In vitro osteogenic cell proliferation, mineralization, and in vivo osseointegration of injection molded high-density polyethylene-based hybrid composites in rabbit animal model

The present work reports the biocompatibility property of injection molded HDPE-HA-Al2O3 hybrid composites. In vitro cytocompatibility results reveal that osteogenic cell viability and bone mineralization are favorably supported in a statistically significant manner on HDPE-20% HA-20% Al2O3 composite, in comparison to HDPE-40 wt.% HA or HDPE-40 wt.% Al2O3. The difference in cytocompatibility property is explained in terms of difference in substrate wettability/surface energy and importantly, both the cell proliferation at 7 days or bone mineralization at 21 days on HDPE-20% HA-20% Al2O3 composite are either comparable or better than sintered HA. The progressive healing of cylindrical femoral bone defects in rabbit animal model was assessed by implantation experiments over 1, 4 and 12 weeks. Based on the histological analysis as well as histomorphometrical evaluation, a better efficacy of HDPE-20% HA-20% Al2O3 over high-density polyethylene (HDPE) for bone regeneration and neobone formation at host bone-implant interface was established. Taken together, the present study unequivocally establishes that despite the presence of 20% Al2O3, HDPE-based hybrid composites are as biocompatible as HA in vitro or better than HDPE in vivo.

Optimal control analysis of the dynamic growth behavior of microorganisms

Understanding the growth behavior of microorganisms using modeling and optimization techniques is an active area of research in the fields of biochemical engineering and systems biology. In this paper, we propose a general modeling framework, based on Monad model, to model the growth of microorganisms. Utilizing the general framework, we formulate an optimal control problem with the objective of maximizing a long-term cellular goal and solve it analytically under various constraints for the growth of microorganisms in a two substrate batch environment. We investigate the relation between long term and short term cellular goals and show that the objective of maximizing cellular concentration at a fixed final time is equivalent to maximization of instantaneous growth rate. We then establish the mathematical connection between the generalized framework and optimal and cybernetic modeling frameworks and derive generalized governing dynamic equations for optimal and cybernetic models. We finally illustrate the influence of various constraints in the cybernetic modeling framework on the optimal growth behavior of microorganisms by solving several dynamic optimization problems using genetic algorithms. (C) 2014 Published by Elsevier Inc.