A model selection approach to discover age-dependent gene expression patterns using quantile regression models

<p>Abstract</p> <p>Background</p> <p>It has been a long-standing biological challenge to understand the molecular regulatory mechanisms behind mammalian ageing. Harnessing the availability of many ageing microarray datasets, a number of studies have shown that it is possible to identify genes that have age-dependent differential expression (DE) or differential variability (DV) patterns. The majority of the studies identify "interesting" genes using a linear regression approach, which is known to perform poorly in the presence of outliers or if the underlying age-dependent pattern is non-linear. Clearly a more robust and flexible approach is needed to identify genes with various age-dependent gene expression patterns.</p> <p>Results</p> <p>Here we present a novel model selection approach to discover genes with linear or non-linear age-dependent gene expression patterns from microarray data. To identify DE genes, our method fits three quantile regression models (constant, linear and piecewise linear models) to the expression profile of each gene, and selects the least complex model that best fits the available data. Similarly, DV genes are identified by fitting and comparing two quantile regression models (non-DV and the DV models) to the expression profile of each gene. We show that our approach is much more robust than the standard linear regression approach in discovering age-dependent patterns. We also applied our approach to analyze two human brain ageing datasets and found many biologically interesting gene expression patterns, including some very interesting DV patterns, that have been overlooked in the original studies. Furthermore, we propose that our model selection approach can be extended to discover DE and DV genes from microarray datasets with discrete class labels, by considering different quantile regression models.</p> <p>Conclusion</p> <p>In this paper, we present a novel application of quantile regression models to identify genes that have interesting linear or non-linear age-dependent expression patterns. One important contribution of this paper is to introduce a model selection approach to DE and DV gene identification, which is most commonly tackled by null hypothesis testing approaches. We show that our approach is robust in analyzing real and simulated datasets. We believe that our approach is applicable in many ageing or time-series data analysis tasks.</p

An Antibody-Based Leukocyte-Capture Microarray for the Diagnosis of Systemic Lupus Erythematosus

The diagnosis of Systemic Lupus Erythematosus (SLE) is challenging due to its heterogeneous clinical presentation and the lack of robust biomarkers to distinguish it from other autoimmune diseases. Further, currently used laboratory tests do not readily distinguish active and inactive disease. Several groups have attempted to apply emerging high throughput profiling technologies to diagnose and monitor SLE. Despite showing promise, many are expensive and technically challenging for routine clinical use. The goal of this work is to develop a better diagnostic and monitoring tool for SLE. We report a highly customisable antibody microarray that consists of a duplicate arrangement of 82 antibodies directed against surface antigens on peripheral blood mononuclear cells (PMBCs). This high-throughput array was used to profile SLE patients (n = 60) with varying disease activity, compared to healthy controls (n = 24), patients with rheumatoid arthritis (n = 25), and other autoimmune diseases (n = 28). We used a computational algorithm to calculate a score from the entire microarray profile and correlated it with SLE disease activity. Our results demonstrate that leukocyte-capture microarray profiles can readily distinguish active SLE patients from healthy controls (AUROC = 0.84). When combined with the standard laboratory tests (serum anti-dsDNA, complements C3 and C4), the microarrays provide significantly increased discrimination. The antibody microarrays can be enhanced by the addition of other markers for potential application to the diagnosis and stratification of SLE, paving the way for the customised and accurate diagnosis and monitoring of SLE

Transcriptomic Comparison of Human Peripartum and Dilated Cardiomyopathy Identifies Differences in Key Disease Pathways

Peripartum cardiomyopathy (PPCM) is a rare form of acute onset heart failure that presents in otherwise healthy pregnant women around the time of delivery. While most of these women respond to early intervention, about 20% progress to end-stage heart failure that symptomatically resembles dilated cardiomyopathy (DCM). In this study, we examined two independent RNAseq datasets from the left ventricle of end-stage PPCM patients and compared gene expression profiles to female DCM and non-failing donors. Differential gene expression, enrichment analysis and cellular deconvolution were performed to identify key processes in disease pathology. PPCM and DCM display similar enrichment in metabolic pathways and extracellular matrix remodeling suggesting these are similar processes across end-stage systolic heart failure. Genes involved in golgi vesicles biogenesis and budding were enriched in PPCM left ventricles compared to healthy donors but were not found in DCM. Furthermore, changes in immune cell populations are evident in PPCM but to a lesser extent compared to DCM, where the latter is associated with pronounced pro-inflammatory and cytotoxic T cell activity. This study reveals several pathways that are common to end-stage heart failure but also identifies potential targets of disease that may be unique to PPCM and DCM.</p

The microtubule signature in cardiac disease:etiology, disease stage, and age dependency

Employing animal models to study heart failure (HF) has become indispensable to discover and test novel therapies, but their translatability remains challenging. Although cytoskeletal alterations are linked to HF, the tubulin signature of common experimental models has been incompletely defined. Here, we assessed the tubulin signature in a large set of human cardiac samples and myocardium of animal models with cardiac remodeling caused by pressure overload, myocardial infarction or a gene defect. We studied levels of total, acetylated, and detyrosinated α-tubulin and desmin in cardiac tissue from hypertrophic (HCM) and dilated cardiomyopathy (DCM) patients with an idiopathic (n = 7), ischemic (n = 7) or genetic origin (n = 59), and in a pressure-overload concentric hypertrophic pig model (n = 32), pigs with a myocardial infarction (n = 28), mature pigs (n = 6), and mice (n = 15) carrying the HCM-associated MYBPC3 2373insG mutation. In the human samples, detyrosinated α-tubulin was increased 4-fold in end-stage HCM and 14-fold in pediatric DCM patients. Acetylated α-tubulin was increased twofold in ischemic patients. Across different animal models, the tubulin signature remained mostly unaltered. Only mature pigs were characterized by a 0.5-fold decrease in levels of total, acetylated, and detyrosinated α-tubulin. Moreover, we showed increased desmin levels in biopsies from NYHA class II HCM patients (2.5-fold) and the pressure-overload pig model (0.2–0.3-fold). Together, our data suggest that desmin levels increase early on in concentric hypertrophy and that animal models only partially recapitulate the proliferated and modified tubulin signature observed clinically. Our data warrant careful consideration when studying maladaptive responses to changes in the tubulin content in animal models. Graphical Abstract: [Figure not available: see fulltext.].</p

Source Coding Optimization for Distributed Average Consensus

Consensus is a common method for computing a function of the data distributed among the nodes of a network. Of particular interest is distributed average consensus, whereby the nodes iteratively compute the sample average of the data stored at all the nodes of the network using only near-neighbor communications. In real-world scenarios, these communications must undergo quantization, which introduces distortion to the internode messages. In this thesis, a model for the evolution of the network state statistics at each iteration is developed under the assumptions of Gaussian data and additive quantization error. It is shown that minimization of the communication load in terms of aggregate source coding rate can be posed as a generalized geometric program, for which an equivalent convex optimization can efficiently solve for the global minimum. Optimization procedures are developed for rate-distortion-optimal vector quantization, uniform entropy-coded scalar quantization, and fixed-rate uniform quantization. Numerical results demonstrate the performance of these approaches. For small numbers of iterations, the fixed-rate optimizations are verified using exhaustive search. Comparison to the prior art suggests competitive performance under certain circumstances but strongly motivates the incorporation of more sophisticated coding strategies, such as differential, predictive, or Wyner-Ziv coding.Comment: Master's Thesis, Electrical Engineering, North Carolina State Universit

Estruturação dos objetivos de aprendizagem para ambientes de educação on-line

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-Graduação em Ciência da Computação.O objetivo deste trabalho é prover o processo e a avaliação funcional dos componentes que compõem um ambiente de e-aprendizagem baseado em Objetos de aprendizagem, apresentando as definições, propriedades e aplicações dos Objetos de aprendizagem, que se referem à criação e reutilização dos objetos para desenvolver ambientes de aprendizagem. Os padrões utilizados para desenvolvimento de conteúdos estruturados para ambientes de aprendizagem para Web também serão descritos. Também é abordado o potencial da Web semântica, a qual transforma a Web em um meio em que a informação é interpretada, trocada e processada. Apresentar como a linguagem XML e a orientação a objeto se relacionam com os Objetos de aprendizagem é outro tópico abordado. O trabalho inclui, ainda, um protótipo para um ambiente de aprendizagem online utilizando os objetos de aprendizagem