Scaffold Architecture and Properties for Osteoblasts Cell Culture: An Optimization Model and Application by Genetic Algo
- PDF / 653,384 Bytes
- 6 Pages / 612 x 792 pts (letter) Page_size
- 67 Downloads / 175 Views
Scaffold Architecture and Properties for Osteoblasts Cell Culture: An Optimization Model and Application by Genetic Algorithm Maraolina Domínguez-Díaz1,*, Marco Antonio Cruz-Chavez1 1 Centro de Investigación en Ingeniería y Ciencias Aplicadas, Universidad Autónoma del Estado de Morelos, Av. Universidad 1001, Cuernavaca, Morelos, 62209, MEXICO. * To whom correspondence should be addressed: [email protected] ABSTRACT In the developing of scaffolds for cell culture, a large number of architectures with different combinations of properties should be tested to determine the best. This can be costly in time, money and materials. In this paper we have proposed an optimization model that aims to maximize the growth of osteoblasts on polymeric scaffolds by regulating their properties and architecture. Based on the optimization model it was implemented a genetic algorithm to calculate the architecture and properties of the scaffolds. The fiber diameter, pore diameter, porosity, Young's modulus and contact angle of the scaffolds were calculated through four electrospinning parameters: voltage (kV), concentration (% w/v), flow rate (ml/h) and distance (cm). A fitness value was assigned to each scaffold and the highest one was chosen as the best condition for osteoblast growth. The preliminary results obtained by the Genetic Algorithm were consistent with the tendencies reported experimentally in other studies. Also, the methodology established here can be easily adapted to different types of polymers and cells. Finally, the optimization model can be applied not only by means of heuristic method, like a Genetic Algorithm, but also by exact methods.
INTRODUCTION The scaffold is a structure with an anisotropic architecture in the several micrometer range along the z-axis (mesh-like structures) that can serve as cell support for tissue engineering applications [1, 2]. The processing conditions generate different configurations of the scaffold, i.e. different architectures and properties, which in turn can affect the proliferation, differentiation and accommodation of the cells [3]. Therefore, the study of the relationship between the properties of the scaffolds and their effects on cells is very important. However, these studies present certain challenges: they usually cover only a short range of possibilities, the time to perform them is long, and the use of cells or tissues is expensive. Thus, the developing of methodologies for the optimization of resources used in these studies is necessary. The Combinatorial Optimization is one of the most active areas in discrete mathematics, which seeks to find the best possible configuration of a system with respect to a target set [4]. The combinatorial methodologies applied to material research have created the branch of Combinatorial Materials Science (CombiSci). The CombiSci can help to prove hypotheses about the relationship between the structure and the properties of the materials, in the accelerated development of new materials, and create large amounts of data and information of t
Data Loading...
