7 resultados para Niemann Pick C1
em Aston University Research Archive
Resumo:
In patients with Pick's disease (PD), high densities of tau positive Pick bodies (PB) have been observed within the granule cell layer of the dentate gyrus. This study investigated the spatial patterns of PB along the granule cell layer in coronal sections of the hippocampus in eight patients with PD. In all patients, there was evidence of clustering of PB within the granule cell layer; however, there was considerable variation in the pattern of clustering. In five patients, the clusters of PB were regularly distributed along the dentate gyms, and in two of these patients, the smaller clusters were aggregated into larger superclusters. In three patients, a single large cluster of PB, more than 1200 μm in diameter, was present. Clustering of PB may reflect a primary degenerative process within the granule cells or the degeneration of pathways that project to the dentate gyrus.
Resumo:
This paper formulates several mathematical models for determining the optimal sequence of component placements and assignment of component types to feeders simultaneously or the integrated scheduling problem for a type of surface mount technology placement machines, called the sequential pick-andplace (PAP) machine. A PAP machine has multiple stationary feeders storing components, a stationary working table holding a printed circuit board (PCB), and a movable placement head to pick up components from feeders and place them to a board. The objective of integrated problem is to minimize the total distance traveled by the placement head. Two integer nonlinear programming models are formulated first. Then, each of them is equivalently converted into an integer linear type. The models for the integrated problem are verified by two commercial packages. In addition, a hybrid genetic algorithm previously developed by the authors is adopted to solve the models. The algorithm not only generates the optimal solutions quickly for small-sized problems, but also outperforms the genetic algorithms developed by other researchers in terms of total traveling distance.
Resumo:
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.
Resumo:
The densities of Pick bodies (PB), Pick cells (PC), senile plaques (SP) and neurofibrillary tangles (NFT) in the frontal and temporal lobe were determined in ten patients diagnosed with Pick's disease (PD). The density of PB was significantly higher in the dentate gyrus granule cells compared with the cortex and the CA sectors of the hippocampus. Within the hippocampus, the highest densities of PB were observed in sector CA1. PC were absent in the dentate gyrus and no significant differences in PC density were observed in the remaining brain regions. With the exception of two patients, the densities of SP and NFT were low with no significant differences in mean densities between cortical regions. In the hippocampus, the density of NFT was greatest in sector CA1. PB and PC densities were positively correlated in the frontal cortex but no correlations were observed between the PD and AD lesions. A principal components analysis (PCA) of the neuropathological variables suggested that variations in the densities of SP in the frontal cortex, temporal cortex and hippocampus were the most important sources of heterogeneity within the patient group. Variations in the densities of PB and NFT in the temporal cortex and hippocampus were of secondary importance. In addition, the PCA suggested that two of the ten patients were atypical. One patient had a higher than average density of SP and one familial patient had a higher density of NFT but few SP.
Resumo:
Clustering of Pick bodies (PB) was studied in the frontal and temporal lobe in 10 cases of Pick's disease (PD). Pick bodies exhibited clustering in 47/50 (94%) brain areas analysed. In 20/50 (40%) brain areas, PB were present in a single large cluster ≤ 6400 μm in diameter, in 27/50 (54%) PB occurred in smaller clusters (200-3200 μm in diameter) which exhibited a regular periodicity relative to the tissue boundary, in 1/50 (2%) there was a regular distribution of individual PB and in 2/50 (4%), PB were randomly distributed. Mean cluster size of the PB was greater in the dentate gyrus compared with the inferior temporal gyrus and lateral occipitotemporal gyrus. Mean cluster size of PB in a brain region was positively correlated with the mean density of PB. Hence, PB exhibit essentially the same spatial patterns as senile plaques and neurofibrillary tangles in Alzheimer's disease (AD) and Lewy bodies in Dementia with Lewy bodies (DLB).
Resumo:
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.
Resumo:
Counts of Pick bodies (PB), Pick cells (PC), senile plaques (SP) and neurofibrillary tangles (NFT) were made in the frontal and temporal cortex from patients with Pick's disease (PD). Lesions were stained histologically with hematoxylin and eosin (HE) and the Bielschowsky silver impregnation method and labeled immunohistochemically with antibodies raised to ubiquitin and tau. The greatest numbers of PB were revealed by immunohistochemistry. Counts of PB revealed by ubiquitin and tau were highly positively correlated which suggested that the two antibodies recognized virtually identical populations of PB. The greatest numbers of PC were revealed by HE followed by the anti-ubiquitin antibody. However, the correlation between counts was poor, suggesting that HE and ubiquitin revealed different populations of PC. The greatest numbers of SP and NFT were revealed by the Bielschowsky method indicating the presence of Alzheimer-type lesions not revealed by the immunohistochemistry. In addition, more NFT were revealed by the anti-ubiquitin compared with the anti-tau antibody. The data suggested that in PD: (i) the anti-ubiquitin and anti-tau antibodies were equally effective at labeling PB; (ii) both HE and anti-ubiquitin should be used to quantitate PC; and (iii) the Bielschowsky method should be used to quantitate SP and NFT.