1,471 research outputs found
Fetal and Early Childhood Undernutrition, Mortality, and Lifelong Health
http://dx.doi.org/10.1126/science.122461
Evaluation of coagulation activation after Rhinovirus infection in patients with asthma and healthy control subjects: an observational study
Background Asthma exacerbations are frequently triggered by rhinovirus infections. Both asthma and respiratory tract infection can activate haemostasis. Therefore we hypothesized that experimental rhinovirus-16 infection and asthmatic airway inflammation act in synergy on the haemostatic balance. Methods 28 patients (14 patients with mild allergic asthma and 14 healthy non-allergic controls) were infected with low-dose rhinovirus type 16. Venous plasma and bronchoalveolar lavage fluid (BAL fluid) were obtained before and 6 days after infection to evaluate markers of coagulation activation, thrombin-antithrombin complexes, von Willebrand factor, plasmin-antiplasmin complexes, plasminogen activator inhibitor type-1, endogenous thrombin potential and tissue factor-exposing microparticles by fibrin generation test, in plasma and/or BAL fluid. Data were analysed by nonparametric tests (Wilcoxon, Mann Whitney and Spearman correlation). Results 13 patients with mild asthma (6 females, 19-29 y) and 11 healthy controls (10 females, 19-31 y) had a documented Rhinovirus-16 infection. Rhinovirus-16 challenge resulted in a shortening of the fibrin generation test in BAL fluid of asthma patients (t = -1: 706 s vs. t = 6: 498 s; p = 0.02), but not of controls (t = -1: 693 s vs. t = 6: 636 s; p = 0.65). The fold change in tissue factor-exposing microparticles in BAL fluid inversely correlated with the fold changes in eosinophil cationic protein and myeloperoxidase in BAL fluid after virus infection (r = -0.517 and -0.528 resp., both p = 0.01). Rhinovirus-16 challenge led to increased plasminogen activator inhibitor type-1 levels in plasma in patients with asthma (26.0 ng/mL vs. 11.5 ng/mL in healthy controls, p = 0.04). Rhinovirus-16 load in BAL showed a linear correlation with the fold change in endogenous thrombin potential, plasmin-antiplasmin complexes and plasminogen activator inhibitor type-1. Conclusions Experimental rhinovirus infection induces procoagulant changes in the airways of patients with asthma through increased activity of tissue factor-exposing microparticles. These microparticle-associated procoagulant changes are associated with both neutrophilic and eosinophilic inflammation. Systemic activation of haemostasis increases with Rhinoviral load
Identification of the slow E3 transition 136mCs -> 136Cs with conversion electrons
We performed at ISOLDE the spectroscopy of the decay of the 8- isomer in
136Cs by and conversion-electron detection. For the first time the excitation
energy of the isomer and the multipolarity of its decay have been measured. The
half-life of the isomeric state was remeasured to T1/2 = 17.5(2) s. This isomer
decays via a very slow 518 keV E3 transition to the ground state. In addition
to this, a much weaker decay branch via a 413 keV M4 and a subsequent 105 keV
E2 transition has been found. Thus we have found a new level at 105 keV with
spin 4+ between the isomeric and the ground state. The results are discussed in
comparison to shell model calculations.Comment: Phys. Rev. C accepted for publicatio
Bench-to-bedside review: Bacterial pneumonia with influenza - pathogenesis and clinical implications
First identification of large electric monopole strength in well-deformed rare earth nuclei
Excited states in the well-deformed rare earth isotopes Sm and
Er were populated via ``safe'' Coulomb excitation at the Munich MLL
Tandem accelerator. Conversion electrons were registered in a cooled Si(Li)
detector in conjunction with a magnetic transport and filter system, the
Mini-Orange spectrometer. For the first excited state in Sm at
1099 keV a large value of the monopole strength for the transition to the
ground state of could be extracted. This confirms the interpretation of the lowest
excited state in Sm as the collective -vibrational
excitation of the ground state. In Er the measured large electric
monopole strength of clearly identifies the state at 1934 keV to be the
-vibrational excitation of the ground state.Comment: submitted to Physics Letters
MeSi(CH2SnRO)3 (R = Ph, Me3SiCH2): Building blocks for triangular-shaped diorganotin oxide macrocycles
The syntheses of the novel silicon-bridged tris(tetraorganotin) compounds MeSi(CH2SnPh2R)3 (2, R=Ph; 5, R=Me3SiCH2) and their halogen-substituted derivatives MeSi(CH2SnPh(3−n)In)3 (3, n=1; 4, n=2) and MeSi(CH2SnI2R)3 (6, R=Me3SiCH2) are reported. The reaction of compound 4 with di-t-butyltin oxide (t-Bu2SnO)3 gives the oktokaideka-nuclear (18-nuclear) molecular diorganotin oxide [MeSi(CH2SnPhO)3]6 (7) while the reaction of 6 with sodium hydroxide, NaOH, provides the trikonta-nuclear (30-nuclear) molecular diorganotin oxide [MeSi(CH2SnRO)3]10 (8, R=Me3SiCH2). Both 7 and 8 show belt-like ladder-type macrocyclic structures and are by far the biggest molecular diorganotin oxides reported to date. The compounds have been characterized by elemental analyses, electrospray mass spectrometry (ESI-MS), NMR spectroscopy, 1H DOSY NMR spectroscopy (7), IR spectroscopy (7, 8), and single-crystal X-ray diffraction analysis (2, 7, 8)
Bench-to-bedside review: Bacterial pneumonia with influenza - pathogenesis and clinical implications
Knowledge-based gene expression classification via matrix factorization
Motivation: Modern machine learning methods based on matrix decomposition techniques, like independent component analysis (ICA) or non-negative matrix factorization (NMF), provide new and efficient analysis tools which are currently explored to analyze gene expression profiles. These exploratory feature extraction techniques yield expression modes (ICA) or metagenes (NMF). These extracted features are considered indicative of underlying regulatory processes. They can as well be applied to the classification of gene expression datasets by grouping samples into different categories for diagnostic purposes or group genes into functional categories for further investigation of related metabolic pathways and regulatory networks.
Results: In this study we focus on unsupervised matrix factorization techniques and apply ICA and sparse NMF to microarray datasets. The latter monitor the gene expression levels of human peripheral blood cells during differentiation from monocytes to macrophages. We show that these tools are able to identify relevant signatures in the deduced component matrices and extract informative sets of marker genes from these gene expression profiles. The methods rely on the joint discriminative power of a set of marker genes rather than on single marker genes. With these sets of marker genes, corroborated by leave-one-out or random forest cross-validation, the datasets could easily be classified into related diagnostic categories. The latter correspond to either monocytes versus macrophages or healthy vs Niemann Pick C disease patients.Siemens AG, MunichDFG (Graduate College 638)DAAD (PPP Luso - Alem˜a and PPP Hispano - Alemanas
Magnetic moments of Coulomb excited states for radioactive beams of Te and Xe isotopes at REX-ISOLDE
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