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                  <text>Coronavirus</text>
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                  <text>Dominio científico: Coronavirus</text>
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                <text>PhyloPythiaS+: a self-training method for the rapid reconstruction of low-ranking taxonomic bins from metagenomes</text>
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                <text>Ivan Gregor, Johannes Dröge, Melanie Schirmer, Christopher Quince, Alice C. McHardy</text>
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                <text>Background. Metagenomics is an approach for characterizing environmental microbial communities in situ, it allows their functional and taxonomic characterization and to recover sequences from uncultured taxa. This is often achieved by a combination of sequence assembly and binning, where sequences are grouped into ‘bins’ representing taxa of the underlying microbial community. Assignment to low-ranking taxonomic bins is an important challenge for binning methods as is scalability to Gb-sized datasets generated with deep sequencing techniques. One of the best available methods for species bins recovery from deep-branching phyla is the expert-trained PhyloPythiaS package, where a human expert decides on the taxa to incorporate in the model and identifies ‘training’ sequences based on marker genes directly from the sample. Due to the manual effort involved, this approach does not scale to multiple metagenome samples and requires substantial expertise, which researchers who are new to the area do not have. Results. We have developed PhyloPythiaS+, a successor to our PhyloPythia(S) software. The new (+) component performs the work previously done by the human expert. PhyloPythiaS+ also includes a new k-mer counting algorithm, which accelerated the simultaneous counting of 4–6-mers used for taxonomic binning 100-fold and reduced the overall execution time of the software by a factor of three. Our software allows to analyze Gb-sized metagenomes with inexpensive hardware, and to recover species or genera-level bins with low error rates in a fully automated fashion. PhyloPythiaS+ was compared to MEGAN, taxator-tk, Kraken and the generic PhyloPythiaS model. The results showed that PhyloPythiaS+ performs especially well for samples originating from novel environments in comparison to the other methods. Availability. PhyloPythiaS+ in a virtual machine is available for installation under Windows, Unix systems or OS X on: https://github.com/algbioi/ppsp/wiki.</text>
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                <text>2016</text>
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                <text>metagenomics, taxonomic classification, machine learning, Bioinformatics</text>
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                <text>DOI: 10.7717/peerj.1603</text>
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                <text>PeerJ</text>
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                <text>PeerJ Inc.</text>
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                <text>Medicine</text>
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              <description>An account of the resource</description>
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                  <text>Dominio científico: Coronavirus</text>
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      <name>Text</name>
      <description>A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text.</description>
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                <text>More and More Coronaviruses: Human Coronavirus HKU1</text>
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                <text>Patrick C. Y. Woo, Susanna K. P. Lau, Cyril C.Y. Yip, Yi Huang, Kwok-yung Yuen</text>
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            <description>An account of the resource</description>
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                <text>After human coronaviruses OC43, 229E and NL63, human coronavirus HKU1 (HCoV-HKU1) is the fourth human coronavirus discovered. HCoV-HKU1 is a group 2a coronavirus that is still not cultivable. The G + C contents of HCoV-HKU1 genomes are 32%, the lowest among all known coronaviruses with complete genome sequences available. Among all coronaviruses, HCoV-HKU1 shows the most extreme codon usage bias, attributed most importantly to severe cytosine deamination. All HCoV-HKU1 genomes contain unique tandem copies of a 30-base acidic tandem repeat of unknown function at the N-terminus of nsp3 inside the acidic domain upstream of papain-like protease 1. Three genotypes, A, B and C, of HCoV-HKU1 and homologous recombination among their genomes, are observed. The incidence of HCoV-HKU1 infections is the highest in winter. Similar to other human coronaviruses, HCoV-HKU1 infections have been reported globally, with a median (range) incidence of 0.9 (0 – 4.4) %. HCoV-HKU1 is associated with both upper and lower respiratory tract infections that are mostly self-limiting. The most common method for diagnosing HCoV-HKU1 infection is RT-PCR or real-time RT-PCR using RNA extracted from respiratory tract samples such as nasopharyngeal aspirates (NPA). Both the pol and nucleocapsid genes have been used as the targets for amplification. Monoclonal antibodies have been generated for direct antigen detection in NPA. For antibody detection, Escherichia coli BL21 and baculovirus-expressed recombinant nucleocapsid of HCoV-HKU1 have been used for IgG and IgM detection in sera of patients and normal individuals, using Western blot and enzyme-linked immunoassay.</text>
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                <text>2009</text>
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                <text>coronavirus, human, HKU1, novel</text>
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            <name>Identifier</name>
            <description>An unambiguous reference to the resource within a given context</description>
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                <text>DOI: 10.3390/v1010057</text>
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            <description>A related resource from which the described resource is derived</description>
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                <text>Viruses</text>
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                <text>MDPI AG</text>
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            <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
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                <text>Microbiology</text>
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            <description>A language of the resource</description>
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                <text>EN</text>
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              <name>Title</name>
              <description>A name given to the resource</description>
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                  <text>Coronavirus</text>
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              <name>Description</name>
              <description>An account of the resource</description>
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                  <text>Dominio científico: Coronavirus</text>
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      <name>Text</name>
      <description>A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text.</description>
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        <name>Dublin Core</name>
        <description>The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.</description>
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                <text>Structural basis of development of multi-epitope vaccine against Middle East respiratory syndrome using in silico approach</text>
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              <elementText elementTextId="8336">
                <text>Srivastava S, Kamthania M, Singh S, Saxena AK, Sharma N</text>
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                <text>Sukrit Srivastava,1,2 Mohit Kamthania,1,3 Soni Singh,1 Ajay K Saxena,2  Nishi Sharma1 1Department of Biotechnology, Mangalayatan University, Aligarh, India; 2Molecular Medicine Lab, School of Life Sciences, Jawaharlal Nehru University, New Delhi, India; 3Department of Biotechnology, Faculty of Life Sciences, Institute of Applied Medicines and Research, Ghaziabad, Uttar Pradesh, India Background: Middle East respiratory syndrome (MERS) is caused by MERS coronavirus (MERS-CoV). Thus far, MERS outbreaks have been reported from Saudi Arabia (2013 and 2014) and South Korea (2015). No specific vaccine has yet been reported against MERS. Purpose: To address the urgent need for an MERS vaccine, in the present study, we have designed two multi-epitope vaccines (MEVs) against MERS utilizing several in silico methods and tools.Methods: The design of both the multi-epitope vaccines (MEVs) are composed of cytotoxic T lymphocyte (CTL) and helper T lymphocyte (HTL) epitopes, screened form thirteen different proteins of MERS-CoV. Both the MEVs also carry potential B-cell linear epitope regions, B-cell discontinuous epitopes as well as interferon-&amp;gamma;-inducing epitopes. Human &amp;beta;-defensin-2 and &amp;beta;-defensin-3 were used as adjuvants to enhance the immune response of MEVs. To design the MEVs, short peptide molecular linkers were utilized to link screened most potential CTL epitopes, HTL epitopes and the adjuvants. Tertiary models for both the MEVs were generated, refined, and further studied for their molecular interaction with toll-like receptor 3. The cDNAs of both MEVs were generated and analyzed in silico for their expression in a mammalian host cell line (human).Results: Screened CTL and HTL epitopes were found to have high propensity for stable molecular interaction with HLA alleles molecules. CTL epitopes were also found to have favorable molecular interaction within the cavity of transporter associated with antigen processing. The selected CTL and HTL epitopes jointly cover upto 94.0% of worldwide human population. Both the CTL and HTL MEVs molecular models have shown to have stable binding and complex formation propensity with toll-like receptor 3. The cDNA analysis of both the MEVs have shown high expression tendency in mammalian host cell line (human).Conclusion: After multistage in silico analysis, both the MEVs are predicted to elicit humoral as well as cell mediated immune response. Epitopes of the designed MEVs are predicted to cover large human population worldwide. Hence both the designed MEVs could be tried in vivo as potential vaccine candidates against MERS. Keywords: Middle East respiratory syndrome, MERS, Middle East respiratory syndrome coronavirus, MERS-CoV, human transporter associated with antigen processing, TAP, toll-like receptor 3, TLR-3, epitope, immunoinformatics, molecular docking, molecular dynamics simulation, MD simulation, multi-epitope vaccine</text>
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                <text>2018</text>
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                <text>Middle East respiratory syndrome (MERS), coronavirus, Human Transporter associated with antigen processing (TAP), Toll-Like Receptor 3 (TLR-3), epitope, immunoinformatics, molecular docking, Molecular dynamics (MD) simulation, multi-epitope vaccine</text>
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                <text>DOI: </text>
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            <name>Source</name>
            <description>A related resource from which the described resource is derived</description>
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              <elementText elementTextId="8341">
                <text>Infection and Drug Resistance</text>
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                <text>Dove Medical Press</text>
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            <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
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                <text>Infectious and parasitic diseases</text>
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            <description>A language of the resource</description>
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                <text>EN</text>
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                  <text>Coronavirus</text>
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              <description>An account of the resource</description>
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                  <text>Dominio científico: Coronavirus</text>
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      <name>Text</name>
      <description>A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text.</description>
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                <text>Norgal: extraction and de novo assembly of mitochondrial DNA from whole-genome sequencing data</text>
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            <description>An entity primarily responsible for making the resource</description>
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              <elementText elementTextId="8326">
                <text>Kosai Al-Nakeeb, Thomas Nordahl Petersen, Thomas Sicheritz-Pontén</text>
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                <text>Abstract Background Whole-genome sequencing (WGS) projects provide short read nucleotide sequences from nuclear and possibly organelle DNA depending on the source of origin. Mitochondrial DNA is present in animals and fungi, while plants contain DNA from both mitochondria and chloroplasts. Current techniques for separating organelle reads from nuclear reads in WGS data require full reference or partial seed sequences for assembling. Results Norgal (de Novo ORGAneLle extractor) avoids this requirement by identifying a high frequency subset of k-mers that are predominantly of mitochondrial origin and performing a de novo assembly on a subset of reads that contains these k-mers. The method was applied to WGS data from a panda, brown algae seaweed, butterfly and filamentous fungus. We were able to extract full circular mitochondrial genomes and obtained sequence identities to the reference sequences in the range from 98.5 to 99.5%. We also assembled the chloroplasts of grape vines and cucumbers using Norgal together with seed-based de novo assemblers. Conclusion Norgal is a pipeline that can extract and assemble full or partial mitochondrial and chloroplast genomes from WGS short reads without prior knowledge. The program is available at: https://bitbucket.org/kosaidtu/norgal .</text>
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                <text>2017</text>
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                <text>mitochondrial DNA, k-mer, Next-generation sequencing, de novo assembly</text>
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                <text>DOI: 10.1186/s12859-017-1927-y</text>
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            <description>A related resource from which the described resource is derived</description>
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              <elementText elementTextId="8331">
                <text>BMC Bioinformatics</text>
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                <text>Therapeutic Uses of Exosomes</text>
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                <text>Zacharias E. Suntres, Milton G. Smith, Fatemeh Momen-Heravi, Jie Hu, Xin Zhang, Ying Wu, Hongguang Zhu, Jiping Wang, Jian Zhou, Winston Patrick Kuo</text>
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                <text>Exosomes are membrane vesicles with a diameter of 40–100 nm that are secreted by many cell types into the extracellular milieu. Exosomes are found in cell culture supernatants and in different biological fluids and are known to be secreted by most cell types under normal and pathological conditions. Considerable research is focusing on the exploitation of exosomes in biological fluids for biomarkers in the diagnosis of disease. More recently, exosomes are being exploited for their therapeutic potential. Exosomes derived from dendritic cells, tumor cells, and malignant effusions demonstrate immunomodulatory functions and are able to present antigens to T-cells and stimulate antigen-specific T-cell responses. Exosomes have also been examined for their therapeutic potential in the treatment of infections such as toxoplasmosis, diphtheria, tuberculosis and atypical severe acute respiratory syndrome as well as autoimmune diseases. Attempts to find practical applications for exosomes continue to expand with the role of exosomes as a drug delivery system for the treatment of autoimmune/inflammatory diseases and cancers.</text>
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                <text>DOI: 10.5772/56522</text>
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                <text>Journal of Circulating Biomarkers</text>
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                <text>Neoplasms. Tumors. Oncology. Including cancer and carcinogens</text>
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                <text>Om å tenke litteraturhistorien på nytt – med utgangspunkt i norsk romantikkforskning</text>
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                <text>Erik Bjerck Hagen</text>
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                <text>The article argues that literary history and historiography ought to be revitalized as central concerns for literary studies. A critical discussion of the arguments raised against literary historiography in the early 1980s serves as the article’s point of departure, while the main section analyzes the concept of Romanticism as it has been used in various historical classifications of Norwegian literature. The link between Romanticism and Realism is seen as a possible clue to a creative renewal of the entire historiographical tradition.</text>
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                <text>2018</text>
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                <text>literary history, Romanticism, realism, historiography, Ernst Sars, Christen Collin</text>
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                <text>DOI: 10.18261/issn.1504-288X-2018-02-02</text>
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                <text>Norsk Litteraturvitenskapelig Tidsskrift</text>
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            <description>An entity responsible for making the resource available</description>
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                <text>Scandinavian University Press/Universitetsforlaget</text>
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                <text>Literature (General)</text>
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                  <text>Dominio científico: Coronavirus</text>
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                <text>Identification of New Respiratory Viruses in the New Millennium</text>
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                <text>Michael Berry, Junaid Gamieldien, Burtram C. Fielding</text>
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            <description>An account of the resource</description>
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                <text>The rapid advancement of molecular tools in the past 15 years has allowed for the retrospective discovery of several new respiratory viruses as well as the characterization of novel emergent strains. The inability to characterize the etiological origins of respiratory conditions, particularly in children, led several researchers to pursue the discovery of the underlying etiology of disease. In 2001, this led to the discovery of human metapneumovirus (hMPV) and soon following that the outbreak of Severe Acute Respiratory Syndrome coronavirus (SARS-CoV) promoted an increased interest in coronavirology and the latter discovery of human coronavirus (HCoV) NL63 and HCoV-HKU1. Human bocavirus, with its four separate lineages, discovered in 2005, has been linked to acute respiratory tract infections and gastrointestinal complications. Middle East Respiratory Syndrome coronavirus (MERS-CoV) represents the most recent outbreak of a completely novel respiratory virus, which occurred in Saudi Arabia in 2012 and presents a significant threat to human health. This review will detail the most current clinical and epidemiological findings to all respiratory viruses discovered since 2001.</text>
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                <text>2015</text>
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                <text>Respiratory viruses, human coronaviruses, hMPV, bocavirus, SARS-CoV, MERS</text>
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                <text>DOI: 10.3390/v7030996</text>
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                <text>Viruses</text>
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                <text>MDPI AG</text>
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                <text>Microbiology</text>
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                  <text>Dominio científico: Coronavirus</text>
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                <text>The impact of the deletion of section 11 (bA) on the deductibility of pre-production raising fees incurred raising fees in the expansion of an existing trade</text>
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                <text>Gerhard Barkhuizen, Leonard Willemse</text>
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                <text>Section 11(bA) was recently deleted and replaced by section 11A in the Income Tax Act No. 58 of 1962 (“the Act” – all references to sections and paragraphs hereafter refer to the Act, unless otherwise indicated). Section 11(bA) and section 11A determined the income tax treatment of qualifying pre-production interest incurred. The article focused on whether or not pre-production raising fees incurred by the taxpayer during the expanding of an existing trade will be deductible in terms of section 11(bA) or section 11A. Section 11(bA) and section 24J allow for the deduction, in certain circumstances, of interest or related finance charges. In the recently decided C:SARS v South African Custodial Services (Pty) Ltd 2012 (1) SA 522 (SCA), 74 SATC 61 (“SA Custodial”) it was found by the court that raising fees can be read under the phrase interest or related finance charges in terms of section 11(bA). The question arose whether or not the taxpayers are being disadvantaged by the fiscus through the deletion of section 11(bA) and its replacement by section 11A, especially in regard to pre-production raising fees incurred during the expansion of an existing trade. This article investigates the interaction between sections 11(bA), 11A and 24J of the Act in order to determine the difference in the income tax treatment between these sections for the pre-production raising fees incurred. The result of the investigation into the interaction of these sections will indicate whether or not the taxpayer is being disadvantaged by the fiscus through the deletion of section 11(bA) and its replacement by section 11A.</text>
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                <text>2015</text>
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                <text>Income Tax Act No. 58 of 1962 (as amended), raising fees, interest or other related fees, pre-production deductions, Trade, brought into use</text>
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                <text>DOI: 10.4102/jef.v8i2.114</text>
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                <text>Journal of Economic and Financial Sciences</text>
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              <elementText elementTextId="8293">
                <text>African Online Scientific Information Systems</text>
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            <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
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                <text>Economics as a science</text>
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        <name>Dublin Core</name>
        <description>The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.</description>
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          <element elementId="50">
            <name>Title</name>
            <description>A name given to the resource</description>
            <elementTextContainer>
              <elementText elementTextId="8277">
                <text>Infection control management of patients with suspected highly infectious diseases in emergency departments: data from a survey in 41 facilities in 14 European countries</text>
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            </elementTextContainer>
          </element>
          <element elementId="39">
            <name>Creator</name>
            <description>An entity primarily responsible for making the resource</description>
            <elementTextContainer>
              <elementText elementTextId="8278">
                <text>Fusco Francesco M, Schilling Stefan, De Iaco Giuseppina, Brodt Hans-Reinhard, Brouqui Philippe, Maltezou Helena C, Bannister Barbara, Gottschalk René, Thomson Gail, Puro Vincenzo, Ippolito Giuseppe</text>
              </elementText>
            </elementTextContainer>
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          <element elementId="41">
            <name>Description</name>
            <description>An account of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="8279">
                <text>Abstract Background In Emergency and Medical Admission Departments (EDs and MADs), prompt recognition and appropriate infection control management of patients with Highly Infectious Diseases (HIDs, e.g. Viral Hemorrhagic Fevers and SARS) are fundamental for avoiding nosocomial outbreaks. Methods The EuroNHID (European Network for Highly Infectious Diseases) project collected data from 41 EDs and MADs in 14 European countries, located in the same facility as a national/regional referral centre for HIDs, using specifically developed checklists, during on-site visits from February to November 2009. Results Isolation rooms were available in 34 facilities (82,9%): these rooms had anteroom in 19, dedicated entrance in 15, negative pressure in 17, and HEPA filtration of exhausting air in 12. Only 6 centres (14,6%) had isolation rooms with all characteristics. Personnel trained for the recognition of HIDs was available in 24 facilities; management protocols for HIDs were available in 35. Conclusions Preparedness level for the safe and appropriate management of HIDs is partially adequate in the surveyed EDs and MADs.</text>
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            </elementTextContainer>
          </element>
          <element elementId="40">
            <name>Date</name>
            <description>A point or period of time associated with an event in the lifecycle of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="8280">
                <text>2012</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="43">
            <name>Identifier</name>
            <description>An unambiguous reference to the resource within a given context</description>
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              <elementText elementTextId="8281">
                <text>DOI: 10.1186/1471-2334-12-27</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="48">
            <name>Source</name>
            <description>A related resource from which the described resource is derived</description>
            <elementTextContainer>
              <elementText elementTextId="8282">
                <text>BMC Infectious Diseases</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="45">
            <name>Publisher</name>
            <description>An entity responsible for making the resource available</description>
            <elementTextContainer>
              <elementText elementTextId="8283">
                <text>BMC</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="38">
            <name>Coverage</name>
            <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
            <elementTextContainer>
              <elementText elementTextId="8284">
                <text>Infectious and parasitic diseases</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="44">
            <name>Language</name>
            <description>A language of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="8285">
                <text>EN</text>
              </elementText>
            </elementTextContainer>
          </element>
        </elementContainer>
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  <item itemId="874" public="1" featured="0">
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      <file fileId="874">
        <src>https://www.socictopen.socict.org/files/original/126438e1d650920fe7e4b8de743fb54e.pdf</src>
        <authentication>ad892f7e175e5e72793b59a95a3437c0</authentication>
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        <elementSet elementSetId="1">
          <name>Dublin Core</name>
          <description>The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.</description>
          <elementContainer>
            <element elementId="50">
              <name>Title</name>
              <description>A name given to the resource</description>
              <elementTextContainer>
                <elementText elementTextId="1">
                  <text>Coronavirus</text>
                </elementText>
              </elementTextContainer>
            </element>
            <element elementId="41">
              <name>Description</name>
              <description>An account of the resource</description>
              <elementTextContainer>
                <elementText elementTextId="2">
                  <text>Dominio científico: Coronavirus</text>
                </elementText>
              </elementTextContainer>
            </element>
          </elementContainer>
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      </elementSetContainer>
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      <name>Text</name>
      <description>A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text.</description>
    </itemType>
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      <elementSet elementSetId="1">
        <name>Dublin Core</name>
        <description>The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.</description>
        <elementContainer>
          <element elementId="50">
            <name>Title</name>
            <description>A name given to the resource</description>
            <elementTextContainer>
              <elementText elementTextId="8267">
                <text>Small Animal Models of Respiratory Viral Infection Related to Asthma</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="39">
            <name>Creator</name>
            <description>An entity primarily responsible for making the resource</description>
            <elementTextContainer>
              <elementText elementTextId="8268">
                <text>Mingyuan Han, Charu Rajput, Tomoko Ishikawa, Caitlin  R. Jarman, Julie Lee, Marc B Hershenson</text>
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            </elementTextContainer>
          </element>
          <element elementId="41">
            <name>Description</name>
            <description>An account of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="8269">
                <text>Respiratory viral infections are strongly associated with asthma exacerbations. Rhinovirus is most frequently-detected pathogen; followed by respiratory syncytial virus; metapneumovirus; parainfluenza virus; enterovirus and coronavirus. In addition; viral infection; in combination with genetics; allergen exposure; microbiome and other pathogens; may play a role in asthma development. In particular; asthma development has been linked to wheezing-associated respiratory viral infections in early life. To understand underlying mechanisms of viral-induced airways disease; investigators have studied respiratory viral infections in small animals. This report reviews animal models of human respiratory viral infection employing mice; rats; guinea pigs; hamsters and ferrets. Investigators have modeled asthma exacerbations by infecting mice with allergic airways disease. Asthma development has been modeled by administration of virus to immature animals. Small animal models of respiratory viral infection will identify cell and molecular targets for the treatment of asthma.</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="40">
            <name>Date</name>
            <description>A point or period of time associated with an event in the lifecycle of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="8270">
                <text>2018</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="8271">
                <text>Animal model, Asthma, Respiratory disease, Rhinovirus, Viral infection</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="43">
            <name>Identifier</name>
            <description>An unambiguous reference to the resource within a given context</description>
            <elementTextContainer>
              <elementText elementTextId="8272">
                <text>DOI: 10.3390/v10120682</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="48">
            <name>Source</name>
            <description>A related resource from which the described resource is derived</description>
            <elementTextContainer>
              <elementText elementTextId="8273">
                <text>Viruses</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="45">
            <name>Publisher</name>
            <description>An entity responsible for making the resource available</description>
            <elementTextContainer>
              <elementText elementTextId="8274">
                <text>MDPI AG</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="38">
            <name>Coverage</name>
            <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
            <elementTextContainer>
              <elementText elementTextId="8275">
                <text>Microbiology</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="44">
            <name>Language</name>
            <description>A language of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="8276">
                <text>EN</text>
              </elementText>
            </elementTextContainer>
          </element>
        </elementContainer>
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