1,393 research outputs found
Joint detection-estimation of directional channel parameters using the 2-D frequency domain SAGE algorithm with serial interference cancellation
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Schools, psychosocial well-being and agency: From fragmentation to coherence
This article is about the relationship between everyday practice in schools and the development of agency. It examines two areas of current concern in which agency is seen to play a key role: young people’s mental health or human flourishing and their development as citizens. The argument is made that the foundation stone of agency is self-efficacy and that related crucial attitudes and beliefs are learned in school. The role of agency in learning and its importance in young people’s psychosocial development are discussed. The latter part of the article focuses upon how schools can become effectively agency orientated.Non
RNA-directed activation of cytoplasmic ayriein-1 in reconstituted transport RNPs
Polarised mRNA transport is a prevalent mechanism for spatial control of protein
synthesis. However, the composition of transported ribonucleoprotein particles (RNPs) and the
regulation of their movement are poorly understood. We have reconstituted microtubule minus
end-directed transport of mRNAs using purified components. A Bicaudal-D (BicD) adaptor protein
and the RNA-binding protein Egalitarian (Egl) are sufficient for long-distance mRNA transport by
the dynein motor and its accessory complex dynactin, thus defining a minimal transport-competent
RNP. Unexpectedly, the RNA is required for robust activation of dynein motility. We show that a
cis-acting RNA localisation signal promotes the interaction of Egl with BicD, which licenses the
latter protein to recruit dynein and dynactin. Our data support a model for BicD activation based
on RNA-induced occupancy of two Egl-binding sites on the BicD dimer. Scaffolding of adaptor
protein assemblies by cargoes is an attractive mechanism for regulating intracellular transport
Radiosensitization by the ATR Inhibitor AZD6738 through Generation of Acentric Micronuclei.
AZD6738 is an orally active ATR inhibitor (ATRi) currently in phase I clinical trials. We found in vitro growth inhibitory activity of this ATRi in a panel of human cancer cell lines. We demonstrated radiosensitization by AZD6738 to single radiation fractions in multiple cancer cell lines independent of both p53 and BRCA2 status by the clonogenic assay. Radiosensitization by AZD6738 to clinically relevant doses of fractionated radiation was demonstrated in vitro using a 3D tumor spheroid model and, in vivo, AZD6738 radiosensitized by abrogating the radiation-induced G2 cell-cycle checkpoint and inhibiting homologous recombination. Mitosis with damaged DNA resulted in mitotic catastrophe as measured by micronucleus formation by live-cell fluorescent-ubiquitination cell-cycle imaging of cell-cycle progression and nuclear morphology. Induction of micronuclei was significantly more prominent for AZD6738 compared with inhibition of the downstream kinase CHK1 alone at isoeffective doses. Micronuclei were characterized as acentric chromosomal fragments, which displayed characteristics of increased DNA damage and cell-cycle dyssynchrony when compared with the primary nucleus. Mol Cancer Ther; 16(1); 25-34. ©2016 AACR
Multimodal imaging needle combining optical coherence tomography and fluorescence for imaging of live breast cancer cells labeled with a fluorescent analog of tamoxifen
Significance: Imaging needles consist of highly miniaturized focusing optics encased within a hypodermic needle. The needles may be inserted tens of millimeters into tissue and have the potential to visualize diseased cells well beyond the penetration depth of optical techniques applied externally. Multimodal imaging needles acquire multiple types of optical signals to differentiate cell types. However, their use has not previously been demonstrated with live cells.Aim: We demonstrate the ability of a multimodal imaging needle to differentiate cell types through simultaneous optical coherence tomography (OCT) and fluorescence imaging.Approach: We characterize the performance of a multimodal imaging needle. This is paired with a fluorescent analog of the therapeutic drug, tamoxifen, which enables cell-specific fluorescent labeling of estrogen receptor-positive (ER+) breast cancer cells. We perform simultaneous OCT and fluorescence in situ imaging on MCF-7 ER+ breast cancer cells and MDA-MB-231 ER-cells. Images are compared against unlabeled control samples and correlated with standard confocal microscopy images.Results: We establish the feasibility of imaging live cells with these miniaturized imaging probes by showing clear differentiation between cancerous cells.Conclusions: Imaging needles have the potential to aid in the detection of specific cancer cells within solid tissue
New genomic resources for switchgrass: a BAC library and comparative analysis of homoeologous genomic regions harboring bioenergy traits
<p>Abstract</p> <p>Background</p> <p>Switchgrass, a C4 species and a warm-season grass native to the prairies of North America, has been targeted for development into an herbaceous biomass fuel crop. Genetic improvement of switchgrass feedstock traits through marker-assisted breeding and biotechnology approaches calls for genomic tools development. Establishment of integrated physical and genetic maps for switchgrass will accelerate mapping of value added traits useful to breeding programs and to isolate important target genes using map based cloning. The reported polyploidy series in switchgrass ranges from diploid (2X = 18) to duodecaploid (12X = 108). Like in other large, repeat-rich plant genomes, this genomic complexity will hinder whole genome sequencing efforts. An extensive physical map providing enough information to resolve the homoeologous genomes would provide the necessary framework for accurate assembly of the switchgrass genome.</p> <p>Results</p> <p>A switchgrass BAC library constructed by partial digestion of nuclear DNA with <it>Eco</it>RI contains 147,456 clones covering the effective genome approximately 10 times based on a genome size of 3.2 Gigabases (~1.6 Gb effective). Restriction digestion and PFGE analysis of 234 randomly chosen BACs indicated that 95% of the clones contained inserts, ranging from 60 to 180 kb with an average of 120 kb. Comparative sequence analysis of two homoeologous genomic regions harboring orthologs of the rice <it>OsBRI1 </it>locus, a low-copy gene encoding a putative protein kinase and associated with biomass, revealed that orthologous clones from homoeologous chromosomes can be unambiguously distinguished from each other and correctly assembled to respective fingerprint contigs. Thus, the data obtained not only provide genomic resources for further analysis of switchgrass genome, but also improve efforts for an accurate genome sequencing strategy.</p> <p>Conclusions</p> <p>The construction of the first switchgrass BAC library and comparative analysis of homoeologous harboring <it>OsBRI1 </it>orthologs present a glimpse into the switchgrass genome structure and complexity. Data obtained demonstrate the feasibility of using HICF fingerprinting to resolve the homoeologous chromosomes of the two distinct genomes in switchgrass, providing a robust and accurate BAC-based physical platform for this species. The genomic resources and sequence data generated will lay the foundation for deciphering the switchgrass genome and lead the way for an accurate genome sequencing strategy.</p
Accuracy of popular automatic QT Interval algorithms assessed by a 'Gold Standard' and comparison with a Novel method: computer simulation study
BACKGROUND: Accurate measurement of the QT interval is very important from a clinical and pharmaceutical drug safety screening perspective. Expert manual measurement is both imprecise and imperfectly reproducible, yet it is used as the reference standard to assess the accuracy of current automatic computer algorithms, which thus produce reproducible but incorrect measurements of the QT interval. There is a scientific imperative to evaluate the most commonly used algorithms with an accurate and objective 'gold standard' and investigate novel automatic algorithms if the commonly used algorithms are found to be deficient. METHODS: This study uses a validated computer simulation of 8 different noise contaminated ECG waveforms (with known QT intervals of 461 and 495 ms), generated from a cell array using Luo-Rudy membrane kinetics and the Crank-Nicholson method, as a reference standard to assess the accuracy of commonly used QT measurement algorithms. Each ECG contaminated with 39 mixtures of noise at 3 levels of intensity was first filtered then subjected to three threshold methods (T1, T2, T3), two T wave slope methods (S1, S2) and a Novel method. The reproducibility and accuracy of each algorithm was compared for each ECG. RESULTS: The coefficient of variation for methods T1, T2, T3, S1, S2 and Novel were 0.36, 0.23, 1.9, 0.93, 0.92 and 0.62 respectively. For ECGs of real QT interval 461 ms the methods T1, T2, T3, S1, S2 and Novel calculated the mean QT intervals(standard deviations) to be 379.4(1.29), 368.5(0.8), 401.3(8.4), 358.9(4.8), 381.5(4.6) and 464(4.9) ms respectively. For ECGs of real QT interval 495 ms the methods T1, T2, T3, S1, S2 and Novel calculated the mean QT intervals(standard deviations) to be 396.9(1.7), 387.2(0.97), 424.9(8.7), 386.7(2.2), 396.8(2.8) and 493(0.97) ms respectively. These results showed significant differences between means at >95% confidence level. Shifting ECG baselines caused large errors of QT interval with T1 and T2 but no error with Novel. CONCLUSION: The algorithms T2, T1 and Novel gave low coefficients of variation for QT measurement. The Novel technique gave the most accurate measurement of QT interval, T3 (a differential threshold method) was the next most accurate by a large margin. The objective and accurate 'gold standard' presented in this paper may be useful to assess new QT measurement algorithms. The Novel algorithm may prove to be more accurate and reliable method to measure the QT interval
Modeling flow cytometry data for cancer vaccine immune monitoring
Flow cytometry (FCM) is widely used in cancer research for diagnosis, detection of minimal residual disease, as well as immune monitoring and profiling following immunotherapy. In all these applications, the challenge is to detect extremely rare cell subsets while avoiding spurious positive events. To achieve this objective, it helps to be able to analyze FCM data using multiple markers simultaneously, since the additional information provided often helps to minimize the number of false positive and false negative events, hence increasing both sensitivity and specificity. However, with manual gating, at most two markers can be examined in a single dot plot, and a sequential strategy is often used. As the sequential strategy discards events that fall outside preceding gates at each stage, the effectiveness of the strategy is difficult to evaluate without laborious and painstaking back-gating. Model-based analysis is a promising computational technique that works using information from all marker dimensions simultaneously, and offers an alternative approach to flow analysis that can usefully complement manual gating in the design of optimal gating strategies. Results from model-based analysis will be illustrated with examples from FCM assays commonly used in cancer immunotherapy laboratories
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