Understanding complex behaviours in the microcirculation: From blood flow to oxygenation

Societies around the world are increasingly struggling with the social and economic challenges of cardiovascular disease (CVD) and elevated CVD risk. Our growing understanding of CVD and elevated risk has focused greater attention on the microcirculation as a major contributor to peripheral vascular disease, but it has also become increasingly apparent that traditional markers of vascular dysfunction (Flammer, Anderson, Celermajer, & Creager, 2012) offer only limited predictive power for understanding more complex functional microvascular outcomes and the dynamic mechanisms aimed to ensure adequate perfusion of organ systems. This group of four reports arose from the symposium entitled ‘Understanding complex behaviours in the microcirculation: From blood flow to oxygenation’, which was presented at the Physiology 2019 meeting of the Physiological Society held in Aberdeen, UK. These reports provide an overview of some of the more recent investigative and conceptual approaches used to gain insight into the complex spatial and temporal behaviours of the microcirculation. They also explore how such innovative approaches can provide new insight into the fundamental mechanisms that underlie impaired microvascular function in individuals with CVD or at risk of CVD. In the first of these papers (Frisbee, Halvorson, Lewis, & Wiseman, 2020), Jefferson Frisbee and colleagues argue that altered haemodynamic behaviour in vascular networks is a strong predictor of functional outcomes. They review their work describing the spatial and temporal shifts in the distribution of perfusion at successive arteriolar bifurcations within the skeletal muscle of the obese Zucker rat model of the metabolic syndrome. The article focuses on the utility of an attractor model (a three-dimensional shape describing the behaviour of a system in time), constructed from the perfusion distribution coefficient (γ) at the bifurcations, to describe the altered patterns of intramuscular perfusion with increasing disease severity. The extent to which a system can adapt in response to imposed challenges and the efficacy of interventions in reversing established vasculopathy and perfusion impairments are evaluated by progressive shifts in the attractor. The extent to which a changing attractor represents a broad concept informing vascular disease risk in other tissues/organs is explored further in the paper by Nandi and Aston (2020). In their symposium report, the authors review how this mathematical method can be applied to routinely sampled periodic physiological waveform data, such as blood pressure, pulse oximetry and ECGs, to re-visualize them in a manner that allows unique quantification of multiple changes in waveform morphology and variability. Like Frisbee et al. (2020), they argue that the additional information provided by features of their attractor model of a waveform could improve the sensitivity needed to detect subtle cardiovascular changes, to flag a patient at risk or to map the response to treatment. Efforts to understand the complex behaviour of the microvasculature have used linear and non-linear mathematical methods both to characterize, predict and model system behaviour and to explore the mechanisms that underlie vasculopathy. To this end, Chipperfield, Thanaj, and Clough (2020) have applied a range of analysis techniques to laser Doppler fluximetry signals derived from the skin microvasculature in individuals at risk of cardiovascular and metabolic disease grouped for the use of calcium channel blockers. This report highlights the use of quantitative measures in different domains (time, frequency and information) and at different scales to gain a better mechanistic understanding of complex behaviours in the microcirculation. The authors provide further evidence that attenuation of flow-motion patterns is associated with increased cardiovascular disease risk and that prophylactic treatment might result in a further decline rather than enhancement of adaptivity, through altered microvascular dynamics. In the final report, arising from the presentation by Sarah Withers, Saxton, Heagerty, and Withers (2020) review the complexity of the communication between the cell populations that constitute perivascular adipose tissue function. They define the mechanisms by which eosinophils contribute to this function through a nitric oxide-dependent effect in small resistance arteries of healthy mice, using ex vivo assessment of contractility and pharmacological tools. The finding that such anti-contractile effects are lost in eosinophil-deficient mice that mimic the obese phenotype provides evidence for an unexpected role of eosinophils beyond simply being an ‘anti-parasitic’ immune cell. ‘Complexity’ defies a simple or unified definition, because it can reasonably be applied to nearly any natural or artificial condition or frame of reference/resolution. Furthermore, much like applications of chaos theory, the understanding of the complexity of a system can be highly reflective of the nature of the data gathered and the analytical approaches taken (Johnson, 2009). The combination of techniques presented in these four symposium reports opens new possibilities for the analysis of signals arising from the microcirculation and elsewhere. The combination of the metrics derived using the different approaches and the relationship between them provide robust parameters that inform our increasingly sophisticated, multiscale understanding of complex conditions, such as vascular disease risk. We are continuing to move into an era defined by advanced data analytics, with the increasing presence of machine learning and artificial intelligence to help us glean more accurate insight into complex physiological questions. As such, we must continue to embrace physiological complexity in both space and time in order to maximize the benefits of our efforts and to gain true insight into the behaviours of these systems. It is truly the ‘undiscovered country’ into which we, as scientists, must now collectively advance. None declared.

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