16,396 research outputs found

    Transcriptional profiling of SNAI2 regulated genes in primary human keratinocytes.

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    Epithelial to mesenchymal transition transcription factors (EMT-TFs) such as SNAI2 have been found to be expressed endogenously in epidermal stem and progenitor cells and downregulated upon differentiation. The presence of SNAI2 in progenitor cells is necessary to repress the expression of differentiation genes by binding directly to their promoters. SNAI2 is downregulated upon differentiation which allows expression of differentiation genes. Furthermore overexpression of SNAI2 can block the differentiation process suggesting that the levels of SNAI2 are crucial to epidermal cell fate decisions. To address on a genome wide level the genes that are impacted by changing the levels of SNAI2, we performed microarray analysis on SNAI2 knockdown and overexpressing epidermal progenitor cells. Here we provide a detailed methods and analysis on these microarray data which has been deposited in Gene Expression Omnibus (GEO): GSE55269

    DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs

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    In this work we address the task of semantic image segmentation with Deep Learning and make three main contributions that are experimentally shown to have substantial practical merit. First, we highlight convolution with upsampled filters, or 'atrous convolution', as a powerful tool in dense prediction tasks. Atrous convolution allows us to explicitly control the resolution at which feature responses are computed within Deep Convolutional Neural Networks. It also allows us to effectively enlarge the field of view of filters to incorporate larger context without increasing the number of parameters or the amount of computation. Second, we propose atrous spatial pyramid pooling (ASPP) to robustly segment objects at multiple scales. ASPP probes an incoming convolutional feature layer with filters at multiple sampling rates and effective fields-of-views, thus capturing objects as well as image context at multiple scales. Third, we improve the localization of object boundaries by combining methods from DCNNs and probabilistic graphical models. The commonly deployed combination of max-pooling and downsampling in DCNNs achieves invariance but has a toll on localization accuracy. We overcome this by combining the responses at the final DCNN layer with a fully connected Conditional Random Field (CRF), which is shown both qualitatively and quantitatively to improve localization performance. Our proposed "DeepLab" system sets the new state-of-art at the PASCAL VOC-2012 semantic image segmentation task, reaching 79.7% mIOU in the test set, and advances the results on three other datasets: PASCAL-Context, PASCAL-Person-Part, and Cityscapes. All of our code is made publicly available online.Comment: Accepted by TPAM

    On-chip SQUID measurements in the presence of high magnetic fields

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    We report a low temperature measurement technique and magnetization data of a quantum molecular spin, by implementing an on-chip SQUID technique. This technique enables the SQUID magnetometery in high magnetic fields, up to 7 Tesla. The main challenges and the calibration process are detailed. The measurement protocol is used to observe quantum tunneling jumps of the S=10 molecular magnet, Mn12-tBuAc. The effect of transverse field on the tunneling splitting for this molecular system is addressed as well.Comment: 7 pages, 3 figure

    Celecoxib concentration predicts decrease in prostaglandin E\u3csub\u3e2\u3c/sub\u3e concentrations in nipple aspirate fluid from high risk women

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    BACKGROUND: Epidemiologic studies suggest that long term low dose celecoxib use significantly lowers breast cancer risk. We previously demonstrated that 400 mg celecoxib taken twice daily for 2 weeks lowered circulating plasma and breast nipple aspirate fluid (NAF) prostaglandin (PG)E2 concentrations in post- but not premenopausal high risk women. We hypothesized that circulating concentrations of celecoxib influenced PGE2 response, and that plasma levels of the drug are influenced by menopausal status. To address these hypotheses, the aims of the study were to determine: 1) if circulating plasma concentrations of celecoxib correlated with the change in plasma or NAF PGE2 concentrations from baseline to end of treatment, and 2) whether menopausal status influenced circulating levels of celecoxib. METHODS: Matched NAF and plasma were collected from 46 high risk women who were administered celecoxib twice daily for two weeks, 20 subjects receiving 200 mg and 26 subjects 400 mg of the agent. NAF and plasma samples were collected before and 2 weeks after taking celecoxib. RESULTS: In women taking 400 mg bid celecoxib, plasma concentrations of the agent correlated inversely with the change in NAF PGE2 levels from pre- to posttreatment. Nonsignificant trends toward higher celecoxib levels were observed in post- compared to premenopausal women. There was a significant decrease in NAF but not plasma PGE2 concentrations in postmenopausal women who took 400 mg celecoxib (p = 0.03). CONCLUSION: In high risk women taking 400 mg celecoxib twice daily, plasma concentrations of celecoxib correlated with downregulation of PGE2 production by breast tissue. Strategies synergistic with celecoxib to downregulate PGE2 are of interest, in order to minimize the celecoxib dose required to have an effect

    Thermal Lattice Boltzmann Simulations of Variable Prandtl Number Turbulent Flows

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    Thermal lattice Boltzmann (TLBE) models that utilize the single relaxation time scalar Bhatnagar, Gross, and Krook collision operator have an invariant Prandtl number. For flows with arbitrary Prandtl number, a matrix collision operator is introduced. The relaxation parameters are generalized so that the transport coefficients become density independent. TLBE simulations are presented for two-dimensional free decaying turbulence induced by a strongly perturbed double velocity shear layer for various Prandtl numbers
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