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    <title>HZI Collection:</title>
    <link>http://hdl.handle.net/10033/218751</link>
    <description />
    <pubDate>Fri, 24 May 2013 05:09:29 GMT</pubDate>
    <dc:date>2013-05-24T05:09:29Z</dc:date>
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      <title>Population Dynamics of Borrelia burgdorferi in Lyme Disease.</title>
      <link>http://hdl.handle.net/10033/291131</link>
      <description>Title: Population Dynamics of Borrelia burgdorferi in Lyme Disease.
Authors: Binder, Sebastian C; Telschow, Arndt; Meyer-Hermann, Michael
Abstract: Many chronic inflammatory diseases are known to be caused by persistent bacterial or viral infections. A well-studied example is the tick-borne infection by the gram-negative spirochaetes of the genus Borrelia in humans and other mammals, causing severe symptoms of chronic inflammation and subsequent tissue damage (Lyme Disease), particularly in large joints and the central nervous system, but also in the heart and other tissues of untreated patients. Although killed efficiently by human phagocytic cells in vitro, Borrelia exhibits a remarkably high infectivity in mice and men. In experimentally infected mice, the first immune response almost clears the infection. However, approximately 1 week post infection, the bacterial population recovers and reaches an even larger size before entering the chronic phase. We developed a mathematical model describing the bacterial growth and the immune response against Borrelia burgdorferi in the C3H mouse strain that has been established as an experimental model for Lyme disease. The peculiar dynamics of the infection exclude two possible mechanistic explanations for the regrowth of the almost cleared bacteria. Neither the hypothesis of bacterial dissemination to different tissues nor a limitation of phagocytic capacity were compatible with experiment. The mathematical model predicts that Borrelia recovers from the strong initial immune response by the regrowth of an immune-resistant sub-population of the bacteria. The chronic phase appears as an equilibration of bacterial growth and adaptive immunity. This result has major implications for the development of the chronic phase of Borrelia infections as well as on potential protective clinical interventions.</description>
      <pubDate>Sun, 01 Jan 2012 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">http://hdl.handle.net/10033/291131</guid>
      <dc:date>2012-01-01T00:00:00Z</dc:date>
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      <title>Discrete-time neural observer for HIV infection dynamic</title>
      <link>http://hdl.handle.net/10033/283212</link>
      <description>Title: Discrete-time neural observer for HIV infection dynamic
Authors: Hernandez-Vargas, Esteban A.; Alanis, Alma Y.; Sanchez, Edgar N.</description>
      <pubDate>Fri, 19 Apr 2013 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">http://hdl.handle.net/10033/283212</guid>
      <dc:date>2013-04-19T00:00:00Z</dc:date>
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    <item>
      <title>Modeling the three stages in HIV infection.</title>
      <link>http://hdl.handle.net/10033/281312</link>
      <description>Title: Modeling the three stages in HIV infection.
Authors: Hernandez-Vargas, Esteban A; Middleton, Richard H
Abstract: A typical HIV infection response consists of three stages: an initial acute infection, a long asymptomatic period and a final increase in viral load with simultaneous collapse in healthy CD4+T cell counts. The majority of existing mathematical models give a good representation of either the first two stages or the last stage of the infection. Using macrophages as a long-term active reservoir, a deterministic model is proposed to explain the three stages of the infection including the progression to AIDS. Simulation results illustrate how chronic infected macrophages can explain the progression to AIDS provoking viral explosion. Further simulation studies suggest that the proposed model retains its key properties even under moderately large parameter variations. This model provides important insights on how macrophages might play a crucial role in the long term behavior of HIV infection.</description>
      <pubDate>Thu, 07 Mar 2013 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">http://hdl.handle.net/10033/281312</guid>
      <dc:date>2013-03-07T00:00:00Z</dc:date>
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    <item>
      <title>Sub-optimal switching with dwell time constraints for control of viral mutation</title>
      <link>http://hdl.handle.net/10033/278892</link>
      <description>Title: Sub-optimal switching with dwell time constraints for control of viral mutation
Authors: Hernandez-Vargas, Esteban A.; Colaneri, Patrizio; Middleton, Richard H.</description>
      <pubDate>Thu, 13 Dec 2012 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">http://hdl.handle.net/10033/278892</guid>
      <dc:date>2012-12-13T00:00:00Z</dc:date>
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