317 research outputs found

    Large-scale 3-D modeling by integration of resistivity models and borehole data through inversion

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    We present an automatic method for parameterization of a 3-D model of the subsurface, integrating lithological information from boreholes with resistivity models through an inverse optimization, with the objective of further detailing of geological models, or as direct input into groundwater models. The parameter of interest is the clay fraction, expressed as the relative length of clay units in a depth interval. The clay fraction is obtained from lithological logs and the clay fraction from the resistivity is obtained by establishing a simple petrophysical relationship, a translator function, between resistivity and the clay fraction. Through inversion we use the lithological data and the resistivity data to determine the optimum spatially distributed translator function. Applying the translator function we get a 3-D clay fraction model, which holds information from the resistivity data set and the borehole data set in one variable. Finally, we use k-means clustering to generate a 3-D model of the subsurface structures. We apply the procedure to the Norsminde survey in Denmark, integrating approximately 700 boreholes and more than 100 000 resistivity models from an airborne survey in the parameterization of the 3-D model covering 156 km2. The final five-cluster 3-D model differentiates between clay materials and different high-resistivity materials from information held in the resistivity model and borehole observations, respectively

    In vitro efficacy of artemisinin-based treatments against SARS-CoV-2

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    Effective and affordable treatments for patients suffering from coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), are needed. We report in vitro efficacy of Artemisia annua extracts as well as artemisinin, artesunate, and artemether against SARS-CoV-2. The latter two are approved active pharmaceutical ingredients of anti-malarial drugs. Concentration–response antiviral treatment assays, based on immunostaining of SARS-CoV-2 spike glycoprotein, revealed that treatment with all studied extracts and compounds inhibited SARS-CoV-2 infection of VeroE6 cells, human hepatoma Huh7.5 cells and human lung cancer A549-hACE2 cells, without obvious influence of the cell type on antiviral efficacy. In treatment assays, artesunate proved most potent (range of 50% effective concentrations (EC50) in different cell types: 7–12 µg/mL), followed by artemether (53–98 µg/mL), A. annua extracts (83–260 µg/mL) and artemisinin (151 to at least 208 µg/mL). The selectivity indices (SI), calculated based on treatment and cell viability assays, were mostly below 10 (range 2 to 54), suggesting a small therapeutic window. Time-of-addition experiments in A549-hACE2 cells revealed that artesunate targeted SARS-CoV-2 at the post-entry level. Peak plasma concentrations of artesunate exceeding EC50 values can be achieved. Clinical studies are required to further evaluate the utility of these compounds as COVID-19 treatment

    Hydroeconomic optimization of reservoir management under downstream water quality constraints

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    A hydroeconomic optimization approach is used to guide water management in a Chinese river basin with the objectives of meeting water quantity and water quality constraints, in line with the China 2011 No. 1 Policy Document and 2015 Ten-point Water Plan. The proposed modeling framework couples water quantity and water quality management and minimizes the total costs over a planning period assuming stochastic future runoff. The outcome includes cost-optimal reservoir releases, groundwater pumping, water allocation, wastewater treatments and water curtailments. The optimization model uses a variant of stochastic dynamic programming known as the water value method. Nonlinearity arising from the water quality constraints is handled with an effective hybrid method combining genetic algorithms and linear programming. Untreated pollutant loads are represented by biochemical oxygen demand (BOD), and the resulting minimum dissolved oxygen (DO) concentration is computed with the Streeter-Phelps equation and constrained to match Chinese water quality targets. The baseline water scarcity and operational costs are estimated to 15.6 billion CNY/year. Compliance to water quality grade Ill causes a relatively low increase to 16.4 billion CNY/year. Dilution plays an important role and increases the share of surface water allocations to users situated furthest downstream in the system. The modeling framework generates decision rules that result in the economically efficient strategy for complying with both water quantity and water quality constraints. (C) 2015 Elsevier B.V. All rights reserved

    Induction of microRNAs, mir-155, mir-222, mir-424 and mir-503, promotes monocytic differentiation through combinatorial regulation

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    Acute myeloid leukemia (AML) involves a block in terminal differentiation of the myeloid lineage and uncontrolled proliferation of a progenitor state. Using phorbol myristate acetate (PMA), it is possible to overcome this block in THP-1 cells (an M5-AML containing the MLL-MLLT3 fusion), resulting in differentiation to an adherent monocytic phenotype. As part of FANTOM4, we used microarrays to identify 23 microRNAs that are regulated by PMA. We identify four PMA-induced micro- RNAs (mir-155, mir-222, mir-424 and mir-503) that when overexpressed cause cell-cycle arrest and partial differentiation and when used in combination induce additional changes not seen by any individual microRNA. We further characterize these prodifferentiative microRNAs and show that mir-155 and mir-222 induce G2 arrest and apoptosis, respectively. We find mir-424 and mir-503 are derived from a polycistronic precursor mir-424-503 that is under repression by the MLL-MLLT3 leukemogenic fusion. Both of these microRNAs directly target cell-cycle regulators and induce G1 cell-cycle arrest when overexpressed in THP-1. We also find that the pro-differentiative mir-424 and mir-503 downregulate the anti-differentiative mir-9 by targeting a site in its primary transcript. Our study highlights the combinatorial effects of multiple microRNAs within cellular systems.Comment: 45 pages 5 figure

    The Viral and Cellular MicroRNA Targetome in Lymphoblastoid Cell Lines

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    Epstein-Barr virus (EBV) is a ubiquitous human herpesvirus linked to a number of B cell cancers and lymphoproliferative disorders. During latent infection, EBV expresses 25 viral pre-microRNAs (miRNAs) and induces the expression of specific host miRNAs, such as miR-155 and miR-21, which potentially play a role in viral oncogenesis. To date, only a limited number of EBV miRNA targets have been identified; thus, the role of EBV miRNAs in viral pathogenesis and/or lymphomagenesis is not well defined. Here, we used photoactivatable ribonucleoside-enhanced crosslinking and immunoprecipitation (PAR-CLIP) combined with deep sequencing and computational analysis to comprehensively examine the viral and cellular miRNA targetome in EBV strain B95-8-infected lymphoblastoid cell lines (LCLs). We identified 7,827 miRNA-interaction sites in 3,492 cellular 3′UTRs. 531 of these sites contained seed matches to viral miRNAs. 24 PAR-CLIP-identified miRNA:3′UTR interactions were confirmed by reporter assays. Our results reveal that EBV miRNAs predominantly target cellular transcripts during latent infection, thereby manipulating the host environment. Furthermore, targets of EBV miRNAs are involved in multiple cellular processes that are directly relevant to viral infection, including innate immunity, cell survival, and cell proliferation. Finally, we present evidence that myc-regulated host miRNAs from the miR-17/92 cluster can regulate latent viral gene expression. This comprehensive survey of the miRNA targetome in EBV-infected B cells represents a key step towards defining the functions of EBV-encoded miRNAs, and potentially, identifying novel therapeutic targets for EBV-associated malignancies

    Assessing the Utility of Thermodynamic Features for microRNA Target Prediction under Relaxed Seed and No Conservation Requirements

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    BACKGROUND: Many computational microRNA target prediction tools are focused on several key features, including complementarity to 5'seed of miRNAs and evolutionary conservation. While these features allow for successful target identification, not all miRNA target sites are conserved and adhere to canonical seed complementarity. Several studies have propagated the use of energy features of mRNA:miRNA duplexes as an alternative feature. However, different independent evaluations reported conflicting results on the reliability of energy-based predictions. Here, we reassess the usefulness of energy features for mammalian target prediction, aiming to relax or eliminate the need for perfect seed matches and conservation requirement. METHODOLOGY/PRINCIPAL FINDINGS: We detect significant differences of energy features at experimentally supported human miRNA target sites and at genome-wide sites of AGO protein interaction. This trend is confirmed on datasets that assay the effect of miRNAs on mRNA and protein expression changes, and a simple linear regression model leads to significant correlation of predicted versus observed expression change. Compared to 6-mer seed matches as baseline, application of our energy-based model leads to ∼3-5-fold enrichment on highly down-regulated targets, and allows for prediction of strictly imperfect targets with enrichment above baseline. CONCLUSIONS/SIGNIFICANCE: In conclusion, our results indicate significant promise for energy-based miRNA target prediction that includes a broader range of targets without having to use conservation or impose stringent seed match rules
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