PMID- 36926695
OWN - NLM
STAT- MEDLINE
DCOM- 20230421
LR  - 20240419
IS  - 1542-0086 (Electronic)
IS  - 0006-3495 (Print)
IS  - 0006-3495 (Linking)
VI  - 122
IP  - 8
DP  - 2023 Apr 18
TI  - The stress-free state of human erythrocytes: Data-driven inference of a 
      transferable RBC model.
PG  - 1517-1525
LID - S0006-3495(23)00172-8 [pii]
LID - 10.1016/j.bpj.2023.03.019 [doi]
AB  - The stress-free state (SFS) of red blood cells (RBCs) is a fundamental reference 
      configuration for the calibration of computational models, yet it remains 
      unknown. Current experimental methods cannot measure the SFS of cells without 
      affecting their mechanical properties, whereas computational postulates are the 
      subject of controversial discussions. Here, we introduce data-driven estimates of 
      the SFS shape and the visco-elastic properties of RBCs. We employ data from 
      single-cell experiments that include measurements of the equilibrium shape of 
      stretched cells and relaxation times of initially stretched RBCs. A hierarchical 
      Bayesian model accounts for these experimental and data heterogeneities. We 
      quantify, for the first time, the SFS of RBCs and use it to introduce a 
      transferable RBC (t-RBC) model. The effectiveness of the proposed model is shown 
      on predictions of unseen experimental conditions during the inference, including 
      the critical stress of transitions between tumbling and tank-treading cells in 
      shear flow. Our findings demonstrate that the proposed t-RBC model provides 
      predictions of blood flows with unprecedented accuracy and quantified 
      uncertainties.
CI  - Copyright (c) 2023 Biophysical Society. Published by Elsevier Inc. All rights 
      reserved.
FAU - Amoudruz, Lucas
AU  - Amoudruz L
AD  - Computational Science and Engineering Laboratory, ETH Zurich, Zurich, 
      Switzerland; School of Engineering and Applied Sciences, Harvard University, 
      Cambridge, Massachusetts.
FAU - Economides, Athena
AU  - Economides A
AD  - Computational Science and Engineering Laboratory, ETH Zurich, Zurich, 
      Switzerland; School of Engineering and Applied Sciences, Harvard University, 
      Cambridge, Massachusetts.
FAU - Arampatzis, Georgios
AU  - Arampatzis G
AD  - Computational Science and Engineering Laboratory, ETH Zurich, Zurich, 
      Switzerland; School of Engineering and Applied Sciences, Harvard University, 
      Cambridge, Massachusetts.
FAU - Koumoutsakos, Petros
AU  - Koumoutsakos P
AD  - Computational Science and Engineering Laboratory, ETH Zurich, Zurich, 
      Switzerland; School of Engineering and Applied Sciences, Harvard University, 
      Cambridge, Massachusetts. Electronic address: petros@seas.harvard.edu.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20230316
PL  - United States
TA  - Biophys J
JT  - Biophysical journal
JID - 0370626
SB  - IM
MH  - Humans
MH  - Bayes Theorem
MH  - Computer Simulation
MH  - *Erythrocytes/physiology
MH  - Viscosity
PMC - PMC10147838
COIS- Declaration of interests The authors declare no competing interests.
EDAT- 2023/03/18 06:00
MHDA- 2023/04/21 06:41
PMCR- 2024/04/18
CRDT- 2023/03/17 02:55
PHST- 2022/06/21 00:00 [received]
PHST- 2022/12/19 00:00 [revised]
PHST- 2023/03/10 00:00 [accepted]
PHST- 2023/04/21 06:41 [medline]
PHST- 2023/03/18 06:00 [pubmed]
PHST- 2023/03/17 02:55 [entrez]
PHST- 2024/04/18 00:00 [pmc-release]
AID - S0006-3495(23)00172-8 [pii]
AID - 10.1016/j.bpj.2023.03.019 [doi]
PST - ppublish
SO  - Biophys J. 2023 Apr 18;122(8):1517-1525. doi: 10.1016/j.bpj.2023.03.019. Epub 
      2023 Mar 16.