Biology subjects

Tithof, J.

Publications and source records attributed to Tithof, J..

11 recordsLinked to original sources

bioRxiv2026

High frame rate in vivo two-photon microscopy to quantify murine cerebrospinal fluid flow heterogeneity

Cerebrospinal fluid (CSF) flows through perivascular spaces (PVSs) surrounding brain vasculature, and impaired flow has been linked to neurodegenerative diseases such as Alzheimer's. However, the mechanisms driving CSF flow and its oscillatory dynamics remain poorly understood. Using high frame rate two-photon imaging (up to 113 Hz), we show that CSF flow is spatially heterogeneous and highly pulsatile, quantified using a regional CSF pulsatility index (PI). Reduced-order simulations with realistic domain length and Windkessel boundary conditions show that arterial pulsations generate peak CSF velocities but contribute negligibly to net transport. PI varies non-monotonically in space and substantially with downstream hydraulic resistance and compliance, indicating that CSF pulsatility is an emergent property of the hydraulic network rather than simply a consequence of local arterial wall motion. Measurements and simulations of the phase between arterial wall motion and CSF velocity further constrain proposed CSF driving mechanisms. Finally, we perform mouse-specific simulations to estimate average and peak wall shear stresses which support the potential role of pulsatile CSF flow in perivascular mechanotransduction. Together, these results establish CSF pulsatility as a measurable signature of network-scale CSF dynamics.

neuroscience↗

bioRxiv2025

Fluid-Structure Interaction Dynamics of Cervical Lymphatic Vessel Pumping and Valvular Function

A substantial portion of cerebrospinal fluid (CSF) drains through cervical lymphatic vessels (CLVs), a pathway mediated by basal and dorsal meningeal lymphatics. Impaired drainage along this route has been implicated in aging, Alzheimers disease, and traumatic brain injury. Despite considerable experimental investigation of CLV structure and function, computational modeling of this pathway remains limited. Here, we present a fully coupled two-dimensional fluid-structure interaction (FSI) model of a murine CLV constructed using the Lattice Boltzmann method for fluid dynamics and the immersed boundary method for the vessel geometry. Distinct from previous lymphatic vessel models, this framework is parameterized using data from recent in vivo imaging studies of CLVs. Using this model, we characterize the transient FSI dynamics within a single lymphangion, the pumping performance across a chain of three lymphangions with varying contraction phase delays, and the role of circular sinus geometry in regulating CSF transport under both favorable and adverse pressure gradients. Our results provide the first high-fidelity simulation of CSF drainage through CLVs, bridging a gap between experimental observations and mechanistic understanding. This work offers new insights into CLV pumping behavior and valve function, which helps inform the design of future experiments and therapeutic strategies aimed at enhancing CSF clearance.

physiology↗

bioRxiv2025

Boundary homogenization and numerical modeling of solute transport across the blood-brain barrier

Effective clearance of amyloid-{beta} (A{beta}) from the brain is essential for preventing neurodegenerative diseases such as Alzheimers. A significant portion of this clearance occurs through the blood-brain barrier (BBB) via receptor-mediated transport. However, current models fail to capture the complex kinetics and spatial heterogeneity of receptors at the BBB. In this study, we derive a novel boundary condition that accounts for finite receptor kinetics, receptor density, and bidirectional transport across the BBB. Specifically, we develop a nonlinear homogenized boundary condition that ensures mass conservation and incorporates receptor-mediated Michaelis-Menten kinetics. We then implement this boundary condition in a cylindrical geometry representing a capillary surrounded by brain tissue. After verifying that the model matches an analytical steady state solution that we derive and that it yields realistic blood A{beta} concentrations, we explore how realistic variations in parameter values drive changes in both steady state A{beta} concentration and transient dynamics. Simulations and analytical results reveal that A{beta} concentrations in the brain are sensitive to receptor number ratios, while concentrations in the blood are primarily affected by the blood clearance rate. Additionally, we use the model to investigate A{beta} clearance during sequential sleep cycles and due to a pathological phenomenon, spreading depolarization. This work presents the first biophysically consistent boundary condition for A{beta} transport across the BBB, offering a powerful tool for studying brain waste clearance under both physiological and pathological conditions.

neuroscience↗

bioRxiv2024

Lumped parameter simulations of cervical lymphatic vessels reveal dynamics of cerebrospinal fluid efflux from the skull

BackgroundGrowing evidence suggests that for rodents, a substantial fraction of cerebrospinal fluid (CSF) drains by crossing the cribriform plate into the nasopharengeal lymphatics, eventually reaching the cervical lymphatic vessels (CLVs). Disruption of this drainage pathway is associated with various neurological disorders. MethodsWe employ a lumped parameter method to numerically model CSF drainage across the cribriform plate to CLVs. Our model uses intracranial pressure as an inlet pressure and central venous blood pressure as an outlet pressure. The model incorporates initial lymphatic vessels (modeling those in the nasal region) that absorb the CSF and collecting lymphatic vessels (modeling CLVs) to transport the CSF against an adverse pressure gradient. To determine unknown parameters such as wall stiffness and valve properties, we utilize a Monte Carlo approach and validate our simulation against recent in vivo experimental measurements. ResultsOur parameter analysis reveals the physical characteristics of CLVs. Our results suggest that the stiffness of the vessel wall and the closing state of the valve are crucial for maintaining the vessel size and volume flow rate observed in vivo. We find that a decreased contraction amplitude and frequency leads to a reduction in volume flow rate, and we test the effects of varying the different pressures acting on the CLVs. Finally, we provide evidence that branching of initial lymphatic vessels may deviate from Murrays law to reduce sensitivity to elevated intracranial pressure. ConclusionsThis is the first numerical study of CSF drainage through CLVs. Our comprehensive parameter analysis offers guidance for future numerical modeling of CLVs. This study also provides a foundation for understanding physiology of CSF drainage, helping guide future experimental studies aimed at identifying causal mechanisms of reduction in CLV transport and potential therapeutic approaches to enhance flow.

neuroscience↗

bioRxiv2023

Image Analysis Techniques for In Vivo Quantification of Cerebrospinal Fluid Flow

Over the last decade, there has been a tremendously increased interest in understanding the neuro-physiology of cerebrospinal fluid (CSF) flow, which plays a crucial role in clearing metabolic waste from the brain. This growing interest was largely initiated by two significant discoveries: the glymphatic system (a pathway for solute exchange between interstitial fluid deep within the brain and the CSF surrounding the brain) and meningeal lymphatic vessels (lymphatic vessels in the layer of tissue surrounding the brain that drain CSF). These two CSF systems work in unison, and their disruption has been implicated in several neurological disorders including Alzheimers disease, stoke, and traumatic brain injury. Here, we present experimental techniques for in vivo quantification of CSF flow via direct imaging of fluorescent microspheres injected into the CSF. We discuss detailed image processing methods, including registration and masking of stagnant particles, to improve the quality of measurements. We provide guidance for quantifying CSF flow through particle tracking and offer tips for optimizing the process. Additionally, we describe techniques for measuring changes in arterial diameter, which is an hypothesized CSF pumping mechanism. Finally, we outline how these same techniques can be applied to cervical lymphatic vessels, which collect fluid downstream from meningeal lymphatic vessels. We anticipate that these fluid mechanical techniques will prove valuable for future quantitative studies aimed at understanding mechanisms of CSF transport and disruption, as well as for other complex biophysical systems.

neuroscience↗

bioRxiv2023

Quantifying the relationship between spreading depolarization and glymphatic flow

Recent studies have linked spreading depolarization (SD, an electro-chemical wave in the brain following stroke, migraine, traumatic brain injury, and more) with increase in cerebrospinal fluid (CSF) flow through the perivascular spaces (PVSs, annular channels lining the brain vasculature). We develop a novel computational model that couples SD and CSF flow. We first use high order numerical simulations to solve a system of physiologically realistic reaction-diffusion equations which govern the spatiotemporal dynamics of ions in the extracellular and intracellular spaces of the brain cortex during SD. We then couple the SD wave with a 1D CSF flow model that captures the change in cross-sectional area, pressure, and volume flow rate through the PVSs. The coupling is modelled using an empirical relationship between the excess potassium ion concentration in the extracellular space following SD and the vessel radius. We find that the CSF volumetric flow rate depends intricately on the length and width of the PVS, as well as the vessel radius and the angle of incidence of the SD wave. We derive analytical expressions for pressure and volumetric flow rates of CSF through the PVS for a given SD wave and quantify CSF flow variations when two SD waves collide. Our numerical approach is very general and could be extended in the future to obtain novel, quantitative insights into how CSF flow in the brain couples with slow waves, functional hyperemia, seizures, or externally applied neural stimulations.

bioengineering↗

bioRxiv2022

Lumped Parameter Liver Simulation to Predict Acute Hemodynamic Alterations Following Partial Resections

Partial liver resections are routinely performed in living donor liver transplantation and to debulk tumors in liver malignancies, but surgical decisions on vessel reconstruction for adequate inflow and outflow are challenging. Pre-operative evaluation is often limited to radiological imaging, which fails to account for post-resection hemodynamic alterations. Substantial evidence suggests post-surgical increase in local volume flow rate enhances shear stress, signaling hepatic regeneration, but excessive shear stress has been postulated to result in small for size syndrome and liver failure. Predicting hemodynamic alterations throughout the liver is particularly challenging due to the dendritic architecture the vasculature, spanning several orders of magnitude in diameter. Therefore, we developed a mathematical lumped parameter model with realistic heterogeneities capturing inflow/outflow of the human liver to simulate acute perfusion alterations following surgical resection. Our model is parameterized using clinical measurements, relies on a single free parameter, and accurately captures established perfusion characteristics. We quantify acute changes in volume flow rate, flow speed, and wall shear stress following variable, realistic liver resections and make comparisons to the intact liver. Our numerical model runs in minutes and can be adapted to patient-specific anatomy, providing a novel computational tool aimed at assisting pre- and intra-operative surgical decisions for liver resections.

bioengineering↗

bioRxiv2021

Social evolution of shared biofilm matrix components

Biofilm formation is an important and ubiquitous mode of growth among bacteria. Central to the evolutionary advantage of biofilm formation is cell-cell and cell-surface adhesion achieved by a variety of factors, some of which are diffusible compounds that may operate as classical public goods - factors that are costly to produce but may benefit other cells. An outstanding question is how diffusible matrix production, in general, can be stable over evolutionary timescales. In this work, using Vibrio cholerae as a model, we show that shared diffusible biofilm matrix proteins are indeed susceptible to cheater exploitation, and that the evolutionary stability of producing these matrix components fundamentally depends on biofilm spatial structure, intrinsic sharing mechanisms of these components, and flow conditions in the environment. We further show that exploitation of diffusible adhesion proteins is localized within a well-defined spatial range around cell clusters that produce them. Based on this exploitation range and the spatial distribution of cell clusters, we construct a model of costly diffusible matrix production and relate these length scales to the relatedness coefficient in social evolution theory. Our results show that production of diffusible biofilm matrix components is evolutionarily stable under conditions consistent with natural biofilm habitats and host environments. We expect the mechanisms revealed in this study to be relevant to other secreted factors that operate as cooperative public goods in bacterial communities, and the concept of exploitation range and the associated analysis tools to be generally applicable.

ecology↗

bioRxiv2021

A network model of glymphatic flow under different experimentally-motivated parametric scenarios

Rapidly growing evidence demonstrates that flow of cerebrospinal fluid (CSF) through perivascular spaces (PVSs) - annular channels surrounding vasculature in the brain - is a critically-important component of neurophysiology. CSF inflow contributes during physiological conditions to clearance of metabolic waste and in pathological situations to edema formation. However, brain-wide imaging methods cannot resolve PVSs, and high-resolution methods cannot access deep tissue or be applied to human subjects, so theoretical models provide essential insight. We model this CSF pathway as a network of hydraulic resistances, built from published parameters. A few parameters have very wide uncertainties, so we focus on the estimated limits of their feasible ranges by analyzing different parametric scenarios. We identify low-resistance PVSs and high-resistance parenchyma (brain tissue) as the scenario that best explains experimental observations. Our results point to the most important parameters that should be measured in future experiments. Extensions of our modeling may help predict stroke severity or lead to neurological disease treatments and drug delivery methods.

neuroscience↗

bioRxiv2020

Bulk flow of cerebrospinal fluid observed in periarterial spaces is not an artifact of injection

Cerebrospinal fluid (CSF) flowing through periarterial spaces is integral to the brains mechanism for clearing metabolic waste products. Experiments that track tracer particles injected into the cisterna magna of mouse brains have shown evidence of pulsatile CSF flow in pial periarterial spaces, with a bulk flow in the same direction as blood flow. However, the driving mechanism remains elusive. Several studies have suggested that the bulk flow might be an artifact, driven by the injection itself. Here, we address this hypothesis with new in vivo experiments where tracer particles are injected into the cisterna magna using a dual-syringe system, with simultaneous injection and withdrawal of equal amounts of fluid. This method produces no net increase in CSF volume and no significant increase in intracranial pressure. Yet, particle-tracking reveals flows in the pial periarterial spaces that are completely consistent with the flows observed in earlier experiments with single-syringe injection.

neuroscience↗

bioRxiv2019

Hydraulic resistance of perivascular spaces in the brain

Perivascular spaces (PVSs) are annular channels that surround arteries and carry cerebrospinal fluid into the brain, sweeping away metabolic waste. In vivo observations reveal that they are not concentric, circular annuli, however: the outer boundaries are often oblate, and the arteries that form the inner boundaries are often offset from the central axis. Here we show that the observed shapes of PVSs have lower hydraulic resistance than concentric, circular annuli of the same size, and therefore allow faster, more efficient flow of cerebrospinal fluid. To calculate hydraulic resistance, we parameterize PVS cross-sections as circles surrounded by ellipses, varying the radii of the circles, major and minor axes of the ellipses, and two-dimensional eccentricities of the circles with respect to the ellipses. For each shape, we solve the governing Navier-Stokes equation to determine the velocity profile for steady laminar flow and the corresponding hydraulic resistance. We find that the minimum hydraulic resistance (and therefore maximum flow rate) for a given PVS cross-sectional area occurs when the ellipse is elongated and intersects the circle, dividing the PVS into two lobes, as is common around pial arteries. We also find that if both the inner and outer boundaries are circular, the minimum hydraulic resistance occurs when the eccentricity is large, as is common around penetrating arteries. The circular, concentric annuli assumed in recent studies maximize hydraulic resistance and therefore minimize flow. Our parameterization can incorporate more realistic resistances into hydraulic network models of flow of cerebrospinal fluid in the brain.\n\nSignificance StatementRecent experiments show that there is bulk flow of cerebrospinal fluid in brain perivascular spaces (PVSs) in the direction of the blood flow, driven by pulsations of arterial walls due to the heartbeat. Published hydraulic network models have argued against such a flow due to the purported high hydraulic resistance of the system. Here we show that these high resistances are due to misrepresentations of the size and shape of PVSs. We present an adjustable model PVS that can match closely the actual shapes observed in vivo and show that these shapes are often nearly optimal, in the sense of offering the least hydraulic resistance. This optimization may well represent an evolutionary adaptation that maximizes clearance of metabolic waste from the brain.

neuroscience↗