Evidence map›Paper›PMID 24909493›Full record

ArticleJournal of theoretical biology2014

Global sensitivity analysis of a mathematical model of acute inflammation identifies nonlinear dependence of cumulative tissue damage on host interleukin-6 responses.

Shibin Mathew, John Bartels, Ipsita Banerjee, Yoram Vodovotz

Abstract read
In one paragraph

Article in Journal of theoretical biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Shibin MathewDepartment of Chemical and Petroleum Engineering, University of Pittsburgh, Pittsburgh, PA 15261, USA. Electronic address: shm82@pitt.edu.
John BartelsImmunetrics, Inc., Pittsburgh, PA 15203, USA.
Ipsita BanerjeeDepartment of Chemical and Petroleum Engineering, University of Pittsburgh, Pittsburgh, PA 15261, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15219, USA; McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA 15219, USA.
Yoram VodovotzImmunetrics, Inc., Pittsburgh, PA 15203, USA; Department of Surgery, University of Pittsburgh, Pittsburgh, PA 15213, USA; Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA 15219, USA. Electronic address: vodovotzy@upmc.edu.

Funding

Regulation of Intestinal Mucosal Injury & Repair After Trauma/Hemorrhagic ShockP50GM053789 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BILLIAR, TIMOTHY R · 1997 to 2013
$18.0M
Defining Mechanisms Controlling Stem Cell Fate During DifferentiationDP2OD006491 · OD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BANERJEE, IPSITA · 2009 to 2009
$2.3M
NIGMS NIH HHS P50 GM053789NIGMS NIH HHS P50-GM-53789NIH HHS 1DP2OD006491-01NIH HHS DP2 OD006491
6 · The paper itself

Abstract

The precise inflammatory role of the cytokine interleukin (IL)-6 and its utility as a biomarker or therapeutic target have been the source of much debate, presumably due to the complex pro- and anti-inflammatory effects of this cytokine. We previously developed a nonlinear ordinary differential equation (ODE) model to explain the dynamics of endotoxin (lipopolysaccharide; LPS)-induced acute inflammation and associated whole-animal damage/dysfunction (a proxy for the health of the organism), along with the inflammatory mediators tumor necrosis factor (TNF)-α, IL-6, IL-10, and nitric oxide (NO). The model was partially calibrated using data from endotoxemic C57Bl/6 mice. Herein, we investigated the sensitivity of the area under the damage curve (AUCD) to the 51 rate parameters of the ODE model for different levels of simulated LPS challenges using a global sensitivity approach called Random Sampling High Dimensional Model Representation (RS-HDMR). We explored sufficient parametric Monte Carlo samples to generate the variance-based Sobol' global sensitivity indices, and found that inflammatory damage was highly sensitive to the parameters affecting the activity of IL-6 during the different stages of acute inflammation. The AUCIL6 showed a bimodal distribution, with the lower peak representing healthy response and the higher peak representing sustained inflammation. Damage was minimal at low AUCIL6, giving rise to a healthy response. In contrast, intermediate levels of AUCIL6 resulted in high damage, and this was due to the insufficiency of damage recovery driven by anti-inflammatory responses from IL-10 and the activation of positive feedback sustained by IL-6. At high AUCIL6, damage recovery was interestingly restored in some population of simulated animals due to the NO-mediated anti-inflammatory responses. These observations suggest that the host's health status during acute inflammation depends in a nonlinear fashion on the magnitude of the inflammatory stimulus, on the host's propensity to produce IL-6, and on NO-mediated downstream responses.

Indexed as

Models, TheoreticalAcute DiseaseHumansInterleukin-6Models, StatisticalMonte Carlo MethodNonlinear DynamicsInterleukin-6CytokinesEndotoxinInflammation dynamicsMeta-modelingNitric oxide

Identifiers

PMID24909493
PMCPMC4125477

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.