Open Access
Method for the simulation of blood platelet shape and its evolution during activation
Maxim A. Yurkin
1
,
Artem R Muliukov
1
,
Alena L Litvinenko
1
,
Vyacheslav M Nekrasov
1
,
Andrei V. Chernyshev
1
,
Valeri P. Maltsev
1
Publication type: Journal Article
Publication date: 2018-03-08
scimago Q1
wos Q1
SJR: 1.503
CiteScore: 7.2
Impact factor: 3.6
ISSN: 1553734X, 15537358
PubMed ID:
29518073
Molecular Biology
Genetics
Computational Theory and Mathematics
Cellular and Molecular Neuroscience
Ecology, Evolution, Behavior and Systematics
Ecology
Modeling and Simulation
Abstract
We present a simple physically based quantitative model of blood platelet shape and its evolution during agonist-induced activation. The model is based on the consideration of two major cytoskeletal elements: the marginal band of microtubules and the submembrane cortex. Mathematically, we consider the problem of minimization of surface area constrained to confine the marginal band and a certain cellular volume. For resting platelets, the marginal band appears as a peripheral ring, allowing for the analytical solution of the minimization problem. Upon activation, the marginal band coils out of plane and forms 3D convoluted structure. We show that its shape is well approximated by an overcurved circle, a mathematical concept of closed curve with constant excessive curvature. Possible mechanisms leading to such marginal band coiling are discussed, resulting in simple parametric expression for the marginal band shape during platelet activation. The excessive curvature of marginal band is a convenient state variable which tracks the progress of activation. The cell surface is determined using numerical optimization. The shapes are strictly mathematically defined by only three parameters and show good agreement with literature data. They can be utilized in simulation of platelets interaction with different physical fields, e.g. for the description of hydrodynamic and mechanical properties of platelets, leading to better understanding of platelets margination and adhesion and thrombus formation in blood flow. It would also facilitate precise characterization of platelets in clinical diagnosis, where a novel optical model is needed for the correct solution of inverse light-scattering problem.
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17
Total citations:
17
Citations from 2024:
4
(23.53%)
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GOST
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Moskalensky A. E. et al. Method for the simulation of blood platelet shape and its evolution during activation // PLoS Computational Biology. 2018. Vol. 14. No. 3. p. e1005899.
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Moskalensky A. E., Yurkin M. A., Muliukov A. R., Litvinenko A. L., Nekrasov V. M., Chernyshev A. V., Maltsev V. P. Method for the simulation of blood platelet shape and its evolution during activation // PLoS Computational Biology. 2018. Vol. 14. No. 3. p. e1005899.
Cite this
RIS
Copy
TY - JOUR
DO - 10.1371/journal.pcbi.1005899
UR - https://dx.plos.org/10.1371/journal.pcbi.1005899
TI - Method for the simulation of blood platelet shape and its evolution during activation
T2 - PLoS Computational Biology
AU - Moskalensky, Alexander E.
AU - Yurkin, Maxim A.
AU - Muliukov, Artem R
AU - Litvinenko, Alena L
AU - Nekrasov, Vyacheslav M
AU - Chernyshev, Andrei V.
AU - Maltsev, Valeri P.
PY - 2018
DA - 2018/03/08
PB - Public Library of Science (PLoS)
SP - e1005899
IS - 3
VL - 14
PMID - 29518073
SN - 1553-734X
SN - 1553-7358
ER -
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BibTex (up to 50 authors)
Copy
@article{2018_Moskalensky,
author = {Alexander E. Moskalensky and Maxim A. Yurkin and Artem R Muliukov and Alena L Litvinenko and Vyacheslav M Nekrasov and Andrei V. Chernyshev and Valeri P. Maltsev},
title = {Method for the simulation of blood platelet shape and its evolution during activation},
journal = {PLoS Computational Biology},
year = {2018},
volume = {14},
publisher = {Public Library of Science (PLoS)},
month = {mar},
url = {https://dx.plos.org/10.1371/journal.pcbi.1005899},
number = {3},
pages = {e1005899},
doi = {10.1371/journal.pcbi.1005899}
}
Cite this
MLA
Copy
Moskalensky, Alexander E., et al. “Method for the simulation of blood platelet shape and its evolution during activation.” PLoS Computational Biology, vol. 14, no. 3, Mar. 2018, p. e1005899. https://dx.plos.org/10.1371/journal.pcbi.1005899.