fluid Interactions Are a Primary Determinant of Cartilage Dynamic Mechanical Properties.</a> ACS Nano. 9 (3), 2614-2625 (2015).</li><li>Arbabi, V., Campoli, G., Weinans, H., Zadpoor, A. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Estimation+of+cartilage+properties+using+indentation+tests,+finite+element+models,+and+artificial+neural+networks.">Estimation of cartilage properties using indentation tests, finite element models, and artificial neural networks.</a> , (2014).</li><li>Arbabi, V., Pouran, B., Campoli, G., Weinans, H., Zadpoor, A. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Determination+of+the+mechanical+and+physical+properties+of+cartilage+by+coupling+poroelastic-based+finite+element+models+of+indentation+with+artificial+neural+networks.">Determination of the mechanical and physical properties of cartilage by coupling poroelastic-based finite element models of indentation with artificial neural networks.</a> Journal of Biomechanics. 49 (5), 631-637 (2016).</li><li>Kokkonen, H. T., 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=Computed+tomography+detects+changes+in+contrast+agent+diffusion+after+collagen+cross-linking+typical+to+natural+aging+of+articular+cartilage.">Computed tomography detects changes in contrast agent diffusion after collagen cross-linking typical to natural aging of articular cartilage.</a> Osteoarthritis and Cartilage. 19 (10), 1190-1198 (2011).</li><li>Decker, S. G., Moeini, M., Chin, H. C., Rosenzweig, D. H., Quinn, T. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Adsorption+and+Distribution+of+Fluorescent+Solutes+near+the+Articular+Surface+of+Mechanically+Injured+Cartilage.">Adsorption and Distribution of Fluorescent Solutes near the Articular Surface of Mechanically Injured Cartilage.</a> Biophysical Journal. 105 (10), 2427-2436 (2013).</li><li>Silvast, T. S., Jurvelin, S. J., Tiitu, V., Quinn, T. M., Töyräs, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bath+Concentration+of+Anionic+Contrast+Agents+Does+Not+Affect+Their+Diffusion+and+Distribution+in+Articular+cartilage+In+Vitro.">Bath Concentration of Anionic Contrast Agents Does Not Affect Their Diffusion and Distribution in Articular cartilage In Vitro.</a> Cartilage. 4 (1), 42-51 (2013).</li><li>Silvast, T. S., Jurvelin, J. S., Lammi, M. J., T&#246;yr&#228;s, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=pQCT+study+on+diffusion+and+equilibrium+distribution+of+iodinated+anionic+contrast+agent+in+human+articular+cartilage+-+associations+to+matrix+composition+and+integrity.">pQCT study on diffusion and equilibrium distribution of iodinated anionic contrast agent in human articular cartilage - associations to matrix composition and integrity.</a> Osteoarthritis and Cartilage. 17 (1), 26-32 (2009).</li><li>Pouran, B., Arbabi, V., Villamar, J., Weinans, H., Zadpoor, A. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Contrast+agent's+transport+across+healthy+articular+cartilage+under+various+bath+conditions.">Contrast agent's transport across healthy articular cartilage under various bath conditions.</a> , (2015).</li><li>Arbabi, V., Pouran, B., Weinans, H., Zadpoor, A. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Application+of+a+biphasic-solute+model+in+predicting+diffusive+properties+of+osteochondral+interface.">Application of a biphasic-solute model in predicting diffusive properties of osteochondral interface.</a> , (2016).</li></ol>

The authors have nothing to disclose.

We presented an experimental protocol combined with a finite element modeling procedure to study the diffusion of neutral and charged solutes across articular cartilage. According to our recent studies, the proposed models could accurately describe the transport of both neutral (biphasic-solute) and negatively charged (multiphasic) solutes across different zones of articular cartilage 8,9. It is widely believed that articular cartilage becomes functionally limite...

Molecular transport plays a vital role in the homeostasis of articulating joints, delivery of therapeutics to articular cartilage and contrast-enhanced cartilage imaging 1,2,3. Factors such as cartilage integration and intactness, solute charge and size as well as osmolality and concentration of bath in contact with cartilage may influence the transport rate 4,5,6. The transport of solutes, either neutral or charged, can be different between articular cartilage zones, because each zone consists of different concentrations and orientations of major extracellular matrix molecules, namely proteoglycans (PGs) and collagen type II 1,7,8,9,10,11. More importantly, the transport of charged solutes can be highly dependent on the concentration of proteoglycans comprising negative fixed charges within the extracellular matrix which increases across articular cartilage 8,9. Those parameters particularly fixed charge density (FCD), orientation of collagen fibrils and water content variation across cartilage may undergo alterations as osteoarthritis (OA) progresses, thereby signifying the importance of studying diffusion across cartilage.
In the current study, a protocol based on previously established experimental and computational studies 6,8,9 is proposed to accurately investigate diffusion under various boundary conditions using neutral and charged solutes in a finite-bath model of diffusion. The proposed methods are composed of micro-Computed Tomography imaging (micro-CT) of a system including cartilage and a finite-bath supported by advanced biphasic-solute and multiphasic finite element models. These models enable obtaining the diffusion coefficients of neutral and charged molecules as well as FCDs across various zones of articular cartilage. Using these models, one can gain better understanding of the behavior of the diffusing neutral and charged molecules that could be used to investigate the interactions between cartilage and overlaying finite-bath.

<table><tbody><tr><td>Hexabrix</td><td>Guerbet</td><td>15HX005D</td><td>Negatively-charged contrast agent</td></tr><tr><td>Visipaque</td><td>GE healthcare</td><td>12570511</td><td>Nuetral contrast agent</td></tr><tr><td>PBS (Phosphate-buffered Saline)</td><td>Life technologies</td><td>10010023</td><td>Medium</td></tr><tr><td>micro-CT</td><td>Perkin Elmer</td><td></td><td>Monitoring diffusion</td></tr><tr><td>Freezing-point osmometer</td><td>Advanced instruments</td><td></td><td>Measuring solution osmolality</td></tr></tbody></table>

an experimental and finite element protocol to investigate the transport of neutral and charged solutes across articular cartilage

Osteoarthritis (OA) is a debilitating disease that is associated with degeneration of articular cartilage and subchondral bone. Degeneration of articular cartilage impairs its load-bearing function substantially as it experiences tremendous chemical degradation, i.e. proteoglycan loss and collagen fibril disruption. One promising way to investigate chemical damage mechanisms during OA is to expose the cartilage specimens to an external solute and monitor the diffusion of the molecules. The degree of cartilage damage (i.e. concentration and configuration of essential macromolecules) is associated with collisional energy loss of external solutes while moving across articular cartilage creates different diffusion characteristics compared to healthy cartilage. In this study, we introduce a protocol, which consists of several steps and is based on previously developed experimental micro-Computed Tomography (micro-CT) and finite element modeling. The transport of charged and uncharged iodinated molecules is first recorded using micro-CT, which is followed by applying biphasic-solute and multiphasic finite element models to obtain diffusion coefficients and fixed charge densities across cartilage zones.

The representative results provided here are adopted from previous research papers 6,8,9,16.
In OA, articular cartilage undergoes significant changes most importantly GAG loss, and collagen fibril damage 17,18,19</s...

Watch this Scientific Journal Video about An Experimental and Finite Element Protocol to Investigate the Transport of Neutral and Charged Solutes across Articular Cartilage at JoVE.com

An Experimental and Finite Element Protocol to Investigate the Transport of Neutral and Charged Solutes across Articular Cartilage

We propose a protocol to investigate the transport of charged and uncharged molecules across articular cartilage with the aid of recently developed experimental and numerical methods.

Osteoarthritis (OA) is a debilitating disease that is associated with degeneration of articular cartilage and subchondral bone. Degeneration of articular ...

an-experimental-finite-element-protocol-to-investigate-transport

Universidad de Cartagena UDEC

Research

JoVE Journal

Bioengineering

6.2K Views.  Delft University of Technology (TU Delft). We propose a protocol to investigate the transport of charged and uncharged molecules across articular cartilage with the aid of recently developed experimental and numerical methods. 

Video: An Experimental and Finite Element Protocol to Investigate the Transport of Neutral and Charged Solutes across Articular Cartilage

Real-time Visualization and Analysis of Chondrocyte Injury Due to Mechanical Loading in Fully Intact Murine Cartilage Explants

Homeostasis of articular cartilage depends on the viability of resident cells (chondrocytes). Unfortunately, mechanical trauma can induce widespread chondrocyte death, potentially leading to irreversible breakdown of the joint and the onset of osteoarthritis. Additionally, maintenance of chondrocyte viability is important in osteochondral graft procedures for optimal surgical outcomes. We present a method to assess the spatial extent of cell injury/death on the articular surface of intact murine synovial joints after application of controlled mechanical loads or impacts. This method can be used in comparative studies to investigate the effects of different mechanical loading regimens, different environmental conditions or genetic manipulations, as well as different stages of cartilage degeneration on short- and/or long-term vulnerability of in situ articular chondrocytes. The goal of the protocol introduced in the manuscript is to assess the spatial extent of cell injury/death on the articular surface of murine synovial joints. Importantly, this method enables testing on fully intact cartilage without compromising native boundary conditions. Moreover, it allows for real-time visualization of vitally stained articular chondrocytes and single image-based analysis of cell injury induced by application of controlled static and impact loading regimens. Our representative results demonstrate that in healthy cartilage explants, the spatial extent of cell injury depends sensitively on load magnitude and impact intensity. Our method can be easily adapted to investigate the effects of different mechanical loading regimens, different environmental conditions or different genetic manipulations on the mechanical vulnerability of in situ articular chondrocytes.

We present a method to assess the spatial extent of cell injury/death on the articular surface of intact murine joints after application of controlled mechanical loads or impacts. This method can be used to investigate how osteoarthritis, genetic factors and/or different loading regimens affect the vulnerability of in situ chondrocytes.

Homeostasis of articular cartilage depends on the viability of resident cells (chondrocytes). Unfortunately, mechanical trauma can induce widespread ...

Application of Atomic Force Microscopy to Detect Early Osteoarthritis

Biomechanical properties of cells and tissues not only regulate their shape and function but are also crucial for maintaining their vitality. Changes in elasticity can propagate or trigger the onset of major diseases like cancer or osteoarthritis (OA). Atomic force microscopy (AFM) has emerged as a strong tool to qualitatively and quantitatively characterize the biomechanical properties of specific biological target structures on a microscopic scale, measuring forces in a range from as small as the piconewton to the micronewton. Biomechanical properties are of special importance in musculoskeletal tissues, which are subjected to high levels of strain. OA as a degenerative disease of the cartilage results in the disruption of the pericellular matrix (PCM) and the spatial rearrangement of the chondrocytes embedded in their extracellular matrix (ECM). Disruption in PCM and ECM has been associated with changes in the biomechanical properties of cartilage. In the present study we used AFM to quantify these changes in relation to the specific spatial pattern changes of the chondrocytes. With each pattern change, significant changes in elasticity were observed for both the PCM and ECM. Measuring the local elasticity thus allows for drawing direct conclusions about the degree of local tissue degeneration in OA.

We present a method to investigate early osteoarthritic changes at the cellular level in articular cartilage by using atomic force microscopy (AFM).

Biomechanical properties of cells and tissues not only regulate their shape and function but are also crucial for maintaining their vitality. Changes in ...

A 3D System for Culturing Human Articular Chondrocytes in Synovial Fluid

Cartilage destruction is a central pathological feature of osteoarthritis, a leading cause of disability in the US. Cartilage in the adult does not regenerate very efficiently in vivo; and as a result, osteoarthritis leads to irreversible cartilage loss and is accompanied by chronic pain and immobility 1,2. Cartilage tissue engineering offers promising potential to regenerate and restore tissue function. This technology typically involves seeding chondrocytes into natural or synthetic scaffolds and culturing the resulting 3D construct in a balanced medium over a period of time with a goal of engineering a biochemically and biomechanically mature tissue that can be transplanted into a defect site in vivo 3-6. Achieving an optimal condition for chondrocyte growth and matrix deposition is essential for the success of cartilage tissue engineering. 
 In the native joint cavity, cartilage at the articular surface of the bone is bathed in synovial fluid. This clear and viscous fluid provides nutrients to the avascular articular cartilage and contains growth factors, cytokines and enzymes that are important for chondrocyte metabolism 7,8. Furthermore, synovial fluid facilitates low-friction movement between cartilaginous surfaces mainly through secreting two key components, hyaluronan and lubricin 9 10. In contrast, tissue engineered cartilage is most often cultured in artificial media. While these media are likely able to provide more defined conditions for studying chondrocyte metabolism, synovial fluid most accurately reflects the natural environment of which articular chondrocytes reside in.
 Indeed, synovial fluid has the advantage of being easy to obtain and store, and can often be regularly replenished by the body. Several groups have supplemented the culture medium with synovial fluid in growing human, bovine, rabbit and dog chondrocytes, but mostly used only low levels of synovial fluid (below 20&#37;) 11-25. While chicken, horse and human chondrocytes have been cultured in the medium with higher percentage of synovial fluid, these culture systems were two-dimensional 26-28. Here we present our method of culturing human articular chondrocytes in a 3D system with a high percentage of synovial fluid (up to 100&#37;) over a period of 21 days. In doing so, we overcame a major hurdle presented by the high viscosity of the synovial fluid. This system provides the possibility of studying human chondrocytes in synovial fluid in a 3D setting, which can be further combined with two other important factors (oxygen tension and mechanical loading) 29,30 that constitute the natural environment for cartilage to mimic the natural milieu for cartilage growth. Furthermore, This system may also be used for assaying synovial fluid activity on chondrocytes and provide a platform for developing cartilage regeneration technologies and therapeutic options for arthritis.

A 3D system of culturing human articular chondrocytes in high levels of synovial fluid is described. Synovial fluid reflects the most natural microenvironment for articular cartilage, and can be easily obtained and stored. This system thus can be used for studying cartilage regeneration and for screening therapeutics for treating arthritis.

Cartilage destruction is a central pathological feature of osteoarthritis, a leading cause of disability in the US. Cartilage in the adult does not ...

Biology

Characterization of Intra-Cartilage Transport Properties of Cationic Peptide Carriers

Several negatively charged tissues in the body, like cartilage, present a barrier to the targeted drug delivery due to their high density of negatively charged aggrecans and, therefore, require improved targeting methods to increase their therapeutic response. Because cartilage has a high negative fixed charge density, drugs can be modified with positively charged drug carriers to take advantage of electrostatic interactions, allowing for enhanced intra-cartilage drug transport. Studying the transport of drug carriers is, therefore, crucial towards predicting the efficacy of drugs in inducing a biological response. We show the design of three experiments which can quantify the equilibrium uptake, depth of penetration and non-equilibrium diffusion rate of cationic peptide carriers in cartilage explants. Equilibrium uptake experiments provide a measure of the solute concentration within the cartilage compared to its surrounding bath, which is useful for predicting the potential of a drug carrier in enhancing therapeutic concentration of drugs in cartilage. Depth of penetration studies using confocal microscopy allow for the visual representation of 1D solute diffusion from the superficial to deep zone of cartilage, which is important for assessing whether solutes reach their matrix and cellular target sites. Non-equilibrium diffusion rate studies using a custom-designed transport chamber enables the measurement of the strength of binding interactions with the tissue matrix by characterizing the diffusion rates of fluorescently labeled solutes across the tissue; this is beneficial for designing carriers of optimal binding strength with cartilage. Together, the results obtained from the three transport experiments provide a guideline for designing optimally charged drug carriers which take advantage of weak and reversible charge interactions for drug delivery applications. These experimental methods can also be applied to evaluate the transport of drugs and drug-drug carrier conjugates. Further, these methods can be adapted for the use in targeting other negatively charged tissues such as meniscus, cornea and the vitreous humor.

This protocol determines equilibrium uptake, depth of penetration and non-equilibrium diffusion rate for cationic peptide carriers in cartilage. Characterization of transport properties is critical for ensuring an effective biological response. These methods can be applied for designing an optimally charged drug carriers for targeting negatively charged tissues.

Several negatively charged tissues in the body, like cartilage, present a barrier to the targeted drug delivery due to their high density of negatively ...

Labeling of Extracellular Vesicles for Monitoring Migration and Uptake in Cartilage Explants

Extracellular vesicles (EVs) are used in different studies to prove their potential as a cell-free treatment due to their cargo derived from their cellular source, such as platelet lysate (PL). When used as treatment, EVs are expected to enter the target cells and effect a response from these. In this research, PL-derived EVs have been studied as a cell-free treatment for osteoarthritis (OA). Thus, a method was set up to label EVs and test their uptake on cartilage explants. PL-derived EVs are labeled with the lipophilic dye PKH26, washed twice through a column, and then tested in an in vitro inflammation-driven&#160;OA model for 5 h after particle quantification by nanoparticle tracking analysis (NTA). Hourly, cartilage explants are fixed, paraffined, cut into 6 &#181;m sections to mount on slides, and observed under a confocal microscope. This allows verification of whether EVs enter the target cells (chondrocytes) during this period and analyze their direct effect.

Here, we present a protocol to label platelet lysate-derived extracellular vesicles to monitor their migration and uptake in cartilage explants used as a model for osteoarthritis.

Extracellular vesicles (EVs) are used in different studies to prove their potential as a cell-free treatment due to their cargo derived from their ...

Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression

In this paper, we present a complete workflow for the biomechanical analysis of atherosclerotic plaque in the coronary vasculature. With atherosclerosis as one of the leading causes of global death, morbidity and economic burden, novel ways of analyzing and predicting its progression are needed. One such computational method is the use of fluid-structure interaction (FSI) to analyze the interaction between the blood flow and artery/plaque domains. Coupled with in vivo imaging, this approach could be tailored to each patient, assisting in differentiating between stable and unstable plaques. We outline the three-dimensional reconstruction process, making use of intravascular Optical Coherence Tomography (OCT) and invasive coronary angiography (ICA). The extraction of boundary conditions for the simulation, including replicating the three-dimensional motion of the artery, is discussed before the setup and analysis is conducted in a commercial finite element solver. The procedure for describing the highly nonlinear hyperelastic properties of the artery wall and the pulsatile blood velocity/pressure is outlined along with setting up the system coupling between the two domains. We demonstrate the procedure by analyzing a non-culprit, mildly stenotic, lipid-rich plaque in a patient following myocardial infarction. Established and emerging markers related to atherosclerotic plaque progression, such as wall shear stress and local normalized helicity, respectively, are discussed and related to the structural response in the artery wall and plaque. Finally, we translate the results to potential clinical relevance, discuss limitations, and outline areas for further development. The method described in this paper shows promise for aiding in the determination of sites at risk of atherosclerotic progression and, hence, could assist in managing the significant death, morbidity, and economic burden of atherosclerosis.

There is a need to determine which atherosclerotic lesions will progress in the coronary vasculature to guide intervention before myocardial infarction occurs. This article outlines the biomechanical modeling of arteries from Optical Coherence Tomography using fluid-structure interaction techniques in a commercial finite element solver to help predict this progression.

In this paper, we present a complete workflow for the biomechanical analysis of atherosclerotic plaque in the coronary vasculature. With atherosclerosis ...

A Friction Testing-Bioreactor Device for Study of Synovial Joint Biomechanics, Mechanobiology, and Physical Regulation

In primary osteoarthritis (OA), normal 'wear and tear' associated with aging inhibits the ability of cartilage to sustain its load-bearing and lubrication functions, fostering a deleterious physical environment. The frictional interactions of articular cartilage and synovium may influence joint homeostasis through tissue level wear and cellular mechanotransduction. To study these mechanical and mechanobiological processes, a device capable of replicating the motion of the joint is described. The friction testing device controls the delivery of reciprocal translating motion and normal load to two contacting biological counterfaces. This study adopts a synovium-on-cartilage configuration, and friction coefficient measurements are presented for tests performed in a phosphate-buffered saline (PBS) or synovial fluid (SF) bath. The testing was performed for a range of contact stresses, highlighting the lubricating properties of SF under high loads. This friction testing device can be used as a biomimetic bioreactor for studying the physical regulation of living joint tissues in response to applied physiologic loading associated with diarthrodial joint articulation.

The present protocol describes a friction testing device that applies simultaneous reciprocal sliding and normal load to two contacting biological counterfaces.

In primary osteoarthritis (OA), normal 'wear and tear' associated with aging inhibits the ability of cartilage to sustain its load-bearing and lubrication ...

Addressing Practical Issues in Atomic Force Microscopy-Based Micro-Indentation on Human Articular Cartilage Explants

Without a doubt, atomic force microscopy (AFM) is currently one of the most powerful and useful techniques to assess micro and even nano-cues in the biological field. However, as with any other microscopic approach, methodological challenges can arise. In particular, the characteristics of the sample, sample preparation, type of instrument, and indentation probe can lead to unwanted artifacts. In this protocol, we exemplify these emerging issues on healthy as well as osteoarthritic articular cartilage explants. To this end, we first show via a step-by-step approach how to generate, grade, and visually classify ex vivo articular cartilage discs according to different stages of degeneration by means of large 2D mosaic fluorescence imaging of the whole tissue explants. The major strength of the ex vivo model is that it comprises aged, native, human cartilage that allows the investigation of osteoarthritis-related changes from early onset to progression. In addition, common pitfalls in tissue preparation, as well as the actual AFM procedure together with the subsequent data analysis, are also presented. We show how basic but crucial steps such as sample preparation and processing, topographic sample characteristics caused by advanced degeneration, and sample-tip interaction can impact data acquisition. We also subject to scrutiny the most common problems in AFM and describe, where possible, how to overcome them. Knowledge of these limitations is of the utmost importance for correct data acquisition, interpretation, and, ultimately, the embedding of findings into a broad scientific context.

We present a step-by-step approach to identify and address the most common problems associated with atomic force microscopy micro-indentations. We exemplify the emerging problems on native human articular cartilage explants characterized by various degrees of osteoarthritis-driven degeneration.

Without a doubt, atomic force microscopy (AFM) is currently one of the most powerful and useful techniques to assess micro and even nano-cues in the ...

Creation of a Knee Joint-on-a-Chip for Modeling Joint Diseases and Testing Drugs

The high prevalence of debilitating joint diseases like osteoarthritis (OA) poses a high socioeconomic burden. Currently, the available drugs that target joint disorders are mostly palliative. The unmet need for effective disease-modifying OA drugs (DMOADs) has been primarily caused by the absence of appropriate models for studying the disease mechanisms and testing potential DMOADs. Herein, we describe the establishment of a miniature synovial joint-mimicking microphysiological system (miniJoint) comprising adipose, fibrous, and osteochondral tissue components derived from human mesenchymal stem cells (MSCs). To obtain the three-dimensional (3D) microtissues, MSCs were encapsulated in photocrosslinkable methacrylated gelatin before or following differentiation. The cell-laden tissue constructs were then integrated into a 3D-printed bioreactor, forming the miniJoint. Separate flows of osteogenic, fibrogenic, and adipogenic media were introduced to maintain the respective tissue phenotypes. A commonly shared stream was perfused through the cartilage, synovial, and adipose tissues to enable tissue crosstalk. This flow pattern allows the induction of perturbations in one or more of the tissue components for mechanistic studies. Furthermore, potential DMOADs can be tested via either &#34;systemic administration&#34; through all the medium streams or &#34;intraarticular administration&#34; by adding the drugs to only the shared &#34;synovial fluid&#34;-simulating flow. Thus, the miniJoint can serve as a versatile in vitro platform for efficiently studying disease mechanisms and testing drugs in personalized medicine.

We provide detailed methods for generating four types of tissues from human mesenchymal stem cells, which are used to recapitulate the cartilage, bone, fat pad, and synovium in the human knee joint. These four tissues are integrated into a customized bioreactor and connected through microfluidics, thus generating a knee joint-on-a-chip.

The high prevalence of debilitating joint diseases like osteoarthritis (OA) poses a high socioeconomic burden. Currently, the available drugs that target ...

Biotribological Testing and Analysis of Articular Cartilage Sliding against Metal for Implants

Osteochondral defects in middle-aged patients might be treated with focal metallic implants. First developed for defects in the knee joint, implants are now available for the shoulder, hip, ankle and the first metatarsalphalangeal joint. While providing pain reduction and clinical improvement, progressive degenerative changes of the opposing cartilage are observed in many patients. The mechanisms leading to this damage are not fully understood. This protocol describes a tribological experiment to simulate a metal-on-cartilage pairing and comprehensive analysis of the articular cartilage. Metal implant material is tested against bovine osteochondral cylinders as a model for human articular cartilage. By applying different loads and sliding speeds, physiological loading conditions can be imitated. To provide a comprehensive analysis of the effects on the articular cartilage, histology, metabolic activity and gene expression analysis are described in this protocol. The main advantage of tribological testing is that loading parameters can be adjusted freely to simulate in vivo conditions. Furthermore, different testing solutions might be used to investigate the influence of lubrication or pro-inflammatory agents. By using gene expression analysis for cartilage-specific genes and catabolic genes, early changes in the metabolism of articular chondrocytes in response to mechanical loading might be detected.

This protocol describes the preparation, biotribological testing, and analysis of osteochondral cylinders sliding against metal implant material. Outcome measures included in this protocol are metabolic activity, gene expression and histology.

Osteochondral defects in middle-aged patients might be treated with focal metallic implants. First developed for defects in the knee joint, implants are ...