A mechanobiological computer optimization framework to design scaffolds to enhance bone regeneration

The Potential of Siraitia grosvenorii to Promote Bone Regeneration via Modulating Macrophage Polarization: A Network Pharmacology and Experimental Study

Siraitia grosvenorii (SG), a traditional Chinese medicinal herb, possesses immunomodulatory and osteoinductive properties, yet its pharmacological mechanisms in bone defect repair remain largely unexplored. This study investigates the therapeutic potential of SG through a combination of network pharmacology and experimental approaches. Active compounds were identified using the Traditional Chinese Medicine Systems Pharmacology (TCMSP) Platform, and protein interaction targets were predicted. Molecular docking and dynamics simulations assessed interactions between SG compounds and critical targets. In vitro, RAW 264.7 macrophages treated with SG-conditioned medium exhibited enhanced M2 polarization and reduced inflammation, promoting osteogenic differentiation of co-cultured MC3T3-E1 cells as evidenced by increased alkaline phosphatase activity. In vivo, scaffolds loaded with low-dose or high-dose SG (LSG/HSG) significantly improved bone regeneration in rat calvarial defects, with HSG achieving near-complete repair and mature trabeculae at 8 weeks, alongside decreased CD86 and TNF-α levels and increased IL-10 expression. Network pharmacology identified 33 shared targets related to bone regeneration and macrophage polarization, with kaempferol and beta-sitosterol demonstrating strong binding affinities to targets such as TNF, PTGS2, and CASP3. These findings highlight the potential of SG in enhancing bone defect repair and its implications for regenerative medicine.

Mechanobiological optimization of scaffolds for bone tissue engineering

Synthetic bone graft scaffolds aim to generate new bone tissue and alleviate the limitations of autografts and allografts. To meet that aim, it is essential to have a design approach able to generate scaffold architectures that will promote bone formation. Here, we present a topology-varying design optimization method, the "mixed-topology" approach, that generates new designs from a set of starting structures. This approach was used with objective functions focusing on improving the scaffold's local mechanical microenvironments to mechanobiologically promote bone formation within the scaffold and constraints to ensure manufacturability and achieve desired macroscale properties. The results demonstrate that this approach can successfully generate scaffold designs with improved microenvironments, taking into account different combinations of relevant stimuli and constraints.

An explainable machine learning-based probabilistic framework for the design of scaffolds in bone tissue engineering

Recently, 3D-printed biodegradable scaffolds have shown great potential for bone repair in critical-size fractures. The differentiation of the cells on a scaffold is impacted among other factors by the surface deformation of the scaffold due to mechanical loading and the wall shear stresses imposed by the interstitial fluid flow. These factors are in turn significantly affected by the material properties, the geometry of the scaffold, as well as the loading and flow conditions. In this work, a numerical framework is proposed to study the influence of these factors on the expected osteochondral cell differentiation. The considered scaffold is rectangular with a 0/90 lay-down pattern and a four-layered strut made of polylactic acid with a 5% steel particle content. The distribution of the different types of cells on the scaffold surface is estimated through a scalar stimulus, calculated by using a mechanobioregulatory model. To reduce the simulation time for the computation of the stimulus, a probabilistic machine learning (ML)-based reduced-order model (ROM) is proposed. Then, a sensitivity analysis is performed using the Shapley additive explanations to examine the contribution of the various parameters to the framework stimulus predictions. In a final step, a multiobjective optimization procedure is implemented using genetic algorithms and the ROM, aiming to identify the material parameters and loading conditions that maximize the percentage of surface area populated by bone cells while minimizing the area corresponding to the other types of cells and the resorption condition. The results of the performed analysis highlight the potential of using ROMs for the scaffold design, by dramatically reducing the simulation time while enabling the efficient implementation of sensitivity analysis and optimization procedures.

Finite element analysis of patient-specific additive-manufactured implants

Introduction: Bone tumors, characterized by diverse locations and shapes, often necessitate surgical excision followed by custom implant placement to facilitate targeted bone reconstruction. Leveraging additive manufacturing, patient-specific implants can be precisely tailored with complex geometries and desired stiffness, enhancing their suitability for bone ingrowth. Methods: In this work, a finite element model is employed to assess patient-specific lattice implants in femur bones. Our model is validated using experimental data obtained from an animal study (n = 9). Results: The results demonstrate the accuracy of the proposed finite element model in predicting the implant mechanical behavior. The model was used to investigate the influence of reducing the elastic modulus of a solid Ti6Al4V implant by tenfold, revealing that such a reduction had no significant impact on bone behavior under maximum compression and torsion loading. This finding suggests a potential avenue for reducing the endoprosthesis modulus without compromising bone integrity. Discussion: Our research suggests that employing fully lattice implants not only facilitates bone ingrowth but also has the potential to reduce overall implant stiffness. This reduction is crucial in preventing significant bone remodeling associated with stress shielding, a challenge often associated with the high stiffness of fully solid implants. The study highlights the mechanical benefits of utilizing lattice structures in implant design for enhanced patient outcomes.

Enhanced bone regeneration in rat calvarial defects through BMP2 release from engineered poly(ethylene glycol) hydrogels

The clinical standard therapy for large bone defects, typically addressed through autograft or allograft donor tissue, faces significant limitations. Tissue engineering offers a promising alternative strategy for the regeneration of substantial bone lesions. In this study, we harnessed poly(ethylene glycol) (PEG)-based hydrogels, optimizing critical parameters including stiffness, incorporation of arginine-glycine-aspartic acid (RGD) cell adhesion motifs, degradability, and the release of BMP2 to promote bone formation. In vitro we demonstrated that human bone marrow derived stromal cell (hBMSC) proliferation and spreading strongly correlates with hydrogel stiffness and adhesion to RGD peptide motifs. Moreover, the incorporation of the osteogenic growth factor BMP2 into the hydrogels enabled sustained release, effectively inducing bone regeneration in encapsulated progenitor cells. When used in vivo to treat calvarial defects in rats, we showed that hydrogels of low and intermediate stiffness optimally facilitated cell migration, proliferation, and differentiation promoting the efficient repair of bone defects. Our comprehensive in vitro and in vivo findings collectively suggest that the developed hydrogels hold significant promise for clinical translation for bone repair and regeneration by delivering sustained and controlled stimuli from active signaling molecules.

Geometric Mismatch Promotes Anatomic Repair in Periorbital Bony Defects in Skeletally Mature Yucatan Minipigs

Porous tissue-engineered 3D-printed scaffolds are a compelling alternative to autografts for the treatment of large periorbital bone defects. Matching the defect-specific geometry has long been considered an optimal strategy to restore pre-injury anatomy. However, studies in large animal models have revealed that biomaterial-induced bone formation largely occurs around the scaffold periphery. Such ectopic bone formation in the periorbital region can affect vision and cause disfigurement. To enhance anatomic reconstruction, geometric mismatches are introduced in the scaffolds used to treat full thickness zygomatic defects created bilaterally in adult Yucatan minipigs. 3D-printed, anatomically-mirrored scaffolds are used in combination with autologous stromal vascular fraction of cells (SVF) for treatment. An advanced image-registration workflow is developed to quantify the post-surgical geometric mismatch and correlate it with the spatial pattern of the regenerating bone. Osteoconductive bone growth on the dorsal and ventral aspect of the defect enhances scaffold integration with the native bone while medio-lateral bone growth leads to failure of the scaffolds to integrate. A strong positive correlation is found between geometric mismatch and orthotopic bone deposition at the defect site. The data suggest that strategic mismatch >20% could improve bone scaffold design to promote enhanced regeneration, osseointegration, and long-term scaffold survivability.