91 research outputs found

    Combined Density Functional Theory and Monte Carlo Analysis of Monomolecular Cracking of Light Alkanes Over H-ZSM-5

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    Density functional calculations applying periodic boundary conditions have been performed to investigate adsorption and cracking of light alkanes (C 3-C 6) on zeolite H-ZSM-5. Intrinsic energy barriers were obtained from single-point calculations by applying the revised form of the PBE functional (RPBE) to structures optimized on the PBE potential energy surface. Dispersion interactions were accounted for by adding a damped dispersion term to the PBE energies. The dependence of the adsorption enthalpy on the carbon number is in agreement with experimental observation. From intrinsic energy barriers, intrinsic rate coefficients were calculated by means of transition state theory. The dependence of the intrinsic enthalpy and entropy of activation on the carbon number is discussed and compared to experimental observations. Transition path sampling was employed to unravel qualitatively the reaction mechanism for cracking of butane. Monte Carlo simulations in the canonical ensemble were conducted to estimate the temperature dependence of the adsorption enthalpy and entropy of propane to n-hexane. These quantities are not constant, as is often assumed in the interpretation of experimental data but become less negative with increasing temperature. It is shown how the selection of adsorption parameters influences the extraction of intrinsic rate parameters from experimental rate data. Based on the present analysis, an alternative partitioning of the experimentally accessible apparent entropy of activation into contributions from adsorption and intrinsic reaction is proposed. © 2012 American Chemical Society

    Large-Scale Computational Screening of Zeolites for Ethane/Ethene Separation

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    Large-scale computational screening of thirty thousand zeolite structures was conducted to find optimal structures for separation of ethane/ethene mixtures. Efficient grand canonical Monte Carlo (GCMC) simulations were performed with graphics processing units (GPUs) to obtain pure component adsorption isotherms for both ethane and ethene. We have utilized the ideal adsorbed solution theory (IAST) to obtain the mixture isotherms, which were used to evaluate the performance of each zeolite structure based on its working capacity and selectivity. In our analysis, we have determined that specific arrangements of zeolite framework atoms create sites for the preferential adsorption of ethane over ethene. The majority of optimum separation materials can be identified by utilizing this knowledge and screening structures for the presence of this feature will enable the efficient selection of promising candidate materials for ethane/ethene separation prior to performing molecular simulations. © 2012 American Chemical Society

    Ab-initio Carbon Capture in Open-Site Metal Organic Frameworks

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    During the formation of metal–organic frameworks (MOFs), metal centres can coordinate with the intended organic linkers, but also with solvent molecules. In this case, subsequent activation by removal of the solvent molecules creates unsaturated ‘open’ metal sites known to have a strong affinity for CO2 molecules, but their interactions are still poorly understood. Common force fields typically underestimate by as much as two orders of magnitude the adsorption of CO2 in open-site Mg-MOF-74, which has emerged as a promising MOF for CO2 capture. Here we present a systematic procedure to generate force fields using high-level quantum chemical calculations. Monte Carlo simulations based on an ab initio force field generated for CO2 in Mg-MOF-74 shed some light on the interpretation of thermodynamic data from flue gas in this material. The force field describes accurately the chemistry of the open metal sites, and is transferable to other structures. This approach may serve in molecular simulations in general and in the study of fluid–solid interactions

    Point-of-Care Testing for Toxoplasma Gondii IgG/IgM Using Toxoplasma ICT IgG-IgM Test with Sera from the United States and Implications for Developing Countries

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    Background Congenital toxoplasmosis is a serious but preventable and treatable disease. Gestational screening facilitates early detection and treatment of primary acquisition. Thus, fetal infection can be promptly diagnosed and treated and outcomes can be improved. Methods We tested 180 sera with the Toxoplasma ICT IgG-IgM point-of-care (POC) test. Sera were from 116 chronically infected persons (48 serotype II; 14 serotype I-III; 25 serotype I-IIIa; 28 serotype Atypical, haplogroup 12; 1 not typed). These represent strains of parasites infecting mothers of congenitally infected children in the U.S. 51 seronegative samples and 13 samples from recently infected persons known to be IgG/IgM positive within the prior 2.7 months also were tested. Interpretation was confirmed by two blinded observers. A comparison of costs for POC vs. commercial laboratory testing methods was performed. Results We found that this new Toxoplasma ICT IgG-IgM POC test was highly sensitive (100%) and specific (100%) for distinguishing IgG/IgM-positive from negative sera. Use of such reliable POC tests can be cost-saving and benefit patients. Conclusions Our work demonstrates that the Toxoplasma ICT IgG-IgM test can function reliably as a point-of-care test to diagnose Toxoplasma gondii infection in the U.S. This provides an opportunity to improve maternal-fetal care by using approaches, diagnostic tools, and medicines already available. This infection has serious, lifelong consequences for infected persons and their families. From the present study, it appears a simple, low-cost POC test is now available to help prevent morbidity/disability, decrease cost, and make gestational screening feasible. It also offers new options for improved prenatal care in low- and middle-income countries

    In silico screening of carbon-capture materials

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    One of the main bottlenecks to deploying large-scale carbon dioxide capture and storage (CCS) in power plants is the energy required to separate the CO 2 from flue gas. For example, near-term CCS technology applied to coal-fired power plants is projected to reduce the net output of the plant by some 30% and to increase the cost of electricity by 60-80%. Developing capture materials and processes that reduce the parasitic energy imposed by CCS is therefore an important area of research. We have developed a computational approach to rank adsorbents for their performance in CCS. Using this analysis, we have screened hundreds of thousands of zeolite and zeolitic imidazolate framework structures and identified many different structures that have the potential to reduce the parasitic energy of CCS by 30-40% compared with near-term technologies. © 2012 Macmillan Publishers Limited. All rights reserved

    Positron emission tomography and magnetic resonance imaging methods and datasets within the Dominantly Inherited Alzheimer Network (DIAN)

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    The Dominantly Inherited Alzheimer Network (DIAN) is an international collaboration studying autosomal dominant Alzheimer disease (ADAD). ADAD arises from mutations occurring in three genes. Offspring from ADAD families have a 50% chance of inheriting their familial mutation, so non-carrier siblings can be recruited for comparisons in case-control studies. The age of onset in ADAD is highly predictable within families, allowing researchers to estimate an individual\u27s point in the disease trajectory. These characteristics allow candidate AD biomarker measurements to be reliably mapped during the preclinical phase. Although ADAD represents a small proportion of AD cases, understanding neuroimaging-based changes that occur during the preclinical period may provide insight into early disease stages of \u27sporadic\u27 AD also. Additionally, this study provides rich data for research in healthy aging through inclusion of the non-carrier controls. Here we introduce the neuroimaging dataset collected and describe how this resource can be used by a range of researchers

    Progastrin Represses the Alternative Activation of Human Macrophages and Modulates Their Influence on Colon Cancer Epithelial Cells

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    Macrophage infiltration is a negative prognostic factor for most cancers but gastrointestinal tumors seem to be an exception. The effect of macrophages on cancer progression depends on their phenotype, which may vary between M1 (pro-inflammatory, defensive) to M2 (tolerogenic, pro-tumoral). Gastrointestinal cancers often become an ectopic source of gastrins and macrophages present receptors for these peptides. The aim of the present study is to analyze whether gastrins can affect the pattern of macrophage infiltration in colorectal tumors. We have evaluated the relationship between gastrin expression and the pattern of macrophage infiltration in samples from colorectal cancer and the influence of these peptides on the phenotype of macrophages differentiated from human peripheral monocytes in vitro. The total number of macrophages (CD68+ cells) was similar in tumoral and normal surrounding tissue, but the number of M2 macrophages (CD206+ cells) was significantly higher in the tumor. However, the number of these tumor-associated M2 macrophages correlated negatively with the immunoreactivity for gastrin peptides in tumor epithelial cells. Macrophages differentiated from human peripheral monocytes in the presence of progastrin showed lower levels of M2-markers (CD206, IL10) with normal amounts of M1-markers (CD86, IL12). Progastrin induced similar effects in mature macrophages treated with IL4 to obtain a M2-phenotype or with LPS plus IFNγ to generate M1-macrophages. Macrophages differentiated in the presence of progastrin presented a reduced expression of Wnt ligands and decreased the number and increased cell death of co-cultured colorectal cancer epithelial cells. Our results suggest that progastrin inhibits the acquisition of a M2-phenotype in human macrophages. This effect exerted on tumor associated macrophages may modulate cancer progression and should be taken into account when analyzing the therapeutic value of gastrin immunoneutralization

    Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

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    Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

    Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

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    This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin
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