B10 - Multiscale Modeling of Nitric Oxide Transport in Cerebral Microvascular Networks Using Green's Function Methods

Introduction: : Nitric oxide (NO) is a critical vasodilator that dynamically regulates cerebral blood flow. It can be produced by nitric oxide synthase in endothelial cells (eNOS), a process triggered by intracellular calcium (Ca²⁺) transients. Once generated, NO diffuses freely across cell membranes to promote smooth muscle relaxation and enhancing blood flow – a key process for maintaining tissue perfusion and oxygen delivery. However, NO’s bioactivity is tightly constrained by rapid scavenging from hemoglobin in red blood cells (RBCs), reducing its effective concentration in the vasculature. A recent study has demonstrated that cerebral capillary endothelial cells (cECs) exhibit spontaneous, robust Ca²⁺ transients (~5000 events/min/mm3) that could serve as localized triggers for NO release, suggesting a mechanism for dynamic microvascular flow control via relaxing nearby pericytes and arteriolar smooth muscle cells (SMC) [1]. In this study we model NO transport in a reconstructed three-dimensional cerebral microvascular network by treating Ca²⁺-driven release as a series of instantaneous point sources, solved using Green's function (GF). This method efficiently captures both the rapid dispersal of NO from the sporadic Ca2+ activity and its scavenging by RBCs. This model reveals how Ca²⁺-driven NO bursts modulate local vascular tone, offering insights into the mechanisms of cerebral blood flow regulation.

Materials and

Methods: : To study NO transport in the cerebral microvasculature, we used a 3D model of ~15,000 interconnected vessel segments within a 1mm3 of brain tissue volume [2]. Stochastic IP3R-mediated calcium (Ca²⁺) events in cECs triggered NO production. The timing and intensity of these events dictated local NO production rate, reflecting the Ca²⁺-dependence of eNOS activity. Vessels are discretized to the approximate length of an cEC. And blood flow in each segment was simulated using Poiseuille’s law while considering the dependence of blood viscosity on diameter and local hematocrit [3]. We traced the stochastic path of each RBC in the network, accounting for the probability of moving to one of the daughter branches at bifurcation points based on the Pries and Secomb empirical correlation for plasma skimming [3]. RBCs served as NO sinks, while cECs acted as transient NO sources during Ca²⁺ events.
The spatial and temporal distribution of NO was modeled using the GF solution of the time-dependent diffusion-reaction equation [4], capturing NO spreads from a discrete unit point source/sink:
G_NO (x-x^*,t-t^* )=〖(4πD_NO (t-t^* ))〗^(-3/2) exp⁡[-r^2/(4πD_NO (t-t^* ) )]
where r=|x-x* | is distance from source and DNO is NO diffusivity. Total NO concentration was calculated by superposition of contributions from all instantaneous point sources/sinks:
C_NO (x,t)=∫_0^t▒∫_(R^3)▒〖G_NO (x-x^*,t-t^* ) q_NO (x,t^* )dx^* dt^*+G_0 〗
Here, q_NO is NO production rate, and G_0 is integration constant that satisfies boundary conditions. A zero net flux across the domain boundaries is assumed [4], with the integration constant set to balance total production and consumption.

Results, Conclusions, and Discussions:: A GF approach to simulate biotransport around complex microvascular networks [4] was adapted and optimized for the transport of NO. The approach offers reduced computational cost and allows simulations in macroscopic brain tissue volumes at realistic time frames (Fig.1). The transient GF approach was validated against the steady-state solution and time dependent FEM simulations. Simulations predicted significant NO bioavailability near active cEC sites, sufficient to modulate tone of pericytes and a SMCs within ~30µm. Transient Ca²⁺ events triggered NO bursts, creating localized hotspots around active capillaries, with clustered activity producing additive effects that can potentially modulate arteriolar dilation, consistent with experimental findings [1]. The model can bridge cellular Ca2+ signaling and NO production to network hemodynamics and can explore novel hypotheses for the regulation of cerebral blood flow in health and in disease.

Acknowledgements and/or References (Optional):: Acknowledgements: This work is supported by the National Institute of Neurological Disorders and Stroke and the National Institute of Aging of the NIH under award number R01NS19971.
References
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