Nonlinear cardiovascular oscillatory dynamics in malaria : Clinical, experimental and theoretical investigations

Abdulhameed, Yunus A. and Stefanovska, Aneta and McClintock, Peter (2020) Nonlinear cardiovascular oscillatory dynamics in malaria : Clinical, experimental and theoretical investigations. PhD thesis, Lancaster University.

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Abstract

Erythrocyte deformability is known to be compromised due to the increased stiffness of the membrane of malaria-infected erythrocytes, and the latter also exhibit abnormal adherence to the endothelial cells that line all the blood vessels. This leads to alterations in the cells’ shapes as well as in the viscosity, flow properties, and oxygenation of the blood, which are all altered by malaria in a specific pattern that is different from that in other diseases. As the red blood cells are the main particles of the blood flowing through the cardiovascular system, these changes result in impaired hemodynamics. The impairments are mostly because of the spatial distributions (arrangement) of red blood cells. A large number of earlier studies into the characteristics of erythrocytes have been invasive and conducted on animal models, and more recently performed with experimental \textit{in vitro} optical assay models. However, recent technological and theoretical breakthroughs in biomedical research are enabling the application of non-invasive imaging techniques, yielding clinically relevant information on humans \textit{in vivo}. In this thesis, we first prove convincingly that the optical technique of laser-Doppler flowmetry (LDF) can be used to evaluate blood flow dynamics in dark-skinned individuals, a matter that has been subject to doubt and discussion since the introduction of the LDF technique. We then address the long-standing question as to whether malaria can be detected at an early stage by investigating the alterations in blood flow and cardiovascular dynamics in febrile and non-febrile malaria patients. The alterations were evaluated not only by optical methods, but also by use of several other sensors, and the resultant time series were analysed based on techniques specifically developed for non-strictly-periodic, but rather time-varying signals. Numerous investigations utilising optical methods have previously reported impaired oxygen delivery, reduced metabolic rate, ATP deficiency and respiratory distress in relation to metabolic acidosis in malaria. However, biological oscillations that manifest in the blood flow and cardiovascular dynamics, and how they change over time, have not yet been utilised. Several measurements of human blood flow and oxygenation \textit{in vivo} have demonstrated the manifestation of these oscillations in cardiovascular dynamics, and their physiological attribution have been established as being significant. These physiological oscillatory processes can in principle provide valuable information about the underlying dynamical properties of the system. Blood flow and cardiovascular dynamics were found to differ markedly in malaria and it is proposed to use such signatures in the development of a diagnostic test for the disease. Besides characterizing the blood flow and cardiovascular dynamics in malaria, probable mechanisms in the causation of the observed alterations are explored. They are associated with two well-known characteristics of malaria: the effect of variant gene expression, race or environmental factors on vascular function; and the long-term effects of malaria recurrence. The former is investigated through the comparative measurements and analyses of microvascular blood flow and tissue oxygenation dynamics in white Caucasians and black Africans. The latter is explored by comparing the blood flow and cardiovascular data recorded from patients of black African origin who had suffered episodes of malaria in the past, and recovered from it, with that of subjects with no history of malaria.

Item Type:
Thesis (PhD)
ID Code:
143045
Deposited By:
Deposited On:
07 Apr 2020 16:35
Refereed?:
No
Published?:
Unpublished
Last Modified:
16 Jul 2024 05:51