Abstract
Diagnosis and management of bone and joint infections (BJI) is a challenging task. The high intra and inter patient’s variability in terms of clinical presentation makes it impossible to rely on a systematic description or classical statistical analysis for its diagnosis. Advances can be achieved through a better understanding of the system behavior that results from the interactions between the components at a micro-scale level, which is difficult to mastered using traditional methods. Multiple studies from the literature report factors and interactions that affect the dynamics of the BJI system. The objectives of this study were (i) to perform a systematic review to identify relevant interactions between agents (cells, pathogens) and parameters values that characterize agents and interactions, and (ii) to develop a two dimensional computational model of the BJI system based on the results of the systematic review. The model would simulate the behavior resulting from the interactions on the cellular and molecular levels to explore the BJI dynamics, using an agent-based modeling approach. The BJI system’s response to different microbial inoculum levels was simulated. The model succeeded in mimicking the dynamics of bacteria, the innate immune cells, and the bone mass during the first stage of infection and for different inoculum levels in a consistent manner. The simulation displayed the destruction in bone tissue as a result of the alteration in bone remodeling process during the infection. The model was used to generate different patterns of system behaviors that could be analyzed in further steps. Simulations results suggested evidence for the existence of latent infections. Finally, we presented a way to analyze and synthesize massive simulated data in a concise and comprehensive manner based on the semi-supervised identification of ordinary differential equations (ODE) systems. It allows to use the known framework for temporal and structural ODE analyses and therefore summarize the whole simulated system dynamical behavior. This first model is intended to be validated by in vivo or in vitro data and expected to generate hypotheses to be challenged by real data. Step by step, it can be modified and complexified based on the test/validation iteration cycles.
Highlights
Bone and joint infections (BJI) are challenging pathologies that seriously affect public health, by means of irreversible bone loss, functional impairment and reduced quality of life (Stengel et al, 2001)
We developed a two-dimensional agent-based model of bone and joint infections (BJI) that introduces a plausible representation of the system and a simulated experimental environment to reproduce the infection and examine its dynamics as a result of cellular interactions
Concerning the investigated bacteria, we studied here in this first model S. aureus in general, which is the major bacteria in BJI, notably because it expresses different strategies of persistence such as producing biofilm or hiding intracellularly, and for that it is mainly involved in relapsing infections
Summary
Bone and joint infections (BJI) are challenging pathologies that seriously affect public health, by means of irreversible bone loss, functional impairment and reduced quality of life (Stengel et al, 2001). The incidence of BJI is increasing annually in the developed countries due to several reasons such as the rise in arthroplasties, and diabetes (Kurtz et al, 2011; Walter et al, 2012). In 2013, 70 cases per 100,000 of the population were reported as BJI related in France, compared to 54 cases in 2008, along with higher readmission frequency and longer hospital stays. In the USA, Olmsted County, the BJI incidence increased from 11.4 cases per 100,000 of population per year in the period from 1969 to 1979 to 24.4 per year in the period from 2000 to 2009 (Kremers et al, 2015). BJI are a significant cause of higher healthcare costs each year. The higher cost is due to prolonged and repeated hospitalizations supplemented by complex and long-term treatments, in addition to the need for surgical intervention (Gentry, 1997; Lipsky et al, 2007)
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