A role for glutathione in the pathophysiology of bipolar disorder and schizophrenia? Animal models and relevance to clinical practice.

The tripeptide, glutathione (glutamylcysteinylglycine) is the primary endogenous free radical scavenger in the human body. When glutathione (GSH) levels are reduced there is an increased potential for cellular oxidative stress, characterised by an increase and accruement of reactive oxygen species (ROS). Oxidative stress has been implicated in the pathology of schizophrenia and bipolar disorder. This could partly be caused by alterations in dopaminergic and glutamatergic activity that are implicated in these illnesses. Glutamate and dopamine are highly redox reactive molecules and produce ROS during normal neurotransmission. Alterations to these neurotransmitter pathways may therefore increase the oxidative burden in the brain. Furthermore, mitochondrial dysfunction, as a source of oxidative stress, has been documented in both schizophrenia and bipolar disorder. The combination of altered neurotransmission and this mitochondrial dysfunction leading to oxidative damage may ultimately contribute to illness symptoms. Animal models have been established to investigate the involvement of glutathione depletion in aspects of schizophrenia and bipolar disorder to further characterise the role of oxidative stress in psychopathology. Stemming from preclinical evidence, clinical studies have recently shown antioxidant precursor treatment to be effective in schizophrenia and bipolar disorder, providing a novel clinical angle to augment often suboptimal conventional treatments.

Empirical investigation of critical success factors for implementing business intelligence systems in multiple engineering asset management organisations

Engineering asset management organisations (EAMOs) are increasingly motivated to implement business intelligence (BI) systems in response to dispersed information environments and compliance requirements. However, the implementation of a business intelligence (BI) system is a complex undertaking requiring considerable resources. Yet, so far, there are few defined critical success factors (CSFs) to which management can refer. Drawing on the CSFs framework derived from a previous Delphi study, a multiple-case design was used to examine how these CSFs could be implemented by five EAMOs. The case studies substantiate the construct and applicability of the CSFs framework. These CSFs are: committed management support and sponsorship, a clear vision and well-established business case, business-centric championship and balanced team composition, a business-driven and iterative develop ment approach, user-oriented change management, a business-driven, scalable and flexible technical framework, and sustainable data quality and integrity. More significantly, the study further reveals that those organisations which address the CSFs from a business orientation approach will be more likely to achieve better results.

Business intelligence systems implementation : testing a critical success factors framework in multiple cases

This paper presents and discusses the critical success factors (CSFs) influencing the implementation of business intelligence (BI) systems. Based on a preliminary critical success factors (CSFs) framework, multiple case studies approach was applied to investigate the CSFs influencing BI systems implementation in seven large engineering enterprises. The empirical findings demonstrate a clear trend towards multidimensional challenges involved in such resourceful and complex undertaking. The CSFs exist in various dimensions composed of organisation, process, and technology perspectives. More significantly, the study reveals that a more fundamental issue concerning the business needs of BI systems may, in the end, impede BI systems success. That is, BI stakeholders are urged to apply a business-orientation approach in tackling implementation challenges and ensuring buy-in from business stakeholders.

A SOA-driven business intelligence architecture

A business intelligence architecture comprises of different unique components to collect, transform, analyze and present the structured and unstructured raw data in simple formats to assist decision makers in making timely decisions. The introduction of service-oriented architecture (SOA) enables reusable services which are accessible over a network on demand. However, there is still a lack of academic literatures on the business intelligence architecture with service-oriented concept. Based upon various references on BI architectures from major vendors, a novel BI architecture that is built on service-oriented concept is presented and described in this paper. The proposed service-oriented architecture enables enterprises to deploy a more agile, flexible, cheaper, reusable, reliable and responsive BI applications in supporting decision making process.

A maturity model of enterprise business intelligence

The implementation of an enterprise-level business intelligence initiative is a large-scale and complex undertaking, involving significant expenditure and multiple stakeholders over a lengthy period. It is therefore imperative to have systematic guidelines for business intelligence stakeholders in referring business intelligence maturity levels. Draw upon the prudent concepts of the Capability Maturity Model, this research proposes a multi-dimensional maturity model with distinct maturity levels for managing enterprise business intelligence initiatives. The maturity model, named Enterprise Business Intelligence Maturiy (EBIM), consists of five core maturity levels and four key dimensions, namely information quality, master data management, warehousing architecture, and analytics. It can be used to assist enterprises in benchmarking their business intelligence maturity level and identifying the critical areas to attain higher level of maturity.