Quantitative analysis of senile plaques in Alzheimer disease: observation of log-normal size distribution and molecular epidemiology of differences associated with apolipoprotein E genotype and trisomy 21 (Down syndrome).

The discovery that the epsilon 4 allele of the apolipoprotein E (apoE) gene is a putative risk factor for Alzheimer disease (AD) in the general population has highlighted the role of genetic influences in this extremely common and disabling illness. It has long been recognized that another genetic abnormality, trisomy 21 (Down syndrome), is associated with early and severe development of AD neuropathological lesions. It remains a challenge, however, to understand how these facts relate to the pathological changes in the brains of AD patients. We used computerized image analysis to examine the size distribution of one of the characteristic neuropathological lesions in AD, deposits of A beta peptide in senile plaques (SPs). Surprisingly, we find that a log-normal distribution fits the SP size distribution quite well, motivating a porous model of SP morphogenesis. We then analyzed SP size distribution curves in genotypically defined subgroups of AD patients. The data demonstrate that both apoE epsilon 4/AD and trisomy 21/AD lead to increased amyloid deposition, but by apparently different mechanisms. The size distribution curve is shifted toward larger plaques in trisomy 21/AD, probably reflecting increased A beta production. In apoE epsilon 4/AD, the size distribution is unchanged but the number of SP is increased compared to apoE epsilon 3, suggesting increased probability of SP initiation. These results demonstrate that subgroups of AD patients defined on the basis of molecular characteristics have quantitatively different neuropathological phenotypes.

Caracterização tecnológica do minério de ouro da Mina Morro do Ouro - Paracatu, MG.

As unidades de beneficiamento de minério de ouro buscam cada vez mais uma produção de baixo custo e maximização dos ganhos financeiros. A caracterização tecnológica está inserida em uma abordagem multidisciplinar que permite agregar conhecimento, alternativas de otimização e redução nos custos de operação. Inserida como uma ferramenta na caracterização tecnológica, a análise de imagens automatizada tem importante papel no setor mineral principalmente pela rapidez das análises, robustez estatística e confiabilidade nos resultados. A técnica pode ser realizada por meio de imagens adquiridas em microscópio eletrônico de varredura, associada a microanálises químicas sendo utilizada em diversas etapas de um empreendimento mineiro. Este estudo tem como objetivo a caraterização tecnológica de minério de ouro da Mina Morro do Ouro, Minas Gerais na qual foi utilizado a técnica de análise de imagens automatizada por MLA em um conjunto de 88 amostras. Foi possível identificar que 90% do ouro está na fração acima de 0,020 mm; o quartzo e mica representam cerca de 80% da massa total do minério; os sulfetos apresentam diâmetro de círculo equivalente entre 80 e 100 ?m e são representados por pirita e arsenopirita, com pirrotita, calcopirita, esfalerita e galena subordinada. Também foi possível observar que o ouro está majoritariamente associado à pirita e arsenopirita e com o aumento de teor de arsênio, cresce a parcela de ouro associado à arsenopirita. As medianas das distribuições de tamanho dos grãos de ouro apresentam um valor médio de 19 ?m. Verificou-se que a composição dos grãos de ouro é bastante diversa, em média 77% de ouro e 23% de prata. Para material abaixo de 0,50 mm observa-se uma parcela expressiva de perímetro exposto dos grãos de ouro (média 73%); o ouro incluso (21% do total dos grãos de ouro) está associado a pirita e arsenopirita, sendo que em 14 das 88 amostras este valor pode superar 40% do total de ouro contido. A ferramenta da análise de imagens automatizada mostrou-se bastante eficiente definindo características particulares o que fornece de forma objetiva subsídios para os trabalhos de planejamento de mina e processamento mineral.

Caracterização tecnológica de minérios auríferos por análise automatizada de imagens obtidas por microscopia eletrônica de varredura.

O ouro, assim como outros bens minerais, é uma commodity, ou seja, um produto não diferenciado, com preço determinado pelo mercado internacional, sem a interferência de seus produtores. Diante desse cenário, associado à exaustão dos depósitos minerais de maiores teores, as mineradoras vêm buscando melhores formas de aproveitamento de matérias-primas minerais mais complexas quanto à extração e ao beneficiamento. Os retornos financeiros são obtidos no estrito controle da produção com redução de custos e mitigação de perdas nas operações unitárias. A caracterização tecnológica está inserida como uma abordagem multidisciplinar e fundamental para o melhor aproveitamento dos bens minerais. Possibilita um maior conhecimento do minério e das associações minerais presentes, que auxiliará no desenvolvimento das alternativas de explotação e na otimização do processo em funcionamento. Dentre os procedimentos de caracterização das associações minerais mais acurados citam-se os sistemas automatizados de análise de imagens adquiridas por microscopia eletrônica de varredura. Permitem a avaliação qualitativa ou quantitativa de grande número de partículas quanto à composição química e mineral, partição de elementos nos minerais presentes, formas de associações e liberação entre os minerais. Este estudo se concentra na caracterização de quatro amostras mineralizadas a ouro, de diferentes regiões do Brasil, pela análise automatizada de imagens e por métodos laboratoriais de separações minerais e extração hidrometalúrgica do ouro. A combinação de procedimentos laboratoriais com a análise de imagens permitiu confrontar os resultados das recuperações potenciais, fornecendo subsídios para abordagens de processo, para obtenção da máxima recuperação do ouro e para diagnosticar as características interferentes nesses processos.

Changes in the Photoreceptor Mosaic of P23H-1 Rats During Retinal Degeneration: Implications for Rod-Cone Dependent Survival

Purpose. To investigate the spatiotemporal relationship between rod and cone degeneration in the P23H-1 rat. Methods. Control Sprague-Dawley (SD) and P23H-1 rats of ages ranging from P30 to P365 were used. Retinas were processed for whole mounts or cross sections and rods and cones were immunodetected. We used newly developed image analysis techniques to quantify the total population of L/M cones (the most abundant cones in the rat) and analyzed the rings of rod-cone degeneration. Results. In P23H-1 rats, rod degeneration occurs rapidly: first the rod outer segment shortens, at P30 there is extensive rod loss, and by P180 rod loss is almost complete except for the most peripheral retina. The numbers of L/M cones are, at all postnatal ages, lower in P23H-1 rats than in control SD rats, and decrease significantly with age (by P180). Rod and cone degeneration is spatiotemporally related and occurs in rings that appear already at P90 and spread throughout the entire retina. At P180, the rings of rod-cone degeneration are more abundant in the equatorial retina and are larger in the dorsal retina. Conclusions. This work describes for the first time that in the P23H-1 rat, rod and cone degeneration is spatiotemporally related and occurs in rings. Cone loss follows rod loss and starts very soon, even before P30, the first age analyzed here. The characteristics of the rings suggest that secondary cone degeneration is influenced by retinal position and/or other intrinsic or extrinsic factors.

Human Behaviour Recognition based on Trajectory Analysis using Neural Networks

Automated human behaviour analysis has been, and still remains, a challenging problem. It has been dealt from different points of views: from primitive actions to human interaction recognition. This paper is focused on trajectory analysis which allows a simple high level understanding of complex human behaviour. It is proposed a novel representation method of trajectory data, called Activity Description Vector (ADV) based on the number of occurrences of a person is in a specific point of the scenario and the local movements that perform in it. The ADV is calculated for each cell of the scenario in which it is spatially sampled obtaining a cue for different clustering methods. The ADV representation has been tested as the input of several classic classifiers and compared to other approaches using CAVIAR dataset sequences obtaining great accuracy in the recognition of the behaviour of people in a Shopping Centre.

A Cloud-based Framework for Security Analysis of Browser Extensions

In today's internet world, web browsers are an integral part of our day-to-day activities. Therefore, web browser security is a serious concern for all of us. Browsers can be breached in different ways. Because of the over privileged access, extensions are responsible for many security issues. Browser vendors try to keep safe extensions in their official extension galleries. However, their security control measures are not always effective and adequate. The distribution of unsafe extensions through different social engineering techniques is also a very common practice. Therefore, before installation, users should thoroughly analyze the security of browser extensions. Extensions are not only available for desktop browsers, but many mobile browsers, for example, Firefox for Android and UC browser for Android, are also furnished with extension features. Mobile devices have various resource constraints in terms of computational capabilities, power, network bandwidth, etc. Hence, conventional extension security analysis techniques cannot be efficiently used by end users to examine mobile browser extension security issues. To overcome the inadequacies of the existing approaches, we propose CLOUBEX, a CLOUd-based security analysis framework for both desktop and mobile Browser EXtensions. This framework uses a client-server architecture model. In this framework, compute-intensive security analysis tasks are generally executed in a high-speed computing server hosted in a cloud environment. CLOUBEX is also enriched with a number of essential features, such as client-side analysis, requirements-driven analysis, high performance, and dynamic decision making. At present, the Firefox extension ecosystem is most susceptible to different security attacks. Hence, the framework is implemented for the security analysis of the Firefox desktop and Firefox for Android mobile browser extensions. A static taint analysis is used to identify malicious information flows in the Firefox extensions. In CLOUBEX, there are three analysis modes. A dynamic decision making algorithm assists us to select the best option based on some important parameters, such as the processing speed of a client device and network connection speed. Using the best analysis mode, performance and power consumption are improved significantly. In the future, this framework can be leveraged for the security analysis of other desktop and mobile browser extensions, too.

New Techniques in Deep Representation Learning

Thesis (Ph.D.)--University of Washington, 2016-06

Proteome analysis of extracellular proteins regulated by the las and rhl quorum sensing systems in Pseudomonas aeruginosa PAO1

The las and rhl quorum sensing (QS) systems regulate the expression of several genes in response to cell density changes in Pseudomonas aeruginosa. Many of these genes encode surface-associated or secreted virulence factors. Proteins from stationary phase culture supernatants were collected from wild-type and P. aeruginosa PAO1 mutants deficient in one or more of the lasRI, rhIRI and vfr genes and analysed using two-dimensional gel electrophoresis. All mutants released significantly lower amounts of protein than the wild-type. Protein spot patterns from each strain were compared using image analysis and visible spot differences were identified using mass spectrometry. Several previously unknown OS-regulated proteins were characterized, including an aminopeptidase (PA2939), an endoproteinase (PrpL) and a unique 'hypothetical' protein (PA0572), which could not be detected in the culture supernatants of Delta/as mutants, although they were unaffected in Deltarhl mutants. Chitin-binding protein (CbpD) and a hypothetical protein (PA4944) with similarity to host factor I (HF-1) could not be detected when any of the lasRI or rhIRI genes were disrupted. Fourteen proteins were present at significantly greater levels in the culture supernatants of OS mutants, suggesting that QS may also negatively control the expression of some genes. Increased levels of two-partner secretion exoproteins (PA0041 and PA4625) were observed and may be linked to increased stability of their cognate transporters in a CS-defective background. Known QS-regulated extracellular proteins, including elastase (lasB), LasA protease (lasA) and alkaline metalloproteinase (aprA) were also detected.

Function and Regulation of Cytochrome P450 4V2 and the Implications in Bietti’s Crystalline Dystrophy

Thesis (Ph.D.)--University of Washington, 2016-06

Fracture load and marginal fit of shrinkage-free ZrSiO4 all-ceramic crowns after chewing simulation

The aim of this in vitro study was to evaluate the fracture load and marginal accuracy of crowns made from a shrinkage-free ZrSiO4 ceramic cemented with glass-ionomer or composite cement after chewing simulation. Thirty-two human mandibular molars were randomly divided into two groups. All teeth were prepared for and restored with shrinkage-free ZrSiO4 ceramic crowns (Everest HPC (R), KaVo). The crowns of group A (N = 16) were luted to the teeth using KetacCem (R) and group B (N = 16) were adhesively cemented using Panavia (R) 21EX. Measurements of the marginal accuracy before and after cementation were made using replicas and an image analysis system. All specimens were exposed to 1.2 million cycles of thermo-mechanical fatigue in a chewing simulator. Surviving specimens were subsequently loaded until fracture in a static testing device. Fracture loads (N) were recorded. All specimens survived chewing simulation. The mean fracture loads (+/- s.d.) were Group A, 1622 N (+/- 433); group B, 1957 N (+/- 806). There was no significant difference between the two groups (P > 0.05). The marginal gap values before cementation were (mean +/- s.d.): Group A, 32.7 mu m (+/- 6.8); group B, 33.0 mu m (+/- 6.7).The mean marginal gap values after cementation were (+/- s.d.): Group A, 44.6 mu m (+/- 6.7); group B, 46.6 mu m (+/- 7.7). The marginal openings were significantly higher after cementation for both groups (P < 0.05). All test groups demonstrated fracture load and marginal accuracy values within the range of clinical acceptability.

An electrical heart model incorporating real geometry and motion

Abstract—This paper describes an electrical model of the ventricles incorporating real geometry and motion. Cardiac geometry and motion is obtained from segmentations of multipleslice MRI time sequences. A static heart model developed previously is deformed to match the observed geometry using a novel shape registration algorithm. The resulting electrocardiograms and body surface potential maps are compared to a static simulation in the resting heart. These results demonstrate that introducing motion into the cardiac model modifies the ECG during the T wave at peak contraction of the ventricles.

Training Bayesian networks for image segmentation

We are concerned with the problem of image segmentation in which each pixel is assigned to one of a predefined finite number of classes. In Bayesian image analysis, this requires fusing together local predictions for the class labels with a prior model of segmentations. Markov Random Fields (MRFs) have been used to incorporate some of this prior knowledge, but this not entirely satisfactory as inference in MRFs is NP-hard. The multiscale quadtree model of Bouman and Shapiro (1994) is an attractive alternative, as this is a tree-structured belief network in which inference can be carried out in linear time (Pearl 1988). It is an hierarchical model where the bottom-level nodes are pixels, and higher levels correspond to downsampled versions of the image. The conditional-probability tables (CPTs) in the belief network encode the knowledge of how the levels interact. In this paper we discuss two methods of learning the CPTs given training data, using (a) maximum likelihood and the EM algorithm and (b) emphconditional maximum likelihood (CML). Segmentations obtained using networks trained by CML show a statistically-significant improvement in performance on synthetic images. We also demonstrate the methods on a real-world outdoor-scene segmentation task.

Use of fundus imaging in quantification of age-related macular change

This review will discuss the use of manual grading scales, digital photography, and automated image analysis in the quantification of fundus changes caused by age-related macular disease. Digital imaging permits processing of images for enhancement, comparison, and feature quantification, and these techniques have been investigated for automated drusen analysis. The accuracy of automated analysis systems has been enhanced by the incorporation of interactive elements, such that the user is able to adjust the sensitivity of the system, or manually add and remove pixels. These methods capitalize on both computer and human image feature recognition and the advantage of computer-based methodologies for quantification. The histogram-based adaptive local thresholding system is able to extract useful information from the image without being affected by the presence of other structures. More recent developments involve compensation for fundus background reflectance, which has most recently been combined with the Otsu method of global thresholding. This method is reported to provide results comparable with manual stereo viewing. Developments in this area are likely to encourage wider use of automated techniques. This will make the grading of photographs easier and cheaper for clinicians and researchers. © 2007 Elsevier Inc. All rights reserved.

Objective analysis of toric intraocular lens rotation and centration

PURPOSE: To assess the repeatability of an objective image analysis technique to determine intraocular lens (IOL) rotation and centration. SETTING: Six ophthalmology clinics across Europe. METHODS: One-hundred seven patients implanted with Akreos AO aspheric IOLs with orientation marks were imaged. Image quality was rated by a masked observer. The axis of rotation was determined from a line bisecting the IOL orientation marks. This was normalized for rotation of the eye between visits using the axis bisecting 2 consistent conjunctival vessels or iris features. The center of ovals overlaid to circumscribe the IOL optic edge and the pupil or limbus were compared to determine IOL centration. Intrasession repeatability was assessed in 40 eyes and the variability of repeated analysis examined. RESULTS: Intrasession rotational stability of the IOL was ±0.79 degrees (SD) and centration was ±0.10 mm horizontally and ±0.10 mm vertically. Repeated analysis variability of the same image was ±0.70 degrees for rotation and ±0.20 mm horizontally and ±0.31 mm vertically for centration. Eye rotation (absolute) between visits was 2.23 ± 1.84 degrees (10%>5 degrees rotation) using one set of consistent conjunctival vessels or iris features and 2.03 ± 1.66 degrees (7%>5 degrees rotation) using the average of 2 sets (P =.13). Poorer image quality resulted in larger apparent absolute IOL rotation (r =-0.45,P<.001). CONCLUSIONS: Objective analysis of digital retroillumination images allows sensitive assessment of IOL rotation and centration stability. Eye rotation between images can lead to significant errors if not taken into account. Image quality is important to analysis accuracy.

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.