The effects of centrally acting ACE inhibitors on the rate of cognitive and functional decline in dementia: a KDD approach

Alzheimer’s Disease and other dementias are one of the most challenging illnesses confronting countries with ageing populations. Treatment options for dementia are limited, and the costs are significant. There is a growing need to develop new treatments for dementia, especially for the elderly. There is also growing evidence that centrally acting angiotensin converting enzyme (ACE) inhibitors, which cross the blood-brain barrier, are associated with a reduced rate of cognitive and functional decline in dementia, especially in Alzheimer’s disease (AD). The aim of this research is to investigate the effects of centrally acting ACE inhibitors (CACE-Is) on the rate of cognitive and functional decline in dementia, using a three phased KDD process. KDD, as a scientific way to process and analysis clinical data, is used to find useful insights from a variety of clinical databases. The data used are from three clinic databases: Geriatric Assessment Tool (GAT), the Doxycycline and Rifampin for Alzheimer’s Disease (DARAD), and the Qmci validation databases, which were derived from several different geriatric clinics in Canada. This research involves patients diagnosed with AD, vascular or mixed dementia only. Patients were included if baseline and end-point (at least six months apart) Standardised Mini-Mental State Examination (SMMSE), Quick Mild Cognitive Impairment (Qmci) or Activities Daily Living (ADL) scores were available. Basically, the rates of change are compared between patients taking CACE-Is, and those not currently treated with CACE-Is. The results suggest that there is a statistically significant difference in the rate of decline in cognitive and functional scores between CACE-I and NoCACE-I patients. This research also validates that the Qmci, a new short assessment test, has potential to replace the current popular screening tests for cognition in the clinic and clinical trials.

An investigation on the use of SNR distributions for the optimisation of coarse-fine spectrum sensing for cognitive radio

This thesis investigates the optimisation of Coarse-Fine (CF) spectrum sensing architectures under a distribution of SNRs for Dynamic Spectrum Access (DSA). Three different detector architectures are investigated: the Coarse-Sorting Fine Detector (CSFD), the Coarse-Deciding Fine Detector (CDFD) and the Hybrid Coarse-Fine Detector (HCFD). To date, the majority of the work on coarse-fine spectrum sensing for cognitive radio has focused on a single value for the SNR. This approach overlooks the key advantage that CF sensing has to offer, namely that high powered signals can be easily detected without extra signal processing. By considering a range of SNR values, the detector can be optimised more effectively and greater performance gains realised. This work considers the optimisation of CF spectrum sensing schemes where the security and performance are treated separately. Instead of optimising system performance at a single, constant, low SNR value, the system instead is optimised for the average operating conditions. The security is still provided such that at the low SNR values the safety specifications are met. By decoupling the security and performance, the system’s average performance increases whilst maintaining the protection of licensed users from harmful interference. The different architectures considered in this thesis are investigated in theory, simulation and physical implementation to provide a complete overview of the performance of each system. This thesis provides a method for estimating SNR distributions which is quick, accurate and relatively low cost. The CSFD is modelled and the characteristic equations are found for the CDFD scheme. The HCFD is introduced and optimisation schemes for all three architectures are proposed. Finally, using the Implementing Radio In Software (IRIS) test-bed to confirm simulation results, CF spectrum sensing is shown to be significantly quicker than naive methods, whilst still meeting the required interference probability rates and not requiring substantial receiver complexity increases.

Towards a cognitive neurobiology of brain-gut axis disorders

The past two decades have seen substantial gains in our understanding of the complex processes underlying disturbed brain-gut communication in disorders such as irritable bowel syndrome (IBS) and inflammatory bowel disease (IBD). Despite a growing understanding of the neurobiology of brain-gut axis dysfunction, there is a relative paucity of investigations into how the various factors involved in dysregulating the brain-gut axis, including stress, immune activation and pain, could impact on fundamental brain processes such as cognitive performance. To this end, we proposed a cognitive neurobiology of brain-gut axis dysfunction and took a novel approach to examine how disturbed brain-gut interactions may manifest as altered cognitive performance in IBS and IBD, both cross-sectionally and prospectively. We have demonstrated that, disorders of the brain-gut axis are characterised by stable deficits in specific cognitive domains. Specifically, patients with IBS exhibit a consistent hippocampal mediated visuospatial memory impairment. In addition we have found evidence to suggest a similar visuospatial impairment in IBD. However, our most consistent finding within this population was that patients with Crohn’s disease exhibit impaired selective attention/ response inhibition on the classic Stroop interference test. These cognitive deficits may serve to perpetuate and sustain brain-gut axis dysfunction. Furthermore, this research has shed light on some of the underlying neurobiological mechanisms that may be mediating cognitive dysfunction in IBS. Our findings may have significant implications for the individual who suffers from a brain-gut axis disorder and may also inform future treatment strategies. Taken together, these findings can be incorporated into existing neurobiological models of brain-gut axis dysfunction, to develop a more comprehensive model accounting for the cognitive-neurobiology of brain-gut axis disorders. This has furthered our understanding of disease pathophysiology and may ultimately aid in both the diagnosis and treatment of these highly prevalent, but poorly understood disorders.