Mesoporous bioactive glasses as drug delivery and bone tissue regeneration platforms

The use of mesoporous bioactive glasses (MBG) for drug delivery and bone tissue regeneration has grown significantly over the past 5 years. In this review, we highlight the recent advances made in the preparation of MBG particles, spheres, fibers and scaffolds. The advantages of MBG for drug delivery and bone scaffold applications are related to this material’s well-ordered mesopore channel structure, superior bioactivity, and the application for the delivery of both hydrophilic and hydrophobic drugs. A brief forward-looking perspective on the potential clinical applications of MBG in regenerative medicine is also discussed.

Effect of modular neck variation on bone and cement mantle mechanics around a total hip arthroplasty stem

Background Total hip arthroplasty carried out using cemented modular-neck implants provides the surgeon with greater intra-operative flexibility and allows more controlled stem positioning. Methods In this study, finite element models of a whole femur implanted with either the Exeter or with a new cemented modular-neck total hip arthroplasty (separate, neck and stem components) were developed. The changes in bone and cement mantle stress/strain were assessed for varying amounts of neck offset and version angle for the modular-neck device for two simulated physiological load cases: walking and stair climbing. Since the Exeter is the gold standard for polished cemented total hip arthroplasty stem design, bone and cement mantle stresses/strains in the modular-neck finite element models were compared with finite element results for the Exeter. Findings For the two physiological load cases, stresses and strains in the bone and cement mantle were similar for all modular-neck geometries. These results were comparable to the bone and cement mechanics surrounding the Exeter. These findings suggest that the Exeter and the modular neck device distribute stress to the surrounding bone and cement in a similar manner. Interpretation It is anticipated that the modular-neck device will have a similar short-term clinical performance to that of the Exeter, with the additional advantages of increased modularity.

Bayesian methodology for genetics of complex diseases

Genetic research of complex diseases is a challenging, but exciting, area of research. The early development of the research was limited, however, until the completion of the Human Genome and HapMap projects, along with the reduction in the cost of genotyping, which paves the way for understanding the genetic composition of complex diseases. In this thesis, we focus on the statistical methods for two aspects of genetic research: phenotype definition for diseases with complex etiology and methods for identifying potentially associated Single Nucleotide Polymorphisms (SNPs) and SNP-SNP interactions. With regard to phenotype definition for diseases with complex etiology, we firstly investigated the effects of different statistical phenotyping approaches on the subsequent analysis. In light of the findings, and the difficulties in validating the estimated phenotype, we proposed two different methods for reconciling phenotypes of different models using Bayesian model averaging as a coherent mechanism for accounting for model uncertainty. In the second part of the thesis, the focus is turned to the methods for identifying associated SNPs and SNP interactions. We review the use of Bayesian logistic regression with variable selection for SNP identification and extended the model for detecting the interaction effects for population based case-control studies. In this part of study, we also develop a machine learning algorithm to cope with the large scale data analysis, namely modified Logic Regression with Genetic Program (MLR-GEP), which is then compared with the Bayesian model, Random Forests and other variants of logic regression.