Biology subjects

Linninger, A.

Publications and source records attributed to Linninger, A..

5 recordsLinked to original sources

bioRxiv2026

Microvascular network organization and hemodynamic perfusion protect the brain against hypoxia

Mechanistic simulations of blood flow and oxygen exchange showed regions of cortical tissue tolerating substantial increase in local oxygen consumption (CMRO2) before reaching hypoxia (pO2<10 mmHg). The observed robustness in O2 supply was attributed to overcapacity in convective oxygen transport in the pial arterial network combined with a surplus in the number of capillary flow paths. Microcirculatory flux analysis suggests that network induced hemodynamic flow patterns impart intrinsic reserve to protect the brain against perfusion variances or metabolic demand surges during activation. Furthermore, oxygen transport in cortical tissue is characterized by two regimes: in the transport zone -- centered on penetrating arteriole trees composed of a single penetrating vessel connected to the post-arteriole capillary transition zone -- strong diffusion supports high oxygen tension with only modest contribution from capillaries. This regime transitions into the terminal/reactive zone where oxygenation is sensitive to capillary density and perfusion. Quasi-dynamic simulations also enabled reconstruction of the BOLD signal underlying functional imaging. Simulations at single micron resolution further show that age-related reductions in arterial saturation and systemic hematocrit were sufficient to induce hypoxic tissue pockets in the terminal zone at nominal perfusion (CBF) and metabolic activity (CMRO2), and neutrophil adhesion induced capillary flow stalling further exacerbates hypoxia.

bioengineering↗

bioRxiv2025

In vitro design of intrathecal drug administration therapies

1Due to the scarcity of reliable in vivo data, the pharmacokinetics of intrathecally (IT) administered drugs remain inadequately quantified. Designing new therapies is further hindered by variability in experimental methods, inter-individual and inter-species differences, and poor reproducibility across animal and human studies. To address these limitations, we developed an anatomically accurate, subject-specific replica of the cerebrospinal fluid-filled spaces of the human central nervous system (CNS) using a multistep mold/casting process. The 3D-printed, transparent, deformable CNS phantom enables precise control of infusion and physiological parameters, allowing systematic generation of reliable and repeatable biodispersion data for lumbar IT infusion protocols. Pulsatile artificial cerebrospinal fluid (CSF) flow within the closed system was tuned to replicate subject-specific stroke volumes and flow rates observed in MRI. The models optical clarity facilitated high-speed visualization and tracking of tracer dispersion, exceeding the temporal resolution of current neuroimaging techniques. Experimental series spanning physiologically relevant CSF and infusion conditions enabled quantification of the spatiotemporal distribution of IT-administered tracers. Inversion of the parabolic diffusion equation provided estimates of the coefficient of effective dispersion. A distributed pharmacokinetic model was used to evaluate the influence of chemical kinetics and mass transfer on tracer behavior. The proposed experimental apparatus for in vitro design of IT therapies offers a complementary or alternative approach to traditional trial-and-error animal studies.

bioengineering↗

bioRxiv2025

Biophysical simulations of fMRI responses using realistic microvascular models: insights into distinct hemodynamics in humans and mice

1Functional Magnetic Resonance Imaging (fMRI) is broadly used to measure human brain activity, however the hemodynamic changes that comprise the fMRI response to neuronal activity are often interpreted using microscopy data in mice. These microscopy data provide ground-truth observations of how individual blood vessels respond to neuronal activity and thus form the basis of our fundamental understanding of neurovascular coupling. Although these invasive experiments provide invaluable insight, there are striking differences in the vascular architecture of mouse and human brains that may influence the hemodynamic response. Motivated by this, we developed a biophysical modeling framework for realistic hemodynamic simulations in both mouse and human cerebral cortex. For this, we utilized Vascular Anatomical Network (VAN) models that explicitly represent the full microvascular tree as a single connected network, originally based on anatomical reconstructions from a given location of mouse cerebral cortex. We extended the VAN modeling framework using synthetic VAN models representing the microvascular network at a single location of the human cerebral cortex. To account for larger size and complexity of the human VAN models, we developed an efficient computational framework to simulate the full hemodynamic responses in this human model and compared the simulated fMRI responses between mice and humans. Our biophysical simulations are based entirely on first principles (e.g., conservation of mass); model parameter values were fixed across all simulations, not tuned to fit data, as they represent meaningful physical constants taken from previous measurements. Only two simple calibrations were tuned for each simulation, to match baseline perfusion rates (blood flow) and oxygen extraction (OEF). Our results show that differences in microvasculature indeed influenced the hemodynamic response and led to observable differences in timing--e.g., the simulated fMRI response peak in humans was delayed by [~]2 s compared to that of mice, consistent with prior fMRI observations. While there are many known differences in vascular architecture in rodents and humans, we also discovered that, unexpectedly, an asymmetry in the numbers of branches of the penetrating intracortical arterioles and venules appears to be conserved across species. We demonstrate through further simulations that this anatomical property may also be needed for suitable hemodynamic responses. Our framework thus provides a valuable tool for bridging in-vivo microscopy of microvascular dynamics to human fMRI.

neuroscience↗

bioRxiv2023

MESH-FREE HIGH-RESOLUTION SIMULATION OF CEREBROCORTICAL OXYGENSUPPLY WITH FAST FOURIER PRECONDITIONING

Oxygen transfer from blood vessels to cortical brain tissue is representative of a class of problems with mixed-domain character. Large-scale efficient computation of tissue oxygen concentration is dependent on the manner in which the tubular network of blood vessels is coupled to the tissue mesh. Models which explicitly resolve the interface between the tissue and vasculature with a contiguous mesh are prohibitively expensive for very dense cerebral microvasculature. We propose a mixed-domain mesh-free technique whereby a vascular anatomical network (VAN) represented as a thin directed graph serves for convection of blood oxygen, and the surrounding extravascular tissue is represented as a Cartesian grid of 3D voxels throughout which oxygen is transported by diffusion. We split the network and tissue meshes by the Schur complement method of domain decomposition to obtain a reduced set of system equations for the tissue oxygen concentration. The use of a Cartesian grid allows the corresponding matrix equation to be solved approximately with a fast Fourier transform based Poisson solver, which serves as an effective preconditioner for Krylov subspace iteration. The performance of this method enables the steady state simulation of cortical oxygen perfusion for anatomically accurate vascular networks down to single micron resolution without the need for supercomputers. Practitioner PointsO_LIWe present a novel mixed-domain framework for efficiently modeling O2 extraction kinetics in the brain. C_LIO_LIModel equations are generated by graph-theoretic methods for mixed domains. C_LIO_LIDual mesh domain decomposition with FFT preconditioning yields very fast simulation times for extremely high spatial resolution. C_LI

bioengineering↗

bioRxiv2021

Cerebral hemodynamics: a mathematical model including autoregulation, baroreflex and extracranial peripheral circulation

Cerebral autoregulation, the physiological capability to regulate cerebral blood flow, may be assisted by short-term mean arterial pressure control via baroreflex, which, among several effects, modulates total peripheral resistance. It is unclear, however, whether the resistance of the head and neck vasculatures is also affected by baroreflex and whether these extracranial vessels assist autoregulation. Since sensing technologies such as functional Near-Infrared Spectroscopy and noninvasive intracranial pressure monitoring by strain gauge may be influenced by superficial tissue, it is clinically relevant to understand the relations between intracranial and extracranial hemodynamics. Therefore, we created an autoregulation model consisting of arteries and arterioles regulated by the intralumial pressure and microcirculation regulated by local blood flow. As the first critical step to quantify the signal deterioration introduced by the extracranial circulation on superficial sensors, the extracranial peripheral circulation of the head and neck and baroreflex regulation of the peripheral vasculature and of heart rate were also included. During simulations of a bout of acute hypotension, the model predicts a rapid return of cerebral blood flow to baseline levels and a prolonged suppression of the blood flow to the external carotid vasculature, in accordance with experimental evidence. The inclusion of peripheral control via baroreflex at the external carotid vasculature did not assist cerebral autoregulation, thus we raise the hypothesis that baroreflex may act on the head and neck vasculatures but this action has negligible effects on regulation of cerebral blood flow. When autoregulation is impaired, results suggest that the blood flow of the brain and of the head and neck present similar dynamics, while they are weakly coupled when autoregulation is intact. The model also provides a mechanistic explanation of the protection brought by cerebral autoregulation to the microvasculature and to the brain parenchyma. Our model forms the foundation for predicting the interference introduced by the superficial tissue to nonivasive sensors.

physiology↗