Maarten Moesen

The effect of pore geometry on the in vitro biological behavior of human periosteum-derived cells seeded on selective laser-melted Ti6Al4V bone scaffolds

The specific aim of this study was to gain insight into the influence of scaffold pore size, pore shape and permeability on the in vitro proliferation and differentiation of three-dimensional (3-D) human periosteum-derived cell (hPDC) cultures. Selective laser melting (SLM) was used to produce six distinct designed geometries of Ti6Al4V scaffolds in three different pore shapes (triangular, hexagonal and rectangular) and two different pore sizes (500 μm and 1000 μm). All scaffolds were characterized by means of two-dimensional optical microscopy, 3-D microfocus X-ray computed tomography (micro-CT) image analysis, mechanical compression testing and computational fluid dynamical analysis. The results showed that SLM was capable of producing Ti6Al4V scaffolds with a broad range of morphological and mechanical properties. The in vitro study showed that scaffolds with a lower permeability gave rise to a significantly higher number of cells attached to the scaffolds after seeding. Qualitative analysis by means of live/dead staining and scanning electron micrography showed a circular cell growth pattern which was independent of the pore size and shape. This resulted in pore occlusion which was found to be the highest on scaffolds with 500 μm hexagonal pores. Interestingly, pore size but not pore shape was found to significantly influence the growth of hPDC on the scaffolds, whereas the differentiation of hPDC was dependent on both pore shape and pore size. The results showed that, for SLM-produced Ti6Al4V scaffolds with specific morphological and mechanical properties, a functional graded scaffold will contribute to enhanced cell seeding and at the same time can maintain nutrient transport throughout the whole scaffold during in vitro culturing by avoiding pore occlusion.

Characterization and Optimization of Cell Seeding in Scaffolds by Factorial Design: Quality by Design Approach for Skeletal Tissue Engineering

Cell seeding into scaffolds plays a crucial role in the development of efficient bone tissue engineering constructs. Hence, it becomes imperative to identify the key factors that quantitatively predict reproducible and efficient seeding protocols. In this study, the optimization of a cell seeding process was investigated using design of experiments (DOE) statistical methods. Five seeding factors (cell type, scaffold type, seeding volume, seeding density, and seeding time) were selected and investigated by means of two response parameters, critically related to the cell seeding process: cell seeding efficiency (CSE) and cell-specific viability (CSV). In addition, cell spatial distribution (CSD) was analyzed by Live/Dead staining assays. Analysis identified a number of statistically significant main factor effects and interactions. Among the five seeding factors, only seeding volume and seeding time significantly affected CSE and CSV. Also, cell and scaffold type were involved in the interactions with other seeding factors. Within the investigated ranges, optimal conditions in terms of CSV and CSD were obtained when seeding cells in a regular scaffold with an excess of medium. The results of this case study contribute to a better understanding and definition of optimal process parameters for cell seeding. A DOE strategy can identify and optimize critical process variables to reduce the variability and assists in determining which variables should be carefully controlled during good manufacturing practice production to enable a clinically relevant implant.

Enhancement of osteogenic gene expression for the differentiation of human periosteal derived cells

The osteogenic differentiation of progenitor populations allows analysis of cell functionality as well as creating a platform for investigating stem cells for bone tissue engineering. Protocols used for osteogenic differentiation of progenitor cells are often identical to those detailed for bone marrow mesenchymal stem cells, however this may be flawed due to cell populations residing in different niches and being in distinct stages of differentiation. We herein describe the individual and combined effects of known osteo-inductive agents; dexamethasone (Dex), 1,25-dihydroxyvitamin D3 (VitD3), all trans-retinoic acid (atRA), cyclic AMP (cAMP) and bone morphogenic protein 2 (BMP2) in combination with fetal bovine serum (FBS) on osteogenesis of human periosteal derived cells (hPDCs). The addition of Dex&FBS was essential for the transition of hPDCs to an ALP positive cell population. Subsequently, atRA, Dex&FBS and BMP2 were required for the expression of transcription factors governing osteogenesis and hence differentiation towards a mature osteoblast. It is also hypothesized that Dex has no direct effect on the differentiation of hPDCs, instead its effect is to augment differentiation in combination with other factors. These data provide a comprehensive assessment of known osteogenic factors, in a novel multiplex system, to evaluate their effect on progenitor cell differentiation.

Robust beam compensation for laser-based additive manufacturing

Abstract Today’s software for laser-based additive manufacturing compensates for the finite dimensions of the laser spot by insetting the contours of a solid part. However, features having smaller dimensions are removed by this operation, which may significantly alter the structure of thin-walled parts. To avoid potential production errors, this work describes in detail an algorithmic framework that makes beam compensation more reliable by computing laser scan paths for thin features. The geometry of the features can be adjusted by the scan paths by means of five intuitive parameters, which are illustrated with examples. Benchmarks show that the scan path generation comes at a reasonable cost without altering the computational complexity of the overall beam compensation framework. The framework was applied to Selective Laser Melting (SLM) to demonstrate that it can significantly improve the robustness of additive manufacturing. Besides robustness, the framework is expected to allow further improvements to the accuracy of additive manufacturing by enabling a geometry-dependent determination of the laser parameters.

Finite element modelling of SMA textiles: superelastic behaviour

The paper describes guidelines for building a finite element model of a unit cell of a textile made of superelastic NiTi wires and illustrates the application of the model for woven and knitted textiles. The goal of the analysis is prediction of the tensile diagram of the textile based on the fabric structure and the superelastic tensile diagram of the wires. The differences between the superelastic behaviour of the fabrics and that of individual wires are discussed. Predictions for a knitted NiTi fabric are compared with experimental data.