Delay of intracortical bone remodelling following a stress change: a theoretical and experimental study

Characterization of mechanical and biological properties of 3-D scaffolds reinforced with zinc oxide for bone tissue engineering

A scaffold for bone tissue engineering should have highly interconnected porous structure, appropriate mechanical and biological properties. In this work, we fabricated well-interconnected porous β-tricalcium phosphate (β-TCP) scaffolds via selective laser sintering (SLS). We found that the mechanical and biological properties of the scaffolds were improved by doping of zinc oxide (ZnO). Our data showed that the fracture toughness increased from 1.09 to 1.40 MPam(1/2), and the compressive strength increased from 3.01 to 17.89 MPa when the content of ZnO increased from 0 to 2.5 wt%. It is hypothesized that the increase of ZnO would lead to a reduction in grain size and an increase in density of the strut. However, the fracture toughness and compressive strength decreased with further increasing of ZnO content, which may be due to the sharp increase in grain size. The biocompatibility of the scaffolds was investigated by analyzing the adhesion and the morphology of human osteoblast-like MG-63 cells cultured on the surfaces of the scaffolds. The scaffolds exhibited better and better ability to support cell attachment and proliferation when the content of ZnO increased from 0 to 2.5 wt%. Moreover, a bone like apatite layer formed on the surfaces of the scaffolds after incubation in simulated body fluid (SBF), indicating an ability of osteoinduction and osteoconduction. In summary, interconnected porous β-TCP scaffolds doped with ZnO were successfully fabricated and revealed good mechanical and biological properties, which may be used for bone repair and replacement potentially.

Prediction of bone density around orthopedic implants delivering bisphosphonate

The fixation of an orthopedic implant depends strongly upon its initial stability. Peri-implant bone may resorb shortly after the surgery. This resorption is directly followed by new bone formation and implants fixation strengthening, the so-called secondary fixation. If the initial stability is not reached, the resorption continues and the implant fixation weakens, which leads to implant loosening. Studies with rats and dogs have shown that a solution to prevent peri-implant resorption is to deliver bisphosphonate from the implant surface. The aims of the study were, first, to develop a model of bone remodeling around an implant delivering bisphosphonate, second, to predict the bisphosphonate dose that would induce the maximal peri-implant bone density, and third to verify in vivo that peri-implant bone density is maximal with the calculated dose. The model consists of a bone remodeling equation and a drug diffusion equation. The change in bone density is driven by a mechanical stimulus and a drug stimulus. The drug stimulus function and the other numerical parameters were identified from experimental data. The model predicted that a dose of 0.3 microg of zoledronate on the implant would induce a maximal bone density. Implants with 0.3 microg of zoledronate were then implanted in rat femurs for 3, 6 and 9 weeks. We measured that peri-implant bone density was 4% greater with the calculated dose compared to the dose empirically described as best. The approach presented in this paper could be used in the design and analysis processes of experiments in local delivery of drug such as bisphosphonate.

In silico evolution of functional morphology: A test on bone tissue biomechanics

Evolutionary algorithms (EAs) use Darwinian principles--selection among random variation and heredity--to find solutions to complex problems. Mostly used in engineering, EAs gain growing interest in ecology and genetics. Here, we assess their usefulness in functional morphology, introducing finite element modelling (FEM) as a simulated mechanical environment for evaluating the 'fitness' of randomly varying structures. We used this method to identify biomechanical adaptations in bone tissue, a long-lasting problem in skeletal morphology. The algorithm started with a bone tissue model containing randomly distributed vascular spaces. The EA randomly mutated the distribution of vascular spaces, and selected the new structure if its mechanical resistance was increased. After some thousands of generations, organized phenotypes emerged, containing vascular canals and sinuses, mimicking real bone tissue organizations. This supported the hypothesis that natural bone microstructures can result from biomechanical adaptation. Despite its limited faithfulness to reality, we discuss the ability of the EA+FEM method to assess adaptation in a dynamic evolutionary framework, which is not possible in the real world because of the generation times of macro-organisms. We also point out the interesting potential of EAs to simulate not only adaptation, but also concurrent evolutionary phenomenons such as historical contingency.