Fabienne Pennec
email: fpennec@laas.fr

David Peyrou

Adrien Broué²

Jérémie Dhennin²

Patrick Pons

Robert Plana

Frédéric Courtade

RF MEMS electrical contact resistance calculation using mechanical contact simulations and analytical models

The testing and development of contact material or topology can be addressed with a dedicated experimental set up for monitoring test structures. However, it is difficult to perform the tests under realistic conditions. Moreover several works have already been published about the different theories describing rough mechanical contact. But they often ignore interaction between asperities, bulk deformation or elastoplastic deformations. In order to tackle these issues advanced simulation tools are needed. These tools for finite element analysis allow us to model assembly structures quickly and accurately with a minimal amount of effort. We have developed an original reverse engineering method for generating rough surfaces on ANSYS platform, by using the actual shape of the contact surface.We used this method to predict the real contact area between rough surfaces as a function of the applied force using the augmented Lagrangian method. The number of asperities in contact, their sizes and their distribution allow us to discriminate the more appropriate electric contact model in diffusive or ballistic electron transport.

MEM test structures with gold-to-gold electric contacts are fabricated and tested with an experimental set up in NovaMEMS/CNES lab and will allow to validate the new methodology. The contact resistance is monitored during all experiments, to correlate the mechanical and electrical behavior of the structure. The measurements are in progress. We can already expect to some discrepancies due to the difficulty to measure accurately contact material properties and to the potential contamination around the metal contact area. Yet this application is a major concern in RF MEMS ohmic switches and shows an original approach to extract a guideline in choosing a design, materials and process flow to minimize the contact resistance.

I.

Introduction

With their extremely low mass and volume, low power consumption and easy integration with electronics, RF MEMS switches have a strong potential to reduce the size and mass of satellite systems and spacecraft with significant cost reduction. Nevertheless, those devices with moveable structures still have some issues to be successfully integrated in industrial products. The first issue deals with the actuation medium and the corresponding reliability. For the DC contact RF MEMS, it has been identified that most of the limitations are related to the quality and the repeatability of the contact that drive the RF performance (insertion losses, isolation, power handling) and the reliability. Metal contacts are source of dominant failure mechanism such as damage, pitting, hardening of the metal contact area, stiction due to microwelding and material transfer, organic deposits and contamination around the contact area. All these failure mechanism are of major concern for long term applications and have to be the subject of an intense research effort. In order to propose new generation of RF MEMS devices, it is important to get a deeper insight on the physic of contact in order to choose appropriate materials, topology and architecture. It has to be furthermore outlined that the insertion of RF MEMS into real architecture will necessitate reduced actuation voltage, dimensions and a better control of the electrical and electromechanical behavior that will give more importance to surface effects and their understanding and modeling.

The aim of this paper is to present a new methodology that will allow the simulation of the DC contact of RF MEMS devices through finite element multi-physic simulation and surface characterization. The innovative tool can thus allow to the designer better understanding the physical phenomena at the contact interface of the studied micro-devices and give some precious guidelines in the choice of contact materials, deposition processes, contact topologies and architectures.

II.

Investigation of current methods

The figure 1 sums up the different ways allowing calculation of the electrical contact resistance. Our objective is to develop an accurate method in order to optimize and reduce the electrical contact resistance and in order to decrease the adhesion forces at the contact opening. The implemented tool will allow analyzing the impact of materials, roughness, contact topologies and switch architectures on the contact performances expressed in the contact resistance and the contact reliability.

Interest of a numerical/analytical method compared with an experimental method

To determine the contact resistance, we have choice between an experimental method and a numerical or analytical method. However the experimental method is exposed to many barriers, concerning the fabrication technology or the experimental measurements. The testing and development of contact material or contact topology can be addressed with a dedicated experimental set up for monitoring test structures. Nevertheless, it is difficult to perform the tests under realistic conditions and in particular to duplicate the switch geometry, the contact geometry and the contact force. Moreover, the fabrication process must be optimized and it may take many months to fabricate a set of switches to test a single candidate contact material or contact bump shape. Finally, this method is costly whereas the results interpretation can prove to be difficult when many physical phenomena appear together (heating, creep, surface contamination…).

To the contrary, a numerical or analytical method doesn't constrained us in the choice of one material, one topology, one deposition process or one architecture. Moreover it is possible to investigate each parameter independently.

Statistical and determinist approaches to describe the surface roughness

The selection of a numerical or analytical method requires firstly the implementation of a mechanical contact analysis and the first step of this analysis is the surface description. The presence of roughness on solid surfaces results in an imperfect contact that leads to the real area of contact being a fraction of the apparent or nominal area of contact [START_REF] Bowden | Friction: An Introduction to Tribology[END_REF]. Therefore, in problems involving actual surfaces it is not possible to neglect the surface roughness because this could lead to evaluate values of contact pressure much smaller than the effective ones and to underestimate the risk of surface failures. The model of contact mechanics will depend on the manner by which the surfaces roughness will be mathematically described. Two different approaches have been developed to describe the surface: a statistical approach, based on a stochastic analysis, and a deterministic one involving the actual surfaces topography [START_REF] Ciulli | Rough contacts between actual engineering surfaces Part I. Simple models for roughness description[END_REF].

The fundament of the statistical approach derives from the observation that common engineering surfaces produced by standard machining process are characterized by a random topography. The random topography of surfaces can be described choosing appropriate asperity distribution functions. Referring to a few parameters, the statistical approach is able to provide faster contact problem solutions [START_REF] Greenwood | Contact of nominally flat surfaces[END_REF]. However these parameters can be difficult to choose. The necessary input date, that is summit asperity height deviation, mean radius and asperity density cannot indeed be easily calculated through the commercial roughness measuring equipment and depend from the instrument resolution. The use of a deterministic approach can better describe the surfaces.

The contact surfaces of RF MEMS switches are produced by standard technological process (sputtering, evaporating, electroplating) and can thus be described by a stochastic approach. However, electrical contact of such devices are generally very localized due to the patterning of contact bump under the suspended membrane or directly on the coplanar line. With the typically contact force generated by the device (~100µN), the apparent contact radius is not larger than 250 nm. Figure 3 shows the topographies, captured by AFM, of the membrane surface and of the signal line. Whereas the contact surface of the membrane seems to be random, the contact surface of the line appears to be disturbed by asperities higher than the neighborhood. It is obvious that the contact between both surfaces will occur through those asperities. And thus a determinist description of the lower contact surface is required to get accurate results.

Moreover, the surface roughness of contact materials will depend of the historical switching of the device. A surface that appears initially stochastic will have to be treated with a determinist approach from a few switching.

In order to investigate the degradation mechanism, the use of a determinist approach can better describe the surfaces.

Interest of a numerical method compared with an analytical method

The theoretical models imply many assumptions and simplifications. They ignore some or all of the correlation between asperities, implying that asperities are far apart. Moreover, bulk deformation is neglected and plasticity models at the asperities do not consider large deformation theory [START_REF] Greenwood | Contact of nominally flat surfaces[END_REF][START_REF] Archard | Elastic deformation and the laws of friction[END_REF][START_REF] Majumdar | Fractal model of elastic-plastic contact between rough surfaces[END_REF][START_REF] Mccool | Comparison of Models for the contact of rough surfaces[END_REF][START_REF] Chang | An elastic-plastic model for the contact of rough surfaces[END_REF]. With the increase of computation capabilities, the numerical methods are of great interest. For an elastoplastic material, finite element analysis is well-adapted and is robust enough to consider interaction between asperities as well as bulk deformation [START_REF] Kogut | Elastic-plastic contact analysis of a sphere and a rigid flat[END_REF][START_REF] Jackson | A finite element study of elasto-plastic hemispherical contact against a rigid flat[END_REF][START_REF] Sahoo | Finite Element contact analysis of fractal surfaces[END_REF].

Nevertheless, the representation of micro-geometry demands a high volume of elements, which implies long times of calculation and memory limitations.

Finite element method seems to be very interesting to better understand the physical mechanism at contact interface, but the results accuracy will have to be confirmed by experimentation.

Calculation of the electrical contact resistance (ECR)

Two ways can be considered to calculate ECR: the first one is a finite element coupled-field analysis and the second one uses analytical formulations.

The use of a multiphysical finite element software, able to offering a well developed solver to simulate many mechanical contact problems coupled with other physics, is advantageous to directly extract the electric contact resistance between two conductive bodies that come into contact. In particular in Ansys [START_REF]ANSYS TM[END_REF], surface-to-surface elements in combination with thermal-electric elements and solid coupled field elements allow modeling of electric current conduction. The method consists in a sequential and coupled-field analysis. The drawback of this method is that it neglects ballistic electron transport and contaminant film resistance, although the low contact forces produced by microswitches results in small contact spots on higher asperity peaks. Thus the method risks underestimating contact resistance for low contact force applications.

In order to evaluate the electrical contact resistance, the use of analytical formulae can better account for the constriction of the electrical current through the separate contact spots. Several works have already been published about the different theories describing the electrical contact [START_REF] Holm | Electric Contacts -Theory and Applications[END_REF][START_REF] Sharvin | [END_REF][START_REF] Mikrajuddin | Size-dependant electrical constriction resistance for contacts of arbitrary size: from Sharvin to Holm limits[END_REF][START_REF] Greenwood | [END_REF][START_REF] Boyer | Contact resistance calculations: generalizations of Greenwood's formula including Interface films[END_REF][START_REF] Timsit | Electrical contact resistance: Properties of stationary interfaces[END_REF][START_REF] Boyer | Constriction resistance of a multispot contact: an improved analytical expression[END_REF]. The way the electrons are transported through electrical connections (ballistic, quasi-ballistic or ohmic transport between two contact parts of a MEMS switch needs to be determined in order to evaluate the resistance of contact (figure 4). In general, multiple asperities come into contact resulting in multiple contact spots of varying sizes. The effective contact resistance arising from the contact spots depends on the radii of the spots and the distribution of the spots on the contact surface. The ballistic contact model can be correctly used if the radius of the apparent contact area (that contains all the contact spots) is smaller than the electron mean free path l e . In this case, the formula of Sharvin's resistance [START_REF] Sharvin | [END_REF] is applied: and where a eff is the effective radius of contact Considering the case of n elementary spots of radius a regularly spread in a disc of radius R representing the interface of contact of two metals of equal resistance ρ, an expression of the resistance is proposed by Holm [START_REF] Holm | Electric Contacts -Theory and Applications[END_REF] for an ohmic contact model,

R na R Holm 2 2 ρ ρ + =
where the first term represents the resistance of all the spots in parallel, and the second term, the resistance due to the interaction between all the spots. Greenwood [START_REF] Greenwood | [END_REF] proposed an improved formula for the constriction resistance of a set of circular spots, taking into account the size of different contact spots and their dispersion on the apparent contact area. The electrodes communicate via the spots with no interface film between them.

∑ ∑∑

∑ ≠ ⋅ + = 2 1 ) ( 2 i j i ij j i i G a d a a a R π ρ ρ
with a i the radius of the spot i, dij the distance between the centers of the spots i and j.

When a conductive film of surface resistance λ (Ωm²) is present between two electrodes communicating through a circular spot of radius a, a resistance due to the presence of this film R film has to be added to the constriction resistance:

2 a R film π λ =
For n circular contact spots of radius a eff , the resistance R film of the interface film is:

2 eff film a n R π λ =

conclusion

A numerical modeling is thus implemented in order to study in depth the mechanical micro-contact. With the increase of computation capabilities and numerical methods, the topography of the surface can be included in finite element simulations. The electrical contact resistance is then deduced from output mechanical data, such as radii of contact spots or their distribution. The principle of our approach is sum up on the figure 5.

III. Selection of the simulation tool

To perform numerical contact simulations, the numerical platform available in LAAS laboratory is under investigation. The commercial software ANSYS [START_REF]ANSYS TM[END_REF] is notably tested. It is an industry standard tool for finite element analysis, historically well-known in mechanical and thermal domains. ANSYS manifested a good accuracy on the results with a reduced time of calculation and is able to solve many contact problems (3D, geometrical, status, material nonlinearities…), with a minimum effort from the user. Ansys is an excellent candidate to be used in our project.

IV. Reverse engineering methodology

So far, surface effects were ignored in the analysis, because of the difficulty to generate a rough surface model and also to simplify the model in order to reduce computation times. With the increase of computation capabilities, the topography of the surface can be included in finite element simulations. Thus we describe the new methodology that allows the simulation of the DC contact of RF MEMS devices through finite element multi-physic simulation and surface characterization.

This numerical method is used to predict the real contact area as a function of the contact force between rough surfaces starting from real shape of the surfaces that come in contact. Then using analytical expressions it is possible to extract the electrical contact resistance. The novel approach relies on a reverse engineering method to generate the real shape of the surface. Figure 6 describes the full method developed on ANSYS platform. We used an optical profilometer (VEECO) or an atomic force microscope to capture three-dimensional data points of Real shape and contact surfaces are extracted from characterization and then implemented in a finite element software

Reverse Engineering Method

Finite element analysis is performed using contact algorithms and a non-linear solver

Mechanical Contact Simulation (ANSYS)

Contact is defined by contact area and pressure distribution Results (post-processing) ANSYS R c is deduced from size of the contact spots, their number and their distribution, using analytical expressions theories for electrical Rc contact surfaces. Then, using Matlab functions we convert the closed surface from a stereo-lithographic format to an ASCII file compatible with ANSYS Parametric Design Language (APDL). In the final step, the rough surface was obtained by creating key points from the imported file. Since the key points are not co-planar, ANSYS uses Coons patches to generate the surface, and then we used a bottom up solid modeling to create the block volume with the rough surface on the top. To perform the finite element contact analysis, we choose the combined method based on penalty and lagrangian methods called the augmented Lagrangian method. The postprocessing generates the distribution of the contact pressure on the contact surface. The last version of ANSYS (version 11) presents a new option allowing knowing directly the contact area on each element and has simplified us the work of extraction of spots contact area. Thus a program Matlab has next been written by using the latest functions of ANSYS to determine the area of each contact spot and their location on the contact surface. Then we applied Greenwood's analytical formulations to deduce the contact resistance.

V. Limitations of simulations

Some examples were treated from a contact surface captured with the optical profilometer VEECO (figure 7).

The obtained resolution step is thus close to 0.9µm, which allows us to simulate contact problems for large contact surfaces (25x25µm²). However, this roughness analysis step makes lose a lot of information on the surface characteristics of the contact material. The obtained contact area is thus overestimated and the contact resistance is under-evaluated (figure 8). The resolution of captured surfaces has thus to be refined and requires the use of atomic force microscopy (AFM). For given sample dimensions, the number of point data is likely to increase and to imply a larger number of elements in the contact model, this demands more resources for the computer to run the simulation.

Our studies show that the implementation of finer details of roughness in the contact model has a great impact on the mechanical contact areas. It seems necessary to take into account a resolution step of at least 10nm of the surface roughness. With this cut off length, the time of calculation can become very significant, and rapidly the available machines in the laboratory fail out off memory. Moreover to obtain reliable results the meshing has to sufficiently refined.

To address this challenge, we propose to reduce the contact model. Two simplification models are proposed on figure 9. The microswitch consists indeed of a suspended membrane that comes into contact on a contact bump patterned on a coplanar line (the bump can also be patterned under the beam) as illustrated on figure 3. The contact bump has a round shape to optimize the contact performance. And thus the contact will occur through the higher asperities. The contact is very localized and thus we can leave aside the roughness in the neighborhood of these higher peaks, limiting thus the number of elements in our contact model.

Moreover the contact surface of the membrane can initially be assumed as smooth due to the fabrication process. Therefore for the first actuations only the roughness on a localized zone of the bump will be depicted and we perform in ANSYS a flexible-to-flexible contact simulation. The contact materials are assumed to be elastoplastic and a bilinear stress-strain curve is implemented.

When the number of actuation cycles is high enough, the surface roughness of the membrane changes and the topography need to be taken into account. Micro-geometries of membrane surface and contact bump surface have to be captured. Now the materials can be considered against elastic, and thus we can perform in ANSYS a rigid-to-flexible contact simulation. The flexible bump will consists of an equivalent elastic material and its roughness will be the sum of both roughness profiles.

E 1 E 2 E 1 E 2 E 1 E 2 E 1 E 2
Materials are assumed to be elastoplastic The set up consists in a MTS nanoindenter with a nanopositioning table used to precisely actuate the microstructure in a mechanical way, controlling the load applied on the free standing part and its resulting displacement. A resistance measurement system has been interfaced with the nanoindenter, and consequently the voltage induced by the current flow is monitored in the control software in the same manner than the load or displacement of the tip. A schematic of the accomplished four point probe is shown in the figure 10 b. In a four probe setup, a current source is used to drive the current in the switch and a Digital voltmeter measures the potential drop through the switch. This set-up filters out the access wire resistances and the contact resistance variation is studied accurately. The contact resistance is thus monitored during all experiments, to correlate the mechanical and electrical behavior of the structure. The measurements are still in progress.

VII. Conclusion

The mainstream toward a more and more propelled miniaturization requires from the RF MEMS switches increased RF performances and reliability. In order to develop an innovative architecture of micro-switches using the ohmic contact in MEMS technology, recognition of surface effects is crucial in order to evaluate accurately the electrical contact resistance and study the degradation mechanisms. An overview of different current methods used to calculate the mechanical contact area between two rough surfaces that come into contact on one hand, and to calculate the electrical contact resistance on other hand is introduced.

Finally, the increase of computation capabilities and numerical methods is to the advantage of use of a multiphysical finite element software. The topography of the surface can be included in numerical simulations and allows providing precious guidelines in the choice of contact materials, deposition processes or contact topologies. The novel approach relies on a reverse engineering method to generate the real shape of the surface. Then a mechanical contact simulation is performed to deduce the size of real contact spot and their distribution. The electrical contact reistance is then calculated by using some analytical formulae.

To describe accurately the microgeometry, it is however required to capture the surface topography with a very small cut off length. Typically, the resolution step of measurements instruments (AFM) doesn't have to overcome 10 nm in the case of low range of contact forces developed by MEMS switches. Reduction of contact models will be implemented by defining only locally the surface roughness on the contact bump and by meshing finely only the higher asperities. These methods will be implemented for MEM test structures with gold-to-gold electric contacts. The contact resistance values obtained by th reverse engineering method will be compared with the experimental measurements performed with a dedicated set up and allow validating the efficiency of our numerical tool.

Figure 1 :

 1 Figure 1: current methods for calculation of electrical contact resistance

Figure 2 :

 2 Figure 2: Example of a random topography or stochastic surface (a) and determinist surface (b)

Figure 3 :

 3 Figure 3: contact surface topographies of the micro-switches captured by AFM

Figure 4 :

 4 Figure 4: Schematic illustration of (a) diffusive and (b) ballistic electron transport in a conductor [19]

Figure 5 :

 5 Figure 5: reverse engineering method description to calculate the contact electrical resistance of a micro-switch

Figure 6 :

 6 Figure 6: Reverse engineering methodology

Figure 7 :

 7 Figure 7: contact model definition

Figure 8 :

 8 Figure 8: Ratio between real contact area and apparent contact area and contact resistance versus appplied force (µN)

Figure 9 :

 9 Figure 9: Reduction of the contact model: fist case (a):first actuations and elastoplastic materials; second case (b): many actuations and assumed elastic materials

  with gold-to-gold electric contacts are fabricated in LAAS laboratory and tested with an experimental set up in NovaMEMS/CNES lab to validate the new methodology. The cross section of a schematic structure is illustrated on figure 10 a. Three lengths of suspended beams are considered (240, 300 and 360 µm) with a width of 40 µm. the contact bumps are 10 µm diameter.

Figure 10 :

 10 Figure 10: (a) cross section of the fabricated structure; (b) four wires measurement set-up

VIII.


Fabienne Pennec
email: fpennec@laas.fr

David Peyrou

Patrick Pons

Modélisation du contact résistif de micro-commutateurs MEMS RF

Les principales limitations des micro-commutateurs MEMS RF à contact ohmique sont liées à la qualité, à la répétitivité du contact et à sa fiabilité. Afin de proposer de nouvelles générations de structures MEMS RF, il est important d'acquérir de meilleurs connaissances de la physique du contact pour pouvoir choisir des matériaux, une topologie et une architecture les mieux appropriés. Dans ce contexte l'outil de simulation en éléments finis est utilisé pour mesurer l'impact des matériaux constituant le contact et de chaque paramètre de design sur les caractéristiques mécaniques et électriques du contact. Dans ce papier nous présentons notamment une nouvelle approche qui combine la caractérisation de surface avec l'analyse en éléments finis pour simuler le contact entre des profils réels de surface. Cette méthode d'ingénierie inverse nous permet de mesurer l'impact de la rugosité sur la résistance de contact du microcommutateur.

Introduction

L'apparition des micro systèmes électro-mécaniques radio fréquences au cours des années 1990 a bouleversé le monde de la microélectronique, en permettant l'intégration (hybride ou monolithique) de fonctions électromécaniques miniatures avec les circuits microélectroniques [START_REF] Tilmans | MEMS for wireless communications[END_REF]. Cette nouvelle technologie laisse entrevoir des possibilités vertigineuses : exceptionnelles performances hyperfréquences, grande linéarité et faible consommation.

Toutefois il a été identifié que les principales limitations des structures MEMS RF à contact ohmique sont dues à la qualité, à la répétitivité et à la fiabilité du contact. Le microcontact métallique constitue un verrou technologique puisqu'il introduit une résistance de contact et ainsi des pertes d'insertion à l'état bas. Par ailleurs, il est source d'importants mécanismes de défaillances tels que le durcissement de la zone de contact, des phénomènes de stiction due à la microfusion, de transport de matériaux, de dépôts organiques autour de la surface de contact. Afin de proposer de nouvelles générations de structures MEMS RF, il est important d'avoir une meilleur vision de la physique du contact pour pouvoir choisir des matériaux, des topologies et des architectures appropriées. Il doit être souligné par ailleurs que l'insertion des MEMS dans des architectures réelles nécessite de nos jours une tension d'actionnement et des dimensions réduites, un meilleur contrôle du comportement électrique et électromécanique ce qui confère plus d'importances aux effets de surface, à leur compréhension et à leur modélisation.

Dans ce contexte, on se propose de modéliser le microcontact et d'utiliser l'analyse en éléments finis pour optimiser les paramètres structuraux du contact. Après simulation du contact entre surfaces lisses pour analyser l'effet de paramètres de design ainsi que des matériaux constituant le contact, nous prenons en compte les effets de surface et décrivons ainsi une nouvelle approche utilisant la méthode d'ingénierie inverse pour générer le profil de la surface réelle et simuler le contact entre surfaces rugueuses. La méthodologie employée peut se révéler comme un outil TCAD (technology computeraided design) très efficace pour l'analyse de l'impact des matériaux, de la rugosité, du procédé technologique, de la topologie sur la qualité et la répétitivité du contact de MEMS RF.

Choix de l'outil de simulation pour l'analyse du micro-contact résistif 2.1 Intérêt de l'analyse en éléments finis

L'étude du contact de micro-commutateurs MEMS RF peut être réalisée par des mesures expérimentales sur des structures tests utilisant un banc d'essai. Cependant, il n'est pas toujours évident d'intégrer de nouveaux matériaux de contact et les tests expérimentaux sont souvent éloignés des conditions réelles sous lesquelles opèrent les micro-commutateurs. En particulier, les tests peuvent difficilement reproduire la géométrie de la structure, la géométrie du contact ou encore la force de contact. L'outil de simulation peut alors se révéler comme précieux et efficace pour l'étude du comportement du contact. La modélisation numérique permet de nous donner des lignes conductrices dans le choix des paramètres de design et des matériaux utilisés et devra être compléter par des tests expérimentaux. Mais sachant qu'en technologie silicium nous sommes limités dans le choix de matériaux, que le procédé de fabrication doit être optimisé pour chaque matériaux, pour chaque topologie, cela peut prendre plusieurs mois pour mettre au point un seul matériau, ou encore une seule forme de contact, alors qu'avec l'amélioration des outils de calcul, il est possible d'obtenir les premiers résultats en quelques heures. La simulation permet alors d'améliorer la technologie existante, et de réduire simultanément le temps de recherche et de développement.

Sélection du logiciel de simulation

Pour simuler des problèmes de contact mécanique, nous avons besoin d'un logiciel bien développé, permettant de mener une analyse en éléments finis pour modéliser des structures qui viennent en contact rapidement et efficacement sollicitant un minimum d'effort de notre part. ANSYS, outil très utilisé dans l'industrie, se révèle être un excellent candidat pour simuler ce genre de problème fortement non linéaire et présente l'originalité de pouvoir simuler des problèmes de contact qui abordent plusieurs physiques, telle que la conduction thermique ou la conduction de courant électrique à travers l'aire de contact.

Modélisation du microcontact lisse

La plupart des micro-commutateurs MEMS RF rencontrés dans la littérature utilise le matériau or pour réaliser le contact résistif. L'or pur a en effet l'avantage d'atteindre de faible résistance de contact en raison de sa faible dureté et de sa faible résistivité [START_REF] Schimkat | Contact materials for microrelays[END_REF][START_REF] Hyman | Contact physics of gold microcontacts for MEMS switches[END_REF][START_REF] Rebeiz | Design and Technology[END_REF]. Par ailleurs sa température de fusion est relativement élevée pour un matériau mou et ce matériau présente peu d'oxydation ou de contamination en surface. Cependant la faible dureté de l'or est aussi à l'origine d'une augmentation importante de la résistance de contact au cours des cycles et entraine des problèmes de stiction due à la microfusion du contact. Il peut être alors intéressant de tester de nouveaux matériaux, plus durs, afin d'augmenter la fiabilité de nos micro-commutateurs.

On peut également étudier l'impact de la géométrie du plot de contact et de l'indenteur, ainsi que l'empilement des couches sur l'aire de contact, la distribution de la pression de contact et des contraintes à l'interface de contact.

Nous présentons la méthodologie de modélisation et simulation dans la figure 1. Un exemple de modèle axisymétrique modélisé sous ANSYS est ensuite illustré en figure 2. Ces modèles de contact, simples à mettre en place, nous offrent quelques grandes lignes conductrices dans le choix des matériaux et de la géométrie du contact. Cependant, les faibles forces de contact engendrées lors de l'actionnement des structures mobiles confèrent plus d'importances aux effets de surfaces. Jusqu'ici ces effets étaient ignorés de l'analyse à cause de la difficulté à générer un modèle de surface rugueuse et à simplifier le modèle pour réduire le temps de calcul. Avec l'amélioration des méthodes de modélisation et de calculs, il devient possible d'intégrer le profil réel de la surface dans la simulation du contact.

Modélisation du microcontact rugueux 4.1 Méthodologie

L'originalité de ce travail repose sur une nouvelle approche utilisant la méthode d'ingénierie inverse pour générer la forme réelle de la surface. Ainsi, on utilise un profilomètre optique ou un microscope à force atomique pour enregistrer les données 3D de la surface du matériau de contact. Puis, utilisant les fonctions Matlab, on convertit le fichier de points en un fichier ASCII compatible avec le langage de design paramétré d'ANSYS (APDL). L'étape finale consiste à créer la surface rugueuse à partir des points issus du fichier importé. Puisque les points ne sont pas coplanaires, ANSYS utilise les patchs de Coon pour générer la surface. La méthode est décrite entièrement dans la figure 3. Pour réaliser l'analyse en éléments finis du contact, nous choisissons une méthode combinant les méthodes de pénalité et des multiplicateurs de Lagrange appelé la méthode du Lagrangien augmenté. Il s'agit d'une série d'itérations de méthode de pénalité avec contrôle de la pénétration. Le post traitement d'ANSYS génère ensuite la distribution de pression de contact sur la surface de contact (figure 4). A partir de la distribution de pression et de la taille de chaque spot de contact, il est ensuite possible de déduire la résistance de contact électrique à partir de formules analytiques (Résistance de Maxwell en constriction ohmique, résistance de Sharvin en modèle balistique [START_REF] Nikolic | Electron transport through a circular constriction[END_REF]).

Cartographie 3D

VEECO -AFM

Le modèle que nous utilisons a été publié par J. A. Greenwood en 1966 [6, 7 8]. On considère que les spots de contact sont de forme circulaire et localisés à l'intérieur d'une surface de contact apparente. La formule simplifiée est la suivante :

∑∑ ∑ ≠ Π + = j i ij i C d n a R 1 2 2 ρ ρ
Où ρ est la résistivité, a i le rayon du spot i, d ij la distance entre les centres des spots i et j et n le nombre de spots.

Exemple d'analyse de microcontact résistif

On considère une structure mobile poutre à actionnement électrostatique, représentée sur la figure 5. Le contact métal-métal est réalisé par l'intermédiaire d'un plot de contact recouvert d'or évaporé de dimension 25x25 µm 2 . Un relevé de la topographie de l'or électrolytique de la ligne de signal en regard avec le plot de contact est réalisé au profilomètre optique. La rugosité de la surface de contact peut ainsi être générée sous ANSYS. La membrane du plot est considérée comme lisse puisque l'or est évaporé sur de la photo-résine sacrificielle. Deux modèles sont réalisés avec le logiciel ANSYS et présentés sur la figure 6. Dans le premier modèle la membrane du plot qui indente la ligne de signal est considérée rigide. Dans le deuxième modèle, cette même membrane est considérée flexible et ayant les propriétés matérielle de l'or évaporé. Le rapport entre l'aire de contact réelle mécanique et l'aire de contact apparente pour une force appliquée allant de 10 à 500 µN est illustré sur la figure 7. Les résultats sont présentés pour des membranes rigide et déformable. La résistance de tous les spots de contact isolés en parallèle est ensuite calculée. Puis on ajoute la résistance due à leur interaction pour obtenir la résistance de contact de la microstructure. Les résultats sont illustrés sur la figure 8.

Conclusion

La course constante à la miniaturisation et à la minimisation de la consommation électrique des micro-commutateurs MEMS RF donne toujours plus d'importance aux effets de surface, à leur compréhension et à leur modélisation. L'outil de simulation peut se révéler alors comme un outil très précieux pour apporter de nouvelles connaissances sur le microcontact résistif de ces structures Nous avons présenté ici une méthode originale qui intègre la topographie de la surface dans le calcul en éléments finis. Cette nouvelle méthode est un outil TCAD très efficace pour analyser l'impact des matériaux, de la rugosité, du procédé technologique et de la topologie sur la qualité et la répétitivité du contact des micro-commutateurs. Elle peut également se révéler comme un outil novateur pour étudier les mécanismes physiques de détérioration des surfaces de contact.

Figure 1 .

 1 Figure 1. Méthodologie de modélisation et simulation du contact lisse

Figure 2 .

 2 Figure 2. Exemple de modèle de contact et modèle axisymétrique réalisé sous ANSYS.

Figure 3 .

 3 Figure 3. Description de la méthode d'ingénierie inverse

Figure. 4

 4 Figure.4 Algorithme de contact et post-traitement dans ANSYS

Figure. 6

 6 Figure.5 définition du modèle de la microstructure

Figure. 7 Figure. 8

 78 Figure.7 Rapport entre aire de contact mécanique et aire de contact apparente versus la force appliquée


Caroline Ceccaldi

Sophie Girod Fullana

Chiara Alfarano

Olivier Lairez

Denis Calise

Daniel Cussac

Angelo Parini

Brigitte Sallerin

Alginate Scaffolds for Mesenchymal Stem Cell Cardiac Therapy: Influence of Alginate Composition

Keywords: Alginate, Cell encapsulation, Mesenchymal stem cells, Biomimetic materials, Heart

Despite the success of alginate scaffolds and mesenchymal stem cells (MSCs) therapy in cardiac failure treatment, the impact of the physicochemical environment provided by alginate matrices on cell behavior has never been investigated. The purpose of this work was double: to determine the alginate composition influence on (1) encapsulated rat MSC viability, paracrine activity, and phenotype in vitro and (2) cardiac implantability and in vivo biocompatibility of patch shape scaffolds. Two alginates, differing in composition and thus presenting different mechanical properties when hydrogels, were characterized. In both cases, encapsulated MSC viability was maintained at around 75%, and their secretion characteristics were retained 28 days postencapsulation. In vivo study revealed a high cardiac compatibility of the tested alginates: cardiac parameters were maintained, and rats did not present any sign of infection. Moreover, explanted hydrogels appeared surrounded by a vascularized tissue. However, scaffold implantability was highly dependent on alginate composition. G-type alginate patches, presenting higher elastic and Young moduli than M-type alginate patches, showed a better implantation easiness and were the only ones that maintained their shape and morphology in vivo. As a consequence of alginate chemical composition and resulting hydrogel structuration, G-type alginate hydrogels appear to be more adapted for cardiac implantation.

INTRODUCTION

The potential of mesenchymal stem cells (MSCs) for the treatment of myocardial infarction is now established. Their beneficial effects appear to be mainly attributed to their paracrine activities providing a regenerative microenvironment at the ischemic area (8,9,55,63). Direct injection in the necrotic zone of bone marrow (BM)derived MSCs is already tested as a therapeutic strategy subsequently to myocardial infarction and reperfusion in clinical trials (62). Unfortunately, benefits of such regenerative therapy are limited by early cell death (around 85%) in the first 3 days after graft (34,38,48,54,57,61). These limitations depend on different mechanisms such as hypoxia, inflammation, or mechanical stress occurring during surgical implantation. Therefore, strategies concerning preservation of cell viability and functionality after implantation are becoming a priority in cardiac cell therapy (7,41,52,53). A promising strategy is to associate MSCs with a biocompatible material that (1) protects but little is known about the influence of alginate composition on biomaterial final properties in this domain.

Alginates are very hopeful for health applications due to their structural similarities with extracellular matrix, their properties to gelify under soft conditions and their low toxicity after purification. Alginates are a family of naturally derived polymers extracted from sea brown algae. Alginates are unbranched binary copolymers consisting of 1,4-linked β-d-mannuronic (M) and α-l-guluronic (G) residues organized in regions of sequential G units (G-blocks), regions of sequential M units (M-blocks), and regions of atactically organized G and M units. Sol-gel transition properties of alginates are based on the formation of a stiff "egg-box" structure due to the selective binding of divalent cations to G-blocks of two adjacent polymeric chains (18). As a consequence, the structure of alginate network is closely related to their monomeric and diadic organization. By varying their M/G proportions and distributions, it is possible to modulate the viscoelastic properties of the resulting crosslinked hydrogel.

In this context, it seems reasonable to hypothesize that the choice of the alginate composition may have a determining impact on the device characteristics and performance. Recent studies demonstrated the importance of cellular environment on matrix entrapped cells ( 16) and more particularly the effects of mechanical properties (5) and chemical composition (10,23,47,50,51,59) of alginates on stem cell behavior in pancreatic, neural, and cartilage tissue engineering fields. These observations underline the relevance of this parameter to design the best suitable device for the targeted application. Concerning cardiac applications, a complete bibliographic study reveals a lack of argumentation in this domain, as already reported injectable alginates and alginate patches appeared to be either G-type (2,15,21,31,33) or M-type (64,65), or even were sometimes not specified (1). As far as we know, the impact of alginate composition and resulting mechanical properties on MSC behavior has never been studied so far. With this scope, we firstly characterized two ultrapur alginate samples with similar molecular weight and different chemical compositions. Secondly, we compared the influence of alginate MSCs entrapment on cell viability and functionality in vitro. Finally, alginate composition influence was evaluated in vivo: calcium alginate hydrogels implantability and biocompatibility were evaluated after cardiac implantation in rats.

MATERIALS AND METHODS

MVG (G-type) and MVM (M-type) ultrapur grade sodium alginates were used (Provona up MVG and Provona up MVM, Novamatrix, Norway). Medium molecular weight alginates were chosen to improve mechanical properties of the materials and to limit their in vivo degradation (30).

Alginate Hydrogels Elaboration

Alginate concentration (1.2%, w/w) was chosen to optimize encapsulation process. Hydrogels were prepared under aseptic conditions (all solutions were sterile filtered and all equipment were autoclaved).

Alginate Dispersion. Solutions of 1.2% (w/w) MVG and MVM ultrapur alginate were prepared in iso-osmotic HEPES buffer (150 mM NaCl, 12.5 mM HEPES, pH 7.4) during 30 min at 1800-2000 rpm (Heidolph RZR-2041, Germany).

Hydrogels Gelification

In Vitro Study. MSCs were encapsulated in alginate microspheres, which permitted to study MSC behavior in alginate-confined environment. Microencapsulations were performed upon generation of monodisperse droplets of sodium alginate solution, containing MSCs (2.5 million of cells/ml of alginate solution) or not, by an encapsulator (IE50R, Inotech, Switzerland), equipped with a vibrating nozzle (300 µm, 850 Hz). Then ionotropic gelation was performed in an iso-osmotic buffer containing calcium ions (CaCl 2 , 0.1 M) during 20 min. Constructs, containing approximately 2,300 cells per microsphere, were cultured in six-well plates in supplemented culture medium (α-MEM, 10% FBS, 1% penicillin/streptomycin, Gibco, France).

When necessary, cells were released from microspheres by incubation in 55 mM sodium citrate for 20 min to liquefy alginate. Cell suspension was then centrifuged (400 rpm, 5 min).

In Vivo Study. Alginate patches were elaborated to allow a very close contact between alginate-based materials and heart. Sodium alginate solutions were placed in 48-well plates. Then ionotropic gelation was performed in an iso-osmotic buffer containing calcium ions (CaCl 2 , 0.1 M) for 20 min.

Alginate hydrogels were then washed three times (10 min in HEPES buffer) prior to in vitro cultivation or in vivo implantation.

H NMR Spectroscopy

Protocols used are derived from the method described by Grasdalen et al. (19). The 1 H NMR spectra of alginate in solution were recorded on a Avance DMX 500 MHz (Bruker Biospin Gmbh, Germany) operating at 500 MHz for 1 H using a 5-mm broadband inverse probe head (BBI 500 MHz). Prior to analysis, the average molecular weight of the alginate was reduced by a mild partial acid hydrolysis performed in two steps. Alginate (0.5 g) moistened with 5 ml ethanol (96%) was dissolved in 50 ml HCl (pH 1.5). The pH was adjusted to 5.0 by addition of NaOH and hydrolyzed at 100°C under reflux for 10 min. After cooling to room temperature, the pH was adjusted to 3.0 by addition of HCl and heated at 100°C under reflux for 20 min. After cooling, the solution was neutralized (pH 7) by addition of NaOH and precipitated in ethanol (96%). The precipitate was left for drying overnight at 70°C. The hydrolyzed alginate was dissolved in D 2 O (1.0%, w/v) and neutralized (pH 7), and 550 µl of the solution was fil-tered through a Whatman 13-mm syringe filter (pore size, 0.45 mm) into a 5-mm NMR tube. The spectra were recorded with a 90° pulse angle and a sweep width of 5,482 Hz. The acquisition time and recycle delay were both 2 s. Thirty-two scans were acquired, and the spectra were recorded with the same receiver gain. During acquisition, the sample temperature was 90°C. 3-(Trimethylsilyl)propionic acid-d4 sodium salt (TSP-d4) was used as chemical shift reference compound (d = 0.0 ppm). The raw data were apodized by 1.0 Hz of exponential line broadening prior to Fourier transformation. No zero filling was applied.

Rheological Characterization

Rheological measurements were carried out using a stress-controlled rheometer (Rheostress RS75, HAAKE, Germany) with a parallel-plate geometry. Test samples were made to match the diameter of the parallel plate (20 mm). Gels were gently pressed with tissue paper to remove surface water before lowering the top plate. Stress sweeps at a constant frequency of 1 Hz were first performed to obtain the linear viscoelastic region for collecting subsequent data. Frequency sweeps were performed in the linear viscoelastic regime to determine the elastic (G′) and viscous (G″) moduli values.

Texturometry

Young's moduli and mechanical behavior of microspheres were studied by three successive uniaxial compression assays (TA-XT2 Texture Analyzer, Stable Micro systems, UK). Briefly, mechanical resistance was determined as the main force required to generate a 50% compression of a sample of microparticles. The apparatus consisted of a mobile probe (314.16 mm 2 ) moving vertically up and down at constant and predefined velocity (0.5 mm/s). The force exerted by the probe on the microspheres was recorded as a function of the displacement, leading to a force versus strain curve. The results were expressed as the average maximal mechanical stress in kPa observed at 50% of strain from at least three independent observations.

Laser Diffraction Granulometry

Particles size distribution was assessed by laser diffraction granulometer (LS100, Coulter, US) on G-type and M-type alginate microparticles in iso-osmotic HEPES buffer. Sauter diameter d(3,2) and polydispersity index were used to follow microspheres swelling, as an evaluation of microspheres stability over time.

Isolation and Culture of Rat MSCs

MSCs were obtained from BM of Lewis male rats (Harlan, France) weighing 180-200 g. Anesthesia was performed by intraperitoneal injection of pentobarbital (0.1 ml/100 g). BM was flushed from rat's femur with minimal essential medium (Gibco, France) supplemented with 10% fetal bovine serum (FBS) and 1% penicillin/ streptomycin (Invitrogen, France) and centrifuged (400 × g, 5 min). Then cells were plated in culture flasks (100,000 cells/cm 2 ). After 3 days, nonadherent cells were removed by changing medium, and MSCs were recovered by their capacity to adhere highly to plastic culture dishes. MSCs were then routinely cultured and were used for the experiments. Most adherent cells expressed MSC markers CD90, CD29, CD106 and were negatives for CD34 (hematopoietic marker), CD45 (B cells marker), and CD31 (vascular cells marker). They were able to differentiate into cells from mesodermal lineage: osteoblasts, chondrocytes, and adipocytes. MSCs were used between the third and the sixth passage.

Quantification of Cell Viability

A live/dead assay was performed with viability/cytotoxicity kit (FluoProbes ® , Interchim, France). Briefly, microspheres were washed two times with α-MEM/ physiological serum (1:1) and immersed (30 min, 37°C) in presence of 2 µM ethidium homodimer-3 (necrotic marker measuring nucleus membrane integrity) and 1 µM calcein AM (viability marker measuring intracellular esterase activity) to stain dead cells in red and live cells in green. After washing with α-MEM, microspheres were observed by confocal microscopy (Zeiss LSM-FCS, Germany). Positive control for 100% cell death was obtained by treating microspheres containing encapsulated MSCs with 70% ethanol for 10 min prior to fluorescent live/dead staining.

Two parameters were measured. First, cell viability, V, was calculated as the percentage of viable entrapped cells. V = N L /(N L + N D ) with N L = Total green pixel number/number of green pixel per live cell and N D = Total red pixel number/number of red pixel per dead cell. The second parameter was total cell density, D, expressed as the number of live and dead cells counted by microsphere area. D = (N L + N D )/A microsphere with A microsphere = area of the microsphere on which measurement was done.

Reverse Transcription-Polymerase Chain Reaction

Total RNA was isolated from 1 million of MSCs using RNeasy ® Kit (Qiagen, France) according to the manufacturer's protocol. RNA (8 ng) was reverse transcripted to cDNA using the SuperScript II reverse transcriptase (Invitrogen, USA). The real-time RT-PCR was performed using SYBR Green PCR Master Mix (ABI Prism 7000 HT Sequence Detection System, Applied Biosystems, USA). Amplification reactions (25 µl were carried out in triplicate with 5 µl of 1:10 diluted template cDNA) and the following primers (Eurogentec, Belgium) were used for the detection of vascular endothelial growth factor (VEGFα), hepatocyte growth factor (HGF), insulin-like growth factor (IGF1), epidermal growth factor (EGF), fibroblast growth factor (FGF2), and granulocyte colony-stimulating factor (G-CSF). Each assay was normalized by amplifying the housekeeping cDNA glyceraldehyde 3-phosphate dehydrogenase (GAPDH) and ribosomal protein L31 (RPL31) from the same cDNA sample and fold to nonencapsulated third passage MSCs.

VEGFα: 5′CAAAAACGAAAGCGCAAGAAA3′/ 5′GTCTGCGGATCTTGGACAAAC3′, HGF: AACAAGGTCTGGACTCACATG3′/ 5′CGTCTGGCTCCCAGAAGATATG3′, IGF1: 5′GACGGGCATTGTGGATGAGT3′/ 5′GGATGGAACGAGCTGACTTTG3′, EGF: 5′CTCACCCTCTCTCCTTGGAAAA3′/ 5′GGCGGGCATCCTGTGTT3′, FGF2: 5′GTGTGTGCGAACCGGTACCT3′/ 5′TATTGGACTCCAGGCGTTCAA3′, G-CSF: 5′TGTGGTGGTACCCAAGAAATCAC3′/ 5′CCTGGGCCCCTGAGACA3′, GAPDH: 5′AGGTCGGTGTGAACGGATTTG3′/ 5′TGTAGACCATGTAGTTGAGGTCA3′, RPL31: 5′CCATGGAGTGGGCTTCAAGA3′/ 5′TCTATGCGCACATCTGGAGTTC3′.

Western Blot

Proteins were extracted from MSCs using RIPA buffer. Analyses were performed with samples normalized for protein concentration. Membranes were probed with rabbit anti-FGF2 antibodies (1:500, Santa Cruz Biotechnology, USA). Following several washes in TBS-Tween (0.2%), membranes were incubated with horse radish peroxidase (HRP)-conjugated anti-rabbit secondary antibody (1:10,000, Santa Cruz Biotechnology, USA). Protein expression was normalized by GAPDH expression (1:1,000, Santa Cruz Biotechnology).

Differentiation Assays

Protocols used are derived from the methods of Neuhuber et al. (39).

Adipogenesis. MSCs were seeded into six-well plates at 20,000 cells/cm 2 and cultured until confluency. Cultures were placed in adipogenic induction medium (Dulbecco's modified Eagle's medium with 4.5 mg/ml glucose, 10% fetal bovine serum, 5% rabbit serum and antibiotics, with 0.5 mM isobutylmethylxanthine, 1 mM dexamethasone, 10 mg/ml insulin, and 1 mM indomethacin) for 3 days and subsequently moved to adipogenic maintenance medium (Dulbecco's modified Eagle's medium with 4.5 g/ml glucose, 10% fetal bovine serum, 5% rabbit serum, antibio tics, and 10 mg/ml insulin) for 1 day. After three cycles, cells remained in maintenance medium for 7 days prior to fixation with 4% paraformaldehyde. Cells were stained with Oil Red O to visualize neutral lipid accumulation.

Chondrogenesis. Five hundred thousand MSCs were pelleted in high-glucose Dulbecco's modified Eagle's medium with 1% fetal bovine serum, antibiotics, 50 mg/ml ascorbate 2-phosphate, 40 mg/ml proline, 2 mM pyruvate, insulin/transferrin/selenium/linoleic acid (ITSþ), 100 nM dexamethasone, 10 ng/ml transforming growth factor-b3, and 200 ng/ml recombinant bone morphogenic protein-2. Medium was changed three times per week. On day 21, pellets were fixed in 4% paraformaldehyde, embedded in paraffin, and sectioned (6 µm). Sections were stained with Alcian blue to reveal mucopolysaccharides and glycosaminoglycans.

Osteogenesis. MSCs were seeded in six-well dishes at 3,000 cells/cm 2 . After 2 days, growth medium was replaced by osteogenic medium (including 100 nM dexamethasone, 50 mM ascorbate-2-phosphate, and 10 mM glycerol phosphate). All chemicals were purchased from Sigma-Aldrich, USA. Medium was replaced twice weekly. After 18 days, cells were stained with Alizarin Red S to visualize the calcify deposition.

In Vivo Implantation of Alginate Scaffolds

Experimental animals were handled in accordance with the European Animal Care Guidelines. Patch implantation was performed in adult female Sprague-Dawley rats (200-250 g) by left thoracotomy via the fourth intercostal space under general anesthesia (isoflurane, 2.5%) and mechanical ventilation. Alginate scaffolds (n = 4 for each alginate type) were implanted onto the surface of the left ventricle after removal of the pericardium over two peripheral sutures using a 7-0 prolene suture. Sham-operated animals were subjected to the same surgical procedure without implantation (n = 2).

Blood Analysis

Hematocrit measurement was performed on blood collected by retro-orbital bleeding on anesthetized animals using heparinized tubes. Hematocrits were evaluated by standard microhematocrit method. Leukocyte differential count was performed on total blood collected on abdominal aorta (MICROS-60, ABX-Diagnostics, France).

Echography

Left ventricular (LV) function was assessed in anesthetized animals with two-dimensional echocardiography with a General Electric Vivid 7 ® (GE Medical System, USA) equipped with a 13-MHz linear probe. For anesthe-sia, rats were induced with isoflurane and received con-tinuous inhaled anesthetic (2%) for the duration of the imaging session. The animals were placed in the supine or lateral position on a warming pad. Numeric images of the heart were obtained in both parasternal long-axis and short-axis views. Two-dimensional end-diastolic and endsystolic long-axis views of the LV were stan-dardized as follows: inclusion of the apex, the posterior papillary muscle, the mitral valve, and the aortic root. Twodimensional echocardiographic measurements were performed with the cine-loop feature to retrospectively catch true end-diastolic and end-systolic phases, defined as the phases in which the largest and the smallest LV cavity sizes were obtained, respectively. End-diastolic and end-systolic areas (A) were obtained by hand tracings of the LV endocardial contours, according to the American Society of Echocardiography leading edge method. On these frames, end-diastolic and end-systolic lengths (L) of the LV were obtained by tracing a line connecting the more distal part of the apex and the center of a line connecting the mitral annular hinge points. End-diastolic and end-systolic volumes (LVEDVs and LVESVs, respectively) were then calculated by means of the single-plane area-length method (volume = 8 × A 2 /3 × π × L). LV ejection fraction (LVEF, %) was calculated as [(LVEDV -LVESV)/LVEDV] × 100. All measurements were averaged on three consecutive cardiac cycles and analyzed by a single observer who was blinded to the treatment status of the animals.

Cyto-and Histological Examinations

Staining of MSCs extracted from microspheres was performed after alginate solubilization and cell removal. Cells were plated in six-well plate, fixed in 4% paraformaldehyde, and stained with Alizarin Red S, Alcian Blue, or Oil Red O coloration using standard procedures. For cell staining in embedded microspheres, paraffin sections of G-type and M-type alginate microspheres were rehydrated and incubated in the presence of biotinylated rat proliferating cell nuclear antigen (PCNA) according to the manufacturer's recommendations. Sections were counterstained with hematoxylin. Sections of rat kidney regenerating after ischemia/reperfusion were used as positive control (29). For CD90 detection, paraffin sections of G-type and M-type alginate microspheres were rehydrated and incubated with anti-rat CD90 antibody (diluted 1:100, 60 min; Santa Cruz Biotechnology, CA). Antibody revelation was performed by using an Alexa Fluor 568 secondary antibody (1:500, 30 min; Invitrogen, CA). For nuclear detection, sections were incubated with to-pro-3 (1:1,000, 20 min; Invitrogen, CA). For histological staining on explanted hearts, hearts were collected and fixed in Carnoy's solution, and paraffin sections (6 µm) were rehydrated and stained with hematoxylin/ eosin coloration using standard methods. α-Smooth muscle actin (α-SMA)-staining implanted heart sections were rehydrated and incubated with mouse monoclonal anti-α-SMA (clone 1A4, Sigma, USA) for 1 h. Tissue was stained using the anti-mouse HRP-DAB and counterstained with hematoxylin.

Statistical Analysis

Results are expressed as mean ± SD. Statistical comparison of the data was performed using the t test for comparison between two groups or one-way ANOVA and post hoc Tukey's test for comparison of more than two groups. A value of p < 0.05 was considered significant.

RESULTS

Characterization of Alginate Hydrogels Determination of Diadic Composition of Alginates.

Gelification process of alginate is described by the "eggbox" model where divalent cations are binded to regions enriched in G-G sequences to form intramolecular and/or intermolecular junctions. The ability of alginate to form a gel in presence of Ca 2+ depends not only on its uronate composition but also on the repartition of mannuronic and guluronic residues along the polymeric chain (22). In this study, fraction of guluronic (F G ) and mannuronic (F M ) residues together with diadic composition (F GG , F GM , and F MM ) of ultrapur alginates were determined by 1 H-RMN spectroscopy. G-type alginate presented significantly more G residues and G-G sequences than M-type alginate (Table 1).

Mechanical Behavior of Alginate Hydrogels. Hydrogels synthesized with these two different alginates were then analyzed by measuring elastic modulus (G′) and loss modulus (G″) by oscillatory shear measurement in a rehometer. Whatever the frequency tested in their viscoelastic domain, both alginate types exhibited elastic moduli G′ higher than their loss moduli G″, confirming that both alginate types were under a hydrogel structured form at the calcium concentration tested for the experiments (0.1 M). As a consequence of its higher G fraction, G-type alginate calcium hydrogels presented higher moduli than M-type alginate hydrogels, revealing a higher structuration degree due to more calcium-binding sites (as can be seen in Table 1, for a frequency of 4 Hz). To complete calcium alginate hydrogels characterization, their mechanical properties were studied under compression strain. Young's modulus presents the advantage not to be dependent of the device geometry but only of the intrinsic mechanical properties of the materials. The mechanical behavior of the two alginates was assessed by three successive compressions, and Young's modulus was determined at 50% of strain (Fig. 1). Alginate microspheres presented a Young's modulus near 38 and 25 kPa for G-type and M-type alginate, respectively. G-type alginate hydrogels showed a time-dependent mechanical resistance, which evidenced viscous or plastic behavior, while M-type alginate hydrogels maintained an elastic behavior over time.

Swelling Behavior of Alginate Hydrogels. Swelling behavior of alginate hydrogels is an essential parameter to describe the device stability in wet environment like during in vitro cultivation time or after animal implantation. Consequently, alginate microspheres were synthetized and immersed for 28 days in iso-osmotic buffer, and their Sauter diameter d(3,2) was weekly assessed by laser diffractometry (Fig. 2). Microspheres sizes and distribution remained stable during the entire immersion test and could consequently be considered as adapted for in vitro and in vivo studies, as no swelling, a sign of hydrogel destabilization, could be observed.

Immobilized MSC Biological Properties

Viability of Entrapped MSCs. Bone marrow MSC via bility was assessed by confocal analysis. Encapsulated MSCs were cultured under proliferation conditions for 28 days, and viability of cells in G-type and M-type alginate microspheres was weekly determined. Cell viability was maintained around 80% (Fig. 3A) for 21 days after encapsulation; a slight decrease was observed from 28 days for both alginate types. Confocal z planes (Fig. 3B andC) of microspheres at 21 days postencapsulation showed a homogenous distribution of viable cells in whole microspheres.

Cell density D was estimated at 151 ± 7.8 and 167 ± 25.2 MSCs/mm 2 for G-type and M-type alginate microspheres, respectively (mean ± SD; p > 0.05) and was found to remain stable along the study. Furthermore, MSC-encapsulated in G-and M-type microspheres did not exhibit any proliferation. Indeed, as observed in Figure 4A-D, G-type and M-type alginate microsphere sections did not show PCNA immunostaining at day 28 postencapsulation. This observation, combined with the absence of significant variation in cell density inside microspheres during culture time, suggests that encapsulated MSCs do not underlie proliferation. This may be related to an alginate/MSC contact inhibition due to the highly confined alginate microenvironment (26,45). These results suggest neither proliferation of MSCs in alginate microspheres nor MSCs decrease over time.

Functionality of Entrapped MSCs. Next we investigated whether encapsulation may affect MSC phenotype. As a first approach, we demonstrated that, after 28 days of encapsulation, 84% ± 3.76% and 86% ± 4.5% of the total cell population for G-type and M-type alginates, respectively (mean ± SD; percentage determined by peroxidase revelation, p > 0.05), were positive for the MSC marker CD90. Then we investigated whether encapsulated MSCs undergo spontaneous differentiation toward classical mesodermal lineage. With this scope, we stained MSCs extracted from G-type or M-type alginate after 28 days with Alizarin red S, Alcian Blue, and Red Oil O specific dyes for osteogenic, chondrogenic, and adipogenic lineage. As shown in Figure 5, in contrast to control MSCs in which specific lineage was chemically induced in vitro, MSCs eluted from microsphere were not stained by any of these dyes. This indicates that encapsulation into G-type and M-type alginate did not induce the commitment of MSCs toward meso dermal lineage.

We have previously shown that paracrine factors, playing a major role in the beneficial effect of cell therapy, were secreted by MSCs (36). As shown in Figure 6A, we found that expressions of cytokines normally produced by MSCs (VEGF, IGF-1, FGF2, HGF, EGF, and G-CSF) were increased for both alginate types as compared to nonencapsulated cells. In addition, the amount of intracellular FGF2, quantified by Western blot, was not modified after MSC encapsulation (Fig. 6B).

In Vivo Alginate Scaffolds Cardiac Compatibility

Implantability of Alginate Scaffolds. Alginate scaffolds were implanted and fixed to the myocardium by two peripheral sutures. All were successfully attached. However, M-type alginate scaffolds appeared to be more difficult to manipulate during surgical intervention due to their friability and their poor mechanical properties.

Cardiac Biocompatibility of Alginate Scaffolds. The effect of alginate scaffolds implantation on adult rat heart was studied. Hematocrits were weekly analyzed (Fig. 7A) during implantation time, and white blood cells (Fig. 7B) were numbered after 28 days postimplantation. No significant differences were observed for these parameters between control group, G-type and M-type alginate implanted groups, suggesting that rats did not present any sign of systemic infection or inflammation.

Cardiac function was weekly determined by echocardiography after implantation. Left ventricular end-diastolic volumes (LVEDV; Fig. 8D), ejection fraction (EF; Fig. 8E), and heart rate (HR; Fig. 8F) showed no significant change in comparison with nonimplanted rat and were stable for 1 month.

Macroscopic and Microscopic Observations of

Explants. Postmortem analyses after 28 days postimplantation revealed that no adherences were observed in the environment of implanted scaffolds. G-type alginate scaffolds were found still attached to the myocardium, conserving their initial morphology (Fig. 9A). On the contrary, M-type alginate scaffolds were found detached from suture, near the heart, in thoracic wall. They were no longer in a patch shape (Fig. 9B).

Eosin/hematoxylin staining of implanted heart revealed normal myocardium (Fig. 10A andB) with foreign body (-) and (+) labeled arrows show CD90-negative MSC and CD90-positive MSC, respectively. (e and f ) Overlays of positive (rat MSCs) and negative controls (rat myocardium), respectively. Scale bars: 100 µm. (B) Specific coloration of osteogenic (Alizarin Red: a, b, and c), chondrogenic (Alcian Blue: d, e, and f), and adipogenic lineage (Red Oil: g, h, and i) of MSCs: optical microscopy of 28 days postencapsulated MSCs in G-type (a, d, and g) or M-type alginate hydrogels (b, e, and h). Positive controls: MSCs after induction of osteogenesis (c), chondrogenesis (f), and adipogenesis (i). Scale bars: 200 µm. giant cells and macrophages at the alginate/myocardium interface. This histomorphological feature is compatible with a classical foreign body reaction probably related to alginate hydrogels. A weak fibrosis surrounding scaffolds was associated with the formation of neovascularization as indicated by arrows in Figure 10C. In the case of M-type alginate, the presence of fibers and cells infiltrating scaffolds was also observed (Fig. 10D). The granulation tissue surrounding scaffolds formed a fibrous capsule. All together, these histomorphological features indicate that implantation of alginate microspheres induced a classical local inflammatory response, as previously reported by other groups (3,35,44).

DISCUSSION

Despite the success of alginate scaffolds and mesenchymal stem cells therapy in cardiac failure treatment, the impact of the physicochemical environment provided by alginate matrices on cell behavior has never been investigated in this application. The purpose of this work was double, to determine alginate composition influence on (1) encapsulated MSC viability, paracrine activity, and phenotype in vitro and (2) cardiac implantability and in vivo biocompatibility of patch shape scaffolds.

In this study, two different alginates, both exhibiting a medium molecular weight, have been selected upon their M/G ratio: a low M/G ratio alginate, so-called G-type alginate, and a high M/G ratio alginate, so-called M-type alginate. NMR characterization showed that selected samples exhibit a G fraction of 68% and 45% and a G-blocks fraction of 55% and 28%, respectively. Shear measurement and determination of swelling behavior revealed that calcium crosslinking of 1.2% G-type and M-type alginate permitted in both cases to obtain a structured and stable polymeric network corresponding to a hydrogel. Characterization of these calcium alginate hydrogels showed that the M/G ratio impacted not only the matrices mechanical strength but also their mechanical behavior: G-type hydrogels were more rigid and presented viscous and/or plastic behavior; on the contrary, M-type hydrogels were less rigid and exhibited an elastic behavior. These macroscopic observations can be explained by differences in chemical compositions and structure of the tested alginates. Effectively, their sol-gel transition involves an "egg-box" model ( 18) through the ionic interaction between divalent cations, in our case, Ca 2+ ions, and adjacent guluronic residues of alginate chain. Therefore, when decreasing M/G ratio and increasing G-blocks content, a denser polymeric network can be obtained ( 22), leading to a more rigid scaffold, less able to swell after compression (40). These latter properties could explain the viscous and/or plastic mechanical behavior observed in the case of G-type hydrogels. Mechanical properties of G-type and M-type alginate hydrogels were statistically different, but both remained compatible with cardiac implantation, as their mechanical strengths match with myocardium tissue Young's modulus; their levels of elasticity seem to be in accordance with dynamical heart environment (66). Concerning MSCs, recent studies demonstrated that the mechanical properties of cell environment (provided by the biomaterial) can have a notifying impact on their behavior. Engler et al. (16) cultivated MSCs on polyacrylamide gels with varying Young's moduli corresponding to the mechanical properties of various organs. They reported that MSCs committed the lineage specified by matrix elasticity, predominantly to the lineage expected after specific cytokine induction. This influence of microenvironment chemical and physical properties was also observed on cells embedded in alginate hydrogels for diabetes therapy purpose. Alginate M/G ratio modulated entrapped murine insulinoma βTC3 cells functionality (10,23,50,51). Such phenomenon was also reported in the case of stem cells. It has been demonstrated that providing to neural stem cells an alginate environment whose mechanical properties are close to those of brain tissues can upregulate neural markers and modify their paracrine activities when varying alginate M/G ratio (5,47). Hence, the choice of alginate composition when elaborating a scaffold, a fortiori in a cardiac application where scaffold mechanical behavior appears as a critical parameter, is far from neutral. Surprisingly, it has never been studied till then.

In this study, in vitro evaluation of G-type and M-type alginates confirmed that both hydrogels were good candidates for MSC encapsulation. MSC viability was maintained around 75% up to 28 days postencapsulation. Moreover, live/dead cells distribution inside microspheres suggested sufficient nutriments and oxygen diffusion in whole microparticles, a necessary prerequisite to maintain cell viability (37).

Functionality of encapsulated MSCs was evaluated through the expression of cytokines responsible of MSCs' beneficial effects. Bioactive factors secreted by MSCs possess angiogenic, antiapoptotic, and immunomodulatory properties that may limit tissue damage extension at the injury site and promote blood supply (9,12,17,25). Among them, FGF-2, HGF, VEGF, G-CSF, EGF, and IGF-1 were clearly identified in literature (4,13,14,20,24,49,56), FGF-2 being the most abundant cytokine secreted by MSCs (36). The measurement of mRNA encoding for these factors and the quantification of intracellular FGF2 showed that MSC paracrine activity was maintained and even increased when encapsulated. Statistical analysis concerning the comparison of biofactor expression levels in encapsulated and nonencapsulated MSCs showed an overexpression of IGF-1 and HGF in the former case (p < 0.001). It has already been demonstrated that three-dimensional configuration can modify biofactor expression levels in encapsulated cells (11). Such mechanisms seem to be related to changes (i) in spatial and mechanical configuration mimicking in vivo environment and (ii) in cell morphology, movement, and density (16,28,51,60).

Concerning cell phenotype, our results showed that most of the entrapped cells express the MSC marker CD90 and maintain the osteogenic, chondrogenic, and adipogenic lineage. These results confirm that most of the entrapped cells maintain the MSC phenotype. MSCs did not undergo transdifferentiation to classical osteoblast, chondroblast, and adipocyte lineages during culture period and expressed the MSC marker CD90, confirming that entrapped cells maintain an MSC phenotype.

Regarding MSC biological parameters investigated here, alginate M/G ratio had no direct impact on their behavior after 28 days of encapsulation. These results confirmed previous work from our laboratory, which demonstrated that encapsulation in alginate microparticles represents a promising approach for MSC engraftment on solid organ (58). Our in vitro results suggest that entrapment in three-dimensional scaffolds elaborated with both types of alginates may represent an excellent alternative to direct intraparenchymal injection and could permit to take advantage of paracrine properties of MSCs in cell therapy. Nevertheless, this conclusion has to be modulated by our in vivo results.

Implanted rats presented no sign of infection and a stable cardiac function, suggesting a good environmental and mechanical compatibility of the devices on beating heart. Patch-shaped scaffolds from G-type and M-type alginate did not disturb cardiac function when implanted on the myocardium. Alginates biocompatibility in relation with their composition and more particularly with their M/G ratio has been a matter of controversy (27,43,44). Consensus is now established about the predominant influence of purity grade on alginate immunogenicity (42,46). This point was confirmed by the observed maintained hematocrit level in both cases during the implantation period. In addition, both alginate scaffolds were well integrated in the myocardial environment: microscopic observation of explants revealed a weak fibrosis associated with a vascularized tissue surrounding the devices. This latter observation is of importance, as oxygenation and nutrition of entrapped cells is a key parameter to obtain long-term viability of the graft, a point that actually limits the benefits of MSC cardiac therapy. Concerning cardiac implantability, two distinct in vivo behaviors were observed as a function of alginate M/G ratio. M-type alginate scaffolds have been more difficult to manipulate due to their lack of cohesion and lower rigidity when compared to G-type alginate scaffolds. These latter were easily manipulated by surgeon and fixed by suture to the myocardium. Twenty-eight days postimplantation, G-type scaffolds were found on the myocardium, still fixed by the initial sutures, while M-type alginate scaffolds were found damaged and detached from sutures. Alginate degradability is generally reported to depend on molecular weight (6). In this study, G-type and M-type alginate viscosities were similar (262 and 440 mPa s, respectively; Table 1), suggesting the same order of magnitude of their molecular weight. Hence, the observed M-type alginate patch destruction may be better related to hydrogel microstructure and resulting mechanical properties. Effectively, G-type alginates, containing a higher F GG fraction than M-type alginates, provide more binding sites for calcium ions, leading to more structured and rigid polymeric networks. Consequently, G-type alginate scaffolds were able to support strain in a dynamic environment, while less structured M-type alginate scaffolds could not.

CONCLUSION

This study presents a double interest: first, it validates the use of alginate three-dimensional scaffolds to take advantage of MSCs' secretory abilities. Second, it points out the impact of alginates chemical composition and, consequently, mechanical behavior on scaffold performance in cardiac therapy field. Even if both alginate types appear highly biocompatible, resulting scaffold implantability and in situ mechanical resistance are to be considered. Alginate G-type hydrogels, exhibiting a higher structural and mechanical resistance, appeared better adapted to bear in vivo cardiac strain.

This study permits expanded knowledge of the critical parameters to consider when considering an alginate MSC scaffold. However, many questions remain unsolved, particularly concerning the device optimal tridimensional geometry. Recent studies have highlighted the interest of a patch shape, but little is known concerning the optimal porosity necessary to combine efficient cell loading, adequate mechanical properties, nutrients circulation, and vascular infiltration. Strategies to optimize alginates scaffold performance for MSC cardiac therapy are currently under investigation in our laboratory.

Figure 1 .

 1 Figure 1. Mechanical properties of alginate hydrogels. Determination of Young's modulus of G-type (black bars) and M-type (white bars) alginate hydrogels by stress measurement under three successive 50% compressive strains (1, 2, and 3). Error bars represent standard deviation; *p ≤ 0.05, **p ≤ 0.01 based on ANOVA analysis.

Figure 2 .

 2 Figure 2. Swelling behavior of alginate hydrogels. Sauter diameter d(3,2) of G-type (black bars) and M-type (white bars) alginate microspheres immersed for 28 days in iso-osmotic buffer.

Figure 3 .

 3 Figure 3. Viability of entrapped MSCs in alginate hydrogels. Quantification of mesenchymal stem cell (MSC) viability (%) and alginate cell density (cells/mm 2 ) by confocal microscopy during 28 days of encapsulation in G-type (full line/black bars, respectively) or M-type (dot line/white bar, respectively) alginate microspheres (A). Confocal z planes of G-type (B) and M-type (C) alginate microspheres after a live/dead staining after 21 days in culture. Five confocal z planes of G-type (D) and M-type (E) alginate microspheres after ethanol treatment showing a diffuse labeling of dead cells with some residual living cells. Scale bars: 200 µm.

Figure 4 .

 4 Figure 4. PCNA immunostaining of encapsulated MSCs. Proliferating cell nuclear antigen (PCNA)-immunostained G-type (A and B) and M-type (C and D) microspheres after 28 days postencapsulation. Sections of rat kidney regenerating after ischemia/reperfusion were used as positive control (E and F). Scale bars: 100 µm.

Figure 6 .

 6 Figure 6. Paracrine activity of encapsulated MSCs. Relative quantification of transcript coding for growth factors in MSCs encapsulated in G-type (black bars) or M-type (white bars) alginate microspheres after 28 days of culture, normalized by glyceraldehyde 3-phosphate dehydrogenase (GAPDH) and ribosomal protein L31 (RPL31), fold to control (A). Control is determined by cytokine expression in cultured MSCs. Quantification of intracellular fibroblast growth factor 2 (FGF2) in MSCs encapsulated in G-type (black bars) or M-type (white bars) alginates microspheres after 28 days of culture or nonencapsulated MSCs (gray bars) normalized by GAPDH (B).

Figure 7 .

 7 Figure 7. Evaluation of alginate hydrogels biocompatibility. Hematocrit levels of implanted rats 28 days after cardiac implantation (A) of G-type (full line), M-type (dot line) hydrogels and control group (dash line). White blood cell differential count 28 days after cardiac implantation (C) of G-type (black bars) and M-type (white bars) alginate scaffolds implanted group and control group (gray bar).

Figure 8 .

 8 Figure 8. Results of echographic measurement. Left: Echographic photography of implanted (A and B) and not implanted (C) hearts. G-type (A) and M-type (B) alginate scaffolds are indicated by arrows. For understanding facility scale bars corresponding to 5 mm have been added. Right: Left ventricular end-diastolic volumes (LVEDV, D), left ventricular ejection fraction (LVEF, E), and heart rate (HR, F) in beats per minute (BPM) of G-type (full line) and M-type (spot line) alginate scaffolds implanted rats and controls (dash line) 28 days after cardiac implantation.

Figure 9 .

 9 Figure 9. Macroscopic morphology of explanted alginate hydrogels. Photography of G-type (A) and M-type (B) alginate scaffolds explanted from the heart 28 days after implantation. Scale bars: 10 mm.

Figure 10 .

 10 Figure 10. Twenty-eight days postimplantation microscopic analysis of explanted alginate hydrogels from the heart. Eosin/hematoxylin staining of explanted G-type (A) and M-type (B and D) alginate scaffolds. α-SMA staining of explanted G-type alginate hydrogel (C); arrows indicate vascular formation in fibrotic tissue. Scale bars: 500 µm (A, B, and D) and 100 µm (C).

Table 1 .

 1 Main Characteristics of Ultrapur Alginates Used in This Study

		Provona Up	Provona Up
	Parameters	MVG	MVM
	F G a	68%	45%
	F GG a	55%	28%
	F GM a	13%	17%
	F MM a	20%	38%
	Elastic modulus (G′) b	31.1 ± 2.6 kPa	9.9 ± 2.7 kPa
	Loss modulus (G″) b	4.2 ± 0.6 kPa	1.3 ± 0.5 kPa
	A pparent viscosity c	262 mPa.s	440 mPa.s
	at 25°C, 1%
	Protein content c	≤0.1%	≤0.1%
	Endotoxins c	<19 EU/g	<25 EU/g

F G , G fraction; F GG , GG fraction; F GM , GM fraction; F MM , MM fraction. a1 H NMR measurement. b Rheological measurement at 4 Hz (mean ± standard deviation). c Data provided by Nova Matrix, FMC BioPolymer (Oslo, Norway).

ACKNOWLEDGMENTS:

We wish to acknowledge H. Ternet for assistance for alginate hydrolysis (Université de Toulouse, CIRIMAT, UPS-INPT-CNRS, Faculté de Pharmacie, Toulouse). We thank A. Milon and O. Saurel at IPBS for providing access to NMR spectrometer (Réseau RMN, Midi-Pyrénées). We wish to acknowledge P. Ramos for his assistance in NMR measurement and process. We are grateful for the excellent technical support and advice of B. Payré and R. d'Angelo (Cellular Imaging Facility, TRI Plateform, Toulouse). We thank S. Estage and A. Estival for assistance in tissue embedding and processing (Service d'anatomie et cytology pathologiques, CHU Rangueil, Toulouse) and C. Frugier (INSERM, U858, Toulouse, F-31432 France) for histological analysis. This work was supported by CNRS (CNRS grant for exploratory projects "Interface Matériau/Vivant"). The authors declare no conflicts of interest.