Genetic and Epigenomic Modifiers of Diabetic Neuropathy

Diabetic neuropathy (DN), the most common chronic and progressive complication of diabetes mellitus (DM), strongly affects patients’ quality of life. DN could be present as peripheral, autonomous or, clinically also relevant, uremic neuropathy. The etiopathogenesis of DN is multifactorial, and genetic components play a role both in its occurrence and clinical course. A number of gene polymorphisms in candidate genes have been assessed as susceptibility factors for DN, and most of them are linked to mechanisms such as reactive oxygen species production, neurovascular impairments and modified protein glycosylation, as well as immunomodulation and inflammation. Different epigenomic mechanisms such as DNA methylation, histone modifications and non-coding RNA action have been studied in DN, which also underline the importance of “metabolic memory” in DN appearance and progression. In this review, we summarize most of the relevant data in the field of genetics and epigenomics of DN, hoping they will become significant for diagnosis, therapy and prevention of DN.     

Region-Based Hierarchical Image Matching

This paper presents an approach to region-based hierarchical image matching, where, given two images, the goal is to identify the largest part in image 1 and its match in image 2 having the maximum similarity measure defined in terms of geometric and photometric properties of regions (e.g., area, boundary shape, and color), as well as region topology (e.g., recursive embedding of regions). To this end, each image is represented by a tree of recursively embedded regions, obtained by a multiscale segmentation algorithm. This allows us to pose image matching as the tree matching problem. To overcome imaging noise, one-to-one, many-to-one, and many-to-many node correspondences are allowed. The trees are first augmented with new nodes generated by merging adjacent sibling nodes, which produces directed acyclic graphs (DAGs). Then, transitive closures of the DAGs are constructed, and the tree matching problem reformulated as finding a bijection between the two transitive closures on DAGs, while preserving the connectivity and ancestor-descendant relationships of the original trees. The proposed approach is validated on real images showing similar objects, captured under different types of noise, including differences in lighting conditions, scales, or viewpoints, amidst limited occlusion and clutter.     

A normal distribution for tensor-valued random variables: applications to diffusion tensor MRI

Diffusion tensor magnetic resonance imaging (DT-MRI) provides a statistical estimate of a symmetric, second-order diffusion tensor of water, D, in each voxel within an imaging volume. We propose a new normal distribution, p(D) alpha exp(-1/2 D: A: D), which describes the variability of D in an ideal DT-MRI experiment. The scalar invariant, D : A : D, is the contraction of a positive definite symmetric, fourth-order precision tensor, A, and D. A correspondence is established between D: A: D and the elastic strain energy density function in continuum mechanics--specifically between D and the second-order infinitesimal strain tensor, and between A and the fourth-order tensor of elastic coefficients. We show that A can be further classified according to different classical elastic symmetries (i.e., isotropy, transverse isotropy, orthotropy, planar symmetry, and anisotropy). When A is an isotropic fourth-order tensor, we derive an explicit analytic expression for p(D), and for the distribution of the three eigenvalues of D, p(gamma1, gamma2, gamma3), which are confirmed by Monte Carlo simulations. We show how A can be estimated from either real or synthetic DT-MRI data for any given experimental design. Here we propose a new criterion for an optimal experimental design: that A be an isotropic fourth-order tensor. This condition ensures that the statistical properties of D (and quantities derived from it) are rotationally invariant. We also investigate the degree of isotropy of several DT-MRI experimental designs. Finally, we show that the univariate and multivariate distributions are special cases of the more general tensor-variate normal distribution, and suggest how to generalize p(D) to treat normal random tensor variables that are of third- (or higher) order. We expect that this new distribution, p(D), should be useful in feature extraction; in developing a hypothesis testing framework for segmenting and classifying noisy, discrete tensor data; and in designing experiments to measure tensor quantities.     

Increasing the Robustness of Boosting Algorithms within the Linear-programming Framework

AdaBoost has been successfully used in many signal classification systems. However, it has been observed that on highly noisy data AdaBoost easily leads to overfitting, which seriously constrains its applicability. In this paper, we address this problem by proposing a new regularized boosting algorithm LP_norm2-AdaBoost (LPNA). This algorithm arises from a close connection between AdaBoost and linear programming. In the algorithm, skewness of the data distribution is controlled during the training to prevent outliers from spoiling decision boundaries. To this end, a smooth convex penalty function (l ₂ norm) is introduced in the objective function of a minimax problem. A stabilized column generation technique is used to transform the optimization problem into a simple linear programming problem. The effectiveness of the proposed algorithm is demonstrated through experiments on many diverse datasets.     

Heat acclimation and the role of RpoS in prolonged heat shock of Escherichia coli O157

Escherichia coli, a commensal mesophile that primarily inhabits the gastro-intestinal tract, responds to temperature up-shifts with transient expression of stress-response proteins. The goal of this study was to identify adaptive proteins of E. coli O157 crucial for growth resumption of this human pathogen after heat shock, with specific focus on the role of the RpoS sigma factor. Using the comparative proteomic analysis of hyper-thermally acclimatized wild-type strain B-1 and rpoS-mutant strain SV521, we identified 39 proteins that underwent significantly-different induction upon temperature shock at 45°C or rpoS mutation. All identified proteins of the heat post-acclimation stimulon fell into two large sub-groups: (i) stress proteins, including molecular chaperons, proteases, DNA/RNA stabilizing enzymes, and anti-oxidant proteins, and (ii) housekeeping proteins. It was found that in the heat stress stimulon RpoS has significantly (P=0.012) limited control over the key stress proteins involved in translation, translational elongation, protein folding and refolding. However, RpoS showed a significant (P=0.035) control over the cellular metabolic processes that included NADPH regeneration, pentose-phosphate shunt, nicotinamide nucleotide and NADP metabolic processes, reflecting its specific importance in promoting resource utilization (energy, protein synthesis etc.) during proliferation of hyperthermally-adapted cells. Pathogenic strains, like E. coli O157, have the ability to survive a variety of harsh stress conditions, leading to their entry into the food chain, and subsequent pathogenesis. This research offers insights into the physiological response of this pathogen during the critical period following adaptation to thermal stress and subsequent resumption of growth.     

Current Concepts on Genetic Aspects of Mitochondrial Dysfunction in Amyotrophic Lateral Sclerosis

Amyotrophic Lateral Sclerosis (ALS), neurodegenerative motor neuron disorder is characterized as multisystem disease with important contribution of genetic factors. The etiopahogenesis of ALS is not fully elucidate, but the dominant theory at present relates to RNA processing, as well as protein aggregation and miss-folding, oxidative stress, glutamate excitotoxicity, inflammation and epigenetic dysregulation. Additionally, as mitochondria plays a leading role in cellular homeostasis maintenance, a rising amount of evidence indicates mitochondrial dysfunction as a substantial contributor to disease onset and progression. The aim of this review is to summarize most relevant findings that link genetic factors in ALS pathogenesis with different mechanisms with mitochondrial involvement (respiratory chain, OXPHOS control, calcium buffering, axonal transport, inflammation, mitophagy, etc.). We highlight the importance of a widening perspective for better understanding overlapping pathophysiological pathways in ALS and neurodegeneration in general. Finally, current and potentially novel therapies, especially gene specific therapies, targeting mitochondrial dysfunction are discussed briefly.     

Testosterone treatment in men with erectile disorder and low levels of total testosterone in serum

Since decreased serum levels of testosterone (T) do not necessarily predict good outcome of testosterone treatment for erectile disorder, the purpose, of this study was to determine which men with erectile disorder and decreased serum levels might benefit from treatment. From a sample of 31 men (mean age = 39 years), 15 (48%) with erectile disorder and decreased serum levels of T responded well after 8 weeks of testosterone treatment (100 mg of testosterone propionate in the sustained-release form given im once a week). Good treatment outcome was associated with several variables, but only high levels of luteinizing hormone (LH) and low values of the T/LH (testosterone/LH) ratio consistently emerged as significant correlates and/or predictors of effective treatment. Levels of LH above 7.5 IU/L or the values of the T/LH ratio equal to or below 0.87 nmol/IU in patients with erectile disorder and decreased serum levels of T suggest that testosterone treatment may be effective.