58 research outputs found

    Mechanistic and Performance Studies on the Ligand Promoted Ullmann Amination Reaction

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    Over the last two decades many different auxiliary ligand systems have been utilized in the copper-catalyzed Ullmann amination reaction. However, there has been little consensus on the relative merits of the varied ligands and the exact role they might play in the catalytic process. Accordingly, in this work some of the most commonly employed auxiliary ligands have been evaluated for C–N coupling using reaction progress kinetic analysis (RPKA) methodology. The results reveal not only the relative kinetic competencies of the different auxiliary ligands but also their markedly different influences on catalyst degradation rates. For the model Ullmann reaction between piperidine and iodobenzene using the soluble organic base bis(tetra-n-butylphosphonium) malonate (TBPM) at room temperature, N-methylglycine was shown to give the best performance in terms of high catalytic rate of reaction and comparatively low catalyst deactivation rates. Further experimental and rate data indicate a common catalytic cycle for all auxiliary ligands studied, although additional off-cycle processes are observed for some of the ligands (notably phenanthroline). The ability of the auxiliary ligand, base (malonate dianion), and substrate (amine) to all act competitively as ligands for the copper center is also demonstrated. On the basis of these results an improved protocol for room-temperature copper-catalyzed C–N couplings is presented with 27 different examples reported

    Measurement of the Bottom-Strange Meson Mixing Phase in the Full CDF Data Set

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    We report a measurement of the bottom-strange meson mixing phase \beta_s using the time evolution of B0_s -> J/\psi (->\mu+\mu-) \phi (-> K+ K-) decays in which the quark-flavor content of the bottom-strange meson is identified at production. This measurement uses the full data set of proton-antiproton collisions at sqrt(s)= 1.96 TeV collected by the Collider Detector experiment at the Fermilab Tevatron, corresponding to 9.6 fb-1 of integrated luminosity. We report confidence regions in the two-dimensional space of \beta_s and the B0_s decay-width difference \Delta\Gamma_s, and measure \beta_s in [-\pi/2, -1.51] U [-0.06, 0.30] U [1.26, \pi/2] at the 68% confidence level, in agreement with the standard model expectation. Assuming the standard model value of \beta_s, we also determine \Delta\Gamma_s = 0.068 +- 0.026 (stat) +- 0.009 (syst) ps-1 and the mean B0_s lifetime, \tau_s = 1.528 +- 0.019 (stat) +- 0.009 (syst) ps, which are consistent and competitive with determinations by other experiments.Comment: 8 pages, 2 figures, Phys. Rev. Lett 109, 171802 (2012

    Numerical methods for the design and description of in vitro expansion processes of human mesenchymal stem cells

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    Human mesenchymal stem cells (hMSCs) are a valuable source of cells for clinical applications (e.g., treatment of acute myocardial infarction or inflammatory diseases), especially in the field of regenerative medicine. However, for autologous (patient-specific) and allogeneic (off-the-shelf) hMSC-based therapies, in vitro expansion is necessary prior to the clinical application in order to achieve the required cell numbers. Safe, reproducible, and economic in vitro expansion of hMSCs for autologous and allogeneic therapies can be problematic because the cell material is restricted and the cells are sensitive to environmental changes. It is beneficial to collect detailed information on the hydrodynamic conditions and cell growth behavior in a bioreactor system, in order to develop a so called “Digital Twin” of the cultivation system and expansion process. Numerical methods, such as Computational Fluid Dynamics (CFD) which has become widely used in the biotech industry for studying local characteristics within bioreactors or kinetic growth modelling, provide possible solutions for such tasks. In this review, we will present the current state-of-the-art for the in vitro expansion of hMSCs. Different numerical tools, including numerical fluid flow simulations and cell growth modelling approaches for hMSCs, will be presented. In addition, a case study demonstrating the applicability of CFD and kinetic growth modelling for the development of an microcarrier-based hMSC process will be shown

    Pan-cancer analysis of whole genomes

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    Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

    Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

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    In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field
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