Soft topographic map for clustering and classification of bacteria

In this work a new method for clustering and building a topographic representation of a bacteria taxonomy is presented. The method is based on the analysis of stable parts of the genome, the so-called “housekeeping genes”. The proposed method generates topographic maps of the bacteria taxonomy, where relations among different type strains can be visually inspected and verified. Two well known DNA alignement algorithms are applied to the genomic sequences. Topographic maps are optimized to represent the similarity among the sequences according to their evolutionary distances. The experimental analysis is carried out on 147 type strains of the Gammaprotebacteria class by means of the 16S rRNA housekeeping gene. Complete sequences of the gene have been retrieved from the NCBI public database. In the experimental tests the maps show clusters of homologous type strains and present some singular cases potentially due to incorrect classification or erroneous annotations in the database.

Rapid synthesis of carbohydrate derivatives, including mimetics of c-linked disaccharides and c-Linked aza disaccharides, using the Hetero-Diels−Alder Reaction

In this work we demonstrate the value of performing a Hetero Diels-Alder reaction (HDAR) between Danishefsky’s diene and a range of aldehydes or imines, under microwave irradiation. By using a range of aldehydes and imines, including those derived from carbohydrates, access to functionalised 2,3-dihydro-4H-pyran-4-ones or 2,3-dihydro-4-pyridinones in good to excellent synthetic yields is possible. A particular strength of the methodology is its ability to access mimetics of C-linked disaccharides and C-linked aza disaccharides, targets of current therapeutic interest, in a rapid, convenient and diastereoselective manner. The effect of high pressure on the HDARs involving carbohydrate derived aldehydes and imines is also explored, with enhancement in yields occurring for the aldehyde substrates. Finally, HDARs using carbohydrate derived ketones, enones and enals are described under a range of conditions. Optimum results were obtained under high pressure conditions, with highly functionalized carbohydrate derivatives being afforded, in good yields, in this way.

Non-genomic signalling of the retinoic X receptor through inhibition of Gq signalling in human platelets

Retinoid X receptors (RXRs) are important transcriptional nuclear hormone receptors, acting as either homodimers or the binding partner for at least one fourth of all the known human nuclear receptors. Functional nongenomic effects of nuclear receptors are poorly understood; however, recently peroxisome proliferator-activated receptor (PPAR) gamma, PPARbeta, and the glucocorticoid receptor have all been found active in human platelets. Human platelets express RXRalpha and RXRbeta. RXR ligands inhibit platelet aggregation and TXA(2) release to ADP and the TXA(2) receptors, but only weakly to collagen. ADP and TXA(2) both signal via the G protein, Gq. RXR rapidly binds Gq but not Gi/z/o/t/gust in a ligand-dependent manner and inhibits Gq-induced Rac activation and intracellular calcium release. We propose that RXR ligands may have beneficial clinical actions through inhibition of platelet activation. Furthermore, our results demonstrate a novel nongenomic mode for nuclear receptor action and a functional cross-talk between G-protein and nuclear receptor signaling families.

Effect of altered dietary n-3 fatty acid intake upon plasma lipid fatty acid composition, conversion of [C-13]alpha-linolenic acid to longer-chain fatty acids and partitioning towards beta-oxidation in older men

The effect of increased dietary intakes of alpha-linolenic acid (ALNA) or eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) for 2 months upon plasma lipid composition and capacity for conversion of ALNA to longer-chain metabolites was investigated in healthy men (52 (SD 12) years). After a 4-week baseline period when the subjects substituted a control spread, a test meal containing [U-C-13]ALNA (700 mg) was consumed to measure conversion to EPA, docosapentaenoic acid (DPA) and DHA over 48 h. Subjects were then randomised to one of three groups for 8 weeks before repeating the tracer study: (1) continued on same intake (control, n 5); (2) increased ALNA intake (10 g/d, n 4); (3) increased EPA+DHA intake (1.5 g/d, n 5). At baseline, apparent fractional conversion of labelled ALNA was: EPA 2.80, DPA 1.20 and DRA 0.04%. After 8 weeks on the control diet, plasma lipid composition and [C-13]ALNA conversion remained unchanged compared with baseline. The high-ALNA diet resulted in raised plasma triacylglycerol-EPA and -DPA concentrations and phosphatidylcholine-EPA concentration, whilst [C-13]ALNA conversion was similar to baseline. The high-(EPA+DHA) diet raised plasma phosphatidylcholine-EPA and -DHA concentrations, decreased [C-13]ALNA conversion to EPA (2-fold) and DPA (4-fold), whilst [C-13]ALNA conversion to DHA was unchanged. The dietary interventions did not alter partitioning of ALNA towards beta-oxidation. The present results indicate ALNA conversion was down-regulated by increased product (EPA+DHA) availability, but was not up-regulated by increased substrate (ALNA) consumption. This suggests regulation of ALNA conversion may limit the influence of variations in dietary n-3 fatty acid intake on plasma lipid compositions.

Characterization and classification of tumor lesions using computerized fractal-based texture analysis and support vector machines in digital mammograms

Objective: This paper presents a detailed study of fractal-based methods for texture characterization of mammographic mass lesions and architectural distortion. The purpose of this study is to explore the use of fractal and lacunarity analysis for the characterization and classification of both tumor lesions and normal breast parenchyma in mammography. Materials and methods: We conducted comparative evaluations of five popular fractal dimension estimation methods for the characterization of the texture of mass lesions and architectural distortion. We applied the concept of lacunarity to the description of the spatial distribution of the pixel intensities in mammographic images. These methods were tested with a set of 57 breast masses and 60 normal breast parenchyma (dataset1), and with another set of 19 architectural distortions and 41 normal breast parenchyma (dataset2). Support vector machines (SVM) were used as a pattern classification method for tumor classification. Results: Experimental results showed that the fractal dimension of region of interest (ROIs) depicting mass lesions and architectural distortion was statistically significantly lower than that of normal breast parenchyma for all five methods. Receiver operating characteristic (ROC) analysis showed that fractional Brownian motion (FBM) method generated the highest area under ROC curve (A z = 0.839 for dataset1, 0.828 for dataset2, respectively) among five methods for both datasets. Lacunarity analysis showed that the ROIs depicting mass lesions and architectural distortion had higher lacunarities than those of ROIs depicting normal breast parenchyma. The combination of FBM fractal dimension and lacunarity yielded the highest A z value (0.903 and 0.875, respectively) than those based on single feature alone for both given datasets. The application of the SVM improved the performance of the fractal-based features in differentiating tumor lesions from normal breast parenchyma by generating higher A z value. Conclusion: FBM texture model is the most appropriate model for characterizing mammographic images due to self-affinity assumption of the method being a better approximation. Lacunarity is an effective counterpart measure of the fractal dimension in texture feature extraction in mammographic images. The classification results obtained in this work suggest that the SVM is an effective method with great potential for classification in mammographic image analysis.

Optimal 3D surface reconstruction from a small number of conventional 2D X-ray images

This paper describes a method for reconstructing 3D frontier points, contour generators and surfaces of anatomical objects or smooth surfaces from a small number, e. g. 10, of conventional 2D X-ray images. The X-ray images are taken at different viewing directions with full prior knowledge of the X-ray source and sensor configurations. Unlike previous works, we empirically demonstrate that if the viewing directions are uniformly distributed around the object's viewing sphere, then the reconstructed 3D points automatically cluster closely on a highly curved part of the surface and are widely spread on smooth or flat parts. The advantage of this property is that the reconstructed points along a surface or a contour generator are not under-sampled or under-represented because surfaces or contours should be sampled or represented with more densely points where their curvatures are high. The more complex the contour's shape, the greater is the number of points required, but the greater the number of points is automatically generated by the proposed method. Given that the number of viewing directions is fixed and the viewing directions are uniformly distributed, the number and distribution of the reconstructed points depend on the shape or the curvature of the surface regardless of the size of the surface or the size of the object. The technique may be used not only in medicine but also in industrial applications.