Multiscale Modeling of Bone Healing

Bone is a living part of the body that can, in most situations, heal itself after fracture. However, in some situations, healing may fail. Compromised conditions, such as large bone defects, aging, immuno-deficiency, or genetic disorders, might lead to delayed or non-unions. Treatment strategies for those conditions remain a clinical challenge, emphasizing the need to better understand the mechanisms behind endogenous bone regeneration. Bone healing is a complex process that involves the coordination of multiple events at different length and time scales. Computer models have been able to provide great insights into the interactions occurring within and across the different scales (organ, tissue, cellular, intracellular) using different modeling approaches [partial differential equations (PDEs), agent-based models, and finite element techniques]. In this review, we summarize the latest advances in computer models of bone healing with a focus on multiscale approaches and how they have contributed to understand the emergence of tissue formation patterns as a result of processes taking place at the lower length scales

Multiscale Modeling of Bone Healing: Toward a Systems Biology Approach

Bone is a living part of the body that can, in most situations, heal itself after fracture. However, in some situations, healing may fail. Compromised conditions, such as large bone defects, aging, immuno-deficiency, or genetic disorders, might lead to delayed or non-unions. Treatment strategies for those conditions remain a clinical challenge, emphasizing the need to better understand the mechanisms behind endogenous bone regeneration. Bone healing is a complex process that involves the coordination of multiple events at different length and time scales. Computer models have been able to provide great insights into the interactions occurring within and across the different scales (organ, tissue, cellular, intracellular) using different modeling approaches [partial differential equations (PDEs), agent-based models, and finite element techniques]. In this review, we summarize the latest advances in computer models of bone healing with a focus on multiscale approaches and how they have contributed to understand the emergence of tissue formation patterns as a result of processes taking place at the lower length scales

Application to a short-stem hip implant

Today, different implant designs exist in the market; however, there is not a clear understanding of which are the best implant design parameters to achieve mechanical optimal conditions. Therefore, the aim of this project was to investigate if the geometry of a commercial short stem hip prosthesis can be further optimized to reduce stress shielding effects and achieve better short- stemmed implant performance. To reach this aim, the potential of machine learning techniques combined with parametric Finite Element analysis was used. The selected implant geometrical parameters were: total stem length (L), thickness in the lateral (R1) and medial (R2) and the distance between the implant neck and the central stem surface (D). The results show that the total stem length was not the only parameter playing a role in stress shielding. An optimized implant should aim for a decreased stem length and a reduced length of the surface in contact with the bone. The two radiuses that characterize the stem width at the distal cross-section in contact with the bone were less influential in the reduction of stress shielding compared with the other two parameters; but they also play a role where thinner stems present better results

Short-run dynamics of income disparities and regional cycle synchronization in the U.S.

Since the 1990s, the issue of regional income convergence and its long-term tendencies has been thoroughly and heatedly discussed. Much less attention, however, has been devoted to the short-run dynamics of regional convergence. In particular, three important aspects have not yet been adequately addressed. First, it is indeed essential to understand whether regional disparities manifest a tendency to move systematically along the national cycle. Then, if this happens to be the case, it becomes crucial to know whether 1) these movements are pro- or counter-cyclical,2) the cyclical evolution of the disparities is a consequence of differences in the timing with which the business cycle is felt in regions or it is motivated by the amplitude differences across local cyclical swings. In this paper, we shed light on these issues using data on personal income for the 48 coterminous U.S. states between 1969 and 2008. Our results indicate that income disparities do not move randomly in the short run but follow a distinct cyclical pattern, moving either pro- or counter-cyclically depending on the period of analysis. These patterns are probably explained by the changes in the direction of capital and labor flows that favor developed or poorer states in different periods. As for the underlying mechanism, it appears that the short-run evolution of the disparities in recent years is largely a consequence of differences in the timing with which the business cycle is felt across states rather than the outcome of amplitude differences across local cyclical swings

BONE HEALING IN MICE: DOES IT FOLLOW GENERIC MECHANO-REGULATION RULES?

Mechanical signals are known to influence bone healing progression. Previous studies have postulated inter-species differences in the mechanical regulation of the bone healing process. The aim of this study is to investigate whether mechanical “rules” explaining tissue formation patterns during bone healing in rat can be translated to a mouse model of bone regeneration. We have used an established mechano-biological computer model that uses finite element techniques to determine the mechanical conditions within the healing region and an agent-based approach to simulate cellular activity. The computer model is set up to simulate the course of bone healing in a femoral osteotomy model stabilized with an external fixator. Computer model predictions are compared to corresponding histological data. Generic mechano-regulation “rules” able to explain bone healing progression in the rat are not able to describe tissue formation over the course of healing in the mouse. According to the differentiation theory proposed by Prendergast, mechanical stimuli within the healing region immediately post-surgery are determined to be favorable for cartilage and fibrous tissue formation. In contrast, in vivo histological data showed initial intramembraneous bone formation at the periosteal side. These results suggest that in mice, bone does not require as much stability as is required in rat to reach timely healing. This finding emphasizes the need to further investigate the species-specific mechano-biological regulation of bone regeneration

Towards in silico Models of the Inflammatory Response in Bone Fracture Healing.

peer reviewedIn silico modeling is a powerful strategy to investigate the biological events occurring at tissue, cellular and subcellular level during bone fracture healing. However, most current models do not consider the impact of the inflammatory response on the later stages of bone repair. Indeed, as initiator of the healing process, this early phase can alter the regenerative outcome: if the inflammatory response is too strongly down- or upregulated, the fracture can result in a non-union. This review covers the fundamental information on fracture healing, in silico modeling and experimental validation. It starts with a description of the biology of fracture healing, paying particular attention to the inflammatory phase and its cellular and subcellular components. We then discuss the current state-of-the-art regarding in silico models of the immune response in different tissues as well as the bone regeneration process at the later stages of fracture healing. Combining the aforementioned biological and computational state-of-the-art, continuous, discrete and hybrid modeling technologies are discussed in light of their suitability to capture adequately the multiscale course of the inflammatory phase and its overall role in the healing outcome. Both in the establishment of models as in their validation step, experimental data is required. Hence, this review provides an overview of the different in vitro and in vivo set-ups that can be used to quantify cell- and tissue-scale properties and provide necessary input for model credibility assessment. In conclusion, this review aims to provide hands-on guidance for scientists interested in building in silico models as an additional tool to investigate the critical role of the inflammatory phase in bone regeneration

Bone morphogenetic protein 2-induced cellular chemotaxis drives tissue patterning during critical-sized bone defect healing: an in silico study.

peer reviewedCritical-sized bone defects are critical healing conditions that, if left untreated, often lead to non-unions. To reduce the risk, critical-sized bone defects are often treated with recombinant human BMP-2. Although enhanced bone tissue formation is observed when BMP-2 is administered locally to the defect, spatial and temporal distribution of callus tissue often differs from that found during regular bone healing or in defects treated differently. How this altered tissue patterning due to BMP-2 treatment is linked to mechano-biological principles at the cellular scale remains largely unknown. In this study, the mechano-biological regulation of BMP-2-treated critical-sized bone defect healing was investigated using a multiphysics multiscale in silico approach. Finite element and agent-based modeling techniques were combined to simulate healing within a critical-sized bone defect (5 mm) in a rat femur. Computer model predictions were compared to in vivo microCT data outcome of bone tissue patterning at 2, 4, and 6 weeks postoperation. In vivo, BMP-2 treatment led to complete healing through periosteal bone bridging already after 2 weeks postoperation. Computer model simulations showed that the BMP-2 specific tissue patterning can be explained by the migration of mesenchymal stromal cells to regions with a specific concentration of BMP-2 (chemotaxis). This study shows how computational modeling can help us to further understand the mechanisms behind treatment effects on compromised healing conditions as well as to optimize future treatment strategies

COMMBINI:an experimentally-informed COmputational Model of Macrophage dynamics in the Bone INjury Immunoresponse

Bone fracture healing is a well-orchestrated but complex process that involves numerous regulations at different scales. This complexity becomes particularly evident during the inflammatory stage, as immune cells invade the healing region and trigger a cascade of signals to promote a favorable regenerative environment. Thus, the emergence of criticalities during this stage might hinder the rest of the process. Therefore, the investigation of the many interactions that regulate the inflammation has a primary importance on the exploration of the overall healing progression. In this context, an in silico model named COMMBINI (COmputational Model of Macrophage dynamics in the Bone INjury Immunoresponse) has been developed to investigate the mechano-biological interactions during the early inflammatory stage at the tissue, cellular and molecular levels. An agent-based model is employed to simulate the behavior of immune cells, inflammatory cytokines and fracture debris as well as their reciprocal multiscale biological interactions during the development of the early inflammation (up to 5 days post-injury). The strength of the computational approach is the capacity of the in silico model to simulate the overall healing process by taking into account the numerous hidden events that contribute to its success. To calibrate the model, we present an in silico immunofluorescence method that enables a direct comparison at the cellular level between the model output and experimental immunofluorescent images. The combination of sensitivity analysis and a Genetic Algorithm allows dynamic cooperation between these techniques, enabling faster identification of the most accurate parameter values, reducing the disparity between computer simulation and histological data. The sensitivity analysis showed a higher sensibility of the computer model to the macrophage recruitment ratio during the early inflammation and to proliferation in the late stage. Furthermore, the Genetic Algorithm highlighted an underestimation of macrophage proliferation by in vitro experiments. Further experiments were conducted using another externally fixated murine model, providing an independent validation dataset. The validated COMMBINI platform serves as a novel tool to deepen the understanding of the intricacies of the early bone regeneration phases. COMMBINI aims to contribute to designing novel treatment strategies in both the biological and mechanical domains.</p

A Novel Smad7 Genetic Variant Mapping on the Genomic Region Targeted by Mongersen Is Associated with Crohn's Disease

Down-regulation of Smad7 with a specific Smad7 antisense (AS) oligonucleotide-containing oral drug (Mongersen) was effective in pre-clinical studies and initial clinical trials in Crohn's disease (CD) patients. A recent phase 3 trial was discontinued due to an apparent inefficacy of the drug, but factors contributing to the failure of this study remain unknown. Here, we analysed the frequency in CD of rs144204026 C/T single nucleotide polymorphism (SNP), which maps on the corresponding region targeted by the Smad7 AS contained in the Mongersen formulation and examined whether such a variant allele affects the ability of Smad7 AS to knockdown Smad7