Bone turnover and mineralisation kinetics control trabecular BMDD and apparent bone density: insights from a discrete statistical bone remodelling model.

The mechanical quality of trabecular bone is influenced by its mineral content and spatial distribution, which is controlled by bone remodelling and mineralisation. Mineralisation kinetics occur in two phases: a fast primary mineralisation and a secondary mineralisation that can last from several months to years. Variations in bone turnover and mineralisation kinetics can be observed in the bone mineral density distribution (BMDD). Here, we propose a statistical spatio-temporal bone remodelling model to study the effects of bone turnover (associated with the activation frequency Ac . f ) and mineralisation kinetics (associated with secondary mineralisation T sec ) on BMDD. In this model, individual basic multicellular units (BMUs) are activated discretely on trabecular surfaces that undergo typical bone remodelling periods. Our results highlight that trabecular BMDD is strongly regulated by Ac . f and T sec in a coupled way. Ca wt% increases with lower Ac . f and short T sec . For example, a Ac . f = 4 BMU/year/mm 3 and T sec = 8 years result in a mean Ca wt% of 25, which is in accordance with Ca wt% values reported in quantitative backscattered electron imaging (qBEI) experiments. However, for lower Ac . f and shorter T sec (from 0.5 to 4 years) one obtains a high Ca wt% and a very narrow skew BMDD to the right. This close link between Ac . f and T sec highlights the importance of considering both characteristics to draw meaningful conclusion about bone quality. Overall, this model represents a new approach to modelling healthy and diseased bone and can aid in developing deeper insights into disease states like osteoporosis.

A new protocol to accurately track long-term orthodontic tooth movement and support patient-specific numerical modeling.

Numerical simulation of long-term orthodontic tooth movement based on Finite Element Analysis (FEA) could help clinicians to plan more efficient and mechanically sound treatments. However, most of FEA studies assume idealized loading conditions and lack experimental calibration or validation. The goal of this paper is to propose a novel clinical protocol to accurately track orthodontic tooth displacement in three-dimensions (3D) and provide 3D models that may support FEA. Our protocol uses an initial cone beam computed tomography (CBCT) scan and several intra-oral scans (IOS) to generate 3D models of the maxillary bone and teeth ready for use in FEA. The protocol was applied to monitor the canine retraction of a patient during seven months. A second CBCT scan was performed at the end of the study for validation purposes. In order to ease FEA, a frictionless and statically determinate lingual device for maxillary canine retraction was designed. Numerical simulations were set up using the 3D models provided by our protocol to show the relevance of our proposal. Comparison of numerical and clinical results highlights the suitability of this protocol to support patient-specific FEA.

Study of Mechanical Properties of PHBHV/Miscanthus Green Composites Using Combined Experimental and Micromechanical Approaches.

In recent years the interest in the realization of green wood plastic composites (GWPC) materials has increased due to the necessity of reducing the proliferation of synthetic plastics. In this work, we study a specific class of GWPCs from its synthesis to the characterization of its mechanical properties. These properties are related to the underlying microstructure using both experimental and modeling approaches. Different contents of Miscanthus giganteus fibers, at 5, 10, 20, 30 weight percent's, were thus combined to a microbial matrix, namely poly (3-hydroxybutyrate)-co-poly(3-hydroxyvalerate) (PHBHV). The samples were manufactured by extrusion and injection molding processing. The obtained samples were then characterized by cyclic-tensile tests, pycnometer testing, differential scanning calorimetry, Fourier transform infrared spectroscopy, X-ray diffraction, and microscopy. The possible effect of the fabrication process on the fibers size is also checked. In parallel, the measured properties of the biocomposite were also estimated using a Mori-Tanaka approach to derive the effective behavior of the composite. As expected, the addition of reinforcement to the polymer matrix results in composites with higher Young moduli on the one hand, and lower failure strains and tensile strengths on the other hand (tensile modulus was increased by 100% and tensile strength decreased by 23% when reinforced with 30 wt % of Miscanthus fibers).

Assessment of romosozumab efficacy in the treatment of postmenopausal osteoporosis: Results from a mechanistic PK-PD mechanostat model of bone remodeling.

This paper introduces a theoretical framework for the study of the efficacy of romosozumab, a humanized monoclonal antibody targeting sclerostin for the treatment of osteoporosis. We developed a comprehensive mechanistic pharmacokinetic-pharmacodynamic (PK-PD) model of the effect of drug treatment on bone remodeling in postmenopausal osteoporosis (PMO). We utilized a one-compartment PK model to represent subcutaneous injections of romosozumab and subsequent absorption into serum. The PD model is based on a recently-developed bone cell population model describing the bone remodeling process at the tissue scale. The latter accounts for mechanical feedback by incorporating nitric oxide (NO) and sclerostin (Scl) as biochemical feedback molecules. Utilizing a competitive binding model, where Wnt and Scl compete for binding to LRP5/6, allows to regulate anabolic bone remodeling responses. Here, we extended this model with respect to romosozumab binding to sclerostin. For the currently approved monthly injections of 210 mg, the model predicted a 6.59%, 10.38% and 15.25% increase in BMD at the lumbar spine after 6, 12 and 24 months, respectively. These results are in good agreement with the data reported in the literature. Our model is also able to distinguish the bone-site specific drug effects. For instance, at the femoral neck, our model predicts a BMD increase of 3.85% after 12 months of 210 mg injections, which is consistent with literature observations. Finally, our simulations indicate rapid bone loss after treatment discontinuation, indicating that some additional interventions such as use of bisphosphonates are required to maintain bone mass.

Mechanobiological osteocyte feedback drives mechanostat regulation of bone in a multiscale computational model.

Significant progress has been made to identify the cells and signaling molecules involved in the mechanobiological regulation of bone remodeling. It is now well accepted that osteocytes act as mechanosensory cells in bone expressing several signaling molecules such as nitric oxide (NO) and sclerostin (Scl) which are able to control bone remodeling responses. In this paper, we present a comprehensive multiscale computational model of bone remodeling which incorporates biochemical osteocyte feedback. The mechanostat theory is quantitatively incorporated into the model using mechanical feedback to control expression levels of NO and Scl. The catabolic signaling pathway RANK-RANKL-OPG is co-regulated via (continuous) PTH and NO, while the anabolic Wnt signaling pathway is described via competitive binding reactions between Wnt, Scl and the Wnt receptors LRP5/6. Using this novel model of bone remodeling, we investigate the effects of changes in the mechanical loading and hormonal environment on bone balance. Our numerical simulations show that we can calibrate the mechanostat anabolic and catabolic regulatory mechanisms so that they are mutually exclusive. This is consistent with previous models that use a Wolff-type law to regulate bone resorption and formation separately. Furthermore, mechanical feedback provides an effective mechanism to obtain physiological bone loss responses due to mechanical disuse and/or osteoporosis.

The heart function as a motor-brake system.

The controversy between passive and active ventricular filling has been debated for decades and the question about the existence of an active diastole remains open. In this work, we advocate the model of active diastole by considering the heart as a suction pump and we add some more clues to support this point of view by the analysis of the pressure-volume (PV) loops of the left heart, comprising of the left ventricle (LV) and atrium (LA). Our working hypothesis is based on the dichotomy motor-brake: the cardiac muscle can act as a motor, when shortening against a load, or as a brake, when lengthening to a load. We discuss our hypothesis by means of a lumped model of the left heart, where both chambers are considered as hollow spherical shells. The notion of active stretch, introduced to describe the contractile behavior of the muscle fibers, plays a major role in our model. Then, the contraction of the muscle is related to the pressure and volume of the chamber through a nonlinear hyperelastic energy density function. Despite its simplicity, the model enlightens some important features of the LV-LA coupling and of the pumping function of the heart. Based on experimental PV data of the left heart of a normal human subject, it is shown that the contraction patterns of the LV and LA are synchronized with each other and have distinguishing features in each phase of the cardiac cycle. These results highlight the interplay between the two chambers and support the idea that the heart may act as a suction pump functioning in turn as a motor or a brake in order to meet specific demands in each phase of the cardiac cycle.

Mechanomics Approaches to Understand Cell Behavior in Context of Tissue Neogenesis, During Prenatal Development and Postnatal Healing.

Mechanomics represents the natural progression of knowledge at the intersection of mechanics and biology with the aim to codify the role of mechanical environment on biological adaptation. Compared to the mapping of the human genome, the challenge of mapping the mechanome remains unsolved. Solving this grand challenge will require both top down and bottom up R&D approaches using experimental and computational tools to visualize and measure adaptation as it occurs. Akin to a mechanical test of a smart material that changes its mechanical properties and local environment under load, stem cells adapt their shape, cytoskeletal architecture, intrinsic mechanical properties, as well as their own niche, through cytoskeletal adaptation as well as up- and down-regulation of structural proteins that modulate their mechanical milieux. Recent advances in live cell imaging allow for unprecedented study and measurements of displacements, shape and volume changes in stem cells, reconfiguring of cytoskeletal machinery (nucleus, cytoskeleton), in response to controlled mechanical forces and stresses applied at cellular boundaries. Coupled with multiphysics computational and virtual power theoretical approaches, these novel experimental approaches enable mechanical testing of stem cells, multicellular templates, and tissues inhabited by stem cells, while the stem cells themselves evolve over time. The novel approach is paving the way to decipher mechanisms of structural and functional adaptation of stem cells in response to controlled mechanical cues. This mini-review outlines integrated approaches and methodologies implemented to date in a series of studies carried out by our consortium. The consortium's body of work is described in context of current roadblocks in the field and innovative, breakthrough solutions and is designed to encourage discourse and cross disciplinary collaboration in the scientific community.

Biocomposites Based on Poly(3-Hydroxybutyrate-co-3-Hydroxyvalerate) (PHBHV) and Miscanthus giganteus Fibers with Improved Fiber/Matrix Interface.

In this paper, green biocomposites based on poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBHV) and Miscanthus giganteus fibers (MIS) were prepared in the presence of dicumyl peroxide (DCP) via reactive extrusion. The objective of this study was to optimize the interfacial adhesion between the reinforcement and the matrix, improving the mechanical properties of the final material. To this aim, two fibers mass fractions (5 and 20 wt %) and two different fiber sizes obtained by two opening mesh sieves (1 mm and 45 µm) were investigated. The impregnation of fibers with DCP before processing was carried out in order to promote the PHBHV grafting onto MIS fibers during the process, favoring, in this way, the interfacial adhesion between fibers and matrix, instead of the crosslinking of the matrix. All composites were realized by extrusion and injection molding processing and then characterized by tensile tests, FTIR-ATR, SEM, DSC and XRD. According to the improved adhesion of fibers to matrix due to DCP, we carried out an implementation of models involving that can predict the effective mechanical properties of the biocomposites. Three phases were taken into account here: fibers, gel (crosslinked matrix), and matrix fractions. Due to the complexity of the system (matrix⁻crosslinked matrix⁻fibers) and to the lack of knowledge about all the phenomena occurring during the reactive extrusion, a mathematical approach was considered in order to obtain information about the modulus of the crosslinked matrix and its fraction in the composites. This study aims to estimate these last values, and to clarify the effect caused by the presence of vegetal fibers in a composite in which different reactions are promoted by DCP.

Tissue mineral density measured at the sub-millimetre scale can provide reliable statistics of elastic properties of bone matrix.

Reliability of multiscale models of bone is related to the accuracy of the experimental information available on bone microstructure. X-ray-based imaging techniques allow to inspect bone structure and mineralization in vitro at the micrometre scale. However, spatial resolution achievable in vivo is much coarser and can produce blurry, uncertain information on bone microstructure. Working with uncertain data calls for new modelling paradigms able to propagate uncertainty through the scales. In this paper we investigate the effects of uncertain bone mineralization on the elastic coefficients of the bone matrix. To this aim, some stochastic concepts were developed and compared with one another in order to identify the best way to account for uncertain input data. These concepts step from a deterministic micromechanical model of bone matrix which was extended in order to account for uncertain bone composition. Uncertainty was introduced by assuming to know only mean value and dispersion of the parameters describing bone composition. Thus, these parameters were modelled as random variables and their distribution functions were obtained using the maximum entropy principle. Either the tissue mineral density (TMD) or the ensuing volume fractions of collagen and mineral were used to describe uncertain bone composition. Moreover, mean value and dispersion were estimated at the scales of either 10 or a few 100 [Formula: see text]m, representative of standard in vitro and in vivo spatial resolutions, respectively. Analysis of these modelling concepts suggests that TMD measured at the sub-millimetre scale can be used to obtain reliable statistical information about the elastic coefficients of bone matrix.

New finite element study protocol: Clinical simulation of orthodontic tooth movement.

The aim of this work was to model tooth movement in a more clinically-exact fashion, thanks to the use of new IT tools and imaging systems (cone-beam). Image segmentation and 3D reconstruction now enable us to model the anatomy realistically, while finite element (FE) analysis makes it possible to evaluate stresses and their distribution on the level of the tooth, the periodontal ligament (PDL) and the alveolar bone when a force is applied. The principle is to monitor tooth movement by obtaining optical impressions at each stage of treatment. The model corresponds to a genuine clinical situation. FE analysis is correlated with the clinically-observed displacement. The protocol remains long and complex. It nevertheless makes it possible to obtain, throughout the duration of treatment, patient-specific models that can be exploited using finite element methods. It requires further validation in more thorough studies but offers interesting prospects: precise study of induced tooth movement, distribution of stresses in the PDL, and development of a customized previsualization tool.

Emergence of Form from Function - Mechanical Engineering Approaches to Probe the Role of Stem Cell Mechanoadaptation in Sealing Cell Fate.

Stem cell "mechanomics" refers to the effect of mechanical cues on stem cell and matrix biology, where cell shape and fate are intrinsic manifestations of form and function. Before specialization, the stem cell itself serves as a sensor and actuator; its structure emerges from its local mechanical milieu as the cell adapts over time. Coupling of novel spatiotemporal imaging and computational methods allows for linking of the energy of adaptation to the structure, biology and mechanical function of the cell. Cutting edge imaging methods enable probing of mechanisms by which stem cells' emergent anisotropic architecture and fate commitment occurs. A novel cell-scale model provides a mechanistic framework to describe stem cell growth and remodeling through mechanical feedback; making use of a generalized virtual power principle, the model accounts for the rate of doing work or the rate of using energy to effect the work. This coupled approach provides a basis to elucidate mechanisms underlying the stem cell's innate capacity to adapt to mechanical stimuli as well as the role of mechanoadaptation in lineage commitment. An understanding of stem cell mechanoadaptation is key to deciphering lineage commitment, during prenatal development, postnatal wound healing, and engineering of tissues.

Stochastic multiscale modelling of cortical bone elasticity based on high-resolution imaging.

Accurate and reliable assessment of bone quality requires predictive methods which could probe bone microstructure and provide information on bone mechanical properties. Multiscale modelling and simulation represent a fast and powerful way to predict bone mechanical properties based on experimental information on bone microstructure as obtained through X-ray-based methods. However, technical limitations of experimental devices used to inspect bone microstructure may produce blurry data, especially in in vivo conditions. Uncertainties affecting the experimental data (input) may question the reliability of the results predicted by the model (output). Since input data are uncertain, deterministic approaches are limited and new modelling paradigms are required. In this paper, a novel stochastic multiscale model is developed to estimate the elastic properties of bone while taking into account uncertainties on bone composition. Effective elastic properties of cortical bone tissue were computed using a multiscale model based on continuum micromechanics. Volume fractions of bone components (collagen, mineral, and water) were considered as random variables whose probabilistic description was built using the maximum entropy principle. The relevance of this approach was proved by analysing a human bone sample taken from the inferior femoral neck. The sample was imaged using synchrotron radiation micro-computed tomography. 3-D distributions of Haversian porosity and tissue mineral density extracted from these images supplied the experimental information needed to build the stochastic models of the volume fractions. Thus, the stochastic multiscale model provided reliable statistical information (such as mean values and confidence intervals) on bone elastic properties at the tissue scale. Moreover, the existence of a simpler "nominal model", accounting for the main features of the stochastic model, was investigated. It was shown that such a model does exist, and its relevance was discussed.

Interstitial fluid flow within bone canaliculi and electro-chemo-mechanical features of the canalicular milieu: a multi-parametric sensitivity analysis.

Canalicular fluid flow is acknowledged to play a major role in bone functioning, allowing bone cells' metabolism and activity and providing an efficient way for cell-to-cell communication. Bone canaliculi are small canals running through the bone solid matrix, hosting osteocyte's dendrites, and saturated by an interstitial fluid rich in ions. Because of the small size of these canals (few hundred nanometers in diameter), fluid flow is coupled with electrochemical phenomena. In our previous works, we developed a multi-scale model accounting for coupled hydraulic and chemical transport in the canalicular network. Unfortunately, most of the physical and geometrical information required by the model is hardly accessible by nowadays experimental techniques. The goal of this study was to numerically assess the influence of the physical and material parameters involved in the canalicular fluid flow. The focus was set on the electro-chemo-mechanical features of the canalicular milieu, hopefully covering any in vivo scenario. Two main results were obtained. First, the most relevant parameters affecting the canalicular fluid flow were identified and their effects quantified. Second, these findings were given a larger scope to cover also scenarios not considered in this study. Therefore, this study gives insight into the potential interactions between electrochemistry and mechanics in bone and provides the rational for further theoretical and experimental investigations.

Multiphysical modelling of fluid transport through osteo-articular media.

In this study, a multiphysical description of fluid transport through osteo-articular porous media is presented. Adapted from the model of Moyne and Murad, which is intended to describe clayey materials behaviour, this multiscale modelling allows for the derivation of the macroscopic response of the tissue from microscopical information. First the model is described. At the pore scale, electrohydrodynamics equations governing the electrolyte movement are coupled with local electrostatics (Gauss-Poisson equation), and ionic transport equations. Using a change of variables and an asymptotic expansion method, the macroscopic description is carried out. Results of this model are used to show the importance of couplings effects on the mechanotransduction of compact bone remodelling.

Multiphysical modelling of fluid transport through osteo-articular media

In this study, a multiphysical description of fluid transport through osteo-articular porous media is presented. Adapted from the model of Moyne and Murad, which is intended to describe clayey materials behaviour, this multiscale modelling allows for the derivation of the macroscopic response of the tissue from microscopical information. First the model is described. At the pore scale, electrohydrodynamics equations governing the electrolyte movement are coupled with local electrostatics (Gauss-Poisson equation), and ionic transport equations. Using a change of variables and an asymptotic expansion method, the macroscopic description is carried out. Results of this model are used to show the importance of couplings effects on the mechanotransduction of compact bone remodelling.

Neste estudo uma descrição multifísica do transporte de fluidos em meios porosos osteo articulares é apresentada. Adaptado a partir do modelo de Moyne e Murad proposto para descrever o comportamento de materiais argilosos a modelagem multiescala permite a derivação da resposta macroscópica do tecido a partir da informação microscópica. Na primeira parte o modelo é apresentado. Na escala do poro as equações da eletro-hidrodinâmica governantes do movimento dos eletrolitos são acopladas com a eletrostática local (equação de Gauss-Poisson) e as equações de transporte iônico. Usando uma mudança de variáveis e o método de expansão assintótica a derivação macroscópica é conduzida. Resultados do modelo proposto são usados para salientar a importância dos efeitos de acoplamento sobre a transdução mecânica da remodelagem de ossos compactados.