Literature DB >> 22425816

A two-compartment mathematical model of endotoxin-induced inflammatory and physiologic alterations in swine.

Gary Nieman1, David Brown, Joydeep Sarkar, Brian Kubiak, Cordelia Ziraldo, Joyeeta Dutta-Moscato, Christopher Vieau, Derek Barclay, Louis Gatto, Kristopher Maier, Gregory Constantine, Timothy R Billiar, Ruben Zamora, Qi Mi, Steve Chang, Yoram Vodovotz.   

Abstract

OBJECTIVE: To gain insights into individual variations in acute inflammation and physiology.
DESIGN: Large-animal study combined with mathematical modeling.
SETTING: Academic large-animal and computational laboratories.
SUBJECTS: Outbred juvenile swine.
INTERVENTIONS: Four swine were instrumented and subjected to endotoxemia (100 µg/kg), followed by serial plasma sampling.
MEASUREMENTS AND MAIN RESULTS: Swine exhibited various degrees of inflammation and acute lung injury, including one death with severe acute lung injury (PaO(2)/FIO(2) ratio μ200 and static compliance μ10 L/cm H(2)O). Plasma interleukin-1β, interleukin-4, interleukin-6, interleukin-8, interleukin-10, tumor necrosis factor-α, high mobility group box-1, and NO(2)/NO(3) were significantly (p μ .05) elevated over the course of the experiment. Principal component analysis was used to suggest principal drivers of inflammation. Based in part on principal component analysis, an ordinary differential equation model was constructed, consisting of the lung and the blood (as a surrogate for the rest of the body), in which endotoxin induces tumor necrosis factor-α in monocytes in the blood, followed by the trafficking of these cells into the lung leading to the release of high mobility group box-1, which in turn stimulates the release of interleukin-1β from resident macrophages. The ordinary differential equation model also included blood pressure, PaO(2), and FIO(2), and a damage variable that summarizes the health of the animal. This ordinary differential equation model could be fit to both inflammatory and physiologic data in the individual swine. The predicted time course of damage could be matched to the oxygen index in three of the four swine.
CONCLUSIONS: The approach described herein may aid in predicting inflammation and physiologic dysfunction in small cohorts of subjects with diverse phenotypes and outcomes.

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Year:  2012        PMID: 22425816      PMCID: PMC3308118          DOI: 10.1097/CCM.0b013e31823e986a

Source DB:  PubMed          Journal:  Crit Care Med        ISSN: 0090-3493            Impact factor:   7.598


  33 in total

1.  The role of initial trauma in the host's response to injury and hemorrhage: insights from a correlation of mathematical simulations and hepatic transcriptomic analysis.

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Journal:  Shock       Date:  2006-12       Impact factor: 3.454

Review 2.  Evaluating disorders with a complex genetics basis. the future roles of meta-analysis and systems biology.

Authors:  David C Whitcomb; Elie Aoun; Yoram Vodovotz; Gilles Clermont; M Michael Barmada
Journal:  Dig Dis Sci       Date:  2005-12       Impact factor: 3.199

3.  Oxygenation index predicts outcome in children with acute hypoxemic respiratory failure.

Authors:  Daniel Trachsel; Brian W McCrindle; Satoshi Nakagawa; Desmond Bohn
Journal:  Am J Respir Crit Care Med       Date:  2005-04-07       Impact factor: 21.405

Review 4.  Sepsis research in the next millennium: concentrate on the software rather than the hardware.

Authors:  Thorsten Tjardes; Edmund Neugebauer
Journal:  Shock       Date:  2002-01       Impact factor: 3.454

5.  In Silico Augmentation of the Drug Development Pipeline: Examples from the study of Acute Inflammation.

Authors:  Gary An; John Bartels; Yoram Vodovotz
Journal:  Drug Dev Res       Date:  2011-03-01       Impact factor: 4.360

6.  Sepsis: Something old, something new, and a systems view.

Authors:  Rami Namas; Ruben Zamora; Rajaie Namas; Gary An; John Doyle; Thomas E Dick; Frank J Jacono; Ioannis P Androulakis; Gary F Nieman; Steve Chang; Timothy R Billiar; John A Kellum; Derek C Angus; Yoram Vodovotz
Journal:  J Crit Care       Date:  2011-07-27       Impact factor: 3.425

Review 7.  Anti-inflammatory therapies in sepsis and septic shock.

Authors:  B D Freeman; C Natanson
Journal:  Expert Opin Investig Drugs       Date:  2000-07       Impact factor: 6.206

8.  Circulating high-mobility group box 1 (HMGB1) concentrations are elevated in both uncomplicated pneumonia and pneumonia with severe sepsis.

Authors:  Derek C Angus; Lihong Yang; Lan Kong; John A Kellum; Russell L Delude; Kevin J Tracey; Lisa Weissfeld
Journal:  Crit Care Med       Date:  2007-04       Impact factor: 7.598

9.  Peritoneal negative pressure therapy prevents multiple organ injury in a chronic porcine sepsis and ischemia/reperfusion model.

Authors:  Brian D Kubiak; Scott P Albert; Louis A Gatto; Kathleen P Snyder; Kristopher G Maier; Christopher J Vieau; Shreyas Roy; Gary F Nieman
Journal:  Shock       Date:  2010-11       Impact factor: 3.454

Review 10.  Mechanistic simulations of inflammation: current state and future prospects.

Authors:  Yoram Vodovotz; Gregory Constantine; Jonathan Rubin; Marie Csete; Eberhard O Voit; Gary An
Journal:  Math Biosci       Date:  2008-08-26       Impact factor: 2.144

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  32 in total

Review 1.  From data patterns to mechanistic models in acute critical illness.

Authors:  Jean-Marie Aerts; Wassim M Haddad; Gary An; Yoram Vodovotz
Journal:  J Crit Care       Date:  2014-03-29       Impact factor: 3.425

2.  The inflammatory response to influenza A virus (H1N1): An experimental and mathematical study.

Authors:  Ian Price; Ericka D Mochan-Keef; David Swigon; G Bard Ermentrout; Sarah Lukens; Franklin R Toapanta; Ted M Ross; Gilles Clermont
Journal:  J Theor Biol       Date:  2015-04-03       Impact factor: 2.691

3.  Inflammation and Disease: Modelling and Modulation of the Inflammatory Response to Alleviate Critical Illness.

Authors:  Judy D Day; Chase Cockrell; Rami Namas; Ruben Zamora; Gary An; Yoram Vodovotz
Journal:  Curr Opin Syst Biol       Date:  2018-08-23

4.  Predicting in vivo responses to biomaterials via combined in vitro and in silico analysis.

Authors:  Matthew T Wolf; Yoram Vodovotz; Stephen Tottey; Bryan N Brown; Stephen F Badylak
Journal:  Tissue Eng Part C Methods       Date:  2014-08-04       Impact factor: 3.056

5.  Cytokine patterns in critically ill patients undergoing percutaneous tracheostomy.

Authors:  U Trahtemberg; N Bazak; S Sviri; M Beil; S Paschke; P V van Heerden
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6.  Global sensitivity analysis of a mathematical model of acute inflammation identifies nonlinear dependence of cumulative tissue damage on host interleukin-6 responses.

Authors:  Shibin Mathew; John Bartels; Ipsita Banerjee; Yoram Vodovotz
Journal:  J Theor Biol       Date:  2014-06-05       Impact factor: 2.691

7.  Removal of inflammatory ascites is associated with dynamic modification of local and systemic inflammation along with prevention of acute lung injury: in vivo and in silico studies.

Authors:  Bryanna Emr; David Sadowsky; Nabil Azhar; Louis A Gatto; Gary An; Gary F Nieman; Yoram Vodovotz
Journal:  Shock       Date:  2014-04       Impact factor: 3.454

Review 8.  Translational applications of evaluating physiologic variability in human endotoxemia.

Authors:  Jeremy D Scheff; Panteleimon D Mavroudis; Steve E Calvano; Ioannis P Androulakis
Journal:  J Clin Monit Comput       Date:  2012-12-01       Impact factor: 2.502

Review 9.  In silico modeling: methods and applications to trauma and sepsis.

Authors:  Yoram Vodovotz; Timothy R Billiar
Journal:  Crit Care Med       Date:  2013-08       Impact factor: 7.598

10.  Individual-specific principal component analysis of circulating inflammatory mediators predicts early organ dysfunction in trauma patients.

Authors:  Rami A Namas; Khalid Almahmoud; Qi Mi; Ali Ghuma; Rajaie Namas; Akram Zaaqoq; Xiaoguang Zhu; Othman Abdul-Malak; Jason Sperry; Ruben Zamora; Timothy R Billiar; Yoram Vodovotz
Journal:  J Crit Care       Date:  2016-07-11       Impact factor: 3.425

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