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.     

Ratio between carcass-and skin-microflora as an abattoir process hygiene indicator

In two abattoirs, each slaughtering both cattle and pigs, 100 cattle and 100 pigs were randomly selected and sampled. From each animal, two samples were taken: a) immediately after sticking of bovines or stunning of pigs, approximately 2000 cm² hide (cattle) or 1500 cm² skin (pigs) areas were sponge-swabbed; and b) at the end of slaughter line but before chilling, the same areas on corresponding dressed carcasses were sponge-swabbed. In each swab-sample (400 in total), total viable count (TVC) and Enterobacteriaceae count (EC), as well as Escherichia coli O157 (in cattle) or Salmonella (in pigs) occurrence, were determined and used to assess process hygiene in the abattoirs. The results indicated that simply fitting mean TVC and/or EC on final carcasses into an acceptable, marginal or unacceptable process hygiene category (according to current microbiological EU process hygiene criteria) did not enable characterisation of each process with respect to its ability to reduce the transfer of incoming microbial loads (i.e. on skins) onto dressed carcasses. On the other hand, determining the ratio between mean TVC and/or EC on final carcasses and those on corresponding skins enabled more precise assessment of the hygiene of each abattoir process, as well as more reliable differentiation between abattoirs. On the other hand, occurrence of E. coli O157 in cattle or Salmonella in pigs (skins and/or carcasses), being dependant on varying factors including those on-farm/pre-abattoir, did not appear to be very useful for characterisation of the process hygiene but is valuable for the purposes of consumer exposure assessment and pathogen reduction.     

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.     

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.     

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.     

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.     

Prolonged cold stress response of Escherichia coli O157 and the role of rpoS

Phenotypic analyses were performed using an enterohemorrhagic Escherichia coli O157 (EHEC) strain (B-1) and a commensal E. coli K-12 strain, exposed to prolonged cold stress. The EHEC E. coli O157 showed significantly (P < 0.05) higher resistance to cold stress compared to non-pathogenic E. coli K-12 DH5α. Further, it was found that RpoS sigma factor plays a significant (P < 0.05) role in the cold stress physiology of the enterohemorrhagic E. coli strain. Using comparative proteomic analysis of hypo-thermally adapted E. coli O157 wild-type and rpoS mutant strains, we identified 21 proteins that were differentially expressed upon cold temperature shifts or rpoS mutation. All identified proteins of cold post-acclimation stimulons fell into two large sub-groups: (i) stress proteins, and (ii) housekeeping proteins. This prolonged cold stress response included proteins involved in mRNA turnover, cell replication efficiency, conditional and post-synthetic modification of membrane lipid bilayers, biosynthetic processes, and the uptake of different sugars. The RpoS sigma factor had no control over the key stress proteins, polynucleotide phosphorylase and elongation factor G, in prolonged stress stimulon. However, RpoS was shown to regulate the expression of proteins involved in homeoviscous adaptation during cold shock, as well as various proteins involved in central metabolic pathways of this food-borne pathogen.     

Perspectives of sustainable development in countries of Southeastern Europe

Countries of SE Europe are at very beginning of planning of their development in accordance with theoretical concept of sustainable development. Sustainable development is defined as the basic imperative and the only model of development in a longer period of time. The basic indicators of sustainable development represent a very useful and quality way for measuring and monitoring the state of sustainable development, as in every country individually so as in the regions and globally as a whole. Values of the indicators of all four subsystems in observed countries are within expectation. Also the current level of development of every country separately is taken into account and in accordance to that it is defined the current position of any country in respect to its international requests. The special value is given by the comparison of obtained results of the state in the developed EU countries, according to which there is an impression of equal degree of sustainable development in France and Germany, whereas the data regarding the state of sustainable development in Greece and at Slovenia has been improved between two analysis. Taking into account the results of the previous and current research there is a clear need for regular observation of the state of every indicator individually but also the need to observe the relationship among them as a whole. The special attention needs to be given to the intensive monitoring of indicators of economic and ecological subsystem. The research showed, among other things, to the fragile relationship of values of indicators of economic and ecological subsystem, by which any change in values of one indicator consequently leads to the changes in the final result. Both conducted researches point to the fact that the value of the mentioned indicators changes at the fastest pace.