Investigation of the nano-mechanical properties and surface topographies of wear particles and human knee cartilages

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Investigation of the nano-mechanical properties and surface topographies of wear particles and Human knee cartilages Meiling Wang, Zhongxiao Peng

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Received date: 16 August 2014 Revised date: 20 November 2014 Accepted date: 28 November 2014 Cite this article as: Meiling Wang, Zhongxiao Peng, Investigation of the nanomechanical properties and surface topographies of wear particles and Human knee cartilages, Wear, http://dx.doi.org/10.1016/j.wear.2014.11.033 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Investigation of the nano-mechanical properties and surface topographies of wear particles and human knee cartilages Meiling Wang*1,2 and Zhongxiao Peng1 1

School of Mechanical & Manufacturing Engineering The University of New South Wales Sydney, NSW 2052 Australia 2

College of Mechanical and Electrical Engineering

Nanjing University of Aeronautics and Astronautics Nanjing 210016, People’s Republic of China *Corresponding author: [email protected] Abstract Although wear particles are the by-products of wear processes in knee joints and carry rich information about the processes and wear conditions, wear debris generated in human knee joints has not been well studied. The purpose of this study was to develop methodologies for investigating the nano-mechanical properties and nano-surface topographies of wear particles found in human knee synovial fluid, and their correlation with those of human cartilages in osteoarthritis (OA) progression. To fulfil the purpose, atomic force microscopy (AFM) was used to study wear particles and human knee articular cartilages in a fluid mode and at a nanometer scale. Young’s moduli of wear debris and human cartilages were examined and compared. Image processing and numerical analysis techniques were established to quantitatively characterize the surface topographies of wear debris. The preliminary results demonstrated that the mechanical property and quantitative surface features of the wear particles were successfully studied by using the established methods. This study provided 1

evidence that the nano-scaled surface textures and nano-mechanical property of the wear particles alter with increasing OA grade, and that there is the need for further evaluation of correlations between wear particles and human cartilages, and the effectiveness of analysing wear particles for revealing nano-mechanical and structural changes in the knee joint conditions. Key words: Wear particles; Young’s modulus; Surface topography; Human cartilages; Wear severity

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1. Introduction

The knee joint, functioning like bearings, sustains wear and can be flexed and extended when transporting loads from the femur to the tibia in the normal human walking process. Each joint has cartilages, subchondral bones and soft tissues at and around its junctions. Cartilage, a wear bearing material, covers the end of the bones in the knee joint. Wear occurs to the articular cartilage surfaces during the normal motions of the knee. Wear particles produced from articulations are released into the synovial fluid and may be involved in biological activities in the knee [1]. Articular cartilage has a limited repair capability [2]. If the regeneration cannot keep pace with the degradation of the matrix due to reasons such as aging and damage, osteoarthritis (OA) will occur. It has been demonstrated that the pathological changes in OA initiate at a molecular scale and gradually spread to higher levels of the architecture, causing mechanical failure and ultimately, complete erosion of the articular cartilage [3]. Therefore, it is important to monitor changes in the structure and function of the knee at the nanometre scale. The nanomechanical properties and nano-scaled surface topographies of human articular cartilages have been investigated for OA studies. For example, the nano-stiffness of normal and diseased human cartilages was found to be able to reveal knee joint conditions [4, 5]. Wen et al. [6] investigated the elastic modulus of collagen fibres in the healthy and diseased cartilages at the nanometer scale and in a dehydrated condition. The nano-surface topographies of human cartilages revealed early signs for OA [7-8]. These studies show that measurements of the nano-stiffness and nano-scaled surface topography of cartilages have the potential to indicate knee joint conditions in an early stage. As the by-products of articular cartilages in the wear process, wear particles carry rich information on knee joint conditions and could potentially be used for the diagnosis and/or 3

prognosis of OA severities. Wear particles found in normal and osteoarthritc human knee joints range from 0.54 µm [9] to 286.3 µm [10] in size. When OA progresses, the wear rate increases, with more and larger wear particles produced. The size of human wear particles in osteoarthritic synovial fluid spreads wider than that in a normal joint [9]. Particles found in healthy knee joints are smooth and thin [11], while those found in diseased knee joints tend to be irregular and chunky [10]. These existing observations demonstrate that the wear particles reveal joint conditions and their changes. To further develop a less intrusive and cost effective technique based on wear debris analysis, it is necessary to investigate the nanomechanical and nano-scaled surface topographical properties of the by-products. These properties have not yet been examined due to the lack of established sample preparation, imaging acquisition and quantitative particle characterisation techniques in the past. The relationships between these properties of wear particles and those of articular cartilages in OA progression are yet to be investigated. Therefore, this study was to develop a protocol for studying the properties of human wear debris and their relationship with the cartilages.

2. Materials and Methods 2.1 Samples and sample preparation for AFM imaging Healthy and osteoarthritic human knee articular cartilages and synovial fluid samples were obtained in Queensland, Australia, under the Ethics Approval Number MHS20100401-01 approved by the Mater Health Services North Queensland Ltd Human Research Ethics Committee. Freshly collected human knee synovial fluid, containing wear particles, was prepared using the procedures described as follows. Firstly, the human knee synovial fluid was centrifuged with a centrifugal force of 2500 g and at 4 ºC for 15 min using a centrifuge. Wear particles were mainly precipitated at the bottom of the tube after the centrifugation. The 4

supernatant of the synovial fluid was taken out. Secondly, the remaining solution underwent a vortex process for 2 min to ensure that wear particles were evenly suspended in the solution. The solution was then passed through a filter paper with a pore size of 60 µm to remove tissues. The filtered solution was then vortex again and diluted with distilled water. The diluted solution was passed through a filter paper with a pore size of 3 µm so wear particles were collected on the filter paper. Thirdly, the collected wear particles were deposited onto an aldehyde functional plasma polymer surface. The wear particles on the functional surfaces were stored at 4 ºC for ~12 h and then brought to AFM for investigations. The entire preparation process was carried out in a Class II cabinet to avoid contamination. Further detailed information on the wear particle preparation procedures can be found in [12]. For the purpose of the methodology development and evaluation, nine synovial fluid samples from nine patients out of 53 synovial fluid samples were used to prepare wear particle samples and obtain initial data. More than 100 particles were imaged and analysed using the methods presented in sections 2.2 and 2.3. Cartilage samples were obtained from femoral knee condyles in the total knee replacement surgeries of seven patients. These samples were prepared with a thickness of 2–4 mm and a diameter of ~4 mm. During the preparation process, cartilage samples were hydrated with drops of sterile phosphate buffered saline (PBS) solution. The prepared cartilages were glued onto the bottom of sterile petri dishes, which were then filled with PBS with protease inhibitor and stored at –20 ºC. Freezing cartilages at -20 °C is commonly used in storing the samples [13, 14]. Previous investigation revealed that changes to the biomechanical properties and histological patters of the cartilage due to the freeze/thaw cycles are not significant [15]. Before carrying out measurements, the frozen samples were thawed at 4 ºC for ~12 h. For each OA grade, at least two cartilage samples were investigated. Detailed information on the preparation of the human cartilages can be referred to [5, 8]. 5

For a comparison purpose, whenever it was possible, both synovial fluid and cartilage samples were collected from the same patients. The degeneration of the collected cartilage samples was graded according to Outerbridge scaling system [16]. The synovial fuild samples were marked with the same grade as the cartilage samples. 2.2 Atomic force microscopic (AFM) imaging and indentation The Peakforce QNM (Quantitative NanoMechanics) tapping mode was operated in a liquid environment using a MultiMode8 AFM (Bruker, Singapore). The Peakforce QNM mode can quantitatively map the modulus, adhesion, surface topographies and deformation of a material in a selected area. Silicon nitride probes (tip height: 2.5–8.0 µm; front angle: 15±2.5º; nominal tip radius: 20 nm; nominal spring constant: 0.35 N/m) were used to image and indent wear particles. During the AFM imaging process, the relative Young’s modulus was measured simultaneously. Cartilage particles have a different relative Young’s modulus value to other particles such as proteins, and by comparing the relative Young’s modulus values, cartilage particles were identified and separated. A deformation of ~10 nm was controlled in the Peakforce QNM mode to measure the Young’s modulus and adhesion. The scan area was set as 5 µm × 5 µm. The tip velocity was 2.19 µms-1. The scan rate was set as 0.1–0.5 Hz and the scan lines were 256 × 256 [12]. The imaging process of human cartilages was operated in the same AFM configurations and used the same AFM probes as for the wear particles. The loading force applied on the cartilages in the scanning process varied because the samples at different OA grades required different loading forces [8]. A smooth cartilage sample (e.g., OA grade 1 sample) required a loading force within a range of 0.2–0.3 nN while a cartilage sample with a rough surface required a loading force from 6.5 nN to 16.5 nN. The scan area of 5 µm × 5 µm, the scan rate in a range of 0.1–0.5 Hz and the scan lines of 256×256 were the same as for the wear 6

particles. The same or similar scanning conditions were set so that direct comparisons of the surface topographies of the cartilages could be made to those of the wear particles. Three to four locations were randomly selected on each cartilage sample. Detailed information can be found in [8]. The nano-indentation of human cartilages was operated in a scanning probe microscope (SPM). V-shape Si3N4 pyramidal tips (the spring constant: 0.56 Nm-1, the nominal tip radius of curvature: 40 nm, the half angle: 22.5º) were used to indent the cartilage samples. Deflection-displacement curves were acquired at translation rates in a range of 2–5 µms-1 in the z-direction. The maximum force for indentation was ~80 nN and the corresponding indentation depth was ~1800 nm. A total of twelve cartilage samples were indented. Generally, two to four locations for each cartilage were randomly indented. Ten repeats were made at each location. Further details on the nano-indentation can be found in [5]. 2.3 Calculation of the Young’s modulus The PeakForce QNM mode controls the force applied to the wear particles by the tip to ensure that their deformation depths are small (~10 nm in this study) so the effect of the substrate on the measured modulus is minimized [17]. The Young’s moduli of wear particles were determined using the Derjaguin-Muller-Toporov (DMT) model [18].

Ftip =

4 * E Rd 3 + Fadh 3

(1)

Where Ftip is the force on the tip, Fadh is the adhesion force, R is the tip end radius, d is the tip-sample separation, and E * is the reduced Young’s modulus. Cartilages are much softer than wear particles. Cartilage surfaces probably deform when the tip approaches the surfaces. Therefore, cartilages need larger deformations to fully fit the tip geometry and to get accurate and reliable indentation data compared to wear particles which 7

are much smaller and thinner than the cartilage samples. Investigations using sheep cartilages suggested that a loading force larger than 20 nN, corresponding to an indentation depth of over 300 nm, was needed to reveal different wear conditions [19]. Therefore, this study investigated the Young’s moduli of the cartilages at indentation depths of 300 nm and 1000 nm. For the cartilage samples, since the indentation depths were much larger than the tip radius, the contact geometry was assumed to fit with a pyramidal geometry. Thus the pyramidal model was used to determine the Young’s moduli of the cartilages [20, 21].

F (d ) =

1.4906 Etanα 2 d 2(1 −ν 2 )

(2)

Where α is the half angle of the pyramidal tip, d is the indentation depth of the tip into a cartilage sample, E is the effective indentation modulus of a cartilage sample, F is the indentation force, and ν is the Poisson’s ratio of human knee cartilage. The Poisson’s ratio of human knee cartilage and wear particles was taken as 0.5 [22, 23]. 2.4 Numerical characterisation and statistics analysis Once the 3D surface data of wear particles was obtained using the particle preparation technique developed in [12] and the AFM imaging method detailed in section 2.2, the numerical characterisations of their surface topographies become feasible. Wear particles and cartilages were imaged under the same conditions using AFM and analysed with the same procedures so that a direct comparison of the results could be made. High quality AFM images were selected and used for numerical characterisations. These AFM images were flattened to remove image bow and scan distortions. Then filtration with nesting index 1 µm was used to extract surface topographic features using a standard Gaussian filter. The surface geometric information was extracted using field and feature 8

parameters defined in ISO 25178-2 [24]. These parameters reveal amplitude, spatial, hybrid and functional related information of a surface. Among the numerical parameters described above, the surface roughness parameter Sa is the most widely used and was reported as an example here to show the quantitative data obtained in this study. The surface roughness (Sa) of wear particles was calculated using Eq. (3) as defined in ISO 25178-2 [24]. Sa =

1 z ( x, y ) dxdy A ∫∫

(3)

where A is the definition area, and z (x, y) is height of the scale limited surface at position x, y. To evaluate the reliability of the obtained results, a statistics analysis of the quantitative data was carried out in a 95% confidence interval. A correlation analysis of the properties of the wear particles and those of the cartilages was performed in Microsoft Excel 2010 to get an idea of their relationship.

3. Results and Discussion As stated before, this work was to establish imaging and quantitative analysis techniques for studying the nano-mechanical properties and nano-scaled surface morphologies of human wear debris. Some preliminary results of the Young’s moduli and surface topographies of wear particles and those of human cartilages were obtained and compared in the study. These results are presented and discussed below to demonstrate that the developed methods have enabled us to obtain the particle information and can be used to carry out further studies on human particle and cartilage samples in the nanometre scale.

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3.1 The Young’s moduli of wear particles and human articular cartilages

For the first time, the Young’s moduli of human wear particles and their changes in OA progression have been investigated. This was done using a very small load so that the nanomechanical property of the top surface could be studied. As shown in Figure 1(a), the preliminary data shows that there was a variation in the mean values of the particle Young’s moduli as OA progressed. The alteration in the moduli of the wear particles was not found to be significant, which was suggested by a t-test with a p value of 0.94. The moderate change to the particle moduli may be explained by the fact that (a) limited wear particles were studied, and (b) wear particles are generated over a long period of time and thus, the information they carry is complicated, revealing both the current condition and the history of the knee. A significant increase was observed at the late stage. It is speculated that the wear particles from the subchondral bone in the samples with knee replacement contribute to the significant increase in the Young’s moduli. A linear regression in SPSS was conducted between the modulus results of the wear debris and OA grades, revealing a correlation coefficient of 0.802 and a coefficient of determination of 0.642. The correlation results revealed that the correlation was strong and that the linear model could predict 64.2% of the total variation, indicating that the overall trend of the Young’s moduli of the wear debris became generally stiffer with increasing severity of degeneration. Although limited data was obtained, it has demonstrated that the Young’s moduli of wear particles can be measured and have the potential to be used to assess the wear severity of the knee joint and to understand the wear process. In addition to the wear particle results, the Young’s moduli of human articular cartilages at indentation depths of 300 nm and 1000 nm were measured and are presented in Figure 2. The values measured at the two depths had the same trend. The preliminary data also showed that the change in the mechanical property of the cartilages was similar to that of the particle. The 10

correlation analysis confirmed the observation above. It was shown that the Young’s moduli of the wear particles had a medium strong correlation with those of the cartilages with a correlation coefficient of 0.71. It is worthwhile to mention that it is important to compare the Young’s modulus results of the particle and those of the cartilages under the same measurement conditions. This is because the mechanical property can vary significantly when measuring in different conditions, including the sample hydration status, indentation depth, tip shape and size, loading rate and magnitude. Under similar conditions, the Young’s modulus results of healthy cartilages reported in this study are similar to previous studies [4, 7, 25, 26, 27] but smaller than the

reported values obtained using conventional micrometre or millmetre scale indenters [4, 28]. The nano-scaled stiffness is different compared to the overall structural stiffness due to the fine nanometre scale structure [29]. The sharp AFM tip depicts the elastic properties of the fine structure of the cartilage, whereas micrometer and larger-scale tests measure its overall structural stiffness. In addition, structural changes induced by the enzyme in the OA process can affect this scale-dependent stiffness differently. We have to admit that the effects of loading rates and magnitudes on the Young’s modulus measurements need to be investigated in the future. As reported in [7, 30, 31], dynamic indentation moduli are sensitive to the indentation load and loading frequency. The mechanical property studied in a low load and slow loading frequency reveals the behaviour in slow activities such as walking. In this study, a very slow loading frequency (<0.5 Hz) and a low load (<20 nN) were used. Under this indentation condition, it is expectable that the Young’s modulus values obtained in this study are smaller than those measured using a higher load and/or loading frequency [7]. The above results need to be confirmed with a large number of wear particles using a range of loads and loading frequencies and in different indentation locations and depths. Reasons for 11

the changes in the Young’s moduli of wear particles are to be investigated in relation to the cartilage components, its permeability and nano-scaled viscoelasticity of the cartilage surface. The collagen fibres and proteoglycan are responsible for the stiffness of the articular cartilage [2]. As the wear product of cartilage, it is believed that the structure and type of collagen, proteoglycan and calcification of wear particles play a role in the nano-stiffness, which was not studied in the current work. Further research on the influence of the components of wear particles on the Young’s modulus should be investigated. 3.2 The nano-surface topographies of wear particles and human cartilages

AFM images of the nano-surface topographies of wear particles and human articular cartilages are displayed in Figure 3. As OA progressed, damages to the network of the articular cartilages became more and more severe, which was revealed by the AFM images in Figure 3. The healthy human cartilage had a well-intact collagen network (Figure 3(a) left), with the collagen fibres clearly seen in the image. The cartilage with mild OA (Figure 3(b) left) looked a bit rough and the surface appeared to have an increasing number of spots. The cartilage surface in a severe OA condition shown in Figure 3(c) left was rougher than that at a mild OA grade. The cartilage surface at an advanced OA grade (Figure 3(c) left) was even rougher, with obvious sharp edges and corners. Simultaneously, the surface textures of the wear particles became rougher with the OA progression. It can be clearly seen from the AFM images (Figure 3 (a-c) right) that the nanosurface topographies of the wear particles had similar features as to the cartilages. The nanoscaled surface topographies of wear particles have the potential to reveal the wear conditions of the knee, and to provide useful information in a non-destructive manner for possible OA management and medical therapy.

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For a quantitative point of view, the Sa values of the wear particles increased with OA progression (Figure 1(b)), confirming that the surface roughness of the wear particles was getting rougher as OA progressed. The Sa values showed a correlation coefficient of 0.84 with the Young’s moduli of these wear particles, denoting that the change in the surface roughness revealed a similar trend to that of the Young’s moduli in the progression of OA. Wear particles were probably involved in the inflammatory activities [1, 2] after being released into the synovial fluid, which probably caused the changes to their properties. The correlation results between the Young’s moduli and surface roughness of wear particles suggest that their changes closely correlated. For the first time, the changes in the surface topographies and Young’s moduli of wear particles in the deterioration process have been correlated with those of human cartilages in OA progression. The findings in this nano-scaled study suggest that the Young’s moduli and surface topographies of wear particles have the potential to reveal knee joint conditions.

4. Conclusion This study has established techniques to investigate the Young’s moduli and surface topographies of wear particles and their relationships with those of cartilages in the OA process in the human knee joint. The results provided evidence that the Young’s moduli and the nano-surface topographies of wear particles could be successfully obtained using the presented methods for studying changes in the nano-mechanical property and severity of the knee joint wear in the future. More wear particles need to be studied to confirm the preliminary results presented in this study. Further work on causes of the changes in the nano-mechanical property and surface topographies of articular cartilages and their wear particles should also be carried out for a better understanding of the OA process in a submicro scale. Responses of cartilages and wear particles to different loading conditions (a 13

range of load magnitudes and frequencies) and at various indentation depths need to be investigated for understanding of their nanoscale dynamic behavior and OA process. Acknowledgement The authors would like to thank Dr James Price for collecting the clinical samples and providing associated data for the project. Laurice Baxter, Emma Horrocks, Peter Bui, Tyler Chin and Yuan Tian are acknowledged for their assistance in the sample collection process. The authors acknowledge Associate Professor K. Vasilev at the University of South Australia, Australia, for supplying the aldehyde functional surfaces. The authors would also like to thank Professor Ketheesan at James Cook University and Ms Lynn Ferris at the University of New South Wales, Australia, for their permissions for accessing their labs to prepare wear particles. Thanks also go to the Mark Wainwright Analytical Centre (Biomedical Imaging facility) at the University of New South Wales, for their support in providing the AFM facility for the study. China Scholarship Council (CSC) is acknowledged for providing Meiling Wang’s PhD scholarship during her PhD candidature. Faculty of Engineering at UNSW is thanked for awarding a postdoctoral writing fellowship. Finally, the authors would like to thank the Australian Research Council (ARC) for funding the project (DP1093975). References [1] D.C. Mears, E.N. Hanley, R. Rutkowski, V.C. Westcott, Ferrography: its application to the study of human joint wear, Wear 50 (1978) 115–125. [2] J. Ewing, Articular cartilage and knee joint function: basic science and arthroscopy, Raven Press, New York, 1990. [3] Thomas Aigner, Nicole Schmitz, Jochen Hagg, AFM tackles osteoarthritis, Nat Nanotechnol 4 (2009) 144–145

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[4] M. Stolz, R. Gottardi, R. Raiteri, S. Miot, I. Martin, R. Imer, U. Staufer, A. Raducanu, M. Düggelin, W. Baschong, Early detection of aging cartilage and osteoarthritis in mice and patient samples using atomic force microscopy, Nat Nanotechnol 4 (2009) 186–192. [5] M. Wang, Z. Peng, J. Price, N. Ketheesan, Study of the nano-mechanical properties of human knee cartilage in different wear conditions, Wear 301 (2013) 188–191. [6] C.Y. Wen, C.B. Wu, B. Tang, T. Wang, C.H. Yan, W.W. Lu, H. Pan, Y. Hu, K.Y. Chiu, Collagen fibril stiffening in osteoarthritic cartilage of human beings revealed by atomic force microscope, Osteoarthritis Cartilage 20 (8) (2012) 926–922. [7] J. Desrocher, M.W. Amrein, J.R. Matyas, Viscoelasticity of the articular surface in early osteoarthritis, Osteoarthritis and Cartilage 20 (2012) 413-421. [8] Z. Peng, M. Wang, Three dimensional surface characterization of human cartilages at a micron and nanometre scale, Wear 301 (2013) 210–217. [9] Z.-G. Zha, C.-C. Yao, M. Tu, Y.-X. Huang, Correlation of the size and shape of the solid particles in synovial fluid and knee joint disease, Curr Appl Phys 7 (2007) e112–e115. [10] P. Podsiadlo, M. Kuster, G.W. Stachowiak, Numerical analysis of wear particles from non-arthritic and osteoarthritic human knee joints, Wear 210 (1997) 318–325. [11] T.B. Kirk, Wear in synovial joints, Department of mechanical engineering, PhD thesis, The University of Western Australia, 1992. [12] M. Wang, Z. Peng, K. Vasilev, N. Ketheesan, Investigation of wear particles generated in human knee joints using atomic force microscopy, Tribol Lett (2013) 1–10. [13] C. P. Brown, R. W. Crawford, A. Oloyede. Indentation stiffness does not discriminate between normal and degraded articular cartilage, Clin Biomech 22 (2007) 843– 848. [14] M. S. Laasanena, J. Töyräs, R. K. Korhonena, J. Rieppo, S . Saarakkala, M. T. Nieminen, J. Hirvonen, J. S. Jurvelin. Biomechanical properties of knee articular cartilage, Biorheology 40 (2003) 133–140. [15] A. Changoor, L. Fereydoonzard, A. Yaroshinsky, M.D. Buschmann, Effects of refrigeration and freezing on the electromechanical and biomechanical properties of articular cartilage, J. Biomech. Eng. 132 (2010) 1–6. [16] R. Outerbridge, J. Dunlop, The problem of chondromalacia patellae, Clin Orthop Relat R110 (1975) 177–196. [17] MultiMode-Manual-PeakForce QNM User Guide-Bruker version (Rev D), Bruker Corporation, 2011

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[18] B.V. Derjaguin, V.M. Muller, Y.P. Toporov, Effect of contact deformations on the adhesion of particles, J Colloid Interf Sci 53 (1975) 314–326. [19] M. Wang, Z. Peng, J.A. Watson, G.S. Watson, L. Yin, Nanoscale study of cartilage surfaces using atomic force microscopy, P I Mech Eng H 226 (2012) 899–910. [20] L. Han, E.H. Frank, J.J. Greene, H.Y. Lee, H.K. Hung, A.J. Grodzinsky, C. Ortiz, Timedependent nanomechanics of cartilage, Biophy J 100 (2011) 1846–1854. [21] G. Bilodeau, Regular pyramid punch problem, J Appl Mech 59 (1992) 519–523. [22] R. Hori, L. Mockros, Indentation tests of human articular cartilage, J Biomech 9 (1976) 259–268. [23] G.E. Kempson, M.A.R. Freeman, S.A.V. Swanson, The determination of a creep modulus for articular cartilage from indentation tests on the human femoral head, J Biomech 4 (1971) 239–250. [24] ISO 25178-2, Geometrical product specifications (GPS)-Surface texture: Areal- Part 2: Terms, definitions and surface texture parameters, 2006. [25] E.M. Darling, R.E. Wilusz, M.P. Bolognesi, S. Zauscher, and F. Guilak, Spatial mapping of the biomechanical properties of the pericellular matrix of articular cartilage measured in situ via atomic force microscopy, Biophysical Journal 98 (2010) 2848–2856. [26] R.E. Wilusz, S. Zauscher, F. Guilak, Micromechanical mapping of early osteoarthritic changes in the pericellular matrix of human articular cartilage, Osteoarthritis and Cartilage 21 (2013) 1895-1903. [27] M. Stacey, D. Dutta, W. Cao, A. Asmar, H. Elsayed-Ali, R. Kelly Jr., A. Beskok, Atomic force microscopy characterization of collagen ‘nanostraws’ in human costal cartilage, Micron 44 (2013) 483–487. [28] W. Grellmann, A. Berghaus, E.-J. Haberland, Y. Jamali, K. Holweg, K. Reincke,1 C. Bierögel, Determination of strength and deformation behavior of human cartilage for the definition of significant parameters, Journal of Biomedical Materials Research Part A 2006 168-174. [29] M. Stolz, R. Raiteri, A.U. Daniels, M.R. VanLandingham, W. Baschong and U. Aebi, Dynamic elastic modulus of porcine articular cartilage determined at two different levels of tissue organization by indentation-type atomic force microscopy, Biophysical Journal 86 (2004) 3269–3283. [30] H.T. Nia, I.S. Bozchalooi, Y. Li, L. Han, H.-H. Hung, E. Frank, K. Youcef-Toumi, C. Ortiz and A. Grodzinsky, High-bandwidth AFM-based rheology reveals that cartilage is most 16

sensitive to high loading rates at early stages of impairment, Biophysical Journal 104 (2013) 1529–1537. [31] I.D. Medalsy and D.J. Müller, Nanomechanical properties of proteins and membranes depend on loading rate and electrostatic interactions, ACS Nano 7 (2013) 2642-2650.

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Figure captions Figure 1 The changes of (a) Young’s moduli and (b) Sa of wear particles found in knee joints with OA progression. The error bars in the figures are the standard errors of the means. Figure 2 The changes in the Young’s moduli of human articular cartilages with OA progression. The error bars in the figures are the standard errors of the means. Figure 3 The nano-surface topographies of cartilages (left) and wear particles (right) collected from (a) a

Healthy knee joint; (b) a knee joint with mild OA; (c) a knee joint with advanced

OA.

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(a)

(b)

19

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(a) Healthy cartilage surface (left) and particle surface (right)

(b) Cartilage surface (left) and particle surface (right) with mild OA

(c) Cartilage surface (left) and particle topography (right) of severe OA specimens

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