Manufacturing conditioned roughness and wear of biomedical oxide ceramics for all-ceramic knee implants

Background: Ceramic materials are used in a growing proportion of hip joint prostheses due to their wear resistance and biocompatibility properties. However, ceramics have not been applied successfully in total knee joint endoprostheses to date. One reason for this is that with strict surface quality requirements, there are significant challenges with regard to machining. High-toughness bioceramics can only be machined by grinding and polishing processes. The aim of this study was to develop an automated process chain for the manufacturing of an all-ceramic knee implant. Methods: A five-axis machining process was developed for all-ceramic implant components. These components were used in an investigation of the influence of surface conformity on wear behavior under simplified knee joint motion. Results: The implant components showed considerably reduced wear compared to conventional material combinations. Contact area resulting from a variety of component surface shapes, with a variety of levels of surface conformity, greatly influenced wear rate. Conclusions: It is possible to realize an all-ceramic knee endoprosthesis device, with a precise and affordable manufacturing process. The shape accuracy of the component surfaces, as specified by the design and achieved during the manufacturing process, has a substantial influence on the wear behavior of the prosthesis. This result, if corroborated by results with a greater sample size, is likely to influence the design parameters of such devices.

EMMA 2--a MAGE-compliant system for the collaborative analysis and integration of microarray data

Background: Understanding transcriptional regulation by genome-wide microarray studies can contribute to unravel complex relationships between genes. Attempts to standardize the annotation of microarray data include the Minimum Information About a Microarray Experiment (MIAME) recommendations, the MAGE-ML format for data interchange, and the use of controlled vocabularies or ontologies. The existing software systems for microarray data analysis implement the mentioned standards only partially and are often hard to use and extend. Integration of genomic annotation data and other sources of external knowledge using open standards is therefore a key requirement for future integrated analysis systems. Results: The EMMA 2 software has been designed to resolve shortcomings with respect to full MAGE-ML and ontology support and makes use of modern data integration techniques. We present a software system that features comprehensive data analysis functions for spotted arrays, and for the most common synthesized oligo arrays such as Agilent, Affymetrix and NimbleGen. The system is based on the full MAGE object model. Analysis functionality is based on R and Bioconductor packages and can make use of a compute cluster for distributed services. Conclusion: Our model-driven approach for automatically implementing a full MAGE object model provides high flexibility and compatibility. Data integration via SOAP-based web-services is advantageous in a distributed client-server environment as the collaborative analysis of microarray data is gaining more and more relevance in international research consortia. The adequacy of the EMMA 2 software design and implementation has been proven by its application in many distributed functional genomics projects. Its scalability makes the current architecture suited for extensions towards future transcriptomics methods based on high-throughput sequencing approaches which have much higher computational requirements than microarrays.