Large bone defects represent a clinical challenge for which the implantation of scaffolds appears as a promising strategy. However, their use in clinical routine is limited, in part due to a lack of understanding of how scaffolds should be designed to support regeneration. Here, we use the power of computer modeling to investigate mechano-biological principles behind scaffold-guided bone regeneration and the influence of scaffold design on the regeneration process. Computer model predictions are compared to experimental data of large bone defect regeneration in sheep. We identified two main key players in scaffold-guided regeneration: (1) the scaffold surface guidance of cellular migration and tissue formation processes and (2) the stimulation of progenitor cell activity by the scaffold material composition. In addition, lower scaffold surface-area-to-volume ratio was found to be beneficial for bone regeneration due to enhanced cellular migration. To a lesser extent, a reduced scaffold Young's modulus favored bone formation. Statement of significance: 3D-printed scaffolds offer promising treatment strategies for large bone defects but their broader clinical use requires a more thorough understanding of their interaction with the bone regeneration process. The predictions of our in silico model compared to two experimental set-ups highlighted the importance of (1) the scaffold surface guidance of cellular migration and tissue formation processes and (2) the scaffold material stimulation of progenitor cell activity. In addition, the model was used to investigate the effect on the bone regeneration process of (1) the scaffold surface-area-to-volume ratio, with lower ratios favoring more bone growth, and (2) the scaffold material properties, with stiffer scaffold materials yielding a lower bone growth.

Our brain undergoes significant micro- and macroscopic changes throughout its life cycle. It is therefore crucial to understand the effect of aging on the mechanical properties of the brain in order to develop accurate personalized simulations and diagnostic tools. Here we systematically probed the mechanical behavior of n=439 brain tissue samples in tension and compression, in different anatomical regions, for different axon orientations, across five age groups. We used Bayesian statistics to characterize the relation between brain age and mechanical properties and quantify uncertainties. Our results, based on our experimental data and material parameters for the isotropic Ogden and the anisotropic Gasser-Ogden-Holzapfel models, reveal a non-linear relationship between age and mechanics across the life cycle of the porcine brain. Both tensile and compressive shear moduli reached peak values ranging from 0.4–1.0 kPa in tension to 0.16–0.32 kPa in compression at three years of age. Anisotropy was most pronounced at six months, and then decreased. These results represent an important step in understanding age-dependent changes in the mechanical properties of brain tissue and provide the scientific basis for more accurate and realistic computational brain simulations. Statement of significance: In this paper, we investigate the age-dependent mechanical properties of brain tissue based on different deformation modes, anatomical regions, and axon orientations. Hierarchical Bayesian modeling was used to identify isotropic and anisotropic material parameters. The study reveals a nonlinear relationship between shear modulus, degree of anisotropy, and tension-compression asymmetry over the life cycle of the brain. By demonstrating the non-linearity of these relationships, the study fills a significant knowledge gap in current research. This work is a fundamental step in accurately characterizing the complex relationship between brain aging and mechanical properties.

Bone fragility is a profound complication of type 1 diabetes mellitus (T1DM), increasing patient morbidity. Within the mineralized bone matrix, osteocytes build a mechanosensitive network that orchestrates bone remodeling; thus, osteocyte viability is crucial for maintaining bone homeostasis. In human cortical bone specimens from individuals with T1DM, we found signs of accelerated osteocyte apoptosis and local mineralization of osteocyte lacunae (micropetrosis) compared with samples from age-matched controls. Such morphological changes were seen in the relatively young osteonal bone matrix on the periosteal side, and micropetrosis coincided with microdamage accumulation, implying that T1DM drives local skeletal aging and thereby impairs the biomechanical competence of the bone tissue. The consequent dysfunction of the osteocyte network hampers bone remodeling and decreases bone repair mechanisms, potentially contributing to the enhanced fracture risk seen in individuals with T1DM. Statement of significance: Type 1 diabetes mellitus (T1DM) is a chronic autoimmune disease that causes hyperglycemia. Increased bone fragility is one of the complications associated with T1DM. Our latest study on T1DM-affected human cortical bone identified the viability of osteocytes, the primary bone cells, as a potentially critical factor in T1DM-bone disease. We linked T1DM with increased osteocyte apoptosis and local accumulation of mineralized lacunar spaces and microdamage. Such structural changes in bone tissue suggest that T1DM speeds up the adverse effects of aging, leading to the premature death of osteocytes and potentially contributing to diabetes-related bone fragility.

Bone adapts to changes in the local mechanical environment (e.g. strains) through formation and resorption processes. However, the bone adaptation response is significantly reduced with increasing age. The mechanical strains induced within the bone by external loading are determined by bone morphology and tissue material properties. Although it is known that changes in bone mass, architecture and bone tissue quality occur with age, to what extent they contribute to the altered bone adaptation response remains to be determined. This study investigated alterations in strains induced in the tibia of different aged female C57Bl/6J mice (young, 10-week-old; adult, 26-week-old; and elderly, 78-week-old) subjected to in vivo compressive loading. Using a combined in vivo/in silico approach, the strains in the bones were assessed by both strain gauging and finite element modeling experiments. In cortical bone, strain magnitudes induced at the mid-diaphysis decreased by 20% from young to adult mice and by 15% from adult to elderly mice. In the cancellous bone (at the proximal metaphysis), induced strains were 70% higher in young compared with adult and elderly mice. Taking into account previous studies showing a reduced bone adaptation response to mechanical loading in adulthood, these results suggest that the diminished adaptive response is in part due to a reduction in the strains induced within the bone.

Substantial tissue loss, such as in large bone defects, represents a clinical challenge for which regenerative therapies and tissue engineering strategies aim at offering treatment alternatives to conventional replacement approaches by metallic implants. 3D printing technologies provide endless opportunities to shape scaffold structures that could support endogenous regeneration. However, it remains unclear which of the numerous parameters at hand eventually enhance tissue regeneration. In the last decades, a significant effort has been made in the development of computer tools to optimize scaffold designs. Here, we aim at giving a more comprehensive overview summarizing current computer optimization framework technologies. We confront these with the most recent advances in scaffold mechano-biological optimization, discuss their limitations and provide suggestions for future development. We conclude that the field needs to move forward to not only optimize scaffolds to avoid implant failures but to improve their mechano-biological behaviour: providing an initial stimulus for fast tissue organisation and healing and accounting for remodelling, scaffold degradation and consecutive filling with host tissue. So far, modelling approaches fall short in including the various scales of tissue dynamics. With this review, we wish to stimulate a move towards multi-dynamic mechano-biological optimization of 3D-printed scaffolds. Statement of significance: Large bone defects represent a clinical challenge for which tissue engineering strategies aim at offering alternatives to conventional treatment strategies. 3D printing technologies provide endless opportunities to shape scaffold structures that could support endogenous regeneration. However, it remains unclear which of the numerous parameters at hand eventually enhance tissue regeneration. In the last decades, a significant effort has been made in the development of computer tools to optimize scaffold designs. This review summarizes current computer optimization frameworks and most recent advances in mechano-biological optimization of bone scaffolds to better stimulate bone regeneration. We wish to stimulate a move towards multi-dynamic mechano-biological optimization of 3D-printed scaffolds.