Fourier classification images in cardiac nuclear medicine

At present, the diagnosis of cardiac left ventricular regional wall motion abnormalities (RWMA) in nuclear medicine is aided mainly by phase images and amplitude images, which picture the spatial distribution of the phase and of the amplitude of the first harmonics of pixel time activity curves, respectively. However, they do not utilize other information contained in the original radionuclide images, and they do not offer a direct diagnostic interpretation of the data. The proposed Fourier classification images (FCI) overcome these deficiencies. Their pixel intensities express directly the diagnostic class of RWMA. The FCI pixel intensities are functions of pixel coordinates, Fourier features of pixel time activity curves, and their distribution parameters, and they are not limited by the first harmonics model. The derivation of the pixel classifier includes normalization transformation of coordinates and activities. Fourier analysis of raw image data, and teaching the computer by examples of already diagnosed cases with the help of discriminant analysis. FCI offer direct and robust diagnosis of RWMA, superior to that derived from phase and amplitude images, especially in the detection of mild RWMA.     

Nature-Inspired Meta-Heuristics on Modern GPUs: State of the Art and Brief Survey of Selected Algorithms

Graphic processing units (GPUs) emerged recently as an exciting new hardware environment for a truly parallel implementation and execution of Nature and Bio-inspired Algorithms with excellent price-to-power ratio. In contrast to common multicore CPUs that contain up to tens of independent cores, the GPUs represent a massively parallel single-instruction multiple-data devices that can nowadays reach peak performance of hundreds and thousands of giga floating-point operations per second. Nature and Bio-inspired Algorithms implement parallel optimization strategies in which a single candidate solution, a group of candidate solutions (population), or multiple populations seek for optimal solution or set of solutions of given problem. Genetic algorithms (GA) constitute a family of traditional and very well-known nature-inspired populational meta-heuristic algorithms that have proved its usefulness on a plethora of tasks through the years. Differential evolution (DE) is another efficient populational meta-heuristic algorithm for real-parameter optimization. Particle swarm optimization (PSO) can be seen as nature-inspired multiagent method in which the interaction of simple independent agents yields intelligent collective behavior. Simulated annealing (SA) is global optimization algorithm which combines statistical mechanics and combinatorial optimization with inspiration in metallurgy. This survey provides a brief overview of the latest state-of-the-art research on the design, implementation, and applications of parallel GA, DE, PSO, and SA-based methods on the GPUs.     

Stretching and deformation vibrations of CH2, C(CH3) and O(CH3) groups of poly(methyl methacrylate)

Infrared and Raman spectra of atactic PMMA and infrared spectra of stereoregular PMMA and of its four deuterated derivatives

, were measured. They were used to assign the bands of stretching and deformation vibrations of CH₂, CCH₃ and OCH₃ groups in the infrared and Raman spectra and to discuss the effect of stereoregularity on these bands in the infrared spectra.     

The joint movement of pebbles in solving the ($$N^2-1$$)-puzzle suboptimally and its applications in rule-based cooperative path-finding

The present paper deals with the problem of solving the (\(n^2 - 1\))-puzzle and cooperative path-finding (CPF) problems sub-optimally by rule-based algorithms. To solve the puzzle, we need to rearrange \(n^2 - 1\) pebbles in the \(n \times n\)-sized square grid using one vacant position to achieve the goal configuration. An improvement to the existing polynomial-time algorithm is proposed and experimentally analyzed. The improved algorithm represents an attempt to move pebbles in a more efficient way compared to the original algorithm by grouping them into so-called snakes and moving them together as part of a snake formation. An experimental evaluation has shown that the snakeenhanced algorithm produces solutions which are 8–9 % shorter than the solutions generated by the original algorithm. Snake-like movement has also been integrated into the rule-based algorithms used in solving CPF problems sub-optimally, which is a closely related task. The task in CPF consists in moving a group of abstract robots on an undirected graph to specific vertices. The robots can move to unoccupied neighboring vertices; no more than one robot can be placed in each vertex. The (\(n^2 - 1\))-puzzle is a special case of CPF where the underlying graph is a 4-connected grid and only one vertex is vacant. Two major rule-based algorithms for solving CPF problems were included in our study—BIBOX and PUSH-and-SWAP (PUSH-and-ROTATE). The use of snakes in the BIBOX algorithm led to consistent efficiency gains of around 30 % for the (\(n^2 - 1\))-puzzle and up to 50 % in for CPF problems on biconnected graphs with various ear decompositions and multiple vacant vertices. For the PUSH-and-SWAP algorithm, the efficiency gain achieved from the use of snakes was around 5–8 %. However, the efficiency gain was unstable and hardly predictable for PUSH-and-SWAP.     

D-Index: Distance Searching Index for Metric Data Sets

In order to speedup retrieval in large collections of data, index structures partition the data into subsets so that query requests can be evaluated without examining the entire collection. As the complexity of modern data types grows, metric spaces have become a popular paradigm for similarity retrieval. We propose a new index structure, called D-Index, that combines a novel clustering technique and the pivot-based distance searching strategy to speed up execution of similarity range and nearest neighbor queries for large files with objects stored in disk memories. We have qualitatively analyzed D-Index and verified its properties on actual implementation. We have also compared D-Index with other index structures and demonstrated its superiority on several real-life data sets. Contrary to tree organizations, the D-Index structure is suitable for dynamic environments with a high rate of delete/insert operations.     

Oxidative Damage in Sporadic Colorectal Cancer: Molecular Mapping of Base Excision Repair Glycosylases MUTYH and hOGG1 in Colorectal Cancer Patients

Oxidative stress, oxidative DNA damage and resulting mutations play a role in colorectal carcinogenesis. Impaired equilibrium between DNA damage formation, antioxidant status, and DNA repair capacity is responsible for the accumulation of genetic mutations and genomic instability. The lesion-specific DNA glycosylases, e.g., hOGG1 and MUTYH, initiate the repair of oxidative DNA damage. Hereditary syndromes (MUTYH-associated polyposis, NTHL1-associated tumor syndrome) with germline mutations causing a loss-of-function in base excision repair glycosylases, serve as straight forward evidence on the role of oxidative DNA damage and its repair. Altered or inhibited function of above glycosylases result in an accumulation of oxidative DNA damage and contribute to the adenoma-adenocarcinoma transition. Oxidative DNA damage, unless repaired, often gives rise G:C > T:A mutations in tumor suppressor genes and proto-oncogenes with subsequent occurrence of chromosomal copy-neutral loss of heterozygosity. For instance, G>T transversions in position c.34 of a KRAS gene serves as a pre-screening tool for MUTYH-associated polyposis diagnosis. Since sporadic colorectal cancer represents more complex and heterogenous disease, the situation is more complicated. In the present study we focused on the roles of base excision repair glycosylases (hOGG1, MUTYH) in colorectal cancer patients by investigating tumor and adjacent mucosa tissues. Although we found downregulation of both glycosylases and significantly lower expression of hOGG1 in tumor tissues, accompanied with G>T mutations in KRAS gene, oxidative DNA damage and its repair cannot solely explain the onset of sporadic colorectal cancer. In this respect, other factors (especially microenvironment) per se or in combination with oxidative DNA damage warrant further attention. Base excision repair characteristics determined in colorectal cancer tissues and their association with disease prognosis have been discussed as well.     

Molecular Mechanisms Underlying Intensive Care Unit-Acquired Weakness and Sarcopenia

Skeletal muscle is a highly adaptable organ, and its amount declines under catabolic conditions such as critical illness. Aging is accompanied by a gradual loss of muscle, especially when physical activity decreases. Intensive care unit-acquired weakness is a common and highly serious neuromuscular complication in critically ill patients. It is a consequence of critical illness and is characterized by a systemic inflammatory response, leading to metabolic stress, that causes the development of multiple organ dysfunction. Muscle dysfunction is an important component of this syndrome, and the degree of catabolism corresponds to the severity of the condition. The population of critically ill is aging; thus, we face another negative effect—sarcopenia—the age-related decline of skeletal muscle mass and function. Low-grade inflammation gradually accumulates over time, inhibits proteosynthesis, worsens anabolic resistance, and increases insulin resistance. The cumulative consequence is a gradual decline in muscle recovery and muscle mass. The clinical manifestation for both of the above conditions is skeletal muscle weakness, with macromolecular damage, and a common mechanism—mitochondrial dysfunction. In this review, we compare the molecular mechanisms underlying the two types of muscle atrophy, and address questions regarding possible shared molecular mechanisms, and whether critical illness accelerates the aging process.     

Hematites Precipitated in Alkaline Precursors: Comparison of Structural and Textural Properties for Methane Oxidation

Hematite (α-Fe₂O₃) catalysts prepared using the precipitation methods was found to be highly effective, and therefore, it was studied with methane (CH₄), showing an excellent stable performance below 500 °C. This study investigates hematite nanoparticles (NPs) obtained by precipitation in water from the precursor of ferric chloride hexahydrate using precipitating agents NaOH or NH₄OH at maintained pH 11 and calcined up to 500 °C for the catalytic oxidation of low concentrations of CH₄ (5% by volume in air) at 500 °C to compare their structural state in a CH₄ reducing environment. The conversion (%) of CH₄ values decreasing with time was discussed according to the course of different transformation of goethite and hydrohematites NPs precursors to magnetite and the structural state of the calcined hydrohematites. The phase composition, the size and morphology of nanocrystallites, thermal transformation of precipitates and the specific surface area of the NPs were characterized in detail by X-ray powder diffraction, transmission electron microscopy, infrared spectroscopy, thermal TG/DTA analysis and nitrogen physisorption measurements. The results support the finding that after goethite dehydration, transformation to hydrohematite due to structurally incorporated water and vacancies is different from hydrohematite α-Fe₂O₃. The surface area SBET of Fe₂O₃_NH-70 precipitate composed of protohematite was larger by about 53 m²/g in comparison with Fe₂O₃_Na-70 precipitate composed of goethite. The oxidation of methane was positively influenced by the hydrohematites of the smaller particle size and the largest lattice volume containing structurally incorporated water and vacancies.     

UV‐Triggered Polymerization,Deposition, and Patterning of Plant Phenolic Compounds

Plant‐derived phenolic compounds, rich in catechol and pyrogallol moieties, can form multifunctional coatings on various substrates following polymerization under mildly alkaline conditions. Despite many appealing features of such coatings, the difficulty to control polymerization of phenolic compounds spatially and temporally limits their number of potential applications. In this study, it is demonstrated that UV irradiation can trigger oxidative polymerization and deposition of plant‐derived phenolic compounds, which opens the possibility to create 2D gradients and patterns of polyphenol coatings and control this polymerization temporally. UV–vis spectroscopy, electrospray ionization mass spectrometry, and cyclic voltammetry analyses are used to investigate the UV‐induced polymerization of several plant‐derived phenolic compounds including pyrogallol, tannic acid, caffeic acid, and gallic acid. Formation of polyphenol coatings on polar and nonpolar substrates after UV irradiation has been studied using water contact angle measurements, atomic force microscopy, time of flight secondary ion mass spectrometry, and X‐ray photoelectron spectroscopy (XPS). The possibility to use UV‐light to accelerate polymerization of phenolic compounds and perform micropatterning can extend the scope of potential applications of the large class of structurally diverse plant‐derived phenolic compounds.