Image-based flow simulation of platelet aggregates under different shear rates.
Journal
PLoS computational biology
ISSN: 1553-7358
Titre abrégé: PLoS Comput Biol
Pays: United States
ID NLM: 101238922
Informations de publication
Date de publication:
07 2023
07 2023
Historique:
received:
23
02
2023
accepted:
10
06
2023
revised:
20
07
2023
medline:
24
7
2023
pubmed:
10
7
2023
entrez:
10
7
2023
Statut:
epublish
Résumé
Hemodynamics is crucial for the activation and aggregation of platelets in response to flow-induced shear. In this paper, a novel image-based computational model simulating blood flow through and around platelet aggregates is presented. The microstructure of aggregates was captured by two different modalities of microscopy images of in vitro whole blood perfusion experiments in microfluidic chambers coated with collagen. One set of images captured the geometry of the aggregate outline, while the other employed platelet labelling to infer the internal density. The platelet aggregates were modelled as a porous medium, the permeability of which was calculated with the Kozeny-Carman equation. The computational model was subsequently applied to study hemodynamics inside and around the platelet aggregates. The blood flow velocity, shear stress and kinetic force exerted on the aggregates were investigated and compared under 800 s-1, 1600 s-1 and 4000 s-1 wall shear rates. The advection-diffusion balance of agonist transport inside the platelet aggregates was also evaluated by local Péclet number. The findings show that the transport of agonists is not only affected by the shear rate but also significantly influenced by the microstructure of the aggregates. Moreover, large kinetic forces were found at the transition zone from shell to core of the aggregates, which could contribute to identifying the boundary between the shell and the core. The shear rate and the rate of elongation flow were investigated as well. The results imply that the emerging shapes of aggregates are highly correlated to the shear rate and the rate of elongation. The framework provides a way to incorporate the internal microstructure of the aggregates into the computational model and yields a better understanding of the hemodynamics and physiology of platelet aggregates, hence laying the foundation for predicting aggregation and deformation under different flow conditions.
Identifiants
pubmed: 37428797
doi: 10.1371/journal.pcbi.1010965
pii: PCOMPBIOL-D-23-00289
pmc: PMC10358939
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e1010965Informations de copyright
Copyright: © 2023 Hao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Déclaration de conflit d'intérêts
The authors have declared that no competing interests exist.
Références
Blood. 2006 May 1;107(9):3537-45
pubmed: 16449527
Biophys J. 2019 Jun 4;116(11):2092-2102
pubmed: 31103230
Math Med Biol. 2011 Mar;28(1):47-84
pubmed: 20439306
J Biomech Eng. 2014 Jul;136(7):
pubmed: 24805351
J Thromb Haemost. 2018 May;16(5):973-983
pubmed: 29488682
Blood. 2014 Sep 11;124(11):1808-15
pubmed: 24951424
Arterioscler Thromb Vasc Biol. 2012 Dec;32(12):2938-45
pubmed: 23087356
Biophys J. 2021 May 18;120(10):1903-1915
pubmed: 33737157
Int J Numer Method Biomed Eng. 2014 Jun;30(6):634-58
pubmed: 24421269
Biophys J. 2013 Apr 16;104(8):1812-23
pubmed: 23601328
Blood. 2007 Jun 15;109(12):5087-95
pubmed: 17311994
Biophys J. 1989 Dec;56(6):1121-41
pubmed: 2611327
Blood. 2014 Sep 11;124(11):1816-23
pubmed: 24951425
Annu Rev Biochem. 1998;67:395-424
pubmed: 9759493
Biophys J. 2020 Nov 17;119(10):2102-2115
pubmed: 33147477
Transfus Apher Sci. 2003 Jun;28(3):257-64
pubmed: 12725952
J Math Biol. 2010 Jan;60(1):1-26
pubmed: 19274464
J R Soc Interface. 2017 Nov;14(136):
pubmed: 29142014
Magn Reson Imaging. 2012 Nov;30(9):1323-41
pubmed: 22770690
J Biomed Res. 2015 Oct 30;29:
pubmed: 26541706
Microvasc Res. 2009 May;77(3):265-72
pubmed: 19323969
Science. 2009 Jun 5;324(5932):1330-4
pubmed: 19498171
Eur J Pharmacol. 2021 Feb 15;893:173830
pubmed: 33347819
Microcirculation. 2010 Nov;17(8):615-28
pubmed: 21044216
Biophys J. 2010 May 19;98(9):L35-7
pubmed: 20441731
Biorheology. 2009;46(3):181-9
pubmed: 19581726
J Biomech. 2020 Oct 9;111:110001
pubmed: 32896744
Exp Physiol. 2003 May;88(3):431-40
pubmed: 12719768
Comput Biol Med. 2019 Mar;106:1-11
pubmed: 30660757
J Mech Behav Biomed Mater. 2012 Jun;10:75-86
pubmed: 22520420
Cell. 1998 Sep 4;94(5):657-66
pubmed: 9741630
J Appl Physiol. 1967 Aug;23(2):178-82
pubmed: 6040532
Blood. 1996 Nov 1;88(9):3456-64
pubmed: 8896411
Curr Opin Hematol. 2001 Sep;8(5):270-6
pubmed: 11604561
Blood. 2006 Sep 15;108(6):1903-10
pubmed: 16772609
Nat Med. 2009 Jun;15(6):665-73
pubmed: 19465929
Bull Math Biol. 2013 Aug;75(8):1255-83
pubmed: 23097125
Biorheology. 2014;51(1):3-14
pubmed: 24598379
Biophys J. 2008 Sep;95(5):2539-55
pubmed: 18515387
Ann Biomed Eng. 2013 Jun;41(6):1297-307
pubmed: 23423707
Clin Chem. 1974 May;20(5):615-6
pubmed: 4826961
J Biomech. 2021 Oct 11;127:110692
pubmed: 34479090
PLoS Comput Biol. 2013;9(6):e1003095
pubmed: 23785270
Thromb Res. 2011 Oct;128(4):358-60
pubmed: 21620440
PLoS One. 2015 Dec 14;10(12):e0144860
pubmed: 26660525
PLoS Comput Biol. 2017 Jan 17;13(1):e1005291
pubmed: 28095402
Thromb Res. 2001 Jun 15;102(6):V215-24
pubmed: 11516455
Biophys J. 2008 Sep;95(5):2556-74
pubmed: 18515386
Sci Rep. 2020 Oct 29;10(1):18604
pubmed: 33122712
Front Physiol. 2019 Oct 17;10:1329
pubmed: 31749708
Future Sci OA. 2015 Nov 01;1(4):FSO30
pubmed: 28031903
J Thromb Haemost. 2009 Jul;7(7):1057-66
pubmed: 19422456
Proc Natl Acad Sci U S A. 2007 May 8;104(19):7899-903
pubmed: 17470810
Ann Biomed Eng. 2021 Dec;49(12):3609-3620
pubmed: 34668098
Blood Coagul Fibrinolysis. 1996 Mar;7(2):157-61
pubmed: 8735807
J Clin Invest. 1998 Jan 15;101(2):479-86
pubmed: 9435321
Pathophysiol Haemost Thromb. 2005;34(2-3):91-108
pubmed: 16432311