38 resultados para Foundations -- Pathology

em Aston University Research Archive


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Neural networks have often been motivated by superficial analogy with biological nervous systems. Recently, however, it has become widely recognised that the effective application of neural networks requires instead a deeper understanding of the theoretical foundations of these models. Insight into neural networks comes from a number of fields including statistical pattern recognition, computational learning theory, statistics, information geometry and statistical mechanics. As an illustration of the importance of understanding the theoretical basis for neural network models, we consider their application to the solution of multi-valued inverse problems. We show how a naive application of the standard least-squares approach can lead to very poor results, and how an appreciation of the underlying statistical goals of the modelling process allows the development of a more general and more powerful formalism which can tackle the problem of multi-modality.

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The objective is to study beta-amyloid (Abeta) deposition in dementia with Lewy bodies (DLB) with Alzheimer's disease (AD) pathology (DLB/AD). The size frequency distributions of the Abeta deposits were studied and fitted by log-normal and power-law models. Patients were ten clinically and pathologically diagnosed DLB/AD cases. Size distributions had a single peak and were positively skewed and similar to those described in AD and Down's syndrome. Size distributions had smaller means in DLB/AD than in AD. Log-normal and power-law models were fitted to the size distributions of the classic and diffuse deposits, respectively. Size distributions of Abeta deposits were similar in DLB/AD and AD. Size distributions of the diffuse deposits were fitted by a power-law model suggesting that aggregation/disaggregation of Abeta was the predominant factor, whereas the classic deposits were fitted by a log-normal distribution suggesting that surface diffusion was important in the pathogenesis of the classic deposits.

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The use of quantitative methods has become increasingly important in the study of neurodegenerative disease. Disorders such as Alzheimer's disease (AD) are characterized by the formation of discrete, microscopic, pathological lesions which play an important role in pathological diagnosis. This article reviews the advantages and limitations of the different methods of quantifying the abundance of pathological lesions in histological sections, including estimates of density, frequency, coverage, and the use of semiquantitative scores. The major sampling methods by which these quantitative measures can be obtained from histological sections, including plot or quadrat sampling, transect sampling, and point-quarter sampling, are also described. In addition, the data analysis methods commonly used to analyse quantitative data in neuropathology, including analyses of variance (ANOVA) and principal components analysis (PCA), are discussed. These methods are illustrated with reference to particular problems in the pathological diagnosis of AD and dementia with Lewy bodies (DLB).

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This paper examines the role of creative resources in the emergence of the Japanese video game industry. We argue that creative resources nurtured by popular cartoons and animation sector, combined with technological knowledge accumulated in the consumer electronics industry, facilitated the emergence of successful video game industry in Japan. First we trace the development of the industry from its origin to the rise of platform developers and software publishers. Then, knowledge and creative foundations that influenced the developmental trajectory of this industry are analyzed, with links to consumer electronics and in regards to cartoons and animation industry.

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When applying multivariate analysis techniques in information systems and social science disciplines, such as management information systems (MIS) and marketing, the assumption that the empirical data originate from a single homogeneous population is often unrealistic. When applying a causal modeling approach, such as partial least squares (PLS) path modeling, segmentation is a key issue in coping with the problem of heterogeneity in estimated cause-and-effect relationships. This chapter presents a new PLS path modeling approach which classifies units on the basis of the heterogeneity of the estimates in the inner model. If unobserved heterogeneity significantly affects the estimated path model relationships on the aggregate data level, the methodology will allow homogenous groups of observations to be created that exhibit distinctive path model estimates. The approach will, thus, provide differentiated analytical outcomes that permit more precise interpretations of each segment formed. An application on a large data set in an example of the American customer satisfaction index (ACSI) substantiates the methodology’s effectiveness in evaluating PLS path modeling results.

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Objective: To quantify the neuronal and glial cell pathology in the hippocampus and the parahippocampal gyrus (PHG) of 8 cases of progressive supranuclear palsy (PSP). Material: tau-immunolabeled sections of the temporal lobe of 8 diagnosed cases of PSP. Method: The densities of lesions were measured in the PHG, CA sectors of the hippocampus and the dentate gyrus (DG) and studied using spatial pattern analysis. Results: Neurofibrillary tangles (NFT) and abnormally enlarged neurons (EN) were most frequent in the PHG and in sector CA1 of the hippocampus, oligodendroglial inclusions (“coiled bodies”) (GI) in the PHG, subiculum, sectors CA1 and CA2, and neuritic plaques (NP) in sectors CA2 and CA4. The DG was the least affected region. Vacuolation and GI were observed in the alveus. No tufted astrocytes (TA) were observed. Pathological changes exhibited clustering, the lesions often exhibiting a regular distribution of the clusters parallel to the tissue boundary. There was a positive correlation between the degree of vacuolation in the alveus and the densities of NFT in CA1 and GI in CA1 and CA2. Conclusion: The pathology most significantly affected the output pathways of the hippocampus, lesions were topographically distributed, and hippocampal pathology may be one factor contributing to cognitive decline in PSP.

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Neurofilament inclusion disease (NID) is a novel neurodegenerative disease characterized histologically by the presence of neurofilament positive neuronal inclusions (NI) and swollen achromatic neurons (SN). The density and distribution of NI and SN were studied in areas of the temporal lobe in four cases of NID. In NID, the density of the NI and SN was greater in areas of the cerebral cortex compared with the hippocampus and dentate gyrus. Lesion densities were similar in the different gyri of the temporal cortex and in the various cornu ammonis sectors of the hippocampus. In the cerebral cortex, the density of the NI and SN was greater in the lower compared with the upper cortical laminae. There was no significant correlation between the densities of the NI and SN. The distribution of the temporal lobe pathology of NID has several differences from that reported in Pick's disease and corticobasal degeneration supporting the hypothesis that NID is a novel and unique type of neurodegenerative disease. © 2003 Elsevier Ireland Ltd. All rights reserved.

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Knowledge is of crucial, and growing importance in social, political and economic relations in modern society. The range and variety of available knowledge dramatically enlarges the available options of social action. This five volume collection brings together a broad array of contributions from a variety of disciplines. Featuring essays from philosophers who have investigated the foundations of knowledge, and addressing different forms of knowledge in society such as common sense and practical knowledge, this collection also discusses the role of knowledge in economic process and gives attention to the role of expert knowledge in political decision making. Including a collection of articles from the sociology of knowledge and science, the set also provides a new introduction by the editors, making it a unique and invaluable research resource for both student and scholar.

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Quantitative variations in the density and distribution of the vacuolation ('spongiform change'), surviving neurons, and prion protein (PrP) deposits were studied in eight brain regions from 11 cases of variant Creutzfeldt-Jakob disease (vCJD). Principal components analysis (PCA) was used to study the similarities and differences between cases and to identify the neuropathological variables which could best account for these variations. Two principal components (PC) were extracted from the data accounting in total for 93.4% of the variance; the majority of the variance (90%) being associated with PC1. Some clustering of the 11 cases in relation to PC1 and PC2 was evident. The densities of the vacuolation in the occipital cortex and the molecular layer of the cerebellum were positively and negatively correlated, respectively, with PC1. No significant variation between cases was associated with PrP deposition. These data suggest that vCJD cases have a consistent neuropathological profile characterised by the presence of vacuolation, neuronal loss and PrP deposition in the form of florid and non-florid deposits. However, there are quantitative variations between cases in the development of the vacuolation especially affecting the occipital cortex and cerebellum. © 2002 Elsevier Science Ireland Ltd. All rights reserved.

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Lesions in Alzheimer's disease (AD) and dementia with Lewy bodies (DLB) have distinct laminar distributions in the cortex. The objective of the present study was to test the hypothesis that the lesions characteristic of Pick's disease (PD) and AD have distinctly different laminar distributions in cases of PD. Hence, the laminar distribution of Pick bodies (PB), Pick cells (PC), senile plaques (SP) and neurofibrillary tangles (NFT) was studied in the frontal and temporal cortex in nine patients with PD. In 57% of analyses of individual cortical areas, the density of PB was maximal in the upper cortex while in 25% of analyses, the distribution of PB was bimodal with density peaks in the upper and lower cortex. The density of PC was maximal in the lower cortex in 77% of analyses while a bimodal distribution was present in 5% of analyses. The density of NFT was maximal in the upper cortex in 50% of analyses, in the lower cortex in 15% of analyses, with a bimodal distribution in 4% of analyses. The density of SP did not vary significantly with cortical depth in 86% of analyses. The vertical densities of PB and PC were negatively correlated in 12/21 (57%) of brain areas. The maximum density of PB in the upper cortex was positively correlated with the maximum density of PC in the lower cortex. In 17/25 (68%) of brain areas, there was no significant correlation between the vertical densities of PB and NFT. The data suggest that the pathogenesis of PB may be related to that of the PC. In addition, although in many areas PB and NFT occur predominantly in the upper cortex, the two lesions appeared to affect different neuronal populations.

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The aim of this study was to test the hypothesis that differences in density of senile plaques (SP) and neurofibrillary tangles (NFT) in the cuneal and lingual gyri of area V1 of the visual cortex could explain the predominantly inferior visual field defects seen in patients with Alzheimer's disease (AD). The density of SP and NFT was measured in the cuneal and lingual gyri of 18 AD patients. In 7/18 (39%) patients, the density of SP and/or NFT was significantly greater in the cuneal compared with the lingual gyri. In 3/18 (17%) patients, densities were greater in the lingual than the cuneal gyri and in 8/18 (44%) patients there were no significant differences among gyri. The data suggest that pathological differences between cuneal and lingual gyri could contribute to the reported visual field defects in some AD patients.

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The spatial patterns of Pick bodies (PB), Pick cells (PC), senile plaques (SP) and neurofibrillary tangles (NFT) were studied in the frontal and temporal lobe in nine cases of Pick’s disease (PD). Pick bodies exhibited clustering in 41/44 (93%) of analyses and clusters of PB were regularly distributed parallel to the tissue boundary in 24/41 (58%) of analyses. Pick cells exhibited clustering with regular periodicity of clusters in 14/16 (88%) analyses, SP in three out of four (75%) analyses and NFT in 21/27 (78%) analyses. The largest clusters of PB were observed in the dentate gyrus and PC in the frontal cortex. In 10/17 (59%) brain areas studied, a positive or negative correlation was observed between the densities of PB and PC. The densities of PB and NFT were not significantly correlated in the majority of brain areas but a negative correlation was observed in 7/29 (24%) brain areas. The data suggest that PB and PC in patients with PD exhibit essentially the same spatial patterns as SP and NFT in Alzheimer’s disease (AD) and Lewy bodies (LB) in dementia with Lewy bodies (DLB). In addition, there was a spatial correlation between the clusters of PB and PC, suggesting a pathogenic relationship between the two lesions. However, in the majority of tissues examined there was no spatial correlation between the clusters of PB and NFT, suggesting that the two lesions develop in association with different populations of neurons.

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The density of Lewy bodies (LB), senile plaques (SP), and neurofibrillary tangles (NFT) was studied in the temporal lobe in four patients diagnosed with ‘pure’ dementia with Lewy bodies (DLB) and eight patients diagnosed with DLB with associated Alzheimer’s disease (DLB/AD). In both patient groups, the density of LB was greatest in the lateral occipitotemporal gyrus (LOT) and least in areaas CA1 and CA4 of the hippocampus. In DLB/AD, the densities of SP and NFT were greatest in the cortical regions and in area CA1 of the hippocampus respectively. Mean LB densities in the temporal lobe were similar in ‘pure’ DLB and DLB/AD patients but mean SP and NFT densities were greater in DLB/AD. No significant correlations were observed between the densities of LB, SP and NFT in any brain region. The data suggest that in the temporal lobe LB and SP/NFT are distributed differently; SP and NFT in DLB/AD are distributed similarly to ‘pure’ AD and also that LB and AD pathologies appear to develop independently. Hence, the data support the hypothesis that some cases of DLB combine the features of DLB and AD.