Bone tissue under the influence of an aged/experienced adaptive immune system

Musculoskeletal conditions are the leading cause of pain, suffering and disability in workplaces and have a huge financial burden. Within this study, age-dependent changes in the immune and skeletal system were investigated in parallel to evaluate the impact of aged immunity on bone structures and quality. In patients with delayed fracture healing a subtype of T cells are at higher abundance compared to normal healing patients. This raises the question of whether the experience in the adaptive immunity directly influences bone structure and formation. The skeletal and immune systems were analyzed in mice aged from 3 months to 24 months. The mice were aged in specific pathogen-free environment thus keeping a relative naïve immunity or exposed to environmental microorganisms allowing the immune system to establish memory. The immune status of the mice was examined via flow cytometry, which was then correlated to their bone structure via microCT and bone competence via biomechanical testing. Bone regeneration was analyzed in vivo in a mouse osteotomy model, and healing outcome was evaluated after 3 and 21 days. Protein analysis was done to unravel the diverging cytokine patterns after fracture. In addition, MSCs from these mice were analyzed for their differentiation potential and ECM production in the presence and absence of immune cell signaling ex vivo. Furthermore, several immunomodulatory interventions were tested in order to improve bone fracture healing under the influence of an aged/experienced adaptive immunity. Age-associated alterations in the immune profile and bone tissue could be itemized between chronological and biological aging. The memory/effector compartment of adaptive immunity was significantly increased in mice that were exposed to environmental microorganisms. The immune experience led to a significantly different bone phenotype both in structure and in competence to withstand loads. The in vivo bone formation was highly affected by age but also by the immune status. Bone tissue formation during healing was delayed in the experienced adaptive immunity group and significant changes in cytokine levels were observed 3 days post-surgery. Furthermore, the tested interventions of regulatory T cells transfer or inhibition of immune cell activation as immunomodulatory approaches laid the foundation of future treatment options. Adaptive immunity directly affects bone tissue formation and tissue remodeling leading to structural differences in bone material organization as well as mechanical competence. Such knowledge is essential for the characterization of healing settings and lays the foundation for novel diagnostics and therapeutics that aim to understand and rescue delayed bone regeneration in immunologically challenging patients. This data is the first to show that a patient’s immune experience needs to be taken into account, in the context of diagnostics as well as in therapy.Erkrankungen des Bewegungsapparates gehören zu den häufigsten Ursachen von Schmerzen, Immobilität und Einschränkungen am Arbeitsplatz. Im Rahmen dieser Studie wurden altersabhängige Veränderungen des Immun- und Skelettsystems untersucht, um den Einfluss der gealterten Immunität auf den Knochen zu bewerten. Bei Patienten mit verzögerter Frakturheilung ist die Häufigkeit eines Subtyps von T Zellen im Vergleich zu normaler Heilung erhöht. Es stellt sich die Frage, ob die Erfahrung in der adaptiven Immunität einen direkten Einfluss auf den Knochen hat. Das Skelett- und das Immunsystem wurden bei Mäusen im Alter von 3 bis 24 Monaten analysiert. Die Mäuse wurden in einer SPF Umgebung gealtert, wodurch eine relativ naive Immunität aufrechterhalten wurde, oder sie wurden Umweltmikroorganismen exponiert, wodurch das Immunsystem eine Erfahrung aufbauen konnte. Die Mäuse wurden auf ihren Immunstatus untersucht, welcher dann mit ihrer Knochenstruktur und -kompetenz korreliert wurde. Die Regeneration wurde in einem Osteotomiemodell analysiert und der Heilungsverlauf nach 3 und 21 Tagen bewertet. Eine Proteinanalyse wurde durchgeführt, um die Zytokinmuster zu entschlüsseln. Zusätzlich wurden MSCs hinsichtlich ihres Differenzierungspotentials und ihrer ECM-Produktion unter Immunzellsignalen analysiert. Darüber hinaus wurden mehrere immunmodulatorische Interventionen getestet, um die beeinträchtigte Heilung unter dem Einfluss einer gealterten/erfahrenen adaptiven Immunität zu verbessern. Eine chronologische und biologische Alterung konnte über eine Trennung der immunologischen und knochengewebsspezifischen Alterung unterschieden werden. Das Gedächtnis-Kompartiment der adaptiven Immunität war bei Mäusen unter exponierter Haltung signifikant erhöht. Diese Immunerfahrung führte zu einem signifikant unterschiedlichen Knochenphänotyp in Bezug auf Struktur und Belastbarkeit. Der Verlauf der Knochenregeneration war vom Alter und vom Immunstatus abhängig. Die Heilung war in der Gruppe mit erfahrener adaptiver Immunität beeinträchtigt, und 3 Tage nach der Osteotomie wurden signifikant veränderte Zytokinspiegel beobachtet. Darüber hinaus bildeten die getesteten Interventionen des adaptiven Transfers von regulatorischen T Zellen oder der Aktivierungshemmung von Immunzellen als Immunmodulation den Grundstein für zukünftige Behandlungsoptionen. Die adaptive Immunität wirkt sich direkt auf die Knochenbildung und den Gewebeumbau aus und führt zu strukturellen Unterschieden in der Knochenmaterialorganisation sowie in der mechanischen Kompetenz. Dieses Wissen ist für die Charakterisierung des Heilungsverlaufs von wesentlicher Bedeutung und bildet die Grundlage für neuartige Diagnostika und Therapeutika, die darauf abzielen, die beeinträchtigte Knochenregeneration bei immunologisch anspruchsvollen Patienten zu verstehen und zu behandeln. Diese Daten zeigen erstmals, dass die Immunerfahrung sowohl in der Diagnostik als auch in der Therapie berücksichtigt werden sollte

Asynchronous variational integration using continuous assumed gradient elements

AbstractAsynchronous variational integration (AVI) is a tool which improves the numerical efficiency of explicit time stepping schemes when applied to finite element meshes with local spatial refinement. This is achieved by associating an individual time step length to each spatial domain. Furthermore, long-term stability is ensured by its variational structure. This article presents AVI in the context of finite elements based on a weakened weak form (W2) Liu (2009) [1], exemplified by continuous assumed gradient elements Wolff and Bucher (2011) [2]. The article presents the main ideas of the modified AVI, gives implementation notes and a recipe for estimating the critical time step

Distance fields on unstructured grids: Stable interpolation, assumed gradients, collision detection and gap function

AbstractThis article presents a novel approach to collision detection based on distance fields. A novel interpolation ensures stability of the distances in the vicinity of complex geometries. An assumed gradient formulation is introduced leading to a C1-continuous distance function. The gap function is re-expressed allowing penalty and Lagrange multiplier formulations. The article introduces a node-to-element integration for first order elements, but also discusses signed distances, partial updates, intermediate surfaces, mortar methods and higher order elements. The algorithm is fast, simple and robust for complex geometries and self contact. The computed tractions conserve linear and angular momentum even in infeasible contact. Numerical examples illustrate the new algorithm in three dimensions

ADAPTIVE RESPONSE SURFACE APPROACH USING ARTIFICIAL NEURAL NETWORKS AND MOVING LEAST SQUARES

In engineering science the modeling and numerical analysis of complex systems and relations plays an important role. In order to realize such an investigation, for example a stochastic analysis, in a reasonable computational time, approximation procedure have been developed. A very famous approach is the response surface method, where the relation between input and output quantities is represented for example by global polynomials or local interpolation schemes as Moving Least Squares (MLS). In recent years artificial neural networks (ANN) have been applied as well for such purposes. Recently an adaptive response surface approach for reliability analyses was proposed, which is very efficient concerning the number of expensive limit state function evaluations. Due to the applied simplex interpolation the procedure is limited to small dimensions. In this paper this approach is extended for larger dimensions using combined ANN and MLS response surfaces for evaluating the adaptation criterion with only one set of joined limit state points. As adaptation criterion a combination by using the maximum difference in the conditional probabilities of failure and the maximum difference in the approximated radii is applied. Compared to response surfaces on directional samples or to plain directional sampling the failure probability can be estimated with a much smaller number of limit state points

INVESTIGATION OF MODELING ERRORS OF DIFFERENT RANDOM FIELD BASED WIND LOAD FORMULATIONS

In this paper the influence of changes in the mean wind velocity, the wind profile power-law coefficient, the drag coefficient of the terrain and the structural stiffness are investigated on different complex structural models. This paper gives a short introduction to wind profile models and to the approach by Davenport A. G. to compute the structural reaction of wind induced vibrations. Firstly with help of a simple example (a skyscraper) this approach is shown. Using this simple example gives the reader the possibility to study the variance differences when changing one of the above mentioned parameters on this very easy example and see the influence of different complex structural models on the result. Furthermore an approach for estimation of the needed discretization level is given. With the help of this knowledge the structural model design methodology can be base on deeper understanding of the different behavior of the single models

Reliability Estimation for Deteriorating Reinforced Concrete Structures using Bayesian Updating

The deterioration mechanisms of reinforced concrete (RC) structures have many kinds of uncertainties, and it is impossible to completely predict the condition of RC structures throughout their lifetime at the initial design stage. Therefore, observation or inspection data, which reflect the actual condition of the existing structures, should be used to reduce the uncertainties of the reliability prediction model of deteriorating RC structures. In this paper, a novel reliability estimation method for deteriorating RC structures using observation data is proposed. Bayesian updating method is used to combine corrosion models with observation data and to update prior probabilistic models, while the structural reliability is calculated with a time-dependent three-dimensional finite element (FE) analysis. Chloride-induced corrosion of reinforcing steels, which is one of the most significant deterioration mechanisms of RC structures, is considered. With Bayesian updating method, the uncertainties in the chloride-ion diffusion model can be reduced, and the probability of corrosion initiation is updated. Finally, as an illustrative case study of the proposed method, the time-dependent structural safety of a box-girder bridge is calculated over its lifetime of 50 yrs. Based on the results of this paper, the structural reliability of deteriorating RC structures can be quantitatively updated, and it can be useful for the appropriate and reasonable decision-making of maintenance

Modelling of changing of dynamic and static parameters of damaged R/C

Dynamic testing for damage assessment as non-destructive method has attracted growing in-terest for systematic inspections and maintenance of civil engineering structures. In this con-text the paper presents the Stochastic Finite Element (SFE) Modeling of the static and dy-namic results of own four point bending experiments with R/C beams. The beams are dam-aged by an increasing load. Between the load levels the dynamic properties are determined. Calculated stiffness loss factors for the displacements and the natural frequencies show differ-ent histories. A FE Model for the beams is developed with a discrete crack formulation. Cor-related random fields are used for structural parameters stiffness and tension strength. The idea is to simulate different crack evolutions. The beams have the same design parameters, but because of the stochastic material properties their undamaged state isn't yet the same. As the structure is loaded a stochastic first crack occurs on the weakest place of the structure. The further crack evolution is also stochastic. These is a great advantage compared with de-terministic formulations. To reduce the computational effort of the Monte Carlo simulation of this nonlinear problem the Latin-Hypercube sampling technique is applied. From the results functions of mean value and standard deviation of displacements and frequencies are calcu-lated. Compared with the experimental results some qualitative phenomena are good de-scribed by the model. Differences occurs especially in the dynamic behavior of the higher load levels. Aim of the investigations is to assess the possibilities of dynamic testing under consideration of effects from stochastic material propertie

SLang - the Structural Language : Solving Nonlinear and Stochastic Problems in Structural Mechanics

Recent developments in structural mechanics indicate an increasing need of numerical methods to deal with stochasticity. This process started with the modeling of loading uncertainties. More recently, also system uncertainty, such as physical or geometrical imperfections are modeled in probabilistic terms. Clearly, this task requires close connenction of structural modeling with probabilistic modeling. Nonlinear effects are essential for a realistic description of the structural behavior. Since modern structural analysis relies quite heavily on the Finite Element Method, it seems to be quite reasonable to base stochastic structural analysis on this method. Commercially available software packages can cover deterministic structural analysis in a very wide range. However, the applicability of these packages to stochastic problems is rather limited. On the other hand, there is a number of highly specialized programs for probabilistic or reliability problems which can be used only in connection with rather simplistic structural models. In principle, there is the possibility to combine both kinds of software in order to achieve the goal. The major difficulty which then arises in practical computation is to define the most suitable way of transferring data between the programs. In order to circumvent these problems, the software package SLang (Structural Language) has been developed. SLang is a command interpreter which acts on a set of relatively complex commands. Each command takes input from and gives output to simple data structures (data objects), such as vectors and matrices. All commands communicate via these data objects which are stored in memory or on disk. The paper will show applications to structural engineering problems, in particular failure analysis of frames and shell structures with random loads and random imperfections. Both geometrical and physical nonlinearities are taken into account