Posts by Radu Precup

Abstract

In this paper a basic mathematical model is introduced to describe the dynamics of three cell lines after allogeneic stem cell transplantation: normal host cells, leukemic host cells and donor cells. Their evolution is one of competitive type and depends upon kinetic and cell–cell interaction parameters. Numerical simulations prove that the evolution can ultimately lead either to the normal hematopoietic state achieved by the expansion of the donor cells and the elimination of the host cells, or to the leukemic hematopoietic state characterized by the proliferation of the cancer line and the suppression of the other cell lines. One state or the other is reached depending on cell–cell interactions (anti-host, anti-leukemia and anti-graft effects) and initial cell concentrations at transplantation. The model also provides a theoretical basis for the control of post-transplant evolution aimed at the achievement of normal hematopoiesis.

Authors

Radu Precup
Department of Mathematics Babes-Bolyai University, Cluj-Napoca, Romania

Smaranda Arghirescu
Department of Hematology, “Victor Babeş” University of Medicine and Pharmacy, Timişoara 300041, Romania

Andrei Cucuianu
Department of Hematology, “Iuliu Haţieganu” University of Medicine and Pharmacy, Cluj 400012, Romania

Margit Şerban
Department of Hematology, “Victor Babeş” University of Medicine and Pharmacy, Timişoara 300041, Romania

Keywords

Mathematical modeling; dynamical system; numerical simulation; stem cell transplantation; acute myeloid leukemia

Paper coordinates

R. Precup, S. Arghirescu, A. Cucuianu, M. Serban, Mathematical modeling of cell dynamics after allogeneic bone marrow transplantation, Int. J. Biomath. 5 (2012) no. 2, 1250026 (18 pages), https://doi.org/10.1142/S1793524511001684

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About this paper

Journal

International Journal of Biomathematics

Publisher Name

World Scientific
Connecting great Minds

Print ISSN

17935245

Online ISSN

17937159

google scholar link

[1] M. Adimy, F. Crauste and A. El Abdllaoui, J. Biol. Syst. 16, 395 (2008). LinkISIGoogle Scholar
[2]
L. K. Andersen and M. C. Mackey, J. Theor. Biol. 209, 113 (2001). CrossrefISIGoogle Scholar
[3]
F. Aversaet al.J. Clin. Oncol. 23, 3447 (2005), DOI: 10.1200/JCO.2005.09.117CrossrefISIGoogle Scholar
[4]
F.   Brauer and C.   Castillo-Chávez , Mathematical Models in Population Biology and Epidemiology ( Springer , Berlin , 2001 ) . CrossrefGoogle Scholar
[5]
A. M. Carella, S. Giralt and S. Slavin, Haematologica 85, 304 (2000). ISIGoogle Scholar
[6]
F. Castiglione and B. Piccoli, Bull. Math. Biol. 68, 255 (2006), DOI: 10.1007/s11538-005-9014-3CrossrefISIGoogle Scholar
[7]
C. Colijn and M. C. Mackey, J. Theor. Biol. 237, 117 (2005), DOI: 10.1016/j.jtbi.2005.03.033CrossrefISIGoogle Scholar
[8]
J. J. Cornelissen and B. Löwenberg, Hematology 2005, 151 (2005), DOI: 10.1182/asheducation-2005.1.151CrossrefGoogle Scholar
[9]
A. Cucuianu and R. Precup, Comput. Math. Methods Med. 11, 49 (2010), DOI: 10.1080/17486700902973751CrossrefISIGoogle Scholar
[10]
R. De Condeet al.J. Theor. Biol. 236, 39 (2005). CrossrefISIGoogle Scholar
[11]
B. R. Dey and T. R. Spitzer, Brit. J. Haematol. 135, 423 (2006), DOI: 10.1111/j.1365-2141.2006.06300.xCrossrefISIGoogle Scholar
[12]
D. Dingli and F. Michor, Stem Cells 24, 2603 (2006), DOI: 10.1634/stemcells.2006-0136CrossrefISIGoogle Scholar
[13]
D. Dingli and J. M. Pacheco, Wiley Interdiscip. Rev. Syst. Biol. Med. 2, 235 (2010). CrossrefISIGoogle Scholar
[14]
B. Djulbegovic and S. Svetina, Cell Proliferat. 18, 307 (1985). CrossrefGoogle Scholar
[15]
M. Eapen and V. Rocha, Lifetime Data Anal. 14, 379 (2008), DOI: 10.1007/s10985-008-9090-4CrossrefISIGoogle Scholar
[16]
A. S. Fokas, J. B. Keller and B. D. Clarkson, Cancer Res. 51, 2084 (1991). ISIGoogle Scholar
[17]
C. Foley and M. C. Mackey, J. Math. Biol. 58, 285 (2009), DOI: 10.1007/s00285-008-0165-3CrossrefISIGoogle Scholar
[18]
L. Fouillardet al.Haematologica 93, 834 (2008), DOI: 10.3324/haematol.11277CrossrefISIGoogle Scholar
[19]
P. S. Kim, P. P. Lee and D. Levy, J. Theor. Biol. 246, 33 (2007), DOI: 10.1016/j.jtbi.2006.12.012CrossrefISIGoogle Scholar
[20]
P. S. Kim, P. P. Lee and D. Levy, Biology and Control Theory: Current Challenges, Lecture Notes in Control and Information Sciences 357 (Springer, Berlin, 2007) pp. 3–20. CrossrefGoogle Scholar
[21]
P. S. Kim, P. P. Lee and D. Levy, Plos Comput. Biol. 4, 1 (2008). ISIGoogle Scholar
[22]
M. C. Mackey, Blood 51, 941 (1978). CrossrefISIGoogle Scholar
[23]
R. Martinoet al.Blood 108, 836 (2006), DOI: 10.1182/blood-2005-11-4503CrossrefISIGoogle Scholar
[24]
J. Mehtaet al.Blood 90, 3808 (1997). Google Scholar
[25]
H. Moore and N. K. Li, J. Theor. Biol. 227, 513 (2004), DOI: 10.1016/j.jtbi.2003.11.024CrossrefISIGoogle Scholar
[26]
J. D.   Murray , Mathematical Biology II: Spatial Models and Biomedical Applications ( Springer , New York , 2003 ) . CrossrefGoogle ScholarM. N. Obeyesekere, P. P. Spicer and M. Korbling, A Mathematical Model for the Progression of an Abnormality in the Hematopoietic System, Lecture Notes in Control and Information Sciences 321 (Springer, New York, 2005) pp. 257–268. CrossrefGoogle Scholar
[27]
V. Rocha, G. Sanz and E. Gluckman, Curr. Opin. Hematol. 11, 375 (2004), DOI: 10.1097/01.moh.0000145933.36985.ebCrossrefISIGoogle Scholar
[28]
S. I. Rubinow and J. L. Lebowitz, Biophys. J. 16, 897 (1976). CrossrefISIGoogle Scholar
[29]
S. I. Rubinow and J. L. Lebowitz, Biophys. J. 16, 1257 (1976). CrossrefISIGoogle Scholar
[30]
S. Slavinet al.Blood 91, 756 (1998). ISIGoogle Scholar
[31]
R. Storb, Curr. Opin. Hematol. 21(), S3 (2009). Google Scholar
[32]
J. F. Tisdale and C. E. Dunbar, Clinical Hematology (Mosby-Elsevier, 2006) pp. 2–15. Google Scholar

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