1,195 research outputs found

    Structural Characterization and Antioxidative Activity of Low-Molecular-Weights Beta-1,3-Glucan from the Residue of Extracted Ganoderma lucidum Fruiting Bodies

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    The major cell wall constituent of Ganoderma lucidum (G. lucidum) is β-1,3-glucan. This study examined the polysaccharide from the residues of alkaline-extracted fruiting bodies using high-performance anion-exchange chromatography (HPAEC), and it employed nuclear magnetic resonance (NMR) and mass spectrometry (MS) to confirm the structures. We have successfully isolated low-molecular-weight β-1,3-glucan (LMG), in high yields, from the waste residue of extracted fruiting bodies of G. lucidum. The 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) assay evaluated the capability of LMG to suppress H2O2-induced cell death in RAW264.7 cells, identifying that LMG protected cells from H2O2-induced damage. LMG treatment decreased H2O2-induced intracellular reactive oxygen species (ROS) production. LMG also influenced sphingomyelinase (SMase) activity, stimulated by cell death to induce ceramide formation, and then increase cell ROS production. Estimation of the activities of neutral and acid SMases in vitro showed that LMG suppressed the activities of both neutral and acid SMases in a concentration-dependent manner. These results suggest that LMG, a water-soluble β-1,3-glucan recycled from extracted residue of G. lucidum, possesses antioxidant capability against H2O2-induced cell death by attenuating intracellular ROS and inhibiting SMase activity

    miRTarBase update 2014: an information resource for experimentally validated miRNA-target interactions

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    MicroRNAs (miRNAs) are small non-coding RNA molecules capable of negatively regulating gene expression to control many cellular mechanisms. The miRTarBase database (http://mirtarbase.mbc.nctu.edu.tw/) provides the most current and comprehensive information of experimentally validated miRNA-target interactions. The database was launched in 2010 with data sources for >100 published studies in the identification of miRNA targets, molecular networks of miRNA targets and systems biology, and the current release (2013, version 4) includes significant expansions and enhancements over the initial release (2010, version 1). This article reports the current status of and recent improvements to the database, including (i) a 14-fold increase to miRNA-target interaction entries, (ii) a miRNA-target network, (iii) expression profile of miRNA and its target gene, (iv) miRNA target-associated diseases and (v) additional utilities including an upgrade reminder and an error reporting/user feedback system

    HuR cytoplasmic expression is associated with increased cyclin A expression and poor outcome with upper urinary tract urothelial carcinoma

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    BACKGROUND: HuR is an RNA-binding protein that post-transcriptionally modulates the expressions of various target genes implicated in carcinogenesis, such as CCNA2 encoding cyclin A. No prior study attempted to evaluate the significance of HuR expression in a large cohort with upper urinary tract urothelial carcinomas (UTUCs). METHODS: In total, 340 cases of primary localized UTUC without previous or concordant bladder carcinoma were selected. All of these patients received ureterectomy or radical nephroureterectomy with curative intents. Pathological slides were reviewed, and clinical findings were collected. Immunostaining for HuR and cyclin A was performed and evaluated by using H-score. The results of cytoplasmic HuR and nuclear cyclin A expressions were correlated with disease-specific survival (DSS), metastasis-free survival (MeFS), urinary bladder recurrence-free survival (UBRFS), and various clinicopathological factors. RESULTS: HuR cytoplasmic expression was significantly related to the pT status, lymph node metastasis, a higher histological grade, the pattern of invasion, vascular and perineurial invasion, and cyclin A expression (p = 0.005). Importantly, HuR cytoplasmic expression was strongly associated with a worse DSS (p < 0.0001), MeFS (p < 0.0001), and UBRFS (p = 0.0370) in the univariate analysis, and the first two results remained independently predictive of adverse outcomes (p = 0.038, relative risk [RR] = 1.996 for DSS; p = 0.027, RR = 1.880 for MeFS). Cyclin A nuclear expression was associated with a poor DSS (p = 0.0035) and MeFS (p = 0.0015) in the univariate analysis but was not prognosticatory in the multivariate analyses. High-risk patients (pT3 or pT4 with/without nodal metastasis) with high HuR cytoplasmic expression had better DSS if adjuvant chemotherapy was performed (p = 0.015). CONCLUSIONS: HuR cytoplasmic expression was correlated with adverse phenotypes and cyclin A overexpression and also independently predictive of worse DSS and MeFS, suggesting its roles in tumorigenesis or carcinogenesis and potentiality as a prognostic marker of UTUC. High HuR cytoplasmic expression might identify patients more likely to be beneficial for adjuvant chemotherapy

    Automatic leukocyte nucleus segmentation by intuitionistic fuzzy divergence based thresholding

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    The paper proposes a robust approach to automatic segmentation of leukocyte‟s nucleus from microscopic blood smear images under normal as well as noisy environment by employing a new exponential intuitionistic fuzzy divergence based thresholding technique. The algorithm minimizes the divergence between the actual image and the ideally thresholded image to search for the final threshold. A new divergence formula based on exponential intuitionistic fuzzy entropy has been proposed. Further, to increase its noise handling capacity, a neighborhood-based membership function for the image pixels has been designed. The proposed scheme has been applied on 110 normal and 54 leukemia (chronic myelogenous leukemia) affected blood samples. The nucleus segmentation results have been validated by three expert haematologists. The algorithm achieves an average segmentation accuracy of 98.52% in noise-free environment. It beats the competitor algorithms in terms of several other metrics. The proposed scheme with neighborhood based membership function outperforms the competitor algorithms in terms of segmentation accuracy under noisy environment. It achieves 93.90% and 94.93% accuracies for Speckle and Gaussian noises respectively. The average area under the ROC curves comes out to be 0.9514 in noisy conditions, which proves the robustness of the proposed algorithm

    Constraints on the χ_(c1) versus χ_(c2) polarizations in proton-proton collisions at √s = 8 TeV

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    The polarizations of promptly produced χ_(c1) and χ_(c2) mesons are studied using data collected by the CMS experiment at the LHC, in proton-proton collisions at √s=8  TeV. The χ_c states are reconstructed via their radiative decays χ_c → J/ψγ, with the photons being measured through conversions to e⁺e⁻, which allows the two states to be well resolved. The polarizations are measured in the helicity frame, through the analysis of the χ_(c2) to χ_(c1) yield ratio as a function of the polar or azimuthal angle of the positive muon emitted in the J/ψ → μ⁺μ⁻ decay, in three bins of J/ψ transverse momentum. While no differences are seen between the two states in terms of azimuthal decay angle distributions, they are observed to have significantly different polar anisotropies. The measurement favors a scenario where at least one of the two states is strongly polarized along the helicity quantization axis, in agreement with nonrelativistic quantum chromodynamics predictions. This is the first measurement of significantly polarized quarkonia produced at high transverse momentum
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