20 resultados para Inheritance of regularity

em Aston University Research Archive


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The objective of this article is to describe the patterns of inheritance exhibited in the human populations and to illustrate them with examples drawn from a variety of ocular diseases.

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This series of articles describes the basic elements of genetics necessary to understand the new advances and the impact these advances will have on the study and treatment of ocular disease. The first article describes the patterns of inheritance of human characteristics, how they are transmitted between the generations and the structure of chromosomes.

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This article reviews: 1) the clinical and pathological features of the different types of catarct, 2) the patterns of inheritance of cataract, 3) the genes that may be associated with the development of cataract, and 4) how the presence of abnormal genes may cause lens opacity.

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We have studied the spatial distribution of plaques in coronal and tangential sections of the parahippocampal gyrus (PHG), the hippocampus, the frontal lobe and the temporal lobe of five SDAT patients. Sections were stained with cresyl violet and examined at two magnifications (x100 and x400). in all cases (and at both magnifications) statistical analysis using the Poisson distribution showed that the plaques were arranged in clumps (x100: V/M = 1.48 - 4.49; x400 V/M = 1.17 - 1.95). this indicates that both large scale and small scale clumping occurs. Application of the statistical techniques of pattern analysis to coronal sections of frontal and temporal cortex and PHG showed. furthermore, that both large (3200-6400 micron) and small scale (100 - 400 micron) clumps were arranged with a high degree of regularity in the tissue. This suggests that the clumps of plaques reflect underlying neural structure.

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Fifteen years ago, twenty-seven countries in Europe and Central Asia embarked on their economic transition paths. For some, the outcome was a considerable success. Several others are still struggling to shed the inheritance of the past and to correct more recent policy mistakes. Why were post-Communist recessions so long in some countries and growth disappointing? Why was fiscal performance so different? Was democracy a factor, which facilitated reforms or rather slowed them down? This book discusses these questions in the context of new empirical evidence, including a critical examination of the main themes in the economics of transition.

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The relationship between sleep apnoea–hypopnoea syndrome (SAHS) severity and the regularity of nocturnal oxygen saturation (SaO2) recordings was analysed. Three different methods were proposed to quantify regularity: approximate entropy (AEn), sample entropy (SEn) and kernel entropy (KEn). A total of 240 subjects suspected of suffering from SAHS took part in the study. They were randomly divided into a training set (96 subjects) and a test set (144 subjects) for the adjustment and assessment of the proposed methods, respectively. According to the measurements provided by AEn, SEn and KEn, higher irregularity of oximetry signals is associated with SAHS-positive patients. Receiver operating characteristic (ROC) and Pearson correlation analyses showed that KEn was the most reliable predictor of SAHS. It provided an area under the ROC curve of 0.91 in two-class classification of subjects as SAHS-negative or SAHS-positive. Moreover, KEn measurements from oximetry data exhibited a linear dependence on the apnoea–hypopnoea index, as shown by a correlation coefficient of 0.87. Therefore, these measurements could be used for the development of simplified diagnostic techniques in order to reduce the demand for polysomnographies. Furthermore, KEn represents a convincing alternative to AEn and SEn for the diagnostic analysis of noisy biomedical signals.

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Secretory protein trafficking is arrested and the Golgi apparatus fragmented when mammalian cells enter mitosis. These changes are thought to facilitate cell cycle progression and Golgi inheritance, and are brought about through the actions of mitotically active protein kinases. To better understand how the Golgi apparatus undergoes mitotic fragmentation we have sought to identify novel Golgi targets for mitotic kinases. We report here the identification of the ARF exchange factor GBF1 as a Golgi phosphoprotein. GBF1 is phosphorylated by CDK1-cyclin B in mitosis, which results in its dissociation from Golgi membranes. Consistent with a reduced level of GBF1 activity at the Golgi membrane there is a reduction in levels of membrane-associated GTP-bound ARF in mitotic cells. Despite the reduced levels of membrane bound GBF1 and ARF, COPI binding to the Golgi membrane appears unaffected in mitotic cells. Surprisingly, this pool of COPI is dependent upon GBF1 for its recruitment to the membrane, suggesting a low level of GBF1 activity persists in mitosis. We propose that the phosphorylation and membrane dissociation of GBF1 and the consequent reduction in ARF-GTP levels in mitosis are important for changes in Golgi dynamics and possibly other mitotic events mediated through effectors other than the COPI vesicle coat.

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The development of abnormal protein aggregates in the form of extracellular plaques and intracellular inclusions is a characteristic feature of many neurodegenerative diseases such as Alzheimer's disease (AD), Creutzfeldt-Jakob disease (CJD) and the fronto-temporal dementias (FTD). An important aspect of a pathological protein aggregate is its spatial topography in the tissue. Lesions may not be randomly distributed within a histological section but exhibit spatial pattern, a departure from randomness either towards regularity or clustering. Information on the spatial pattern of a lesion may be useful in elucidating its pathogenesis and in studying the relationships between different lesions. This article reviews the methods that have been used to study the spatial topography of lesions. These include simple tests of whether the distribution of a lesion departs significantly from random using randomized points or sample fields, and more complex methods that employ grids or transects of contiguous fields and which can detect the intensity of aggregation and the sizes, distribution and spacing of the clusters. The usefulness of these methods in elucidating the pathogenesis of protein aggregates in neurodegenerative disease is discussed.

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This article reviews the statistical methods that have been used to study the planar distribution, and especially clustering, of objects in histological sections of brain tissue. The objective of these studies is usually quantitative description, comparison between patients or correlation between histological features. Objects of interest such as neurones, glial cells, blood vessels or pathological features such as protein deposits appear as sectional profiles in a two-dimensional section. These objects may not be randomly distributed within the section but exhibit a spatial pattern, a departure from randomness either towards regularity or clustering. The methods described include simple tests of whether the planar distribution of a histological feature departs significantly from randomness using randomized points, lines or sample fields and more complex methods that employ grids or transects of contiguous fields, and which can detect the intensity of aggregation and the sizes, distribution and spacing of clusters. The usefulness of these methods in understanding the pathogenesis of neurodegenerative diseases such as Alzheimer's disease and Creutzfeldt-Jakob disease is discussed. © 2006 The Royal Microscopical Society.

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Discrete pathological lesions, which include extracellular protein deposits, intracellular inclusions and changes in cell morphology, occur in the brain in the majority of neurodegenerative disorders. These lesions are not randomly distributed in the brain but exhibit a spatial pattern, that is, a departure from randomness towards regularity or clustering. The spatial pattern of a lesion may reflect pathological processes affecting particular neuroanatomical structures and, therefore, studies of spatial pattern may help to elucidate the pathogenesis of a lesion and of the disorders themselves. The present article reviews first, the statistical methods used to detect spatial patterns and second, the types of spatial patterns exhibited by pathological lesions in a variety of disorders which include Alzheimer's disease, Down syndrome, dementia with Lewy bodies, Creutzfeldt-Jakob disease, Pick's disease and corticobasal degeneration. These studies suggest that despite the morphological and molecular diversity of brain lesions, they often exhibit a common type of spatial pattern (i.e. aggregation into clusters that are regularly distributed in the tissue). The pathogenic implications of spatial pattern analysis are discussed with reference to the individual disorders and to studies of neurodegeneration as a whole.

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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.

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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.

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The present article reviews the patterns of inheritance associated with glaucoma, how the genes linked to the disease have been located and identified, and considers how the effect of some of these genes could lead to glaucoma.

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This article reviews the patterns of inheritance associated with glaucoma, how the genes linked to glaucoma have been located and identified and considers how the effect of some of these genes could lead to glaucoma.

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Jackson System Development (JSD) is an operational software development method which addresses most of the software lifecycle either directly or by providing a framework into which more specialised techniques can fit. The method has two major phases: first an abstract specification is derived that is in principle executable; second the specification is implemented using a variety of transformations. The object oriented paradigm is based on data abstraction and encapsulation coupled to an inheritance architecture that is able to support software reuse. Its claims of improved programmer productivity and easier program maintenance make it an important technology to be considered for building complex software systems. The mapping of JSD specifications into procedural languages typified by Cobol, Ada, etc., involves techniques such as inversion and state vector separation to produce executable systems of acceptable performance. However, at present, no strategy exists to map JSD specifications into object oriented languages. The aim of this research is to investigate the relationship between JSD and the object oriented paradigm, and to identify and implement transformations capable of mapping JSD specifications into an object oriented language typified by Smalltalk-80. The direction which the transformational strategy follows is one whereby the concurrency of a specification is removed. Two approaches implementing inversion - an architectural transformation resulting in a simulated coroutine mechanism being generated - are described in detail. The first approach directly realises inversions by manipulating Smalltalk-80 system contexts. This is possible in Smalltalk-80 because contexts are first class objects and are accessible to the user like any other system object. However, problems associated with this approach are expounded. The second approach realises coroutine-like behaviour in a structure called a `followmap'. A followmap is the results of a transformation on a JSD process in which a collection of followsets is generated. Each followset represents all possible state transitions a process can undergo from the current state of the process. Followsets, together with exploitation of the class/instance mechanism for implementing state vector separation, form the basis for mapping JSD specifications into Smalltalk-80. A tool, which is also built in Smalltalk-80, supports these derived transformations and enables a user to generate Smalltalk-80 prototypes of JSD specifications.