ArticleBiophysical journal2003
Stochastic model of autocrine and paracrine signals in cell culture assays.
Article in Biophysical journal, 2003. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
- Insights into human melanocyte development and characteristics through pluripotent stem cells combined with single-cell sequencing.iScience · 2025Article
- Kinetic Monte Carlo methods for three-dimensional diffusive capture problems in exterior domains.Royal Society open science · 2025Article
- Modelling the dynamics of senescence spread.Aging cell · 2023Article
- Dissecting Particle Uptake Heterogeneity in a Cell Population Using Bayesian Analysis.Biophysical journal · 2020Article
- Modeling heterogeneous tumor growth dynamics and cell-cell interactions at single-cell and cell-population resolution.Current opinion in systems biology · 2019Article
- An implicit lipid model for efficient reaction-diffusion simulations of protein binding to surfaces of arbitrary topology.The Journal of chemical physics · 2019Article
- A solution to prevent secondary flow in adherent cell cultures.Biology open · 2019Article
- Quantitative Analysis of the Correlation between Cell Size and Cellular Uptake of Particles.Biophysical journal · 2019Article
- Boundary homogenization for a sphere with an absorbing cap of arbitrary size.The Journal of chemical physics · 2016Article
- Note: Boundary homogenization for a circle with periodic absorbing arcs. Exact expression for the effective trapping rate.The Journal of chemical physics · 2015Article
- Article
- Trapping of diffusing particles by striped cylindrical surfaces. Boundary homogenization approach.The Journal of chemical physics · 2015Article
- Analysis of single-cell cytokine secretion reveals a role for paracrine signaling in coordinating macrophage responses to TLR4 stimulation.Science signaling · 2015Article
- Minireview: intraislet regulation of insulin secretion in humans.Molecular endocrinology (Baltimore, Md.) · 2013Review
- Models of signalling networks - what cell biologists can gain from them and give to them.Journal of cell science · 2013Review
- Communication: Clusters of absorbing disks on a reflecting wall: competition for diffusing particles.The Journal of chemical physics · 2012Article
- Predictive microfluidic control of regulatory ligand trajectories in individual pluripotent cells.Proceedings of the National Academy of Sciences of the United States of America · 2012Article
- Cell surface concentrations and concentration ranges for testing in vitro autocrine loops and small molecules.PloS one · 2012Article
- A Monte-Carlo step-by-step simulation code of the non-homogeneous chemistry of the radiolysis of water and aqueous solutions. Part I: theoretical framework and implementation.Radiation and environmental biophysics · 2011Article
- Quantitative understanding of cell signaling: the importance of membrane organization.Current opinion in biotechnology · 2010Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Autocrine signaling systems are commonly studied under cell culture conditions. In a typical cell culture assay, a layer of liquid medium covers a random two-dimensional dispersion of cells, which secrete ligands. In a growing number of experiments, it is important to characterize the spatial range of autocrine and paracrine cell communication. Currently, the spatial distribution of diffusing signals can be analyzed only indirectly, from their effects on the intracellular signaling or physiological responses of autocrine cells. To directly characterize the spatial range of secreted ligands, we propose a stochastic model for autocrine cell cultures and analyze it using a combination of analytical and computational tools. The two main results derived within the framework of this model are 1), an expression for the fraction of autocrine trajectories, i.e., the probability for a ligand to be trapped by the same cell from which it has been secreted; and 2), an expression for the spatial distribution of trapping points of paracrine trajectories. We test these analytical results by stochastic simulations with efficient Brownian dynamics code and apply our model to analyze the spatial operation of autocrine epidermal growth factor receptor systems.
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