5,705 research outputs found

    Natural products and synthetic analogs as a source of antitumor drugs

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    Cancer is a heterogeneous disease and one of the major issues of health concern, especially for the public health system globally. Nature is a source of anticancer drugs with abundant pool of diverse chemicals and pharmacologically active compounds. In recent decade, some natural products and synthetic analogs have been investigated for the cancer treatment. This article presents the utilization of natural products as a source of antitumor drugs.This work was supported by CONICYT PIA/APOYO CCTE AFB170007

    An appropriate tool for entrepreneurial learning in SMEs? The case of the 20Twenty Leadership Programme

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    The 20Twenty Leadership Programme was developed by Cardiff Metropolitan University as an executive education programme to be delivered within South Wales to small businesses. It is funded by the European Social Fund (ESF) and administered by the Welsh European Funding Office and has the key aim of developing SME’s growth potential via a range of leadership and management skills, including a focus on ‘soft’ skills. The focus of this paper is to place the 20Twenty Leadership Programme within the wider context of entrepreneurship policy and SME training initiatives in particular, and then to examine the rationale and delivery methods of the Programme in relation to these. It also reflects on the Programme’s success (or otherwise) to date where possible. Finally, the paper seeks to suggest fruitful areas of further research both in terms of the 20Twenty Leadership Programme itself, but also with regard to evaluation in relation to other parallel programmes, and to SME training initiatives more generally

    Evolution favors protein mutational robustness in sufficiently large populations

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    BACKGROUND: An important question is whether evolution favors properties such as mutational robustness or evolvability that do not directly benefit any individual, but can influence the course of future evolution. Functionally similar proteins can differ substantially in their robustness to mutations and capacity to evolve new functions, but it has remained unclear whether any of these differences might be due to evolutionary selection for these properties. RESULTS: Here we use laboratory experiments to demonstrate that evolution favors protein mutational robustness if the evolving population is sufficiently large. We neutrally evolve cytochrome P450 proteins under identical selection pressures and mutation rates in populations of different sizes, and show that proteins from the larger and thus more polymorphic population tend towards higher mutational robustness. Proteins from the larger population also evolve greater stability, a biophysical property that is known to enhance both mutational robustness and evolvability. The excess mutational robustness and stability is well described by existing mathematical theories, and can be quantitatively related to the way that the proteins occupy their neutral network. CONCLUSIONS: Our work is the first experimental demonstration of the general tendency of evolution to favor mutational robustness and protein stability in highly polymorphic populations. We suggest that this phenomenon may contribute to the mutational robustness and evolvability of viruses and bacteria that exist in large populations

    Molecular cloning and transcriptional activity of a new Petunia calreticulin gene involved in pistil transmitting tract maturation, progamic phase, and double fertilization

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    Calreticulin (CRT) is a highly conserved and ubiquitously expressed Ca2+-binding protein in multicellular eukaryotes. As an endoplasmic reticulum-resident protein, CRT plays a key role in many cellular processes including Ca2+ storage and release, protein synthesis, and molecular chaperoning in both animals and plants. CRT has long been suggested to play a role in plant sexual reproduction. To begin to address this possibility, we cloned and characterized the full-length cDNA of a new CRT gene (PhCRT) from Petunia. The deduced amino acid sequence of PhCRT shares homology with other known plant CRTs, and phylogenetic analysis indicates that the PhCRT cDNA clone belongs to the CRT1/CRT2 subclass. Northern blot analysis and fluorescent in situ hybridization were used to assess PhCRT gene expression in different parts of the pistil before pollination, during subsequent stages of the progamic phase, and at fertilization. The highest level of PhCRT mRNA was detected in the stigma–style part of the unpollinated pistil 1 day before anthesis and during the early stage of the progamic phase, when pollen is germinated and tubes outgrow on the stigma. In the ovary, PhCRT mRNA was most abundant after pollination and reached maximum at the late stage of the progamic phase, when pollen tubes grow into the ovules and fertilization occurs. PhCRT mRNA transcripts were seen to accumulate predominantly in transmitting tract cells of maturing and receptive stigma, in germinated pollen/growing tubes, and at the micropylar region of the ovule, where the female gametophyte is located. From these results, we suggest that PhCRT gene expression is up-regulated during secretory activity of the pistil transmitting tract cells, pollen germination and outgrowth of the tubes, and then during gamete fusion and early embryogenesis

    Molecular dynamics simulations of oscillatory Couette flows with slip boundary conditions

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    The effect of interfacial slip on steady-state and time-periodic flows of monatomic liquids is investigated using non-equilibrium molecular dynamics simulations. The fluid phase is confined between atomically smooth rigid walls, and the fluid flows are induced by moving one of the walls. In steady shear flows, the slip length increases almost linearly with shear rate. We found that the velocity profiles in oscillatory flows are well described by the Stokes flow solution with the slip length that depends on the local shear rate. Interestingly, the rate dependence of the slip length obtained in steady shear flows is recovered when the slip length in oscillatory flows is plotted as a function of the local shear rate magnitude. For both types of flows, the friction coefficient at the liquid-solid interface correlates well with the structure of the first fluid layer near the solid wall.Comment: 31 pages, 11 figure

    Gold nanocrystals with variable index facets as highly effective cathode catalysts for lithium-oxygen batteries

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    © 2015 Nature Publishing Group All rights reserved. Cathode catalysts are the key factor in improving the electrochemical performance of lithium-oxygen (Li-O2) batteries via their promotion of the oxygen reduction and oxygen evolution reactions (ORR and OER). Generally, the catalytic performance of nanocrystals (NCs) toward ORR and OER depends on both composition and shape. Herein, we report the synthesis of polyhedral Au NCs enclosed by a variety of index facets: cubic gold (Au) NCs enclosed by {100} facets; truncated octahedral Au NCs enclosed by {100} and {110} facets; and trisoctahedral (TOH) Au NCs enclosed by 24 high-index {441} facets, as effective cathode catalysts for Li-O2 batteries. All Au NCs can significantly reduce the charge potential and have high reversible capacities. In particular, TOH Au NC catalysts demonstrated the lowest charge-discharge overpotential and the highest capacity of ∼ 20 298 mA h g-1. The correlation between the different Au NC crystal planes and their electrochemical catalytic performances was revealed: high-index facets exhibit much higher catalytic activity than the low-index planes, as the high-index planes have a high surface energy because of their large density of atomic steps, ledges and kinks, which can provide a high density of reactive sites for catalytic reactions

    From Nonspecific DNA–Protein Encounter Complexes to the Prediction of DNA–Protein Interactions

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    ©2009 Gao, Skolnick. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.doi:10.1371/journal.pcbi.1000341DNA–protein interactions are involved in many essential biological activities. Because there is no simple mapping code between DNA base pairs and protein amino acids, the prediction of DNA–protein interactions is a challenging problem. Here, we present a novel computational approach for predicting DNA-binding protein residues and DNA–protein interaction modes without knowing its specific DNA target sequence. Given the structure of a DNA-binding protein, the method first generates an ensemble of complex structures obtained by rigid-body docking with a nonspecific canonical B-DNA. Representative models are subsequently selected through clustering and ranking by their DNA–protein interfacial energy. Analysis of these encounter complex models suggests that the recognition sites for specific DNA binding are usually favorable interaction sites for the nonspecific DNA probe and that nonspecific DNA–protein interaction modes exhibit some similarity to specific DNA–protein binding modes. Although the method requires as input the knowledge that the protein binds DNA, in benchmark tests, it achieves better performance in identifying DNA-binding sites than three previously established methods, which are based on sophisticated machine-learning techniques. We further apply our method to protein structures predicted through modeling and demonstrate that our method performs satisfactorily on protein models whose root-mean-square Ca deviation from native is up to 5 Å from their native structures. This study provides valuable structural insights into how a specific DNA-binding protein interacts with a nonspecific DNA sequence. The similarity between the specific DNA–protein interaction mode and nonspecific interaction modes may reflect an important sampling step in search of its specific DNA targets by a DNA-binding protein
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