The locking compression plates (LCP) are efficient tools in open reduction and internal fixation (ORIF), especially in osteoporotic bones. Two important factors of screw density and screw position can affect the functionality of the bone plate. Several studies have assessed the influence of the screw configurations on the bone-plate stiffness, but the effects of screw positions on the interfragmentary strain, εIF of LCP construct have not been investigated yet. In this study, finite element method was used to investigate the influence of screws number and position on the interfragmentary strain of LCP-femur system for a mid-shaft fracture. Results of this study showed that by insertion of screws closer to the fracture site, εIF decreases by 2 nd degree polynomial function versus screw position, but by adding the screws from the ends of the plate, or by moving and placing the screws towards the fracture site, the reduction of εIF will be linear. Results of this study were compared and are in agreement with some studies in the literature, even though their scope was mostly stability of the bone-implant system, whereas our scope was focused on the interfragmentary strain.
To date, several studies have implied the importance of early stage mechanical stability in the bone fracture healing process. This study aimed at finding a correlation between the predicted different tissue phenotypes in the early stages of healing and the ultimate healing outcome. For this purpose, the process of fracture healing was numerically simulated employing an axisymmetric bi-phasic finite element (FE) model for three initial gap sizes of 1, 3 and 6[Formula: see text]mm and four initial interfragmentary strains (IFS) of 7%, 11%, 15% and 19%. The model was validated with experimental and other numerical studies from the literature. Results of this study showed that the amount of cartilage and fibrous tissue observed in the early stage after fracture can be used to qualitatively assess the outcome of complete bone healing process. Greater amount of cartilage in early stage of healing process yielded faster callus maturation, and delayed maturation of callus was predicted in the case of high fibrous tissue production. Results of this study can be used to provide an estimation of the performance of different fixation systems by considering the amounts of cartilage and fibrous tissues observed in the early stage of healing.
Agent-based modeling (ABM) has been extensively used to study the collective behavior of systems emerging from the interaction of numerous independent individuals called agents. Python and C++ are commonly used for ABM thanks to their unique features; the latter offers superior performance while the former provides ease-of-use and rich libraries in data science, visualization, and machine learning. We present the framework CppyABM that unifies these features by providing identical ABM semantic and development styles in both C++ and Python as well as the essential binding tools to expose a certain functionality from C++ to Python. The binding feature allows users to tailor and further extend a type or function within Python while it is originally defined in C++. Using CppyABM, users can choose either C++ or Python depending on their expertise and the specialty of the model or combine them to benefit from the advantages of both languages simultaneously. We provide showcases of CppyABM capabilities using several examples in computational biology, ecology, and virology. These examples are implemented in different formats using either C++ or Python or a combination of both to provide a comparison between the performance of implementation scenarios. The results of the example show a clear performance advantage of the models entirely or partly implemented in C++ compared to purely Python-based implementations.
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