ArticleBiophysical journal2008
Adhesive dynamics simulation of neutrophil arrest with stochastic activation.
Article in Biophysical journal, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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.
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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.
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Who cites it
8 citing papers in PubMed, 17 citations in OpenAlex.
- The role of adhesive receptor patterns on cell transport in complex microvessels.Biomechanics and modeling in mechanobiology · 2022Article
- Protrusive and Contractile Forces of Spreading Human Neutrophils.Biophysical journal · 2015Article
- Adhesive dynamics.Journal of biomechanical engineering · 2014Review
- Computational and experimental models of cancer cell response to fluid shear stress.Frontiers in oncology · 2013Article
- An integrated stochastic model of "inside-out" integrin activation and selective T-lymphocyte recruitment.Langmuir : the ACS journal of surfaces and colloids · 2012Article
- Optimization of ultrasound contrast agents with computational models to improve selection of ligands and binding strength.Biotechnology and bioengineering · 2010Article
- Integrin clustering is driven by mechanical resistance from the glycocalyx and the substrate.PLoS computational biology · 2009Article
- Adhesive dynamics simulation of G-protein-mediated chemokine-activated neutrophil adhesion.Biophysical journal · 2009Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
The transition from rolling to firm adhesion is a key step in the adhesion cascade that permits a neutrophil to exit the bloodstream and make its way to a site of inflammation. In this work, we construct an integrated model of neutrophil activation and arrest that combines a biomechanical model of neutrophil adhesion and adhesive dynamics, with fully stochastic signal transduction modeling, in the form of kinetic Monte Carlo simulation within the microvilli. We employ molecular binding parameters gleaned from the literature and from simulation of cell-free rolling mediated by selectin molecules. We create a simplified model of lymphocyte function-associated antigen-1 activation that links P-selectin glycoprotein ligand-1 ligation to integrin activation. The model utilizes an energy profile of various integrin activation states drawn from literature data and permits manipulation of signal diffusivity within the microvillus. Our integrated model recreates neutrophil arrest within physiological timescales, and we demonstrate that increasing signal diffusivity within a microvillus accelerates arrest. If the energy barrier between free unactivated and free activated lymphocyte function-associated antigen-1 increases, the period of rolling before arrest increases. We further demonstrate that, within our model, modification of endothelial ligand surface densities can control arrest. In addition, the relative concentrations of signaling molecules control the fractional activation of the overall signaling pathway and the rolling time to arrest. This work presents the first, to our knowledge, fully stochastic model of neutrophil activation, which, though simplified, can recapitulate significant physiological details of neutrophil arrest yet retains the capacity to incorporate additional information regarding mechanisms of neutrophil signal transduction as they are elucidated.
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Registered trials
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.