Organisational challenges in understanding and implementing effective buiness continuity management strategies in a complex and critical organisation : an airport case study

With the increasing complexity of modern day threats and the growing sophistication of interlinked and interdependent operating environments, Business Continuity Management (BCM) has emerged as a new discipline, offering a strategic approach to safeguarding organisational functions. Of significant interest is the application of BCM frameworks and strategies within critical infrastructure, and in particular the aviation industry. Given the increased focus on security and safety for critical infrastructures, research into the adoption of BCM principles within an airport environment provides valuable management outcomes and research into a previously neglected area of inquisition. This research has used a single case study methodology to identify possible impediments to BCM adoption and implementation by the Brisbane Airport Corporation (BAC). It has identified a number of misalignments between the required breadth of focus for a BCM program, identified differing views on specific roles and responsibilities required during a major disruptive event and illustrated the complexities of the Brisbane Airport which impede the understanding and implementation of effective Business Continuity Management Strategies.

Candidate metastasis suppressor genes uncovered by array comparative genomic hybridization in a mouse allograft model of prostate cancer.

Background The purpose of this study was to identify candidate metastasis suppressor genes from a mouse allograft model of prostate cancer (NE-10). This allograft model originally developed metastases by twelve weeks after implantation in male athymic nude mice, but lost the ability to metastasize after a number of in vivo passages. We performed high resolution array comparative genomic hybridization on the metastasizing and non-metastasizing allografts to identify chromosome imbalances that differed between the two groups of tumors. Results This analysis uncovered a deletion on chromosome 2 that differed between the metastasizing and non-metastasizing tumors. Bioinformatics filters were employed to mine this region of the genome for candidate metastasis suppressor genes. Of the 146 known genes that reside within the region of interest on mouse chromosome 2, four candidate metastasis suppressor genes (Slc27a2, Mall, Snrpb, and Rassf2) were identified. Quantitative expression analysis confirmed decreased expression of these genes in the metastasizing compared to non-metastasizing tumors. Conclusion This study presents combined genomics and bioinformatics approaches for identifying potential metastasis suppressor genes. The genes identified here are candidates for further studies to determine their functional role in inhibiting metastases in the NE-10 allograft model and human prostate cancer.