159 resultados para Canonical Correlation Analysis
Resumo:
Migraine is a common complex disorder characterized by severe recurrent headache and usually accompanied by nausea and vomiting. Previous studies in our laboratory have utilized three large multigenerational Australian pedigrees affected with migraine to indicate that the disease is genetically heterogeneous, with linkage results implicating genomic susceptibility regions on both chromosomes 19p and Xq. The present study explores the possibility of a correlation between genetic and clinical heterogeneity in these affected pedigrees. Specifically, the clinical characteristics of migraine including subtype, age of onset, frequency, duration, and disease symptoms were compared between the migraine pedigrees, and gender differences were also assessed. Our exploratory analyses revealed no significant differences in any of the clinical characteristics tested between the chromosome 19-linked family and the two X-linked families. Also, we did not detect any differences in male vs. female clinical features for these pedigrees. In conclusion, migraine is considered to be a clinically and genetically heterogeneous disorder; however, our study provided no conclusive evidence that variation in genomic susceptibility region is related to heterogeneity at the clinical level in these migraine-affected pedigrees.
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In our laboratory we have developed a quantitative-polymerase chain reaction (Q-PCR) strategy to examine the differential expression of adenosine receptor (ADOR), A(1), A(2A), A(2B) and A(3), and estrogen receptors (ER) alpha and beta. Brain and uterine mRNA were first used to optimise specific amplification conditions prior to SYBR Green I real time analysis of receptor subtype expression. SYBR Green I provided a convenient and sensitive means of examining specific PCR amplification product in real time, and allowed the generation of standard curves from which relative receptor abundance could be determined. Real time Q-PCR analysis was then performed, to examine changes in receptor expression levels in brains of adult female Wistar rats 3-month post ovariectomy. Comparison with sham-operated age-matched control rats demonstrated both comparative and absolute-copy number changes in receptor levels. Evaluation of both analytical methods investigated 18S rRNA as an internal reference for comparative gene expression analysis in the brain. The results of this study revealed preferential repression of ADORA(2A) (>4-fold down) and consistent (>2-fold) down-regulation of ADORA(1), ADORA(3), and ER-beta, following ovariectomy. No change was found in ADORA(2B) or ER-alpha. Analysis of absolute copy number in this study revealed a correlation between receptor expression in response to ovariectomy, and relative receptor subtype abundance in the brain.
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The quality of dried food is affected by a number of factors including quality of raw material, initial microstructure, and drying conditions. The structure of the food materials goes through deformations due to the simultaneous effect of heat and mass transfer during the drying process. Shrinkage and changes in porosity, microstructure and appearance are some of the most remarkable features that directly influence overall product quality. Porosity and microstructure are the important material properties in relation to the quality attributes of dried foods. Fractal dimension (FD) is a quantitative approach of measuring surface, pore characteristics, and microstructural changes [1]. However, in the field of fractal analysis, there is a lack of research in developing relationship between porosity, shrinkage and microstructure of different solid food materials in different drying process and conditions [2-4]. Establishing a correlation between microstructure and porosity through fractal dimension during convective drying is the main objective of this work.
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The method of generalized estimating equations (GEE) is a popular tool for analysing longitudinal (panel) data. Often, the covariates collected are time-dependent in nature, for example, age, relapse status, monthly income. When using GEE to analyse longitudinal data with time-dependent covariates, crucial assumptions about the covariates are necessary for valid inferences to be drawn. When those assumptions do not hold or cannot be verified, Pepe and Anderson (1994, Communications in Statistics, Simulations and Computation 23, 939–951) advocated using an independence working correlation assumption in the GEE model as a robust approach. However, using GEE with the independence correlation assumption may lead to significant efficiency loss (Fitzmaurice, 1995, Biometrics 51, 309–317). In this article, we propose a method that extracts additional information from the estimating equations that are excluded by the independence assumption. The method always includes the estimating equations under the independence assumption and the contribution from the remaining estimating equations is weighted according to the likelihood of each equation being a consistent estimating equation and the information it carries. We apply the method to a longitudinal study of the health of a group of Filipino children.
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This paper provides details on comparative testing of axle-to-chassis forces of two heavy vehicles (HVs) based on an experimental programme carried out in 2007. Dynamic forces at the air springs were measured against speed and roughness values for the test roads used. One goal of that programme was to determine whether dynamic axle-to-chassis forces could be reduced by using larger-than-standard diameter longitudinal air lines. This paper presents a portion of the methodology, analysis and results from that programme. Two analytical techniques and their results are presented. The first uses correlation coefficients of the forces between air springs and the second is a student’s t-test. These were used to determine the causality surrounding improved dynamic load sharing between heavy vehicle air springs with larger air lines installed longitudinally compared with the standard sized air lines installed on the majority of air-sprung heavy vehicles.
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Background Tumour necrosis (TN) is recognized to be a consequence of chronic cellular hypoxia. TN and hypoxia correlate with poor prognosis in solid tumours. Methods In a retrospective study the prognostic implications of the extent of TN was evaluated in non-small cell lung cancer (NSCLC) and correlated with clinicopathological variables and expression of epidermal growth factor receptor, Bcl-2, p53 and matrix metalloproteinase-9 (MMP-9). Tissue specimens from 178 surgically resected cases of stage I-IIIA NSCLC with curative intent were studied. The specimens were routinely processed, formalin-fixed and paraffin-embedded. TN was graded as extensive or either limited or absent by two independent observers; disagreements were resolved using a double-headed microscope. The degree of reproducibility was estimated by re-interpreting 40 randomly selected cases after a 4 month interval. Results Reproducibility was attained in 36/40 cases, Kappa score=0.8 P<0.001. TN correlated with T-stage (P=0.001), platelet count (P=0.004) and p53 expression (P=0.031). Near significant associations of TN with N-stage (P=0.063) and MMP-9 expression (P=0.058) were seen. No association was found with angiogenesis (P=0.98). On univariate (P=0.0016) and multivariate analysis (P=0.023) TN was prognostic. Conclusion These results indicate that extensive TN reflects an aggressive tumour phenotype in NSCLC and may improve the predictive power of the TMN staging system. The lack of association between TN and angiogenesis may be important although these variables were not evaluated on serial sections. © 2002 Elsevier Science Ireland Ltd. All rights reserved.
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The non-canonical Wnt pathway, a regulator of cellular motility and morphology, is increasingly implicated in cancer metastasis. In a quantitative PCR array analysis of 84 Wnt pathway associated genes, both non-canonical and canonical pathways were activated in primary and metastatic tumors relative to normal prostate. Expression of the Wnt target gene PITX2 in a prostate cancer (PCa) bone metastasis was strikingly elevated over normal prostate (over 2,000-fold) and primary prostate cancer (over 200-fold). The elevation of PITX2 protein was also evident on tissue microarrays, with strong PITX2 immunostaining in PCa skeletal and, to a lesser degree, soft tissue metastases. PITX2 is associated with cell migration during normal tissue morphogenesis. In our studies, overexpression of individual PITX2A/B/C isoforms stimulated PC-3 PCa cell motility, with the PITX2A isoform imparting a specific motility advantage in the presence of non-canonical Wnt5a stimulation. Furthermore, PITX2 specific shRNA inhibited PC-3 cell migration toward bone cell derived chemoattractant. These experimental results support a pivotal role of PITX2A and non-canonical Wnt signaling in enhancement of PCa cell motility, suggest PITX2 involvement in homing of PCa to the skeleton, and are consistent with a role for PITX2 in PCa metastasis to soft and bone tissues. Our findings, which significantly expand previous evidence that PITX2 is associated with risk of PCa biochemical recurrence, indicate that variation in PITX2 expression accompanies and may promote prostate tumor progression and metastasis.
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Nitrous oxide (N2O) is one of the greenhouse gases that can contribute to global warming. Spatial variability of N2O can lead to large uncertainties in prediction. However, previous studies have often ignored the spatial dependency to quantify the N2O - environmental factors relationships. Few researches have examined the impacts of various spatial correlation structures (e.g. independence, distance-based and neighbourhood based) on spatial prediction of N2O emissions. This study aimed to assess the impact of three spatial correlation structures on spatial predictions and calibrate the spatial prediction using Bayesian model averaging (BMA) based on replicated, irregular point-referenced data. The data were measured in 17 chambers randomly placed across a 271 m(2) field between October 2007 and September 2008 in the southeast of Australia. We used a Bayesian geostatistical model and a Bayesian spatial conditional autoregressive (CAR) model to investigate and accommodate spatial dependency, and to estimate the effects of environmental variables on N2O emissions across the study site. We compared these with a Bayesian regression model with independent errors. The three approaches resulted in different derived maps of spatial prediction of N2O emissions. We found that incorporating spatial dependency in the model not only substantially improved predictions of N2O emission from soil, but also better quantified uncertainties of soil parameters in the study. The hybrid model structure obtained by BMA improved the accuracy of spatial prediction of N2O emissions across this study region.
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Most persistent organic pollutants (POPs) like polychlorinated biphenyls (PCBs), a range of polybrominated diphenyl ethers (PBDEs) and organochlorine pesticides (OCPs) are readily absorbed (via the ingestion and inhalation) and accumulate in fatty tissue, including adipose tissue and human milk [1]. Health effects related to exposure to these chemicals may include neurological effects, altered functioning of the nervous system and/or endocrine disruption [2-4]. The burden of environmental disease is recognized as much higher for children than adults, especially in young children under 5 years of age worldwide [5]. There is increased concern regarding the environmental impact on the health of children who have been disproportionately affected by environmental problems. For example they may be subjected to relatively higher exposure, have greater physiological susceptibility and/or suffer more extreme consequences due to growth [6-9]. It is therefore worthwhile to assess the correlation between burden of disease and exposure to xenobiotic chemical pollutants like POPs. Such assessment may provide guidance for legislative changes regarding chemical bans and give reliable advice to parents including lactating mothers.
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For a planetary rover to successfully traverse across unstructured terrain autonomously, one of the major challenges is to assess its local traversability such that it can plan a trajectory to achieve its mission goals efficiently while minimising risk to the vehicle itself. This paper aims to provide a comparative study on different approaches for representing the geometry of Martian terrain for the purpose of evaluating terrain traversability. An accurate representation of the geometric properties of the terrain is essential as it can directly affect the determination of traversability for a ground vehicle. We explore current state-of-the-art techniques for terrain estimation, in particular Gaussian Processes (GP) in various forms, and discuss the suitability of each technique in the context of an unstructured Martian terrain. Furthermore, we present the limitations of regression techniques in terms of spatial correlation and continuity assumptions, and the impact on traversability analysis of a planetary rover across unstructured terrain. The analysis was performed on datasets of the Mars Yard at the Powerhouse Museum in Sydney, obtained using the onboard RGB-D camera.
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Many cell types form clumps or aggregates when cultured in vitro through a variety of mechanisms including rapid cell proliferation, chemotaxis, or direct cell-to-cell contact. In this paper we develop an agent-based model to explore the formation of aggregates in cultures where cells are initially distributed uniformly, at random, on a two-dimensional substrate. Our model includes unbiased random cell motion, together with two mechanisms which can produce cell aggregates: (i) rapid cell proliferation, and (ii) a biased cell motility mechanism where cells can sense other cells within a finite range, and will tend to move towards areas with higher numbers of cells. We then introduce a pair-correlation function which allows us to quantify aspects of the spatial patterns produced by our agent-based model. In particular, these pair-correlation functions are able to detect differences between domains populated uniformly at random (i.e. at the exclusion complete spatial randomness (ECSR) state) and those where the proliferation and biased motion rules have been employed - even when such differences are not obvious to the naked eye. The pair-correlation function can also detect the emergence of a characteristic inter-aggregate distance which occurs when the biased motion mechanism is dominant, and is not observed when cell proliferation is the main mechanism of aggregate formation. This suggests that applying the pair-correlation function to experimental images of cell aggregates may provide information about the mechanism associated with observed aggregates. As a proof of concept, we perform such analysis for images of cancer cell aggregates, which are known to be associated with rapid proliferation. The results of our analysis are consistent with the predictions of the proliferation-based simulations, which supports the potential usefulness of pair correlation functions for providing insight into the mechanisms of aggregate formation.
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Computer vision is increasingly becoming interested in the rapid estimation of object detectors. The canonical strategy of using Hard Negative Mining to train a Support Vector Machine is slow, since the large negative set must be traversed at least once per detector. Recent work has demonstrated that, with an assumption of signal stationarity, Linear Discriminant Analysis is able to learn comparable detectors without ever revisiting the negative set. Even with this insight, the time to learn a detector can still be on the order of minutes. Correlation filters, on the other hand, can produce a detector in under a second. However, this involves the unnatural assumption that the statistics are periodic, and requires the negative set to be re-sampled per detector size. These two methods differ chie y in the structure which they impose on the co- variance matrix of all examples. This paper is a comparative study which develops techniques (i) to assume periodic statistics without needing to revisit the negative set and (ii) to accelerate the estimation of detectors with aperiodic statistics. It is experimentally verified that periodicity is detrimental.
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Orthotopic or intracardiac injection of human breast cancer cell lines into immunocompromised mice allows study of the molecular basis of breast cancer metastasis. We have established a quantitative real-time PCR approach to analyze metastatic spread of human breast cancer cells inoculated into nude mice via these routes. We employed MDA-MB-231 human breast cancer cells genetically tagged with a bacterial β-galactosidase (Lac-Z) retroviral vector, enabling their detection by TaqMan® real-time PCR. PCR detection was linear, specific, more sensitive than conventional PCR, and could be used to directly quantitate metastatic burden in bone and soft organs. Attesting to the sensitivity and specificity of the PCR detection strategy, as few as several hundred metastatic MDA-MB-231 cells were detectable in 100 μm segments of paraffin-embedded lung tissue, and only in samples adjacent to sections that scored positive by histological detection. Moreover, the measured real-time PCR metastatic burden in the bone environment (mouse hind-limbs, n = 48) displayed a high correlation to the degree of osteolytic damage observed by high resolution X-ray analysis (r2 = 0.972). Such a direct linear relationship to tumor burden and bone damage substantiates the so-called 'vicious cycle' hypothesis in which metastatic tumor cells promote the release of factors from the bone which continue to stimulate the tumor cells. The technique provides a useful tool for molecular and cellular analysis of human breast cancer metastasis to bone and soft organs, can easily be extended to other cell/marker/organ systems, and should also find application in preclinical assessment of anti-metastatic modalities.
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In the present study, we examined a panel of human breast cancer cell lines with regard to their expression of CD44 and ability to bind and degrade hyaluronan. The cell lines expressed varying amounts of different molecular weight forms of CD44 (85-200 kDa) and, in general, those that expressed the greatest amounts of CD44 were the most invasive as judged by in vitro assays. In addition, the ability to bind and degrade hyaluronan was restricted to the cell lines expressing high levels of CD44, and both these functions were blocked by an antibody to CD44 (Hermes-1). Moreover, the rate of [3H]hyaluronan degradation was highly correlated with the amount of CD44 (r = 0.951, P < 0.0001), as well as with the invasive potential of the cells. Scatchard analysis of the [3H]hyaluronan binding of these cells revealed the existence of significant differences in both their binding capacity and their dissociation constant. To determine the source of this deviation, the different molecular weight forms of CD44 were partially separated by gel filtration chromatography. In all cell lines, the 85 kDa form was able to bind hyaluronan, although with different affinities. In contrast, not all of the high molecular weight forms of CD44 had this ability. These results illustrate the diversity of CD44 molecules in invasive tumor cells, and suggest that one of their major functions is to degrade hyaluronan.
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Differential settlement at the bridge approach between the deck and rail track on ground is often considered as a source of challenging technical and economical problem. This caused by the sudden stiffness changes between the bridge deck and the track on ground, and changes in soil stiffness of backfill and sub-grade with soil moisture content and loading history. To minimise the negative social and economic impacts due to poor performances of railway tracks at bridge transition zones, it is important, a special attention to be given at design, construction and maintenance stages. It is critically challenging to obtain an appropriate design solution for any given site condition and most of the existing conventional design approaches are unable to address the actual on-site behaviour due to their inherent assumptions of continuity and lack of clarifying of the local effects. An evaluation of existing design techniques is considered to estimate their contributions to a potential solution for bridge transition zones. This paper analyses five different approaches: the Chinese Standard, the European Standard with three different approaches, and the Australian approach. Each design approach is used to calculate the layer thicknesses, accounting critical design features such as the train speed, the axle load, the backfill subgrade condition, and the dynamic loading response. Considering correlation between track degradation and design parameters, this paper concludes that there is still a need of an optimised design approach for bridge transition zones.