Computational modeling reveals a key role for polarized myeloid cells in controlling osteoclast activity during bone injury repair

A Mathematical Model for Fibrous Dysplasia: The Role of the Flow of Mutant Cells

Fibrous dysplasia (FD) is a mosaic non-inheritable genetic disorder of the skeleton in which normal bone is replaced by structurally unsound fibro-osseous tissue. There is no curative treatment for FD, partly because its pathophysiology is not yet fully known. We present a simple mathematical model of the disease incorporating its basic known biology, to gain insight on the dynamics of the involved bone-cell populations, and shed light on its pathophysiology. We develop an analytical study of the model and study its basic properties. The existence and stability of steady states are studied, an analysis of sensitivity on the model parameters is done, and different numerical simulations provide findings in agreement with the analytical results. We discuss the model dynamics match with known facts on the disease, and how some open questions could be addressed using the model.

An agent-based model of tissue maintenance and self-repair

We hypothesized that a system that possesses the capacity for ongoing maintenance of its tissues will necessarily also have the capacity to self-heal following a perturbation. We used an agent-based model of tissue maintenance to investigate this idea, and in particular to determine the extent to which the current state of the tissue must influence cell behavior in order for tissue maintenance and self-healing to be stable. We show that a mean level of tissue density is robustly maintained when catabolic agents digest tissue at a rate proportional to local tissue density, but that the spatial heterogeneity of the tissue at homeostasis increases with the rate at which tissue is digested. The rate of self-healing is also increased by increasing either the amount of tissue removed or deposited at each time step by catabolic or anabolic agents, respectively, and by increasing the density of both agent types on the tissue. We also found that tissue maintenance and self-healing are stable with an alternate rule in which cells move preferentially to tissue regions of low density. The most basic form of self-healing can thus be achieved with cells that follow very simple rules of behavior, provided these rules are based in some way on the current state of the local tissue. Straightforward mechanisms can accelerate the rate of self-healing, as might be beneficial to the organism.

Integrated computational and in vivo models reveal Key Insights into macrophage behavior during bone healing

Myeloid-derived monocyte and macrophages are key cells in the bone that contribute to remodeling and injury repair. However, their temporal polarization status and control of bone-resorbing osteoclasts and bone-forming osteoblasts responses is largely unknown. In this study, we focused on two aspects of monocyte/macrophage dynamics and polarization states over time: 1) the injury-triggered pro- and anti-inflammatory monocytes/macrophages temporal profiles, 2) the contributions of pro- versus anti-inflammatory monocytes/macrophages in coordinating healing response. Bone healing is a complex multicellular dynamic process. While traditional in vitro and in vivo experimentation may capture the behavior of select populations with high resolution, they cannot simultaneously track the behavior of multiple populations. To address this, we have used an integrated coupled ordinary differential equations (ODEs)-based framework describing multiple cellular species to in vivo bone injury data in order to identify and test various hypotheses regarding bone cell populations dynamics. Our approach allowed us to infer several biological insights including, but not limited to,: 1) anti-inflammatory macrophages are key for early osteoclast inhibition and pro-inflammatory macrophage suppression, 2) pro-inflammatory macrophages are involved in osteoclast bone resorptive activity, whereas osteoblasts promote osteoclast differentiation, 3) Pro-inflammatory monocytes/macrophages rise during two expansion waves, which can be explained by the anti-inflammatory macrophages-mediated inhibition phase between the two waves. In addition, we further tested the robustness of the mathematical model by comparing simulation results to an independent experimental dataset. Taken together, this novel comprehensive mathematical framework allowed us to identify biological mechanisms that best recapitulate bone injury data and that explain the coupled cellular population dynamics involved in the process. Furthermore, our hypothesis testing methodology could be used in other contexts to decipher mechanisms in complex multicellular processes.

Myeloid-derived monocytes/macrophages are key cells for bone remodeling and injury repair. However, their temporal polarization status and control of bone-resorbing osteoclasts and bone-forming osteoblasts responses is largely unknown. In this study, we focused on two aspects of monocyte/macrophage population dynamics: 1) the injury-triggered pro- and anti-inflammatory monocytes/macrophages temporal profiles, 2) the contributions of pro- versus anti-inflammatory monocytes/macrophages in coordinating healing response. In order to test various hypotheses regarding bone cell populations dynamics, we have integrated a coupled ordinary differential equations-based framework describing multiple cellular species to in vivo bone injury data. Our approach allowed us to infer several biological insights including: 1) anti-inflammatory macrophages are key for early osteoclast inhibition and pro-inflammatory macrophage suppression, 2) pro-inflammatory macrophages are involved in osteoclast bone resorptive activity, whereas osteoblasts promote osteoclast differentiation, 3) Pro-inflammatory monocytes/macrophages rise during two expansion waves, which can be explained by the anti-inflammatory macrophages-mediated inhibition phase between the two waves. Taken together, this mathematical framework allowed us to identify biological mechanisms that recapitulate bone injury data and that explain the coupled cellular population dynamics involved in the process.

New Generation of Meso and Antiprogestins (SPRMs) into the Osteoporosis Approach

Receptor activator of nuclear factor κB (RANK) and its ligand (RANKL) play key roles in bone metabolism and the immune system. The RANK/RANKL complex has also been shown to be critical in the formation of mammary epithelia cells. The female hormones estradiol and progesterone closely control the action of RANKL with RANK. Blood concentration of these sex hormones in the postmenopausal period leads to an increase in RANK/RANKL signaling and are a major cause of women's osteoporosis, characterized by altered bone mineralization. Knowledge of the biochemical relationships between hormones and RANK/RANKL signaling provides the opportunity to design novel therapeutic agents to inhibit bone loss, based on the anti-RANKL treatment and inhibition of its interaction with the RANK receptor. The new generation of both anti- and mesoprogestins that inhibit the NF-κB-cyclin D1 axis and blocks the binding of RANKL to RANK can be considered as a potential source of new RANK receptor ligands with anti-RANKL function, which may provide a new perspective into osteoporosis treatment itself as well as limit the osteoporosis rise during breast cancer metastasis to the bone.

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

In 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.