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A System Dynamics Model to Predict the Human Monocyte Response to Endotoxins

Overview of attention for article published in Frontiers in immunology, August 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

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Title
A System Dynamics Model to Predict the Human Monocyte Response to Endotoxins
Published in
Frontiers in immunology, August 2017
DOI 10.3389/fimmu.2017.00915
Pubmed ID
Authors

Enrique Álvarez, Víctor Toledano, Fernando Morilla, Enrique Hernández-Jiménez, Carolina Cubillos-Zapata, Aníbal Varela-Serrano, José Casas-Martín, José Avendaño-Ortiz, Luis A. Aguirre, Francisco Arnalich, Charbel Maroun-Eid, Alejandro Martín-Quirós, Manuel Quintana Díaz, Eduardo López-Collazo

Abstract

System dynamics is a powerful tool that allows modeling of complex and highly networked systems such as those found in the human immune system. We have developed a model that reproduces how the exposure of human monocytes to lipopolysaccharides (LPSs) induces an inflammatory state characterized by high production of tumor necrosis factor alpha (TNFα), which is rapidly modulated to enter into a tolerant state, known as endotoxin tolerance (ET). The model contains two subsystems with a total of six states, seven flows, two auxiliary variables, and 14 parameters that interact through six differential and nine algebraic equations. The parameters were estimated and optimized to obtain a model that fits the experimental data obtained from human monocytes treated with various LPS doses. In contrast to publications on other animal models, stimulation of human monocytes with super-low-dose LPSs did not alter the response to a second LPSs challenge, neither inducing ET, nor enhancing the inflammatory response. Moreover, the model confirms the low production of TNFα and increased levels of C-C motif ligand 2 when monocytes exhibit a tolerant state similar to that of patients with sepsis. At present, the model can help us better understand the ET response and might offer new insights on sepsis diagnostics and prognosis by examining the monocyte response to endotoxins in patients with sepsis.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 29%
Researcher 7 29%
Student > Master 3 13%
Student > Bachelor 1 4%
Unspecified 1 4%
Other 2 8%
Unknown 3 13%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 21%
Mathematics 3 13%
Immunology and Microbiology 3 13%
Agricultural and Biological Sciences 3 13%
Business, Management and Accounting 2 8%
Other 4 17%
Unknown 4 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 17. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 May 2018.
All research outputs
#2,172,585
of 25,932,719 outputs
Outputs from Frontiers in immunology
#2,133
of 32,608 outputs
Outputs of similar age
#39,879
of 331,648 outputs
Outputs of similar age from Frontiers in immunology
#43
of 433 outputs
Altmetric has tracked 25,932,719 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 32,608 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.5. This one has done particularly well, scoring higher than 93% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 331,648 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 433 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.