The study was carried out to evaluate deformable and
aggregative erythrocyte properties in humans under normal and pathological
states and in rats exposed to various stressors. A strong correlation between
the erythrocyte rheological determinants, i.e. deformability index and
aggregation rate, was found under pathological and stress-induced states. The
physiological significance of this phenomenon is to maintain the native
structure of blood flow.
References
[1]
Chien, S. (1970) Shear dependence of effective cell volume as a determinant of blood viscosity. Science, 168, 977-979. http://dx.doi.org/10.1126/science.168.3934.977
[2]
Muralidharan, E., Tateishi, N. and Maeda, N. (1994) Simultaneous influence of erythrocyte deformability and macromolecules in the medium on erythrocyte aggregation: A kinetic study by a laser scattering technique. Biochimica et Biophysica Acta, 194, 255-263. http://dx.doi.org/10.1016/0005-2736(94)90307-7
[3]
Reinhart, W.H. and Singh, A. (1990) Erythrocyte aggregation: The role of cell deformability and geometry. European Journal of Clinical Investigation, 20, 458-462. http://dx.doi.org/10.1111/j.1365-2362.1990.tb01884.x
[4]
Bagchi, P., Johnson, P.C. and Popel, A.S. (2005) Computational fluid dynamic simulation of aggregation of deformable cells in a shear flow. Journal of Biomechanical Engineering, 127, 35-54. http://dx.doi.org/10.1115/1.2112907
[5]
Suzuki, Y., Tateishi, N., Cicha, I. and Maeda, N. (2001) Aggregation and sedimentation of mixed of erythrocytes with different properties. Clinical Hemorheology and Microcirculation, 25, 105-117.
[6]
Clark, M.R., Mohandas, N. and Shohet, S.B. (1983) Osmotic gradient ektacytometry: Comprehensive characterization of red cell volume and surface maintenance. Blood, 61, 899-910.
[7]
Johnson, R.M. (1989) Ektacytometry of red blood cells. Methods in Enzymology, 173, 35-54. http://dx.doi.org/10.1016/S0076-6879(89)73004-4
[8]
Ohta, K., Gotoh, F., Tomita, M., et al. (1992) Animal species differences in erythrocyte aggregability. American Journal of Physiology—Heart and Circulatory Physiology, 262, 1009-1012.
[9]
Elbert, T., Ray, W.Y., Kowalik, Z.J., et al. (1994) Chaos and physiology: Deterministic chaos in excitable cell assemblies. Physiological Reviews, 74, 1-47.
[10]
Iasemidis, L.D., Sackellares, J.C., Zaveri, H.P. and Williams, W.J. (1990) Phase space topography and the Lyapunov exponent of electrocorticograms in partial seizures. Brain Topography, 2, 187-201. http://dx.doi.org/10.1007/BF01140588
[11]
Kowalik, Z.J. (2000) Nonlinear mechanism of cortical oscillations. Neurologia i Neurochirurgia Polska, 34, 53-65.
[12]
Lai, Y.C., Harrison, M.A., Frei, M.G. and Osorio, I. (2004) Controlled test for predictive power of lyapunov exponents: Their inability to predict epileptic seizures. Chaos, 14, 630-642. http://dx.doi.org/10.1063/1.1777831
[13]
Meyer, M., Rahmel, A., Marconi, C., Grassi, B., Cerretelli, P. and Skinner, J.E. (1998) Stability of heartbeat interval distributions in chronic high altitude hypoxia. Integrative Physiological and Behavioral Science, 33, 344-362.
[14]
Mühlnickel, W., Rendtorff, N., Kowalik, Z.J., Rockstroh, B., Miltner, W. and Elbert, T. (1994) Testing the determinism of EEG and MEG. Integrative Physiological and Behavioral Science, 29, 262-269. http://dx.doi.org/10.1007/BF02691330
[15]
Skinner, J.E., Carpeggiani, C., Landisman, C.R. and Fulton, K.W. (1991) Correlation dimension of heartbeat intervals is reduced in conscious pigs by myocardial ischemia. Circulation Research, 68, 966-976. http://dx.doi.org/10.1161/01.RES.68.4.966
[16]
Skinner, J.E., Nester, B.A. and Dalsev, W.C. (2000) Nonlinear dynamics of heart rate variability during experimental hemorrhage in ketamine-anesthetized rats. American Journal of Physiology—Heart and Circulatory Physiology, 279, H1669-H1678.
[17]
Skinner, J.E., Pratt, C.M. and Vybiral, T. (1993) Reduction in the correlation dimension of heartbeat intervals precedes imminent ventricular fibrillation in human subjects. American Heart Journal, 125, 731-743. http://dx.doi.org/10.1016/0002-8703(93)90165-6
