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New insights into the analysis of red blood cells from leukemia and anemia patients: Nonlinear quantifiers, fractal mathematics, and Wavelet Transform

Author

Listed:
  • Bortolato, Santiago A.
  • Mancilla Canales, Manuel A.
  • Riquelme, Bibiana D.
  • Raviola, Mariana
  • Leguto, Alcides J.
  • Rebechi, Juan P.
  • Ponce de León, Patricia
  • Korol, Ana M.

Abstract

The alterations of red blood cells (RBCs) membrane in many hematological diseases prevent blood to accomplish its functions, but how these alterations occur is not completely understood. Hence, the development of a simple and accurate methodology for the characterization of different populations of RBCs is necessary for hematology and clinical diagnosis. In this work, we focus on different pathologies that affect the hemorheological properties of human beings blood. The results were obtained by studying healthy individuals, anemia and leukemia patient samples. Data analysis involved the use of non-linear methods, based on two different analytical strategies. On one hand, we used nonlinear mathematical quantifiers (False Nearest Neighbors, Embedding Dimension, May–Sugihara Correlation, and Hurst Exponent) on ektacytometrically recorded time series measuring the elongation of re-suspended RBCs subjected to well-defined shear stress. On the other hand, we developed an analytical methodology to aid in the diagnosis of those pathologies, based on the box-counting dimension from digital images of cells suspensions that were denoised standardly by application of Wavelet Transform. The results allowed preliminary discrimination of different populations studied and a correlation with its membrane damage.

Suggested Citation

  • Bortolato, Santiago A. & Mancilla Canales, Manuel A. & Riquelme, Bibiana D. & Raviola, Mariana & Leguto, Alcides J. & Rebechi, Juan P. & Ponce de León, Patricia & Korol, Ana M., 2021. "New insights into the analysis of red blood cells from leukemia and anemia patients: Nonlinear quantifiers, fractal mathematics, and Wavelet Transform," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).
  • Handle: RePEc:eee:phsmap:v:567:y:2021:i:c:s0378437120309432
    DOI: 10.1016/j.physa.2020.125645
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    References listed on IDEAS

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    1. Korol, A.M. & Foresto, P. & Rosso, O.A., 2007. "Self-organizing dynamics of human erythrocytes under shear stress," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 386(2), pages 770-775.
    2. Simonsen, Ingve, 2003. "Measuring anti-correlations in the nordic electricity spot market by wavelets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 322(C), pages 597-606.
    3. Mancilla Canales, M.A. & Leguto, A.J. & Riquelme, B.D. & León, P. Ponce de & Bortolato, S.A. & Korol, A.M., 2017. "Hurst exponent: A Brownian approach to characterize the nonlinear behavior of red blood cells deformability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 488(C), pages 1-7.
    4. Ingve Simonsen, 2001. "Measuring Anti-Correlations in the Nordic Electricity Spot Market by Wavelets," Papers cond-mat/0108033, arXiv.org, revised Apr 2003.
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