95 research outputs found

    Methodology of calculation of construction and hydrodynamic parameters of a foam layer apparatus for mass-transfer processes

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    Промислова реалізація методу стабілізації газорідинного шару дозволяє значно розширити галузь застосування пінних апаратів і відкриває нові можливості інтенсифікації технологічних процесів з одночасним створенням маловідходних технологій. У статті встановлені основні параметри, що впливають на гідродинаміку пінних апаратів, розглянуті основні конструкції та режими роботи пінних апаратів. Виявлено зв'язок гідродинамічних параметрів. Розглянуто гідродинамічні закономірності пінного шару. Вказані фактори, що впливають на процес масообміну, як в газовій, так і в рідкій фазах. Проведений аналіз ряду досліджень показав, що перспективним напрямком інтенсифікації процесу масообміну є розробка апаратів з трифазним псевдозрідженим шаром зрошуваної насадки складних форм із сітчастих матеріалів. Отже, необхідне проведення спеціальних досліджень гідродинамічних режимів роботи апарату з сітчастою насадкою і визначенням параметрів, що впливають на швидкість переходу насадки з одного режиму в інший.Industrial implementation of the stabilization method of the gas-liquid layer can significantly expand the field of use of foaming apparatus and opens up new opportunities for intensifying technological processes with the simultaneous creation of low-waste technologies. The article establishes the basic parameters influencing the hydrodynamics of foam apparatus, considers the basic constructions and operating modes of foam apparatus. The connection of hydrodynamic parameters is revealed. The hydrodynamic laws of the foam layer are considered. The indicated factors affecting the process of mass transfer, both in the gas and in the liquid phases. The conducted analysis of a number of studies showed that the perspective direction of intensification of the mass transfer process is the development of apparatuses with a three-phase fluidized bed of an irrigated nozzle of complex forms with mesh materials

    Cytokine Levels Correlate with Immune Cell Infiltration after Anti-VEGF Therapy in Preclinical Mouse Models of Breast Cancer

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    The effect of blocking VEGF activity in solid tumors extends beyond inhibition of angiogenesis. However, no studies have compared the effectiveness of mechanistically different anti-VEGF inhibitors with respect to changes in tumor growth and alterations in the tumor microenvironment. In this study we use three distinct breast cancer models, a MDA-MB-231 xenograft model, a 4T1 syngenic model, and a transgenic model using MMTV-PyMT mice, to explore the effects of various anti-VEGF therapies on tumor vasculature, immune cell infiltration, and cytokine levels. Tumor vasculature and immune cell infiltration were evaluated using immunohistochemistry. Cytokine levels were evaluated using ELISA and electrochemiluminescence. We found that blocking the activation of VEGF receptor resulted in changes in intra-tumoral cytokine levels, specifically IL-1β, IL-6 and CXCL1. Modulation of the level these cytokines is important for controlling immune cell infiltration and ultimately tumor growth. Furthermore, we demonstrate that selective inhibition of VEGF binding to VEGFR2 with r84 is more effective at controlling tumor growth and inhibiting the infiltration of suppressive immune cells (MDSC, Treg, macrophages) while increasing the mature dendritic cell fraction than other anti-VEGF strategies. In addition, we found that changes in serum IL-1β and IL-6 levels correlated with response to therapy, identifying two possible biomarkers for assessing the effectiveness of anti-VEGF therapy in breast cancer patients

    Mutational analysis of the C-terminal FATC domain of Saccharomyces cerevisiae Tra1

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    Tra1 is a component of the Saccharomyces cerevisiae SAGA and NuA4 complexes and a member of the PIKK family, which contain a C-terminal phosphatidylinositol 3-kinase-like (PI3K) domain followed by a 35-residue FATC domain. Single residue changes of L3733A and F3744A, within the FATC domain, resulted in transcriptional changes and phenotypes that were similar but not identical to those caused by mutations in the PI3K domain or deletions of other SAGA or NuA4 components. The distinct nature of the FATC mutations was also apparent from the additive effect of tra1-L3733A with SAGA, NuA4, and tra1 PI3K domain mutations. Tra1-L3733A associates with SAGA and NuA4 components and with the Gal4 activation domain, to the same extent as wild-type Tra1; however, steady-state levels of Tra1-L3733A were reduced. We suggest that decreased stability of Tra1-L3733A accounts for the phenotypes since intragenic suppressors of tra1-L3733A restored Tra1 levels, and reducing wild-type Tra1 led to comparable growth defects. Also supporting a key role for the FATC domain in the structure/function of Tra1, addition of a C-terminal glycine residue resulted in decreased association with Spt7 and Esa1, and loss of cellular viability. These findings demonstrate the regulatory potential of mechanisms targeting the FATC domains of PIKK proteins

    Linking Proteomic and Transcriptional Data through the Interactome and Epigenome Reveals a Map of Oncogene-induced Signaling

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    Cellular signal transduction generally involves cascades of post-translational protein modifications that rapidly catalyze changes in protein-DNA interactions and gene expression. High-throughput measurements are improving our ability to study each of these stages individually, but do not capture the connections between them. Here we present an approach for building a network of physical links among these data that can be used to prioritize targets for pharmacological intervention. Our method recovers the critical missing links between proteomic and transcriptional data by relating changes in chromatin accessibility to changes in expression and then uses these links to connect proteomic and transcriptome data. We applied our approach to integrate epigenomic, phosphoproteomic and transcriptome changes induced by the variant III mutation of the epidermal growth factor receptor (EGFRvIII) in a cell line model of glioblastoma multiforme (GBM). To test the relevance of the network, we used small molecules to target highly connected nodes implicated by the network model that were not detected by the experimental data in isolation and we found that a large fraction of these agents alter cell viability. Among these are two compounds, ICG-001, targeting CREB binding protein (CREBBP), and PKF118–310, targeting β-catenin (CTNNB1), which have not been tested previously for effectiveness against GBM. At the level of transcriptional regulation, we used chromatin immunoprecipitation sequencing (ChIP-Seq) to experimentally determine the genome-wide binding locations of p300, a transcriptional co-regulator highly connected in the network. Analysis of p300 target genes suggested its role in tumorigenesis. We propose that this general method, in which experimental measurements are used as constraints for building regulatory networks from the interactome while taking into account noise and missing data, should be applicable to a wide range of high-throughput datasets.National Science Foundation (U.S.) (DB1-0821391)National Institutes of Health (U.S.) (Grant U54-CA112967)National Institutes of Health (U.S.) (Grant R01-GM089903)National Institutes of Health (U.S.) (P30-ES002109

    Current concepts in clinical radiation oncology

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    A women empowerment model

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    The Circe principle explains how resource-rich land can waylay pollinators in fragmented landscapes.

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    Global declines in pollinators, associated with land-use change [1-6] and fragmentation [7-10], constitute a serious threat to crop production and biodiversity [11]. Models investigating impacts of habitat fragmentation on pollen flow have categorized landscapes simply in terms of habitat and nonhabitat. We show that pollen flow depends strongly on types of land use between habitat fragments. We used paternity analysis of seeds and a combination of circuit and general linear models to analyze pollen flow for the endangered tree Gomortega keule (Gomortegaceae) [12] in the fragmented Central Chile Biodiversity Hotspot [13]. Pollination probability was highest over pine plantation, moderate over low-intensity agriculture and native forest, and lowest over clearfells. Changing the proportions of the land uses over one kilometer altered pollination probability up to 7-fold. We explain our results by the novel "Circe principle." In contrast to models where land uses similar to native habitat promote pollinator movement, pollinators may actually be waylaid in resource-rich areas between habitat patches. Moreover, pollinators may move with higher probability between habitat patches separated by some resource-poor land uses. Pollination research in fragmented landscapes requires explicit recognition of the nature of the nonhabitat matrix, rather than applying simple binary landscape models

    Learning to solve nonlinear least squares for monocular stereo

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    Sum-of-squares objective functions are very popular in computer vision algorithms. However, these objective functions are not always easy to optimize. The underlying assumptions made by solvers are often not satisfied and many problems are inherently ill-posed. In this paper, we propose a neural nonlinear least squares optimization algorithm which learns to effectively optimize these cost functions even in the presence of adversities. Unlike traditional approaches, the proposed solver requires no hand-crafted regularizers or priors as these are implicitly learned from the data. We apply our method to the problem of motion stereo ie. jointly estimating the motion and scene geometry from pairs of images of a monocular sequence. We show that our learned optimizer is able to efficiently and effectively solve this challenging optimization problem
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