Multivariate gene expression analysis reveals functional connectivity changes between normal/tumoral prostates

Abstract Background Prostate cancer is a leading cause of death in the male population, therefore, a comprehensive study about the genes and the molecular networks involved in the tumoral prostate process becomes necessary. In order to understand the biological process behind potential biomarkers, we have analyzed a set of 57 cDNA microarrays containing ~25,000 genes. Results Principal Component Analysis (PCA) combined with the Maximum-entropy Linear Discriminant Analysis (MLDA) were applied in order to identify genes with the most discriminative information between normal and tumoral prostatic tissues. Data analysis was carried out using three different approaches, namely: (i) differences in gene expression levels between normal and tumoral conditions from an univariate point of view; (ii) in a multivariate fashion using MLDA; and (iii) with a dependence network approach. Our results show that malignant transformation in the prostatic tissue is more related to functional connectivity changes in their dependence networks than to differential gene expression. The MYLK, KLK2, KLK3, HAN11, LTF, CSRP1 and TGM4 genes presented significant changes in their functional connectivity between normal and tumoral conditions and were also classified as the top seven most informative genes for the prostate cancer genesis process by our discriminant analysis. Moreover, among the identified genes we found classically known biomarkers and genes which are closely related to tumoral prostate, such as KLK3 and KLK2 and several other potential ones. Conclusion We have demonstrated that changes in functional connectivity may be implicit in the biological process which renders some genes more informative to discriminate between normal and tumoral conditions. Using the proposed method, namely, MLDA, in order to analyze the multivariate characteristic of genes, it was possible to capture the changes in dependence networks which are related to cell transformation.

Increased vertebral morphometric fracture in patients with postsurgical hypoparathyroidism despite normal bone mineral density

Background In human malaria, the naturally-acquired immune response can result in either the elimination of the parasite or a persistent response mediated by cytokines that leads to immunopathology. The cytokines are responsible for all the symptoms, pathological alterations and the outcome of the infection depends on the reciprocal regulation of the pro and anti-inflammatory cytokines. IL-10 and IFN-gamma are able to mediate this process and their production can be affected by single nucleotide polymorphisms (SNPs) on gene of these cytokines. In this study, the relationship between cytokine IL-10/IFN-gamma levels, parasitaemia, and their gene polymorphisms was examined and the participation of pro-inflammatory and regulatory balance during a natural immune response in Plasmodium vivax-infected individuals was observed. Methods The serum levels of the cytokines IL-4, IL-12, IFN-gamma and IL-10 from 132 patients were evaluated by indirect enzyme-linked immunosorbent assays (ELISA). The polymorphism at position +874 of the IFN-gamma gene was identified by allele-specific polymerase chain reaction (ASO-PCR) method, and the polymorphism at position -1082 of the IL-10 gene was analysed by PCR-RFLP (PCR-Restriction Fragment Length Polymorphism). Results The levels of a pro- (IFN-gamma) and an anti-inflammatory cytokine (IL-10) were significantly higher in P. vivax-infected individuals as compared to healthy controls. The IFN-gamma levels in primoinfected patients were significantly higher than in patients who had suffered only one and more than one previous episode. The mutant alleles of both IFN-gamma and IL-10 genes were more frequent than the wild allele. In the case of the IFNG+874 polymorphism (IFN-gamma) the frequencies of the mutant (A) and wild (T) alleles were 70.13% and 29.87%, respectively. Similar frequencies were recorded in IL-10-1082, with the mutant (A) allele returning a frequency of 70.78%, and the wild (G) allele a frequency of 29.22%. The frequencies of the alleles associated with reduced production of both IFN-gamma and IL-10 were high, but this effect was only observed in the production of IFN-gamma. Conclusions This study has shown evidence of reciprocal regulation of the levels of IL-10 and IFN-gamma cytokines in P. vivax malaria, which is not altered by the presence of polymorphism in the IL-10 gene.

Metabolism of plasma cholesterol and lipoprotein parameters are related to a higher degree of insulin sensitivity in high HDL-C healthy normal weight subjects

Abstract Background We have searched if plasma high density lipoprotein-cholesterol (HDL-C) concentration interferes simultaneously with whole-body cholesterol metabolism and insulin sensitivity in normal weight healthy adult subjects. Methods We have measured the activities of several plasma components that are critically influenced by insulin and that control lipoprotein metabolism in subjects with low and high HDL-C concentrations. These parameters included cholesteryl ester transfer protein (CETP), phospholipid transfer protein (PLTP), lecithin cholesterol acyl transferase (LCAT), post-heparin lipoprotein lipase (LPL), hepatic lipase (HL), pre-beta-1HDL, and plasma sterol markers of cholesterol synthesis and intestinal absorption. Results In the high-HDL-C group, we found lower plasma concentrations of triglycerides, alanine aminotransferase, insulin, HOMA-IR index, activities of LCAT and HL compared with the low HDL-C group; additionally, we found higher activity of LPL and pre-beta-1HDL concentration in the high-HDL-C group. There were no differences in the plasma CETP and PLTP activities. Conclusions These findings indicate that in healthy hyperalphalipoproteinemia subjects, several parameters that control the metabolism of plasma cholesterol and lipoproteins are related to a higher degree of insulin sensitivity.

Parallel modeling of the electric field distribution in the brain

The term "Brain Imaging" identi�es a set of techniques to analyze the structure and/or functional behavior of the brain in normal and/or pathological situations. These techniques are largely used in the study of brain activity. In addition to clinical usage, analysis of brain activity is gaining popularity in others recent �fields, i.e. Brain Computer Interfaces (BCI) and the study of cognitive processes. In this context, usage of classical solutions (e.g. f MRI, PET-CT) could be unfeasible, due to their low temporal resolution, high cost and limited portability. For these reasons alternative low cost techniques are object of research, typically based on simple recording hardware and on intensive data elaboration process. Typical examples are ElectroEncephaloGraphy (EEG) and Electrical Impedance Tomography (EIT), where electric potential at the patient's scalp is recorded by high impedance electrodes. In EEG potentials are directly generated from neuronal activity, while in EIT by the injection of small currents at the scalp. To retrieve meaningful insights on brain activity from measurements, EIT and EEG relies on detailed knowledge of the underlying electrical properties of the body. This is obtained from numerical models of the electric �field distribution therein. The inhomogeneous and anisotropic electric properties of human tissues make accurate modeling and simulation very challenging, leading to a tradeo�ff between physical accuracy and technical feasibility, which currently severely limits the capabilities of these techniques. Moreover elaboration of data recorded requires usage of regularization techniques computationally intensive, which influences the application with heavy temporal constraints (such as BCI). This work focuses on the parallel implementation of a work-flow for EEG and EIT data processing. The resulting software is accelerated using multi-core GPUs, in order to provide solution in reasonable times and address requirements of real-time BCI systems, without over-simplifying the complexity and accuracy of the head models.

Implications of regional fault distribution and kinematics for the uplift of rift flanks around the Rwenzori Mountains, Southwestern Uganda

Das Ziel dieser Arbeit bestand in der Untersuchung der Störungsverteilung und der Störungskinematik im Zusammenhang mit der Hebung der Riftschultern des Rwenzori Gebirges.rnDas Rwenzori Gebirge befindet sich im NNE-SSWbis N-S verlaufenden Albertine Rift, des nördlichsten Segments des westlichen Armes des Ostafrikanischen Grabensystems. Das Albertine Rift besteht aus Becken unterschiedlicher Höhe, die den Lake Albert, Lake Edward, Lake George und Lake Kivu enthalten. Der Rwenzori horst trennt die Becken des Lake Albert und des Lake Edward. Es erstreckt sich 120km in N-S Richtung, sowie 40-50km in E-W Richtung, der h¨ochste Punkt befindet sich 5111 ü. NN. Diese Studie untersucht einen Abschnitt des Rifts zwischen etwa 1°N und 0°30'S Breite sowie 29°30' und 30°30' östlicher Länge ersteckt. Auch die Feldarbeit konzentrierte sich auf dieses Gebiet.rnrnHauptzweck dieser Studie bestand darin, die folgende These auf ihre Richtigkeit zu überprüfen: ’Wenn es im Verlauf der Zeit tatsächlich zu wesentlichen Änderungen in der Störungskinematik kam, dann ist die starke Hebung der Riftflanken im Bereich der Rwenzoris nicht einfach durch Bewegung entlang der Graben-Hauptst¨orungen zu erklären. Vielmehr ist sie ein Resultat des Zusammenspiels mehrerer tektonische Prozesse, die das Spannungsfeld beeinflussen und dadurch Änderungen in der Kinematik hervorrufen.’ Dadurch konzentrierte sich die Studie in erster Linie auf die Störungsanalyse.rnrnDie Kenntnis regionaler Änderungen der Extensionsrichtung ist entscheidend für das Verständnis komplexer Riftsysteme wie dem Ostafrikanischen Graben. Daher bestand der Kern der Untersuchung in der Kartierung von Störungen und der Untersuchung der Störungskinematik. Die Aufnahme strukturgeologischer Daten konzentrierte sich auf die Ugandische Seite des Rifts, und Pal¨aospannungen wurden mit Hilfe von St¨orungsdaten durch Spannungsinversion rekonstruiert.rnDie unterschiedliche Orientierung spr¨oder Strukturen im Gelände, die geometrische Analyse der geologischen Strukturen sowie die Ergebnisse von Mikrostrukturen im Dünnschliff (Kapitel 4) weisen auf verschiedene Spannungsfelder hin, die auf mögliche Änderungen der Extensionsrichtung hinweisen. Die Resultate der Spannungsinversion sprechen für Ab-, Über- und Blattverschiebungen sowie für Schrägüberschiebungen (Kapitel 5). Aus der Orientierung der Abschiebungen gehen zwei verschiedene Extensionsrichtungen hervor: im Wesentlichen NW-SE Extension in fast allen Gebieten, sowie NNE-SSW Extension im östlichen Zentralbereich.rnAus der Analyse von Blattverschiebungen ergaben sich drei unterschiedliche Spannungszustände. Zum Einen NNW-SSE bis N-S Kompression in Verbindung mit ENE-WSW bzw E-W Extension wurde für die nördlichen und die zentralen Ruwenzoris ausgemacht. Ein zweiter Spannungszustand mit WNW-ESE Kompression/NNE-SSW Extension betraf die Zentralen Rwenzoris. Ein dritter Spannungszustand mit NNW-SSE Extension betraf den östlichen Zentralteil der Rwenzoris. Schrägüberschiebungen sind durch dazu schräge Achsen charakterisiert, die für N-S bis NNW-SSE Kompression sprechen und ausschließlich im östlichen Zentralabschnitt auftreten. Überschiebungen, die hauptsächlich in den zentralen und den östlichen Rwenzoris auftreten, sprechen für NE-SW orientierten σ2-Achsen und NW-SE Extension.rnrnEs konnten drei unterschiedliche Spannungseinflüsse identifiziert werden: auf die kollisionsbedingte Bildung eines Überschiebungssystem folgte intra-kratonische Kompression und schließlich extensionskontrollierte Riftbildung. Der Übergang zwischen den beiden letztgenannten Spannungszuständen erfolgte Schrittweise und erzeugte vermutlich lokal begrenzte Transpression und Transtension. Gegenw¨artig wird die Störungskinematik der Region durch ein tensiles Spannungsregime in NW-SE bis N-S Richtung bestimmt.rnrnLokale Spannungsvariationen werden dabei hauptsächlich durch die Interferenzrndes regionalen Spannungsfeldes mit lokalen Hauptst¨orungen verursacht. Weitere Faktoren die zu lokalen Veränderungen des Spannungsfeldes führen können sind unterschiedliche Hebungsgeschwindigkeiten, Blockrotation oder die Interaktion von Riftsegmenten. Um den Einfluß präexistenter Strukturen und anderer Bedingungen auf die Hebung der Rwenzoris zu ermitteln, wurde der Riftprozeß mit Hilfe eines analogen ’Sandbox’-Modells rekonstruiert (Kapitel 6). Da sich die Moho-Diskontinuität im Bereich des Arbeitsgebietes in einer Tiefe von 25 km befindet, aktive Störungen aber nur bis zu einer Tiefe von etwa 20 km beobachtet werden können (Koehn et al. 2008), wurden nur die oberen 25 km im Modell nachbebildet. Untersucht und mit Geländebeobachtungen verglichen wurden sowohl die Reihenfolge, in der Riftsegmente entstehen, als auch die Muster, die sich im Verlauf der Nukleierung und des Wachstums dieser Riftsegmente ausbilden. Das Hauptaugenmerk wurde auf die Entwicklung der beiden Subsegmente gelegt auf denen sich der Lake Albert bzw. der Lake Edward und der Lake George befinden, sowie auf das dazwischenliegende Rwenzori Gebirge. Das Ziel der Untersuchung bestand darin herauszufinden, in welcher Weise das südwärts propagierende Lake Albert-Subsegment mit dem sinistral versetzten nordwärts propagierenden Lake Edward/Lake George-Subsegment interagiert.rnrnVon besonderem Interesse war es, in welcherWeise die Strukturen innerhalb und außerhalb der Rwenzoris durch die Interaktion dieser Riftsegmente beeinflußt wurden. rnrnDrei verschiedene Versuchsreihen mit unterschiedlichen Randbedingungen wurden miteinander verglichen. Abhängig vom vorherrschenden Deformationstyp der Transferzone wurden die Reihen als ’Scherungs-dominiert’, ’Extensions-dominiert’ und als ’Rotations-dominiert’ charakterisiert. Die Beobachtung der 3-dimensionalen strukturellen Entwicklung der Riftsegmente wurde durch die Kombination von Modell-Aufsichten mit Profilschnitten ermöglicht. Von den drei genannten Versuchsreihen entwickelte die ’Rotationsdominierten’ Reihe einen rautenförmiger Block im Tranferbereich der beiden Riftsegmente, der sich um 5−20° im Uhrzeigersinn drehte. DieserWinkel liegt im Bereich des vermuteten Rotationswinkel des Rwenzori-Blocks (5°). Zusammengefasst untersuchen die Sandbox-Versuche den Einfluss präexistenter Strukturen und der Überlappung bzw. Überschneidung zweier interagierender Riftsegmente auf die Entwicklung des Riftsystems. Sie befassen sich darüber hinaus mit der Frage, welchen Einfluss Blockbildung und -rotation auf das lokale Stressfeld haben.

Cardiogoniometric parameters for detection of coronary artery disease at rest as a function of stenosis localization and distribution

Cardiogoniometry (CGM), a spatiotemporal electrocardiologic 5-lead method with automated analysis, may be useful in primary healthcare for detecting coronary artery disease (CAD) at rest. Our aim was to systematically develop a stenosis-specific parameter set for global CAD detection. In 793 consecutively admitted patients with presumed non-acute CAD, CGM data were collected prior to elective coronary angiography and analyzed retrospectively. 658 patients fulfilled the inclusion criteria, 405 had CAD verified by coronary angiography; the 253 patients with normal coronary angiograms served as the non-CAD controls. Study patients--matched for age, BMI, and gender--were angiographically assigned to 8 stenosis-specific CAD categories or to the controls. One CGM parameter possessing significance (P < .05) and the best diagnostic accuracy was matched to one CAD category. The area under the ROC curve was .80 (global CAD versus controls). A set containing 8 stenosis-specific CGM parameters described variability of R vectors and R-T angles, spatial position and potential distribution of R/T vectors, and ST/T segment alterations. Our parameter set systematically combines CAD categories into an algorithm that detects CAD globally. Prospective validation in clinical studies is ongoing.

Evaluation of radial distribution of cartilage degeneration and necessity of pre-contrast measurements using radial dGEMRIC in adults with acetabular dysplasia

Background The purpose of the present study was to investigate the radial distribution patterns of cartilage degeneration in dysplastic hips at different stages of secondary osteoarthritis (OA) by using radial delayed gadolinium-enhanced magnetic resonance imaging of cartilage (dGEMRIC), and to assess whether pre-contrast measurements are necessary. Methods Thirty-five hips in 21 subjects (mean age ± SD, 27.6 ± 10.8 years) with acetabular dysplasia (lateral CE angle < 25°) were studied. Severity of OA was assessed on radiographs using Tönnis grading. Pre- (T1pre) and post-contrast T1 (T1Gd) values were measured at 7 sub-regions on radial reformatted slices acquired from a 3-dimensional (3D) T1 mapping sequence using a 1.5 T MR scanner. Values of radial T1pre, T1Gd and ΔR1 (1/T1Gd - 1/T1pre) of subgroups with different severity of OA were compared to those of the subgroup without OA using nonparametric tests, and bivariate linear Pearson correlations between radial T1Gd and ΔR1 were analyzed for each subgroup. Results Compared to the subgroup without OA, the subgroup with mild OA was observed with a significant decrease in T1Gd in the anterosuperior to superior sub-regions (mean, 476 ~ 507 ms, p = 0.026 ~ 0.042) and a significant increase in ΔR1 in the anterosuperior to superoposterior and posterior sub-regions (mean, 0.93 ~ 1.37 s-1, p = 0.012 ~ 0.042). The subgroup with moderate to severe OA was observed with a significant overall decrease in T1Gd (mean, 404 ~ 452 ms, p = 0.001 ~ 0.020) and an increase in ΔR1 (mean, 1.17 ~1.69 s-1, p = 0.001 ~ 0.020). High correlations were observed between radial T1Gd and ΔR1 for all subgroups (r = −0.869 ~ −0.944, p < 0.001). Conclusions Radial dGEMRIC without pre-contrast measurements is useful for evaluating different patterns of cartilage degeneration in the entire hip joint of patients with hip dysplasia, particularly for those in early stages of secondary OA.

Influence of end-expiratory level and tidal volume on gravitational ventilation distribution during tidal breathing in healthy adults

Our understanding of regional filling of the lung and regional ventilation distribution is based on studies using stepwise inhalation of radiolabelled tracer gases, magnetic resonance imaging and positron emission tomography. We aimed to investigate whether these differences in ventilation distribution at different end-expiratory levels (EELs) and tidal volumes (V (T)s) held also true during tidal breathing. Electrical impedance tomography (EIT) measurements were performed in ten healthy adults in the right lateral position. Five different EELs with four different V (T)s at each EEL were tested in random order, resulting in 19 combinations. There were no measurements for the combination of the highest EEL/highest V (T). EEL and V (T) were controlled by visual feedback based on airflow. The fraction of ventilation directed to different slices of the lung (VENT(RL1)-VENT(RL8)) and the rate of the regional filling of each slice versus the total lung were analysed. With increasing EEL but normal tidal volume, ventilation was preferentially distributed to the dependent lung and the filling of the right and left lung was more homogeneous. With increasing V (T) and maintained normal EEL (FRC), ventilation was preferentially distributed to the dependent lung and regional filling became more inhomogeneous (p < 0.05). We could demonstrate that regional and temporal ventilation distribution during tidal breathing was highly influenced by EEL and V (T).

Impact of del32-71-GH (exon 3 skipped GH) on intracellular GH distribution, secretion and cell viability: a quantitative confocal microscopy analysis

BACKGROUND: Familial isolated growth hormone deficiency (IGHD) is a disorder with about 5-30% of patients having affected relatives. Among those familial types, IGHD type II is an autosomal dominant form of short stature, associated in some families with mutations that result in missplicing to produce del32-71-GH, a GH peptide which cannot fold properly. The mechanism by which this mutant GH may alter the controlled secretory pathway and therefore suppress the secretion of the normal 22-kDa GH product of the normal allele is not known in detail. Previous studies have shown variance depending on cell type, transfection technique used, as well as on the method of analysis performed. AIM: The aim of our study was to analyse and compare the subcellular distribution/localization of del32-71-GH or wild-type (wt)-GH (22-kDa GH), each stably transfected into AtT-20, a mouse pituitary cell line endogenously producing ACTH, employed as the internal control for secretion assessment. METHODS: Colocalization of wt- and del32-71 mutant GH form was studied by quantitative confocal microscopy analysis. Using the immunofluorescent technique, cells were double stained for GH plus one of the following organelles: endoplasmic reticulum (ER anti-Grp94), Golgi (anti-betaCOP) or secretory granules (anti-Rab3a). In addition, GH secretion and cell viability were analysed in detail. RESULTS/CONCLUSIONS: Our results show that in AtT-20 neuroendocrine cells, in comparison to the wt-GH, the del32-71-GH has a major impact on the secretory pathway not only affecting GH but also other peptides such as ACTH. The del32-71-GH is still present at the secretory vesicles' level, albeit in reduced quantity when compared to wt-GH but, importantly, was secretion-deficient. Furthermore, while focusing on cell viability an additional finding presented that the various splice site mutations, even though leading eventually to the same end product, namely del32-71-GH, have different and specific consequences on cell viability and proliferation rate.

A Functional-Based Distribution Diagnostic for a Linear Model with Correlated Outcomes: Technical Report

Despite the widespread popularity of linear models for correlated outcomes (e.g. linear mixed modesl and time series models), distribution diagnostic methodology remains relatively underdeveloped in this context. In this paper we present an easy-to-implement approach that lends itself to graphical displays of model fit. Our approach involves multiplying the estimated marginal residual vector by the Cholesky decomposition of the inverse of the estimated marginal variance matrix. Linear functions or the resulting "rotated" residuals are used to construct an empirical cumulative distribution function (ECDF), whose stochastic limit is characterized. We describe a resampling technique that serves as a computationally efficient parametric bootstrap for generating representatives of the stochastic limit of the ECDF. Through functionals, such representatives are used to construct global tests for the hypothesis of normal margional errors. In addition, we demonstrate that the ECDF of the predicted random effects, as described by Lange and Ryan (1989), can be formulated as a special case of our approach. Thus, our method supports both omnibus and directed tests. Our method works well in a variety of circumstances, including models having independent units of sampling (clustered data) and models for which all observations are correlated (e.g., a single time series).

Cholesky Residuals for Assessing Normal Errors in a Linear Model with Correlated Outcomes: Technical Report

Despite the widespread popularity of linear models for correlated outcomes (e.g. linear mixed models and time series models), distribution diagnostic methodology remains relatively underdeveloped in this context. In this paper we present an easy-to-implement approach that lends itself to graphical displays of model fit. Our approach involves multiplying the estimated margional residual vector by the Cholesky decomposition of the inverse of the estimated margional variance matrix. The resulting "rotated" residuals are used to construct an empirical cumulative distribution function and pointwise standard errors. The theoretical framework, including conditions and asymptotic properties, involves technical details that are motivated by Lange and Ryan (1989), Pierce (1982), and Randles (1982). Our method appears to work well in a variety of circumstances, including models having independent units of sampling (clustered data) and models for which all observations are correlated (e.g., a single time series). Our methods can produce satisfactory results even for models that do not satisfy all of the technical conditions stated in our theory.

Semiparametric Normal Transformation Models for Spatially Correlated Survival Data

There is an emerging interest in modeling spatially correlated survival data in biomedical and epidemiological studies. In this paper, we propose a new class of semiparametric normal transformation models for right censored spatially correlated survival data. This class of models assumes that survival outcomes marginally follow a Cox proportional hazard model with unspecified baseline hazard, and their joint distribution is obtained by transforming survival outcomes to normal random variables, whose joint distribution is assumed to be multivariate normal with a spatial correlation structure. A key feature of the class of semiparametric normal transformation models is that it provides a rich class of spatial survival models where regression coefficients have population average interpretation and the spatial dependence of survival times is conveniently modeled using the transformed variables by flexible normal random fields. We study the relationship of the spatial correlation structure of the transformed normal variables and the dependence measures of the original survival times. Direct nonparametric maximum likelihood estimation in such models is practically prohibited due to the high dimensional intractable integration of the likelihood function and the infinite dimensional nuisance baseline hazard parameter. We hence develop a class of spatial semiparametric estimating equations, which conveniently estimate the population-level regression coefficients and the dependence parameters simultaneously. We study the asymptotic properties of the proposed estimators, and show that they are consistent and asymptotically normal. The proposed method is illustrated with an analysis of data from the East Boston Ashma Study and its performance is evaluated using simulations.

Distribution of amyloid precursor protein and amyloid-beta immunoreactivity in DBA/2J glaucomatous mouse retinas

PURPOSE: Evidence suggests that altered metabolism of amyloid precursor protein (APP) may play a role in the pathophysiology of retinal ganglion cell (RGC) death in the etiology of glaucoma. The authors sought to determine the distribution of APP and amyloid-beta (Abeta) in DBA/2J glaucomatous mouse retinas. METHODS: The retinas of 3- and 15-month-old DBA/2J mice and C57/BL-6 mice (control group) were fixed with 4% paraformaldehyde and processed for immunohistochemistry. Antibodies used included a polyclonal antibody to the C terminus of Abeta 40 and a polyclonal antibody to the APP ectodomain. Immunohistochemically stained tissue was graded using light microscopy. Distribution and semiquantitative expression of APP and Abeta in young and old glaucomatous and normal retinas were determined and compared. RESULTS: Strong APP and Abeta immunoreactivity was found in the RGC layer, optic nerve, and pia/dura of old DBA/2J retinas, with considerably higher intensity found in the old compared with the young DBA/2J mice. In contrast to glaucomatous mice, the control group did not show any notable age-related difference. CONCLUSIONS: Disruption of the homeostatic properties of secreted APP with consecutive Abeta cytotoxicity might be a contributing factor of ganglion cell loss in glaucomatous mouse retinas.

Online distribution management framework by incorporating wind generation

In distribution system operations, dispatchers at control center closely monitor system operating limits to ensure system reliability and adequacy. This reliability is partly due to the provision of remote controllable tie and sectionalizing switches. While the stochastic nature of wind generation can impact the level of wind energy penetration in the network, an estimate of the output from wind on hourly basis can be extremely useful. Under any operating conditions, the switching actions require human intervention and can be an extremely stressful task. Currently, handling a set of switching combinations with the uncertainty of distributed wind generation as part of the decision variables has been nonexistent. This thesis proposes a three-fold online management framework: (1) prediction of wind speed, (2) estimation of wind generation capacity, and (3) enumeration of feasible switching combinations. The proposed methodology is evaluated on 29-node test system with 8 remote controllable switches and two wind farms of 18MW and 9MW nameplate capacities respectively for generating the sequence of system reconfiguration states during normal and emergency conditions.

Bayesian change-point analysis in linear regression model with scale mixtures of normal distributions

In this thesis, we consider Bayesian inference on the detection of variance change-point models with scale mixtures of normal (for short SMN) distributions. This class of distributions is symmetric and thick-tailed and includes as special cases: Gaussian, Student-t, contaminated normal, and slash distributions. The proposed models provide greater flexibility to analyze a lot of practical data, which often show heavy-tail and may not satisfy the normal assumption. As to the Bayesian analysis, we specify some prior distributions for the unknown parameters in the variance change-point models with the SMN distributions. Due to the complexity of the joint posterior distribution, we propose an efficient Gibbs-type with Metropolis- Hastings sampling algorithm for posterior Bayesian inference. Thereafter, following the idea of [1], we consider the problems of the single and multiple change-point detections. The performance of the proposed procedures is illustrated and analyzed by simulation studies. A real application to the closing price data of U.S. stock market has been analyzed for illustrative purposes.