- Author:
- Hanne <Hanne@hanne-nielsens-macbook.local>
- Date:
- 2009-12-10 11:36:59+13:00
- Desc:
- Added images in ai and svg format, removed non pub med reference
- Permanent Source URI:
- https://models.physiomeproject.org/workspace/mittler_sulzer_neumann_perelson_1998/rawfile/f6ef467824f18e32e0e40547869b099572c6a372/mittler_sulzer_neumann_perelson_1998.cellml
<?xml version='1.0' encoding='utf-8'?>
<!-- FILE : mittler_model_1998.xml
CREATED : 5th December 2003
LAST MODIFIED : 2nd May 2005
AUTHOR : Catherine Lloyd
Bioengineering Institute
The University of Auckland
MODEL STATUS : This model conforms to the CellML 1.0 Specification released on
10th August 2001, and the 16/1/02 CellML Metadata 1.0 Specification.
DESCRIPTION : This file contains a CellML description of Mittler et al.'s 1998 mathematical model of the influence of delayed viral production on viral dynamics in HIV-1 infected patients.
CHANGES:
2/05/2005 - PJV - Changed unit dimensions to make them consistent.
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<article>
<articleinfo>
<title>Influence of Delayed Viral Production on Viral Dynamics in HIV-1 Infected Patients</title>
<author>
<firstname>Catherine</firstname>
<surname>Lloyd</surname>
<affiliation>
<shortaffil>Bioengineering Institute, University of Auckland</shortaffil>
</affiliation>
</author>
</articleinfo>
<section id="sec_status">
<title>Model Status</title>
<para>
This is the original unchecked version of the model imported from the previous
CellML model repository, 24-Jan-2006.
</para>
</section>
<sect1 id="sec_structure">
<title>Model Structure</title>
<para>
The time course of HIV-1 infection and immunodeficiency that characterises AIDS typically displays three phases:
</para>
<orderedlist inheritnum="ignore" continuation="restarts">
<listitem>
<para>Following the initial infection with HIV-1, the viral load in the blood rapidly increases.</para>
</listitem>
<listitem>
<para>After a few weeks (or months) this initially high viral load stabilises at a lower level, and a long period of clinical latency ensues, during which the virus persists at a relatively stable level, and the CD4+ T-cell count falls.</para>
</listitem>
<listitem>
<para>Finally, the viral load rapidly increases and the T-cell count declines to a point where the immune system fails. Death usually occurs due to an infection that the immune system cannot destroy.</para>
</listitem>
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<para>
One of the challenges of AIDS research is to understand the events that occur during the long latency period. Disturbing this quasi-steady state with antiretroviral drugs has lead to an increased knowledge about the underlying mechanical processes. Mathematical models have been developed which consider free virus, cells susceptible to infection (target cells), and infected cells (see <xref linkend="fig_cell_diagram"/> and <xref linkend="fig_cell_diagram2"/> below). Model simulations have produced parameter values for the decline in HIV-1 plasma levels in patients which have been treated with retroviral drugs. For example, the model by <ulink url="${HTML_EXMPL_PERELSON_MODEL}">Perelson <emphasis>et al.</emphasis> (1996)</ulink> suggested that the half-life of the free virus is 6 hours or less. This study, together with others has influenced strategies for treating HIV-1 with antiretroviral drugs.
</para>
<para>
In this current study by Mittler <emphasis>et al.</emphasis>, Perelson <emphasis>et al.'s</emphasis> 6 hour estimate for the viral half-life is tested. The authors extend the Perelson <emphasis>et al.</emphasis> model to account for intracellular delays (the period between the infection of a cell and the production of new virus particles). They concluded that, with the information about the length of the intracellular delay, it is possible to estimate viral clearance rate and other viral dynamic parameters from clinical data sets.
</para>
<para>
The complete original paper reference is cited below:
</para>
<para>
Influence of Delayed Viral Production on Viral Dynamics in HIV-1 Infected Patients, John E. Mittler, Bernhard Sulzer, Avidan U. Neumann, and Alan S. Perelson, 1998, <emphasis>Mathematical Biosciences</emphasis>
, 152, 143-163. <ulink url="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=9780612&dopt=Abstract">PubMed ID: 9780612</ulink>
</para>
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<caption>Schematic summary of the dynamics of HIV-1 infection <emphasis>in vivo</emphasis> captured by the Perelson <emphasis>et al.</emphasis> 1996 model.</caption>
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<caption>Schematic summary of the dynamics of viral infection <emphasis>in vivo</emphasis> captured by the <ulink url="${HTML_EXMPL_HERZ_MODEL}">Herz <emphasis>et al.</emphasis> 1996 model</ulink>.</caption>
</informalfigure>
</sect1>
</article>
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Influence of delayed viral production on viral dynamics in HIV-1
infected patients
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This is the CellML description of Mittler et al.'s 1998 mathematical
model of the influence of delayed viral production on viral dynamics
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The University of Auckland, Bioengineering Institute
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Mittler et al.'s 1998 mathematical model of the influence of delayed
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