There is a distinct gap between mechanistic mathematical modelling of human biology, experimental evidence, and their clinical applications. To date, clinical decision making remains largely based on observations in populations without benefiting from extant experimental and integrative modelling knowledge. Conversely, experimental procedures are intricate and time consuming thus limiting their impact on the clinical process. Although mechanistic modelling has partly succeeded in integrating existing experimental knowledge and is thought to be primed for clinical applications, its capabilities remain under-utilized. Within the clinical sciences, a significant emphasis is placed on pharmacological and surgical procedures which often impact patient health negatively. There is a requirement for improved understanding of disease mechanisms, and for non-intrusive and effective therapies to reduce the burden of clinical harm, which is the third largest killer in Canada and elsewhere.

In this Research Topic, we focus on modeling of vascular disease and of non-pharmacological and non-surgical therapies. This topic aims to encourage identification of non-generic therapy mechanisms. The contributions to this topic will highlight the strengths of modelling as an evidence-generating tool that can streamline experiment design and guide clinical trial design.

This Research Topic welcomes review papers and original research on the following research fields but is not limited to them:

1. Human organ vasculature multi-scale or multi-physics modelling that provides evidence for effects of dietary, environmental, or other factors (e.g. stress, exercise).
2. Normal and pathophysiological neurovascular control of micro-, organ, or whole body vascular hemodynamics.
3. Electrical autoregulatory mechanisms in the vasculature, in health and disease.
4. Electrical activity in arterio-venous systems, including electrophysiology of blood vessel components.
5. Role of immune system in vascular function.
6. Device and novel therapy testing.
7. Descriptions of open source verifiable scientific platforms for this research.
8. Experimental results that call for modeling to extend and deepen knowledge.

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Frontiers in Physiology

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