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<export-example>
  <doc>
    <id>1008</id>
    <completedYear>2017</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">A pilot study on fingerprinting Leishmania species from the Old World using Fourier transform infrared spectroscopy</title>
    <abstract language="eng">Leishmania species are protozoan parasites and the causative agents of leishmaniasis, a vector borne disease that imposes a large health burden on individuals living mainly in tropical and subtropical regions. Different Leishmania species are responsible for the distinct clinical patterns, such as cutaneous, mucocutaneous, and visceral leishmaniasis, with the latter being potentially fatal if left untreated. For this reason, it is important to perform correct species identification and differentiation. Fourier transform infrared spectroscopy (FTIR) is an analytical spectroscopic technique increasingly being used as a potential tool for identification of microorganisms for diagnostic purposes. By employing mid-infrared (MIR) spectral data, it is not only possible to assess the chemical structures but also to achieve differentiation supported by multivariate statistic analysis. This work comprises a pilot study on differentiation of Leishmania species of the Old World (L. major, L. tropica, L. infantum, and L. donovani) as well as hybrids of distinct species by using vibrational spectroscopic fingerprints. Films of intact Leishmania parasites and their deoxyribonucleic acid (DNA) were characterized comparatively with respect to their biochemical nature and MIR spectral patterns. The strains’ hyperspectral datasets were multivariately examined by means of variance-based principal components analysis (PCA) and distance-based hierarchical cluster analysis (HCA). With the implementation of MIR spectral datasets we show that a phenotypic differentiation of Leishmania at species and intra-species level is feasible. Thus, FTIR spectroscopy can be further exploited for building up spectral databases of Leishmania parasites in view of high-throughput analysis of clinical specimens.</abstract>
    <parentTitle language="eng">Analytical and Bioanalytical Chemistry</parentTitle>
    <identifier type="issn">1432-1130</identifier>
    <identifier type="urn">urn:nbn:de:kobv:526-opus4-10080</identifier>
    <enrichment key="SourceTitle">Hornemann, A., Sinning, D., Cortes, S. et al. Anal Bioanal Chem (2017). https://doi.org/10.1007/s00216-017-0655-5</enrichment>
    <enrichment key="DOI_VoR">https://doi.org/10.1007/s00216-017-0655-5</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Andrea Hornemann</author>
    <author>Denise Sinning</author>
    <author>Sofia Cortes</author>
    <author>Lenea Campino</author>
    <author>Peggy Emmer</author>
    <author>Katrin Kuhls</author>
    <author>Gerhard Ulm</author>
    <author>Marcus Frohme</author>
    <author>Burkhard Beckhoff</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Fourier transform infrared spectroscopy</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>hierarchical cluster analysis (HCA)</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>principal components analysis (PCA)</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Leishmania</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>DNA</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>multivariate differentiation</value>
    </subject>
    <collection role="ddc" number="570">Biowissenschaften; Biologie</collection>
    <collection role="institutes" number="">Fachbereich Ingenieur- und Naturwissenschaften</collection>
    <collection role="open_access" number="">open_access</collection>
    <collection role="green_open_access" number="4">Hybrid Open Access</collection>
    <thesisPublisher>Technische Hochschule Wildau</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-th-wildau/files/1008/s00216-017-0655-5.pdf</file>
  </doc>
</export-example>
