815 research outputs found

    The cascade structure of linear instability in collapsible channel flows

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    This paper studies the unsteady behaviour and linear stability of the flow in a collapsible channel using a fluid–beam model. The solid mechanics is analysed in a plane strain configuration, in which the principal stretch is defined with a zero initial strain. Two approaches are employed: unsteady numerical simulations solving the nonlinear fully coupled fluid–structure interaction problem; and the corresponding linearized eigenvalue approach solving the Orr–Sommerfeld equations modified by the beam. The two approaches give good agreement with each other in predicting the frequencies and growth rates of the perturbation modes, close to the neutral curves. For a given Reynolds number in the range of 200–600, a cascade of instabilities is discovered as the wall stiffness (or effective tension) is reduced. Under small perturbation to steady solutions for the same Reynolds number, the system loses stability by passing through a succession of unstable zones, with mode number increasing as the wall stiffness is decreased. It is found that this cascade structure can, in principle, be extended to many modes, depending on the parameters. A puzzling ‘tongue’ shaped stable zone in the wall stiffness–Re space turns out to be the zone sandwiched by the mode-2 and mode-3 instabilities. Self-excited oscillations dominated by modes 2–4 are found near their corresponding neutral curves. These modes can also interact and form period-doubling oscillations. Extensive comparisons of the results with existing analytical models are made, and a physical explanation for the cascade structure is proposed

    Synergy of Two Assembly Languages in DNA Nanostructures: Self-Assembly of Sequence-Defined Polymers on DNA Cages

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    DNA base-pairing is the central interaction in DNA assembly. However, this simple four-letter (A–T and G–C) language makes it difficult to create complex structures without using a large number of DNA strands of different sequences. Inspired by protein folding, we introduce hydrophobic interactions to expand the assembly language of DNA nanotechnology. To achieve this, DNA cages of different geometries are combined with sequence-defined polymers containing long alkyl and oligoethylene glycol repeat units. Anisotropic decoration of hydrophobic polymers on one face of the cage leads to hydrophobically driven formation of quantized aggregates of DNA cages, where polymer length determines the cage aggregation number. Hydrophobic chains decorated on both faces of the cage can undergo an intrascaffold “handshake” to generate DNA-micelle cages, which have increased structural stability and assembly cooperativity, and can encapsulate small molecules. The polymer sequence order can control the interaction between hydrophobic blocks, leading to unprecedented “doughnut-shaped” DNA cage-ring structures. We thus demonstrate that new structural and functional modes in DNA nanostructures can emerge from the synergy of two interactions, providing an attractive approach to develop protein-inspired assembly modules in DNA nanotechnology

    Tumor necrosis Factor (TNF) Bioactivity at the site of an acute cell-Mediated immune response is Preserved in rheumatoid arthritis Patients responding to anti-TNF Therapy

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    The impact of anti-tumor necrosis factor (TNF) therapies on inducible TNF-dependent activity in humans has never been evaluated in vivo. We aimed to test the hypothesis that patients responding to anti-TNF treatments exhibit attenuated TNF-dependent immune responses at the site of an immune challenge. We developed and validated four context-specific TNF-inducible transcriptional signatures to quantify TNF bioactivity in transcriptomic data. In anti-TNF treated rheumatoid arthritis (RA) patients, we measured the expression of these biosignatures in blood, and in skin biopsies from the site of tuberculin skin tests (TSTs) as a human experimental model of multivariate cell-mediated immune responses. In blood, anti-TNF therapies attenuated TNF bioactivity following ex vivo stimulation. However, at the site of the TST, TNF-inducible gene expression and genome-wide transcriptional changes associated with cell-mediated immune responses were comparable to that of RA patients receiving methotrexate only. These data demonstrate that anti-TNF agents in RA patients do not inhibit inducible TNF activity at the site of an acute inflammatory challenge in vivo, as modeled by the TST. We hypothesize instead that their therapeutic effects are limited to regulating TNF activity in chronic inflammation or by alternative non-canonical pathways

    Compromised Function of Regulatory T Cells in Rheumatoid Arthritis and Reversal by Anti-TNFα Therapy

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    Regulatory T cells have been clearly implicated in the control of disease in murine models of autoimmunity. The paucity of data regarding the role of these lymphocytes in human autoimmune disease has prompted us to examine their function in patients with rheumatoid arthritis (RA). Regulatory (CD4+CD25+) T cells isolated from patients with active RA displayed an anergic phenotype upon stimulation with anti-CD3 and anti-CD28 antibodies, and suppressed the proliferation of effector T cells in vitro. However, they were unable to suppress proinflammatory cytokine secretion from activated T cells and monocytes, or to convey a suppressive phenotype to effector CD4+CD25− T cells. Treatment with antitumor necrosis factor α (TNFα; Infliximab) restored the capacity of regulatory T cells to inhibit cytokine production and to convey a suppressive phenotype to “conventional” T cells. Furthermore, anti-TNFα treatment led to a significant rise in the number of peripheral blood regulatory T cells in RA patients responding to this treatment, which correlated with a reduction in C reactive protein. These data are the first to demonstrate that regulatory T cells are functionally compromised in RA, and indicate that modulation of regulatory T cells by anti-TNFα therapy may be a further mechanism by which this disease is ameliorated

    Maternal Use of Antibiotics, Hospitalisation for Infection during Pregnancy, and Risk of Childhood Epilepsy: A Population-Based Cohort Study

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    BACKGROUND: Maternal infection during pregnancy may be a risk factor for epilepsy in offspring. Use of antibiotics is a valid marker of infection. METHODOLOGY/PRINCIPAL FINDINGS: To examine the relationship between maternal infection during pregnancy and risk of childhood epilepsy we conducted a historical cohort study of singletons born in northern Denmark from 1998 through 2008 who survived ≥29 days. We used population-based medical databases to ascertain maternal use of antibiotics or hospital contacts with infection during pregnancy, as well as first-time hospital contacts with a diagnosis of epilepsy among offspring. We compared incidence rates (IR) of epilepsy among children of mothers with and without infection during pregnancy. We examined the outcome according to trimester of exposure, type of antibiotic, and total number of prescriptions, using Poisson regression to estimate incidence rate ratios (IRRs) while adjusting for covariates. Among 191,383 children in the cohort, 948 (0.5%) were hospitalised or had an outpatient visit for epilepsy during follow-up, yielding an IR of 91 per 100 000 person-years (PY). The five-year cumulative incidence of epilepsy was 4.5 per 1000 children. Among children exposed prenatally to maternal infection, the IR was 117 per 100,000 PY, with an adjusted IRR of 1.40 (95% confidence interval (CI): 1.22-1.61), compared with unexposed children. The association was unaffected by trimester of exposure, antibiotic type, or prescription count. CONCLUSIONS/SIGNIFICANCE: Prenatal exposure to maternal infection is associated with an increased risk of epilepsy in childhood. The similarity of estimates across types of antibiotics suggests that processes common to all infections underlie this outcome, rather than specific pathogens or drugs

    Remodeling of central metabolism in invasive breast cancer compared to normal breast tissue - a GC-TOFMS based metabolomics study

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    BACKGROUND: Changes in energy metabolism of the cells are common to many kinds of tumors and are considered a hallmark of cancer. Gas chromatography followed by time-of-flight mass spectrometry (GC-TOFMS) is a well-suited technique to investigate the small molecules in the central metabolic pathways. However, the metabolic changes between invasive carcinoma and normal breast tissues were not investigated in a large cohort of breast cancer samples so far. RESULTS: A cohort of 271 breast cancer and 98 normal tissue samples was investigated using GC-TOFMS-based metabolomics. A total number of 468 metabolite peaks could be detected; out of these 368 (79%) were significantly changed between cancer and normal tissues (p80%. Two-metabolite classifiers, constructed as ratios of the tumor and normal tissues markers, separated cancer from normal tissues with high sensitivity and specificity. Specifically, the cytidine-5-monophosphate / pentadecanoic acid metabolic ratio was the most significant discriminator between cancer and normal tissues and allowed detection of cancer with a sensitivity of 94.8% and a specificity of 93.9%. CONCLUSIONS: For the first time, a comprehensive metabolic map of breast cancer was constructed by GC-TOF analysis of a large cohort of breast cancer and normal tissues. Furthermore, our results demonstrate that spectrometry-based approaches have the potential to contribute to the analysis of biopsies or clinical tissue samples complementary to histopathology
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