The spatial patterns of beta-amyloid deposits and neurofibrillary tangles in the cerebral cortex in Alzheimer's disease

In Alzheimer's disease (AD) brain, beta-amyloid (Abeta) deposits and neurofibrillary tangles (NFT) are not randomly distributed but exhibit a spatial pattern, i.e., a departure from randomness towards regularity or clustering. Studies of the spatial pattern of a lesion may contribute to an understanding of its pathogenesis and therefore, of AD itself. This article describes the statistical methods most commonly used to detect the spatial patterns of brain lesions and the types of spatial patterns exhibited by ß-amyloid deposits and NFT in the cerebral cortex in AD. These studies suggest that within the cerebral cortex, Abeta deposits and NFT exhibit a similar spatial pattern, i.e., an aggregation of individual lesions into clusters which are regularly distributed parallel to the pia mater. The location, size and distribution of these clusters supports the hypothesis that AD is a 'disconnection syndrome' in which degeneration of specific cortical pathways results in the formation of clusters of NFT and Abeta deposits. In addition, a model to explain the development of the pathology within the cerebral cortex is proposed.

Measuring the degree of spatial correlation between pathological lesions in Alzheimer's disease

The pathological lesions characteristic of Alzheimer's disease (AD), viz., senile plaques (SP) and neurofibrillary tangles (NFT) may not be randomly distributed with reference to each other but exhibit a degree of sptial association or correlation, information on the degree of association between SP and NFT or between the lesions and normal histological features, such as neuronal perikarya and blood vessels, may be valuable in elucidating the pathogenesis of AD. This article reviews the statistical methods available for studying the degree of spatial association in histological sections of AD tissue. These include tests of interspecific association between two or more histological features using chi-square contingency tables, measurement of 'complete' and 'absolute' association, and more complex methods that use grids of contiguous samples. In addition, analyses of association using correlation matrices and stepwise multiple regression methods are described. The advantages and limitations of each method are reviewed and possible future developments discussed.

Analysis of population dispersion in histological sections

Stereology and other image analysis methods have enabled rapid and objective quantitative measurements to be made on histological sections. These mesurements may include total volumes, surfaces, lengths and numbers of cells and blood vessels or pathological lesions. Histological features, however, may not be randomly distributed across a section but exhibit 'dispersion', a departure from randomness either towards regularity or aggregation. Information of population dispersion may be valuable not only in understanding the two-or three-dimensional structure but also in elucidating the pathogenesis of lesions in pathological conditions. This article reviews some of the statistical methods available for studying dispersion. These range from simple tests of whether the distribution of a histological faeture departs significantly from random to more complex methods which can detect the intensity of aggregation and the sizes, distribution and spacing of the clusters.

The usefulness of spatial pattern analysis in understanding the pathogenesis of neurodegenerative disorders, with particular reference to plaque formation in Alzheimer's disease

Discrete, microscopic lesions are developed in the brain in a number of neurodegenerative diseases. These lesions may not be randomly distributed in the tissue but exhibit a spatial pattern, i.e., a departure from randomness towards regularlity or clustering. The spatial pattern of a lesion may reflect its development in relation to other brain lesions or to neuroanatomical structures. Hence, a study of spatial pattern may help to elucidate the pathogenesis of a lesion. A number of statistical methods can be used to study the spatial patterns of brain lesions. They range from simple tests of whether the distribution of a lesion departs from random to more complex methods which can detect clustering and the size, distribution and spacing of clusters. This paper reviews the uses and limitations of these methods as applied to neurodegenerative disorders, and in particular to senile plaque formation in Alzheimer's disease.

The board of directors, executives and risk knowledge management

Enterprise Risk Management (ERM) and Knowledge Management (KM) both encompass top-down and bottom-up approaches developing and embedding risk knowledge concepts and processes in strategy, policies, risk appetite definition, the decision-making process and business processes. The capacity to transfer risk knowledge affects all stakeholders and understanding of the risk knowledge about the enterprise's value is a key requirement in order to identify protection strategies for business sustainability. There are various factors that affect this capacity for transferring and understanding. Previous work has established that there is a difference between the influence of KM variables on Risk Control and on the perceived value of ERM. Communication among groups appears as a significant variable in improving Risk Control but only as a weak factor in improving the perceived value of ERM. However, the ERM mandate requires for its implementation a clear understanding, of risk management (RM) policies, actions and results, and the use of the integral view of RM as a governance and compliance program to support the value driven management of the organization. Furthermore, ERM implementation demands better capabilities for unification of the criteria of risk analysis, alignment of policies and protection guidelines across the organization. These capabilities can be affected by risk knowledge sharing between the RM group and the Board of Directors and other executives in the organization. This research presents an exploratory analysis of risk knowledge transfer variables used in risk management practice. A survey to risk management executives from 65 firms in various industries was undertaken and 108 answers were analyzed. Potential relationships among the variables are investigated using descriptive statistics and multivariate statistical models. The level of understanding of risk management policies and reports by the board is related to the quality of the flow of communication in the firm and perceived level of integration of the risk policy in the business processes.

Automated mapping of environmental variables from a SEIS or SISE perspective

The INTAMAP FP6 project has developed an interoperable framework for real-time automatic mapping of critical environmental variables by extending spatial statistical methods and employing open, web-based, data exchange protocols and visualisation tools. This paper will give an overview of the underlying problem, of the project, and discuss which problems it has solved and which open problems seem to be most relevant to deal with next. The interpolation problem that INTAMAP solves is the generic problem of spatial interpolation of environmental variables without user interaction, based on measurements of e.g. PM10, rainfall or gamma dose rate, at arbitrary locations or over a regular grid covering the area of interest. It deals with problems of varying spatial resolution of measurements, the interpolation of averages over larger areas, and with providing information on the interpolation error to the end-user. In addition, monitoring network optimisation is addressed in a non-automatic context.

Innovation in the pharmaceutical industry:a study of the effects of regulation on the U.K. pharmaceutical industry

A history of government drug regulation and the relationship between the pharmaceutical companies in the U.K. and the licensing authority is outlined. Phases of regulatory stringency are identified with the formation of the Committees on Safety of Drugs and Medicines viewed as watersheds. A study of the impact of government regulation on industrial R&D activities focuses on the effects on the rate and direction of new product innovation. A literature review examines the decline in new chemical entity innovation. Regulations are cited as a major but not singular cause of the decline. Previous research attempting to determine the causes of such a decline on an empirical basis is given and the methodological problems associated with such research are identified. The U.K. owned sector of the British pharmaceutical industry is selected for a study employing a bottom-up approach allowing disaggregation of data. A historical background to the industry is provided, with each company analysed or a case study basis. Variations between companies regarding the policies adopted for R&D are emphasised. The process of drug innovation is described in order to determine possible indicators of the rate and direction of inventive and innovative activity. All possible indicators are considered and their suitability assessed. R&D expenditure data for the period 1960-1983 is subsequently presented as an input indicator. Intermediate output indicators are treated in a similar way and patent data are identified as a readily-available and useful source. The advantages and disadvantages of using such data are considered. Using interview material, patenting policies for most of the U.K. companies are described providing a background for a patent-based study. Sources of patent data are examined with an emphasis on computerised systems. A number of searches using a variety of sources are presented. Patent family size is examined as a possible indicator of an invention's relative importance. The patenting activity of the companies over the period 1960-1983 is given and the variation between companies is noted. The relationship between patent data and other indicators used is analysed using statistical methods resulting in an apparent lack of correlation. An alternative approach taking into account variations in company policy and phases in research activity indicates a stronger relationship between patenting activity, R&D Expenditure and NCE output over the period. The relationship is not apparent at an aggregated company level. Some evidence is presented for a relationship between phases of regulatory stringency, inventive and innovative activity but the importance of other factors is emphasised.

The application of artificial neural networks to the interpretation and classification of freshwater benthic invertebrate communities

This thesis presents a thorough and principled investigation into the application of artificial neural networks to the biological monitoring of freshwater. It contains original ideas on the classification and interpretation of benthic macroinvertebrates, and aims to demonstrate their superiority over the biotic systems currently used in the UK to report river water quality. The conceptual basis of a new biological classification system is described, and a full review and analysis of a number of river data sets is presented. The biological classification is compared to the common biotic systems using data from the Upper Trent catchment. This data contained 292 expertly classified invertebrate samples identified to mixed taxonomic levels. The neural network experimental work concentrates on the classification of the invertebrate samples into biological class, where only a subset of the sample is used to form the classification. Other experimentation is conducted into the identification of novel input samples, the classification of samples from different biotopes and the use of prior information in the neural network models. The biological classification is shown to provide an intuitive interpretation of a graphical representation, generated without reference to the class labels, of the Upper Trent data. The selection of key indicator taxa is considered using three different approaches; one novel, one from information theory and one from classical statistical methods. Good indicators of quality class based on these analyses are found to be in good agreement with those chosen by a domain expert. The change in information associated with different levels of identification and enumeration of taxa is quantified. The feasibility of using neural network classifiers and predictors to develop numeric criteria for the biological assessment of sediment contamination in the Great Lakes is also investigated.

The geochemistry of the sedimentary rocks of the Harlech Dome, North Wales

Bedrock geochemical analysis, coupled with detailed data analysis, was carried out on some 260 samples taken from two areas of 'the Harlech Dome, near Dolgellau, North Wales. This was done to determine if rocks from mineralised and non-mineralised areas could be distinguished, and to determine mineralisation types and wall rock alterations. The Northern Area, near Talsarnau, has no recorded mineralisation, while the Southern Area, near Bontddu, has been exploited for gold. The rocks sampled, in both areas, were from the Cambrian Gamlan Flags, Clogau Shales, Vigra Flags, later vein materials, and igneous intrusions. All samples were analysed, using a new rapid, atomic absorption spectrophotometric technique, for Si, AI, Fe, Cu, Ni, Zn, Pb, Sr, Hg, and Ba. In addition 60 samples were analysed by X-ray fluorescence for Mn, Ti, Ca, K, Na, P, Cr, Ce, La, S, Y , Rh, and Th. Total CO2 was determined, on selected samples, using a combustion technique. Elemental distributions, for each rock type, in each area, were· plotted, and means, standard deviations, and enrichment indices were calculated. Multivariate statistical analysis on the results distinguished a Cu-type mineralisation in the Northern area, and both Cu and Pb/Zn types in the Southern Area. It also showed the Northern Area to be less strongly mineralised than the Southern one in which both mineralisation types are associated with wall rock alteration. Elemental associations and trends due to sedimentary processes were distinguished from those related to mineralisation. Hg is related to mineralisation, and plots of factor scores, on the sampling grid, produced clusters of mineralisation related factors in areas of known mineralisation. A double Fourier Trend Analysis program, with a wavelength search routine, was developed and used to recognise sedimentary trends for Sr. Y., Rb, and Th. These trends were interpreted to represent areas of low pH and reducing conditions. They also indicate that the supply of sediment remained constant over Gamlan, Clogau, and Vigra times. The trend surface of Hg showed no association with rock type. It is shown that analysis of a small number of samples, for a carefully selected number of elements, with detailed data analysis, can provide more useful information than analysis of a large number of samples for many elements. The mineralisation is suggested to have been the result of water solutions leaching ore metals from the sedimentary rocks and redepositing them in veins.

The influence of the socio-educational reading environment in an Arab University upon English reading performance

Research into FL/EFL macro-reading (the effect of the broader context of reading) has been little explored in spite of its importance in the FL/EFL reading programmes. This study was designed to build on previous work by explaining in more depth the influence of the socio-educational reading environment in an Arab university (Al-Fateh University in Tripoli, Libya) - as reported by students, upon these students' reading ability in English and Arabic (particularly the former). Certain aspects of the lecturers' reading habits and attitudes and classroom operation were also investigated. Written cloze tests in English and Arabic and self-administered questionnaires were given to 125 preliminary-year undergraduates in three faculties of Al-Fateh University on the basis of their use of English as a medium of instruction (one representing the Arts' stream and two representing the Science stream). Twenty two lecturers were interviewed and observed by an inventory technique along with twenty other preliminary-year students. Factor analysis and standard multiple regression technique were among the statistical methods used to analyse the main data. The findings demonstrate a significant relationship between reading ability in English and the reading individual and environmental variables - as defined in the study. A combination of common and different series of such predictors were found accountable for the variation (43% for the first year English specialist; 48% for the combined Medicine student sample) in the English reading tests. Also found was a significant, though not very large, relationship between reading ability in Arabic and the reading environment. Non-statistical but objective analyses, based on the present data, also revealed an overall association between English reading performance and an important number of reading environmental variables - where many `poor' users of the reading environment (particularly the academic one) obtained low scores in the English cloze tests. Accepting the limitations of a single study, it is nevertheless clear that the reading environment at the University is in need of improvement and that students' use of it also requires better guidance and training in how to use it effectively. Suggestions are made for appropriate educational changes.

The effects of solid contamination in hydraulic fluids on axial piston pumps

The fluids used in hydraulic systems inevitably contain large numbers of small, solid particles, a phenomenon known as 'fluid contamination'. Particles enter a hydraulic system from the environment, and are generated within it by processes of wear. At the same time, particles are removed from the system fluid by sedimentation and in hydraulic filters. This thesis considers the problems caused by fluid contamination, as they affect a manufacturer of axial piston pumps. The specific project aim was to investigate methods of predicting or determining the effects of fluid contamination on this type of pump. The thesis starts with a theoretical analysis of the contaminated lubrication of a slipper-pad bearing. Statistical methods are used to develop a model of the blocking, by particles, of the control capillaries used in such bearings. The results obtained are compared to published, experimental data. Poor correlation between theory and practice suggests that more research is required in this area before such theoretical analysis can be used in industry. Accelerated wear tests have been developed in the U.S.A. in an attempt to predict pump life when operating on contaminated fluids. An analysis of such tests shows that reliability data can only be obtained from extensive test programmes. The value of contamination testing is suggested to be in determining failure modes, and in identifying those pump components which are susceptible to the effects of contamination. A suitable test is described, and the results of a series of tests on axial piston pumps are presented and discussed. The thesis concludes that pump reliability data can only be obtained from field experience. The level of confidence which can be placed in results from normal laboratory testing is shown to be too low for the data to be of real value. Recommendations are therefore given for the ways in which service data should be collected and analysed.

Addressing missing data in geochemistry: a non-linear approach

Exploratory analysis of petroleum geochemical data seeks to find common patterns to help distinguish between different source rocks, oils and gases, and to explain their source, maturity and any intra-reservoir alteration. However, at the outset, one is typically faced with (a) a large matrix of samples, each with a range of molecular and isotopic properties, (b) a spatially and temporally unrepresentative sampling pattern, (c) noisy data and (d) often, a large number of missing values. This inhibits analysis using conventional statistical methods. Typically, visualisation methods like principal components analysis are used, but these methods are not easily able to deal with missing data nor can they capture non-linear structure in the data. One approach to discovering complex, non-linear structure in the data is through the use of linked plots, or brushing, while ignoring the missing data. In this paper we introduce a complementary approach based on a non-linear probabilistic model. Generative topographic mapping enables the visualisation of the effects of very many variables on a single plot, while also dealing with missing data. We show how using generative topographic mapping also provides an optimal method with which to replace missing values in two geochemical datasets, particularly where a large proportion of the data is missing.

Comparative risk of microalbuminuria and proteinuria in UK residents of south Asian and white European ethnic background with type 2 diabetes:a report from UKADS

Objective - This study investigated and compared the prevalence of microalbuminuria and overt proteinuria and their determinants in a cohort of UK resident patients of white European or south Asian ethnicity with type 2 diabetes mellitus. Research design and methods - A total of 1978 patients, comprising 1486 of south Asian and 492 of white European ethnicity, in 25 general practices in Coventry and Birmingham inner city areas in England were studied in a cross-sectional study. Demographic and risk factor data were collected and presence of microalbuminuria and overt proteinuria assessed. Main outcome measures - Prevalences of microalbuminuria and overt proteinuria. Results - Urinary albumin:creatinine measurements were available for 1852 (94%) patients. The south Asian group had a lower prevalence of microalbuminuria, 19% vs. 23% and a higher prevalence of overt proteinuria, 8% vs. 3%, X2?=?15.85, 2df, P?=?0.0004. In multiple logistic regression models, adjusted for confounding factors, significantly increased risk for the south Asian vs. white European patients for overt proteinuria was shown; OR (95% CI) 2.17 (1.05, 4.49), P?=?0.0365. For microalbuminuria, an interaction effect for ethnicity and duration of diabetes suggested that risk for south Asian patients was lower in early years following diagnosis; OR for SA vs. WH at durations 0 and 1 year were 0.56 (0.37, 0.86) and 0.59 (0.39, 0.89) respectively. After 20 years’ duration, OR?=?1.40 (0.63, 3.08). Limitations - Comparability of ethnicity defined groups; statistical methods controlled for differences between groups, but residual confounding may remain. Analyses are based on a single measure of albumin:creatinine ratio. Conclusions - There were significant differences between ethnicity groups in risk factor profiles and microalbuminuria and overt proteinuria outcomes. Whilst south Asian patients had no excess risk of microalbuminuria, the risk of overt proteinuria was elevated significantly, which might be explained by faster progression of renal dysfunction in patients of south Asian ethnicity.

Extracting protein-protein interactions from MEDLINE using the hidden vector state model

A major challenge in text mining for biomedicine is automatically extracting protein-protein interactions from the vast amount of biomedical literature. We have constructed an information extraction system based on the Hidden Vector State (HVS) model for protein-protein interactions. The HVS model can be trained using only lightly annotated data whilst simultaneously retaining sufficient ability to capture the hierarchical structure. When applied in extracting protein-protein interactions, we found that it performed better than other established statistical methods and achieved 61.5% in F-score with balanced recall and precision values. Moreover, the statistical nature of the pure data-driven HVS model makes it intrinsically robust and it can be easily adapted to other domains.

R.A. Armstrong

Richard Armstrong was educated at King’s College London (1968-1971) and subsequently at St. Catherine’s College Oxford (1972-1976). His early research involved the application of statistical methods to problems in botany and ecology. For the last 34 years, he has been a lecturer in Botany, Microbiology, Ecology, Neuroscience, and Optometry at the University of Aston. His current research interests include the application of quantitative methods to the study of neuropathology of neurodegenerative diseases with special reference to vision and the visual system.