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.

Towards Models of the Inflammatory Response in Bone Fracture Healing.

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.

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

Critical-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.

Biomechanical models: key considerations in study design.

This manuscript summarizes presentations of a symposium on key considerations in design of biomechanical models at the 2019 Basic Science Focus Forum of the Orthopaedic Trauma Association. The first section outlines the most important characteristics of a high-quality biomechanical study. The second section considers choices associated with designing experiments using finite element modeling versus synthetic bones versus human specimens.

Age-Related Changes in the Mechanical Regulation of Bone Healing Are Explained by Altered Cellular Mechanoresponse.

Increasing age is associated with a reduced bone regeneration potential and increased risk of morbidities and mortality. A reduced bone formation response to mechanical loading has been shown with aging, and it remains unknown if the interplay between aging and mechanical stimuli during regeneration is similar to adaptation. We used a combined in vivo/in silico approach to investigate age-related alterations in the mechanical regulation of bone healing and identified the relative impact of altered cellular function on tissue patterns during the regenerative cascade.

Machine learning techniques for the optimization of joint replacements: 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.

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.