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@ARTICLE{Parker:825974,
      author       = {Parker, Robert and Hogg, Justin and Roy, Anirban and
                      Kellum, John and Rimmelé, Thomas and Daun-Gruhn, Silvia and
                      Fedorchak, Morgan and Valenti, Isabella and Federspiel,
                      William and Rubin, Jonathan and Vodovotz, Yoram and Lagoa,
                      Claudio and Clermont, Gilles},
      title        = {{M}odeling and {H}emofiltration {T}reatment of {A}cute
                      {I}nflammation},
      journal      = {Processes},
      volume       = {4},
      number       = {4},
      issn         = {2227-9717},
      address      = {Basel},
      publisher    = {MDPI},
      reportid     = {FZJ-2017-00246},
      pages        = {38 -},
      year         = {2016},
      abstract     = {The body responds to endotoxins by triggering the acute
                      inflammatory response system to eliminate the threat posed
                      by gram-negative bacteria (endotoxin) and restore health.
                      However, an uncontrolled inflammatory response can lead to
                      tissue damage, organ failure, and ultimately death; this is
                      clinically known as sepsis. Mathematical models of acute
                      inflammatory disease have the potential to guide treatment
                      decisions in critically ill patients. In this work, an
                      8-state (8-D) differential equation model of the acute
                      inflammatory response system to endotoxin challenge was
                      developed. Endotoxin challenges at 3 and 12 mg/kg were
                      administered to rats, and dynamic cytokine data for
                      interleukin (IL)-6, tumor necrosis factor (TNF), and IL-10
                      were obtained and used to calibrate the model. Evaluation of
                      competing model structures was performed by analyzing model
                      predictions at 3, 6, and 12 mg/kg endotoxin challenges with
                      respect to experimental data from rats. Subsequently, a
                      model predictive control (MPC) algorithm was synthesized to
                      control a hemoadsorption (HA) device, a blood purification
                      treatment for acute inflammation. A particle filter (PF)
                      algorithm was implemented to estimate the full state vector
                      of the endotoxemic rat based on time series cytokine
                      measurements. Treatment simulations show that: (i) the
                      apparent primary mechanism of HA efficacy is white blood
                      cell (WBC) capture, with cytokine capture a secondary
                      benefit; and (ii) differential filtering of cytokines and
                      WBC does not provide substantial improvement in treatment
                      outcomes vs. existing HA devices.},
      cin          = {INM-3},
      ddc          = {570},
      cid          = {I:(DE-Juel1)INM-3-20090406},
      pnm          = {572 - (Dys-)function and Plasticity (POF3-572)},
      pid          = {G:(DE-HGF)POF3-572},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000391592700005},
      doi          = {10.3390/pr4040038},
      url          = {https://juser.fz-juelich.de/record/825974},
}