496 research outputs found

    Classification of fibroglandular tissue distribution in the breast based on radiotherapy planning CT

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    Accurate segmentation of breast tissues is required for a number of applications such as model based deformable registration in breast radiotherapy. The accuracy of breast tissue segmentation is affected by the spatial distribution (or pattern) of fibroglandular tissue (FT). The goal of this study was to develop and evaluate texture features, determined from planning computed tomography (CT) data, to classify the spatial distribution of FT in the breas

    Automated segmentation of normal and diseased coronary arteries – The ASOCA challenge

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    Cardiovascular disease is a major cause of death worldwide. Computed Tomography Coronary Angiography (CTCA) is a non-invasive method used to evaluate coronary artery disease, as well as evaluating and reconstructing heart and coronary vessel structures. Reconstructed models have a wide array of for educational, training and research applications such as the study of diseased and non-diseased coronary anatomy, machine learning based disease risk prediction and in-silico and in-vitro testing of medical devices. However, coronary arteries are difficult to image due to their small size, location, and movement, causing poor resolution and artefacts. Segmentation of coronary arteries has traditionally focused on semi-automatic methods where a human expert guides the algorithm and corrects errors, which severely limits large-scale applications and integration within clinical systems. International challenges aiming to overcome this barrier have focussed on specific tasks such as centreline extraction, stenosis quantification, and segmentation of specific artery segments only. Here we present the results of the first challenge to develop fully automatic segmentation methods of full coronary artery trees and establish the first large standardized dataset of normal and diseased arteries. This forms a new automated segmentation benchmark allowing the automated processing of CTCAs directly relevant for large-scale and personalized clinical applications

    Water-Driven Assembly of Laser Ablation-Induced Au Condensates as Mesomorphic Nano- and Micro-Tubes

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    Reddish Au condensates, predominant atom clusters and minor amount of multiply twinned particles and fcc nanoparticles with internal compressive stress, were produced by pulsed laser ablation on gold target in de-ionized water under a very high power density. Such condensates were self-assembled as lamellae and then nano- to micro-diameter tubes with multiple walls when aged at room temperature in water for up to 40 days. The nano- and micro-tubes have a lamellar- and relaxed fcc-type wall, respectively, both following partial epitaxial relationship with the co-existing multiply twinned nanoparticles. The entangled tubes, being mesomorphic with a large extent of bifurcation, flexibility, opaqueness, and surface-enhanced Raman scattering, may have potential encapsulated and catalytic/label applications in biomedical systems

    MicroRNA signatures in B-cell lymphomas

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    Accurate lymphoma diagnosis, prognosis and therapy still require additional markers. We explore the potential relevance of microRNA (miRNA) expression in a large series that included all major B-cell non-Hodgkin lymphoma (NHL) types. The data generated were also used to identify miRNAs differentially expressed in Burkitt lymphoma (BL) and diffuse large B-cell lymphoma (DLBCL) samples. A series of 147 NHL samples and 15 controls were hybridized on a human miRNA one-color platform containing probes for 470 human miRNAs. Each lymphoma type was compared against the entire set of NHLs. BL was also directly compared with DLBCL, and 43 preselected miRNAs were analyzed in a new series of routinely processed samples of 28 BLs and 43 DLBCLs using quantitative reverse transcription-polymerase chain reaction. A signature of 128 miRNAs enabled the characterization of lymphoma neoplasms, reflecting the lymphoma type, cell of origin and/or discrete oncogene alterations. Comparative analysis of BL and DLBCL yielded 19 differentially expressed miRNAs, which were confirmed in a second confirmation series of 71 paraffin-embedded samples. The set of differentially expressed miRNAs found here expands the range of potential diagnostic markers for lymphoma diagnosis, especially when differential diagnosis of BL and DLBCL is required

    Asian dust-storm activity dominated by Chinese dynasty changes since 2000 BP

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    The Asian monsoon (AM) played an important role in the dynastic history of China, yet it remains unknown whether AM-mediated shifts in Chinese societies affect earth surface processes to the point of exceeding natural variability. Here, we present a dust storm intensity record dating back to the first unified dynasty of China (the Qin Dynasty, 221–207 B.C.E.). Marked increases in dust storm activity coincided with unified dynasties with large populations during strong AM periods. By contrast, reduced dust storm activity corresponded to decreased population sizes and periods of civil unrest, which was co-eval with a weakened AM. The strengthened AM may have facilitated the development of Chinese civilizations, destabilizing the topsoil and thereby increasing the dust storm frequency. Beginning at least 2000 years ago, human activities might have started to overtake natural climatic variability as the dominant controls of dust storm activity in eastern China

    Measurement of the Bottom-Strange Meson Mixing Phase in the Full CDF Data Set

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    We report a measurement of the bottom-strange meson mixing phase \beta_s using the time evolution of B0_s -> J/\psi (->\mu+\mu-) \phi (-> K+ K-) decays in which the quark-flavor content of the bottom-strange meson is identified at production. This measurement uses the full data set of proton-antiproton collisions at sqrt(s)= 1.96 TeV collected by the Collider Detector experiment at the Fermilab Tevatron, corresponding to 9.6 fb-1 of integrated luminosity. We report confidence regions in the two-dimensional space of \beta_s and the B0_s decay-width difference \Delta\Gamma_s, and measure \beta_s in [-\pi/2, -1.51] U [-0.06, 0.30] U [1.26, \pi/2] at the 68% confidence level, in agreement with the standard model expectation. Assuming the standard model value of \beta_s, we also determine \Delta\Gamma_s = 0.068 +- 0.026 (stat) +- 0.009 (syst) ps-1 and the mean B0_s lifetime, \tau_s = 1.528 +- 0.019 (stat) +- 0.009 (syst) ps, which are consistent and competitive with determinations by other experiments.Comment: 8 pages, 2 figures, Phys. Rev. Lett 109, 171802 (2012

    GLP-1 receptor signalling promotes β-cell glucose metabolism via mTOR-dependent HIF-1α activation

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    Glucagon-like peptide-1 (GLP-1) promotes insulin secretion from pancreatic ß-cells in a glucose dependent manner. Several pathways mediate this action by rapid, kinase phosphorylation-dependent, but gene expression-independent mechanisms. Since GLP-1-induced insulin secretion requires glucose metabolism, we aimed to address the hypothesis that GLP-1 receptor (GLP-1R) signalling can modulate glucose uptake and utilization in ß-cells. We have assessed various metabolic parameters after short and long exposure of clonal BRIN-BD11 ß-cells and rodent islets to the GLP-1R agonist Exendin-4 (50 nM). Here we report for the first time that prolonged stimulation of the GLP-1R for 18 hours promotes metabolic reprogramming of ß-cells. This is evidenced by up-regulation of glycolytic enzyme expression, increased rates of glucose uptake and consumption, as well as augmented ATP content, insulin secretion and glycolytic flux after removal of Exendin-4. In our model, depletion of Hypoxia-Inducible Factor 1 alpha (HIF-1a) impaired the effects of Exendin-4 on glucose metabolism, while pharmacological inhibition of Phosphoinositide 3-kinase (PI3K) or mTOR completely abolished such effects. Considering the central role of glucose catabolism for stimulus-secretion coupling in ß-cells, our findings suggest that chronic GLP-1 actions on insulin secretion include elevated ß-cell glucose metabolism. Moreover, our data reveal novel aspects of GLP-1 stimulated insulin secretion involving de novo gene expression

    Bioactive Electrospun Scaffolds Delivering Growth Factors and Genes for Tissue Engineering Applications

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    A biomaterial scaffold is one of the key factors for successful tissue engineering. In recent years, an increasing tendency has been observed toward the combination of scaffolds and biomolecules, e.g. growth factors and therapeutic genes, to achieve bioactive scaffolds, which not only provide physical support but also express biological signals to modulate tissue regeneration. Huge efforts have been made on the exploration of strategies to prepare bioactive scaffolds. Within the past five years, electrospun scaffolds have gained an exponentially increasing popularity in this area because of their ultrathin fiber diameter and large surface-volume ratio, which is favored for biomolecule delivery. This paper reviews current techniques that can be used to prepare bioactive electrospun scaffolds, including physical adsorption, blend electrospinning, coaxial electrospinning, and covalent immobilization. In addition, this paper also analyzes the existing challenges (i.e., protein instability, low gene transfection efficiency, and difficulties in accurate kinetics prediction) to achieve biomolecule release from electrospun scaffolds, which necessitate further research to fully exploit the biomedical applications of these bioactive scaffolds
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