86 resultados para Ventricular Premature Complexes


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Interactions of mercury(II) with the microtubule network of cells may lead to genotoxicity. Complexation of mercury(II) with EDTA is currently being discussed for its employment in detoxification processes of polluted sites. This prompted us to re-evaluate the effects of such complexing agents on certain aspects of mercury toxicity, by examining the influences of mercury(II) complexes on tubulin assembly and kinesin-driven motility of microtubules. The genotoxic effects were studied using the micronucleus assay in V79 Chinese hamster fibroblasts. Mercury(II) complexes with EDTA and related chelators interfered dose-dependently with tubulin assembly and microtubule motility in vitro. The no-effect-concentration for assembly inhibition was 1 μM of complexed Hg(II), and for inhibition of motility it was 0.05 μM, respectively. These findings are supported on the genotoxicity level by the results of the micronucleus assay, with micronuclei being induced dose-dependently starting at concentrations of about 0.05 μM of complexed Hg(II). Generally, the no-effect-concentrations for complexed mercury(II) found in the cell-free systems and in cellular assays (including the micronucleus test) were identical with or similar to results for mercury tested in the absence of chelators. This indicates that mercury(II) has a much higher affinity to sulfhydryls of cytoskeletal proteins than to this type of complexing agents. Therefore, the suitability of EDTA and related compounds for remediation of environmental mercury contamination or for other detoxification purposes involving mercury has to be questioned.

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This study reports a hybrid of two metal-organic semiconductors that are based on organic charge transfer complexes of 7,7,8,8-tetracyanoquinodimethane (TCNQ). It is shown that the spontaneous reaction between semiconducting microrods of CuTCNQ with Ag+ ions leads to the formation of a CuTCNQ/AgTCNQ hybrid, both in aqueous solution and acetonitrile, albeit with completely different reaction mechanisms. In an aqueous environment, the reaction proceeds by a complex galvanic replacement (GR) mechanism, wherein in addition to AgTCNQ nanowires, Ag0 nanoparticles and Cu(OH)2 crystals decorate the surface of CuTCNQ microrods. Conversely, in acetonitrile, a GR mechanism is found to be thermodynamically unfavorable and instead a corrosion-recrystallization mechanism leads to the decoration of CuTCNQ microrods with AgTCNQ nanoplates, resulting in a pure CuTCNQ/AgTCNQ hybrid metal-organic charge transfer complex. While hybrids of two different inorganic semiconductors are regularly reported, this report pioneers the formation of a hybrid involving two metal-organic semiconductors that will expand the scope of TCNQ-based charge transfer complexes for improved catalysis, sensing, electronics and biological applications.

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Heteroleptic complexes of the type \[RuL2L′](PF6)2 (L, L′ = combinations of 1,10-phenanthroline (phen) and 2,2′-bipyridine (bipy)) were found to cocrystallize with \[Ni(phen)3](PF6)2 to produce cocrystals of \[Ni(phen)3]x\[RuL2L′]1–x(PF6)2. In this report we show that the ability of the complexes to cocrystallize is influenced by the number of common ligands between complexes in solution. Supramolecular selection is a phenomenon caused by molecular recognition through which cocrystals can grow from the same solution but contain different ratios of the molecular components. It was found that systems where L = phen displayed less supramolecular selection than systems where L = bipy. With increasing supramolecular selection, the composition of cocrystals was found to vary significantly from the initial relative concentration in the cocrystallizing solution, and therefore it was increasingly difficult to control the final composition of the resultant cocrystals. Consequently, modulation of concentration-dependent properties such as phase was also found to be less predictable with increasing supramolecular selection. Notwithstanding the complication afforded by the presence of supramolecular selection, our results reaffirm the robustness of the \[M(phen)3](PF6)2 structure because it was maintained even when ca. 90% of the complexes in the cocrystals were \[Ru(phen)(bipy)2](PF6)2, which in its pure form is not isomorphous with \[M(phen)3](PF6)2. Experiments between complexes without common ligands, i.e., \[Ru(bipy)3](PF6)2 cocrystallized with \[Ni(phen)3](PF6)2, were found to approach the limit to which molecular recognition processes can be confused into cocrystallizing different molecules to form single cocrystals. For these systems the result was the formation of block-shaped crystals skewered by a needle-shaped crystals.

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A series of Pt(II) diimine complexes bearing benzothiazolylfluorenyl (BTZ-F8), diphenylaminofluorenyl (NPh2- F8), or naphthalimidylfluorenyl (NI-F8) motifs on the bipyridyl or acetylide ligands (Pt-4−Pt-8), (i.e., {4,4′-bis[7-R1-F8-(≡)n-]bpy}Pt(7- R2-F8- ≡ -)2, where F8 = 9,9′-di(2-ethylhexyl)fluorene, bpy = 2,2′- bipyridine, Pt-4: R1 = R2 = BTZ, n = 0; Pt-5: R1 = BTZ, R2 = NI, n = 0; Pt-6: R1 = R2 = BTZ, n = 1; Pt-7: R1 = BTZ, R2 = NPh2, n = 1; Pt- 8: R1 = NPh2, R2 = BTZ, n = 1) were synthesized. Their ground-state and excited-state properties and reverse saturable absorption performances were systematically investigated. The influence of these motifs on the photophysics of the complexes was investigated by spectroscopic methods and simulated by time-dependent density functional theory (TDDFT). The intense absorption bands below 410 nm for these complexes is assigned to predominantly 1π,π* transitions localized on either the bipyridine or the acetylide ligands; while the broad low-energy absorption bands between 420 and 575 nm are attributed to essentially 1MLCT (metal-to-ligand charge transfer)/ 1LLCT (ligand-to-ligand charge transfer) transitions, likely mixed with some 1ILCT (intraligand charge transfer) transition for Pt-4−Pt-7, and predominantly 1ILCT transition admixing with minor 1MLCT/1LLCT characters for Pt-8. The different substituents on the acetylide and bipyridyl ligands, and the degrees of π-conjugation in the bipyridyl ligand influence both the 1π,π* and charge transfer transitions pronouncedly. All complexes are emissive at room temperature. Upon excitation at their respective absorption band maxima, Pt-4, Pt-6, and Pt-8 exhibit acetylide ligand localized 1π,π* fluorescence and 3MLCT/3LLCT phosphorescence in CH2Cl2, while Pt-5 manifests 1ILCT fluorescence and 3ILCT phosphorescence. However, only 1LLCT fluorescence was observed for Pt-7 at room temperature. The nanosecond transient absorption study was carried out for Pt-4−Pt-8 in CH3CN. Except for Pt-7 that contains NPh2 at the acetylide ligands, Pt-4−Pt-6 and Pt-8 all exhibit weak to moderate excited-state absorption in the visible spectral region. Reverse saturable absorption (RSA) of these complexes was demonstrated at 532 nm using 4.1 ns laser pulses in a 2 mm cuvette. The strength of RSA follows this trend: Pt-4 > Pt-5 > Pt-7 > Pt-6 > Pt-8. Incorporation of electron-donating substituent NPh2 on the bipyridyl ligand significantly decreases the RSA, while shorter π-conjugation in the bipyridyl ligand increases the RSA. Therefore, the substituent at either the acetylide ligands or the bipyridyl ligand could affect the singlet and triplet excited-state characteristics significantly, which strongly influences the RSA efficiency.

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The kaolinite (Kaol) intercalated with potassium acetate (Ac) was prepared and characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and thermogravimetry. Molecular dynamic simulation was performed to investigate the structure of Kaol–Ac intercalation complex and the hydrogen bonds between Kaol and intercalated Ac andwater using INTERFACE forcefield. The acetate anions andwater arranged in a bilayer structure in the interlayer space of Kaol. The potassium cations distributed in the interlayer space and strongly coordinated with acetate anions aswell aswater rather than keyed into the ditrigonal holes of tetrahedral surface of Kaol. Strong hydrogen bonds formed between the hydrogen atoms of hydroxyl on the octahedral surface and oxygen atoms of both acetate anions and water. The acetate anions andwater also weakly bonded hydrogen to the silica tetrahedral surface through their hydrogen atoms with the oxygen atoms of silica tetrahedral surface.

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A series of kaolinite–methanol complexes with different basal spacings were synthesized using guest displacement reactions of the intercalation precursors kaolinite–N-methyformamide (Kaol–NMF), kaolinite–urea (Kaol–U), or kaolinite–dimethylsulfoxide (Kaol–DMSO), with methanol (Me). The interaction of methanol with kaolinite was examined using X-ray diffraction (XRD), infrared spectroscopy (IR), and nuclear magnetic resonance (NMR). Kaolinite (Kaol) initially intercalated with N-methyformamide (NMF), urea (U), or dimethylsulfoxide (DMSO) before subsequent reaction with Me formed final kaolinite–methanol (Kaol–Me) complexes characterized by basal spacing ranging between 8.6 Å and 9.6 Å, depending on the pre-intercalated reagent. Based on a comparative analysis of the three Kaol–Me displacement intercalation complexes, three types of Me intercalation products were suggested to have been present in the interlayer space of Kaol: (1) molecules grafted onto a kaolinite octahedral sheet in the form of a methoxy group (Al-O-C bond); (2) mobile Me and/or water molecules kept in the interlayer space via hydrogen bonds that could be partially removed during drying; and (3) a mixture of types 1 and 2, with the methoxy group (Al-O-C bond) grafted onto the Kaol sheet and mobile Me and/or water molecules coexisted in the system after the displacement reaction by Me. Various structural models that reflected four possible complexes of Kaol–Me were constructed for use in a complimentary computational study. Results from the calculation of the methanol kaolinite interaction indicate that the hydroxyl oxygen atom of methanol plays the dominant role in the stabilization and localization of the molecule intercalated in the interlayer space, and that water existing in the intercalated Kaol layer is inevitable.

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A description of a computer program to analyse cine angiograms of the heart and pressure waveforms to calculate valve gradients.

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Particle Swarm Optimization (PSO) is a biologically inspired computational search and optimization method based on the social behaviors of birds flocking or fish schooling. Although, PSO is represented in solving many well-known numerical test problems, but it suffers from the premature convergence. A number of basic variations have been developed due to solve the premature convergence problem and improve quality of solution founded by the PSO. This study presents a comprehensive survey of the various PSO-based algorithms. As part of this survey, the authors have included a classification of the approaches and they have identify the main features of each proposal. In the last part of the study, some of the topics within this field that are considered as promising areas of future research are listed.

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Despite substantial progress in measuring the 3D profile of anatomical variations in the human brain, their genetic and environmental causes remain enigmatic. We developed an automated system to identify and map genetic and environmental effects on brain structure in large brain MRI databases . We applied our multi-template segmentation approach ("Multi-Atlas Fluid Image Alignment") to fluidly propagate hand-labeled parameterized surface meshes into 116 scans of twins (60 identical, 56 fraternal), labeling the lateral ventricles. Mesh surfaces were averaged within subjects to minimize segmentation error. We fitted quantitative genetic models at each of 30,000 surface points to measure the proportion of shape variance attributable to (1) genetic differences among subjects, (2) environmental influences unique to each individual, and (3) shared environmental effects. Surface-based statistical maps revealed 3D heritability patterns, and their significance, with and without adjustments for global brain scale. These maps visualized detailed profiles of environmental versus genetic influences on the brain, extending genetic models to spatially detailed, automatically computed, 3D maps.

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Despite substantial progress in measuring the anatomical and functional variability of the human brain, little is known about the genetic and environmental causes of these variations. Here we developed an automated system to visualize genetic and environmental effects on brain structure in large brain MRI databases. We applied our multi-template segmentation approach termed "Multi-Atlas Fluid Image Alignment" to fluidly propagate hand-labeled parameterized surface meshes, labeling the lateral ventricles, in 3D volumetric MRI scans of 76 identical (monozygotic, MZ) twins (38 pairs; mean age = 24.6 (SD = 1.7)); and 56 same-sex fraternal (dizygotic, DZ) twins (28 pairs; mean age = 23.0 (SD = 1.8)), scanned as part of a 5-year research study that will eventually study over 1000 subjects. Mesh surfaces were averaged within subjects to minimize segmentation error. We fitted quantitative genetic models at each of 30,000 surface points to measure the proportion of shape variance attributable to (1) genetic differences among subjects, (2) environmental influences unique to each individual, and (3) shared environmental effects. Surface-based statistical maps, derived from path analysis, revealed patterns of heritability, and their significance, in 3D. Path coefficients for the 'ACE' model that best fitted the data indicated significant contributions from genetic factors (A = 7.3%), common environment (C = 38.9%) and unique environment (E = 53.8%) to lateral ventricular volume. Earlier-maturing occipital horn regions may also be more genetically influenced than later-maturing frontal regions. Maps visualized spatially-varying profiles of environmental versus genetic influences. The approach shows promise for automatically measuring gene-environment effects in large image databases.

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We developed and validated a new method to create automated 3D parametric surface models of the lateral ventricles in brain MRI scans, providing an efficient approach to monitor degenerative disease in clinical studies and drug trials. First, we used a set of parameterized surfaces to represent the ventricles in four subjects' manually labeled brain MRI scans (atlases). We fluidly registered each atlas and mesh model to MRIs from 17 Alzheimer's disease (AD) patients and 13 age- and gender-matched healthy elderly control subjects, and 18 asymptomatic ApoE4-carriers and 18 age- and gender-matched non-carriers. We examined genotyped healthy subjects with the goal of detecting subtle effects of a gene that confers heightened risk for Alzheimer's disease. We averaged the meshes extracted for each 3D MR data set, and combined the automated segmentations with a radial mapping approach to localize ventricular shape differences in patients. Validation experiments comparing automated and expert manual segmentations showed that (1) the Hausdorff labeling error rapidly decreased, and (2) the power to detect disease- and gene-related alterations improved, as the number of atlases, N, was increased from 1 to 9. In surface-based statistical maps, we detected more widespread and intense anatomical deficits as we increased the number of atlases. We formulated a statistical stopping criterion to determine the optimal number of atlases to use. Healthy ApoE4-carriers and those with AD showed local ventricular abnormalities. This high-throughput method for morphometric studies further motivates the combination of genetic and neuroimaging strategies in predicting AD progression and treatment response. © 2007 Elsevier Inc. All rights reserved.

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We developed an anatomical mapping technique to detect hippocampal and ventricular changes in Alzheimer disease (AD). The resulting maps are sensitive to longitudinal changes in brain structure as the disease progresses. An anatomical surface modeling approach was combined with surface-based statistics to visualize the region and rate of atrophy in serial MRI scans and isolate where these changes link with cognitive decline. Fifty-two high-resolution MRI scans were acquired from 12 AD patients (age: 68.4 ± 1.9 years) and 14 matched controls (age: 71.4 ± 0.9 years), each scanned twice (2.1 ± 0.4 years apart). 3D parametric mesh models of the hippocampus and temporal horns were created in sequential scans and averaged across subjects to identify systematic patterns of atrophy. As an index of radial atrophy, 3D distance fields were generated relating each anatomical surface point to a medial curve threading down the medial axis of each structure. Hippocampal atrophic rates and ventricular expansion were assessed statistically using surface-based permutation testing and were faster in AD than in controls. Using color-coded maps and video sequences, these changes were visualized as they progressed anatomically over time. Additional maps localized regions where atrophic changes linked with cognitive decline. Temporal horn expansion maps were more sensitive to AD progression than maps of hippocampal atrophy, but both maps correlated with clinical deterioration. These quantitative, dynamic visualizations of hippocampal atrophy and ventricular expansion rates in aging and AD may provide a promising measure to track AD progression in drug trials.

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We recently noticed an error in the demographic data in this article. The validity of the findings and the conclusions of the paper is not affected. However, there is an error in the reported sample size and in the means and standard deviations of the subjects’ ages and MMSE scores. We would like to correct this error, which came to light when we were re-analyzing the data for a meta-analysis. The error occurred because an older version of a spreadsheet was incorrectly used when reporting the sample composition. Instead of examining 12 Alzheimer's disease patients and 14 healthy elderly controls, we in fact examined 17 Alzheimer’s disease patients and 14 healthy elderly controls. All maps and morphometric data reported in the paper are correct, except that the sample size was in fact slightly higher than that originally reported, and the maps computed in the paper were based on the larger sample (which included five more subjects in the Alzheimer’s disease group). All of the maps and figures in the paper are correct, and the conclusions of the paper are unchanged. We apologize for this error, which falls under the sole responsibility of the first author. The corrected demographic information appears below.