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.

The effects of formulation and processing on surface characteristics and functional properties of dairy powders

The objectives of this thesis were to (i) study the effect of increasing protein concentration in milk protein concentrate (MPC) powders on surface composition and sorption properties; (ii) examine the effect of increasing protein content on the rehydration properties of MPC; (iii) study the physicochemical properties of spraydried emulsion-containing powders having different water and oil contents; (iv) analyse the effect of protein type on water sorption and diffusivity properties in a protein/lactose dispersion, and; (v) characterise lactose crystallisation and emulsion stability of model infant formula containing intact or hydrolysed whey proteins. Surface composition of MPC powders (protein contents 35 - 86 g / 100 g) indicated that fat and protein were preferentially located on the surface of powders. Low protein powder (35 g / 100 g) exhibited lactose crystallisation, whereas powders with higher protein contents did not, due to their high protein: lactose ratio. Insolubility was evident in high protein MPCs and was primarily related to insolubility of the casein fraction. High temperature (50 °C) was required for dissolution of high protein MPCs (protein content > 60 g / 100 g). The effect of different oil types and spray-drying outlet temperature on the physicochemical properties of the resultant fat-filled powders was investigated and showed that increasing outlet temperature reduced water content, water activity and tapped bulk density, irrespective of oil type, and increased solvent-extractable free fat for all oil types and onset of glass transition (Tg) and crystallisation (Tcr) temperature. Powder dispersions of protein/lactose (0.21:1), containing either intact or hydrolysed whey protein (12 % degree of hydrolysis; DH), were spray-dried at pilot scale. Moisture sorption analysis at 25 °C showed that dispersions containing intact whey protein exhibited lactose crystallisation at a lower relative humidity (RH). Dispersions containing hydrolysed whey protein had significantly higher (P < 0.05) water diffusivity. Finally, a spray-dried model infant formula was produced containing hydrolysed or intact whey as the protein with sunflower oil as the fat source. Reconstituted, hydrolysed formula had a significantly (P < 0.05) higher fat globule size and lower emulsion stability than intact formula. Lactose crystallisation in powders occurred at higher RH for hydrolysed formula. In conclusion, this research has shown the effect of altering the protein type, protein composition, and oil type on the surface composition and physical properties of different dairy powders, and how these variations greatly affect their rehydration characteristics and storage stability.

Content-aware compression for big textual data analysis

A substantial amount of information on the Internet is present in the form of text. The value of this semi-structured and unstructured data has been widely acknowledged, with consequent scientific and commercial exploitation. The ever-increasing data production, however, pushes data analytic platforms to their limit. This thesis proposes techniques for more efficient textual big data analysis suitable for the Hadoop analytic platform. This research explores the direct processing of compressed textual data. The focus is on developing novel compression methods with a number of desirable properties to support text-based big data analysis in distributed environments. The novel contributions of this work include the following. Firstly, a Content-aware Partial Compression (CaPC) scheme is developed. CaPC makes a distinction between informational and functional content in which only the informational content is compressed. Thus, the compressed data is made transparent to existing software libraries which often rely on functional content to work. Secondly, a context-free bit-oriented compression scheme (Approximated Huffman Compression) based on the Huffman algorithm is developed. This uses a hybrid data structure that allows pattern searching in compressed data in linear time. Thirdly, several modern compression schemes have been extended so that the compressed data can be safely split with respect to logical data records in distributed file systems. Furthermore, an innovative two layer compression architecture is used, in which each compression layer is appropriate for the corresponding stage of data processing. Peripheral libraries are developed that seamlessly link the proposed compression schemes to existing analytic platforms and computational frameworks, and also make the use of the compressed data transparent to developers. The compression schemes have been evaluated for a number of standard MapReduce analysis tasks using a collection of real-world datasets. In comparison with existing solutions, they have shown substantial improvement in performance and significant reduction in system resource requirements.