An ovine knee simulator: description and proof of concept.

Aims: The ovine stifle is an established model for evaluation of knee treatments, such as meniscus replacement. This study introduces a novel ovine gait simulator for pre-testing of surgical treatments prior to in vivo animal trials. Furthermore, we describe a pilot study that assessed gait kinematics and contact pressures of native ovine stifle joints and those implanted with a novel fiber-matrix reinforced polyvinyl alcohol-polyethylene glycol (PVA-PEG) hydrogel meniscus to illustrate the efficacy of the simulator. Methods: The gait simulator controlled femoral flexion-extension and applied a 980N axial contact force to the distal tibia, whose movement was guided by the natural ligaments. Five right ovine stifle joints were implanted with a PVA-PEG total medial meniscus replacement, fixed to the tibia via transosseous tunnels and interference screws. Six intact and five implanted right ovine stifle joints were tested for 500 k gait cycles at 1.55 Hz. Implanted stifle joint contact pressures and kinematics in the simulator were compared to the intact group. Contact pressures were measured at 55° flexion using pressure sensitive film inserted sub-meniscally. 3D kinematics were measured optically across two 30-s captures. Results: Peak contact pressures in intact stifles were 3.6 ± 1.0 MPa and 6.0 ± 2.1 MPa in the medial and lateral condyles (p < 0.05) and did not differ significantly from previous studies (p > 0.4). Medial peak implanted pressures were 4.3 ± 2.2 MPa (p > 0.4 versus intact), while lateral peak pressures (9.4 ± 0.8 MPa) were raised post medial compartment implantation (p < 0.01). The range of motion for intact joints was flexion/extension 37° ± 1°, varus/valgus 1° ± 1°, external/internal rotation 5° ± 3°, lateral/medial translation 2 ± 1 mm, anterior/posterior translation 3 ± 1 mm and distraction/compression 1 ± 1 mm. Ovine joint kinematics in the simulator did not differ significantly from published in vivo data for the intact group, and the intact and implanted groups were comparable (p > 0.01), except for in distraction-compression (p < 0.01). Conclusion: These findings show correspondence of the ovine simulator kinematics with in vivo gait parameters. The efficacy of the simulator to evaluate novel treatments was demonstrated by implanting a PVA-PEG hydrogel medial meniscal replacement, which restored the medial peak contact pressures but not lateral. This novel simulator may enable future work on the development of surgical procedures, derisking subsequent work in live animals.

A Comprehensive Review on Modeling Aspects of Infusion-Based Drug Delivery in the Brain.

Brain disorders represent an ever-increasing health challenge worldwide. While conventional drug therapies are less effective due to the presence of the blood-brain barrier, infusion-based methods of drug delivery to the brain represent a promising option. Since these methods are mechanically controlled and involve multiple physical phases ranging from the neural and molecular scales to the brain scale, highly efficient and precise delivery procedures can significantly benefit from a comprehensive understanding of drug-brain and device-brain interactions. Behind these interactions are principles of biophysics and biomechanics that can be described and captured using mathematical models. Although biomechanics and biophysics have received considerable attention, a comprehensive mechanistic model for modeling infusion-based drug delivery in the brain has yet to be developed. Therefore, this article reviews the state-of-the-art mechanistic studies that can support the development of next-generation models for infusion-based brain drug delivery from the perspective of fluid mechanics, solid mechanics, and mathematical modeling. The supporting techniques and database are also summarized to provide further insights. Finally, the challenges are highlighted and perspectives on future research directions are provided. STATEMENT OF SIGNIFICANCE: Despite the immense potential of infusion-based drug delivery methods for bypassing the blood-brain barrier and efficiently delivering drugs to the brain, achieving optimal drug distribution remains a significant challenge. This is primarily due to our limited understanding of the complex interactions between drugs and the brain that are governed by principles of biophysics and biomechanics, and can be described using mathematical models. This article provides a comprehensive review of state-of-the-art mechanistic studies that can help to unravel the mechanism of drug transport in the brain across the scales, which underpins the development of next-generation models for infusion-based brain drug delivery. More broadly, this review will serve as a starting point for developing more effective treatments for brain diseases and mechanistic models that can be used to study other soft tissue and biomaterials.

Boundary Lubrication Performance of Polyelectrolyte-Surfactant Complexes on Biomimetic Surfaces.

Aqueous mixtures of oppositely charged polyelectrolytes and surfactants are useful in many industrial applications, such as shampoos and hair conditioners. In this work, we investigate the friction between biomimetic hair surfaces in the presence of adsorbed complexes formed from cationic polyelectrolytes and anionic surfactants in an aqueous solution. We apply nonequilibrium molecular dynamics (NEMD) simulations using the coarse-grained MARTINI model. We first developed new MARTINI parameters for cationic guar gum (CGG), a functionalized, plant-derived polysaccharide. The complexation of CGG and the anionic surfactant sodium dodecyl sulfate (SDS) on virgin and chemically damaged biomimetic hair surfaces was studied using a sequential adsorption approach. We then carried out squeeze-out and sliding NEMD simulations to assess the boundary lubrication performance of the CGG-SDS complex compressed between two hair surfaces. At low pressure, we observe a synergistic friction behavior for the CGG-SDS complex, which gives lower shear stress than either pure CGG or SDS. Here, friction is dominated by viscous dissipation in an interfacial layer comprising SDS and water. At higher pressures, which are probably beyond those usually experienced during hair manipulation, SDS and water are squeezed out, and friction increases due to interdigitation. The outcomes of this work are expected to be beneficial to fine-tune and screen sustainable hair care formulations to provide low friction and therefore a smooth feel and reduced entanglement.

Invariant dynamics in a united-atom model of an ionic liquid.

We study a united-atom model of the ionic liquid 1-butyl-1-methylpyrrolidinium bis(trifluoromethyl)sulfonylamide to determine to what extent there exist curves in the phase diagram along which the microscopic dynamics are invariant when expressed in dimensionless, or reduced, form. The initial identification of these curves, termed isodynes, is made by noting that contours of reduced shear viscosity and reduced self-diffusion coefficient coincide to a good approximation. Choosing specifically the contours of reduced viscosity as nominal isodynes, further simulations were carried out for state points on these, and other aspects of dynamics were investigated to study their degree of invariance. These include the mean-squared displacement, shear-stress autocorrelation function, and various rotational correlation functions. These were invariant to a good approximation, with the main exception being rotations of the anion about its long axis. The dynamical features that are invariant have in common that they are aspects that would be relevant for a coarse-grained description of the system; specifically, removing the most microscopic degrees of freedom in principle leads to a simplification of the potential energy landscape, which allows for the existence of isodynes.

Investigating Deep Sedation With Intravenous Ketamine in Spontaneous Respiration During Pulsed-Field Ablation.

OBJECTIVES: The authors report their experience of a protocol for deep sedation with ketamine in spontaneous respiration during the pulsed-field ablation (PFA) of atrial fibrillation (AF). DESIGN: Observational, prospective, nonrandomized fashion. SETTING: Single-center hospitalized patients. PARTICIPANTS: All consecutive patients undergoing PFA of AF. INTERVENTIONS: Patients undergoing deep sedation with intravenous ketamine. MEASUREMENTS AND MAIN RESULTS: The authors' sedation protocol involves the intravenous administration of fentanyl (1.5 µg/kg) and midazolam (2 mg) at low doses before local anesthesia with lidocaine. A ketamine adjunct (1 mg/kg) in 5-minute boluses was injected about 5 minutes before the first PFA delivery. The authors enrolled 117 patients (age = 59 ± 10 y, 74.4% males, body mass index = 27.6 ± 5 kg/m2, fluoroscopy time = 24 ± 14 minutes, skin-to-skin time = 80 ± 40 minutes and PFA LA dwell time = 24 ± 7 minutes). By the end of the procedure, pulmonary vein isolation had been achieved in all patients using PFA alone. The mean time under sedation was 54.9 ± 6 minutes, with 92 patients (79%) being sedated for <1 hour. A satisfactory Ramsay Sedation Scale level before ketamine administration was achieved in all patients, except one (80.3% of the patients with rank 3; 18.4% with rank 2). In all procedures, the satisfaction level was found acceptable by both the patient and the primary operator (satisfactory in 98.2% of cases). All patients achieved a Numeric Rating Scale for Pain ≤3 (none or mild). No major procedure or anesthesia-related complications were reported. CONCLUSION: The authors' standardized sedation protocol with the administration of drugs with rapid onset and pharmacologic offset at low doses was safe and effective, with an optimal degree of patient and operator satisfaction.

Porosity-permeability tensor relationship of closely and randomly packed fibrous biomaterials and biological tissues: Application to the brain white matter.

The constitutive model for the porosity-permeability relationship is a powerful tool to estimate and design the transport properties of porous materials, which has attracted significant attention for the advancement of novel materials. However, in comparison with other materials, biomaterials, especially natural and artificial tissues, have more complex microstructures e.g. high anisotropy, high randomness of cell/fibre dimensions/position and very low porosity. Consequently, a reliable microstructure-permeability relationship of fibrous biomaterials has proven elusive. To fill this gap, we start a mathematical derivation from the fundamental brain white matter (WM) formed by nerve fibres. This is augmented by a numerical characterisation and experimental validations to obtain an anisotropic permeability tensor of the brain WM as a function of the tissue porosity. A versatile microstructure generation software (MicroFiM) for fibrous biomaterial with complex microstructure and low porosity was built accordingly and made freely accessible here. Moreover, we propose an anisotropic poro-hyperelastic model enhanced by the newly defined porosity-permeability tensor relationship which precisely captures the tissues macro-scale permeability changes due to the microstructural deformation in an infusion scenario. The constitutive model, theories and protocols established in this study will both provide improved design strategies to tailor the transport properties of fibrous biomaterials and enable the non-invasive characterisation of the transport properties of biological tissues. This will lead to the provision of better patient-specific medical treatments, such as drug delivery. STATEMENT OF SIGNIFICANCE: Due to the microstructural complexity, a reliable microstructure-permeability relationship of fibrous biomaterials has proven elusive, which hinders our way of tuning the fluid transport property of the biomaterials by directly programming their microstructure. The same problem hinders non-invasive characterisations of fluid transport properties in biological tissues, which can significantly improve the efficiency of treatments e.g. drug delivery, directly from the tissues accessible microstructural information, e.g. porosity. Here, we developed a validated mathematical formulation to link the random microstructure to a fibrous material's macroscale permeability tensor. This will advance our capability to design complex biomaterials and make it possible to non-invasively characterise the permeability of living tissues for precise treatment planning. The newly established theory and protocol can be easily adapted to various types of fibrous biomaterials.

Effects of surfactant adsorption on the wettability and friction of biomimetic surfaces.

The properties of solid-liquid interfaces can be markedly altered by surfactant adsorption. Here, we use molecular dynamics (MD) simulations to study the adsorption of ionic surfactants at the interface between water and heterogeneous solid surfaces with randomly arranged hydrophilic and hydrophobic regions, which mimic the surface properties of human hair. We use the coarse-grained MARTINI model to describe both the hair surfaces and surfactant solutions. We consider negatively-charged virgin and bleached hair surface models with different grafting densities of neutral octadecyl and anionic sulfonate groups. The adsorption of cationic cetrimonium bromide (CTAB) and anionic sodium dodecyl sulfate (SDS) surfactants from water are studied above the critical micelle concentration. The simulated adsorption isotherms suggest that cationic surfactants adsorb to the surfaces via a two-stage process, initially forming monolayers and then bilayers at high concentrations, which is consistent with previous experiments. Anionic surfactants weakly adsorb via hydrophobic interactions, forming only monolayers on both virgin and medium bleached hair surfaces. We also conduct non-equilibrium molecular dynamics simulations, which show that applying cationic surfactant solutions to bleached hair successfully restores the low friction seen with virgin hair. Friction is controlled by the combined surface coverage of the grafted lipids and the adsorbed CTAB molecules. Treated surfaces containing monolayers and bilayers both show similar friction, since the latter are easily removed by compression and shear. Further wetting MD simulations show that bleached hair treated with CTAB increases the hydrophobicity to similar levels seen for virgin hair. Treated surfaces containing CTAB monolayers with the tailgroups pointing predominantly away from the surface are more hydrophobic than bilayers due to the electrostatic interactions between water molecules and the exposed cationic headgroups.

Transforming sustainable plant proteins into high performance lubricating microgels.

With the resource-intensive meat industry accounting for over 50% of food-linked emissions, plant protein consumption is an inevitable need of the hour. Despite its significance, the key barrier to adoption of plant proteins is their astringent off-sensation, typically associated with high friction and consequently poor lubrication performance. Herein, we demonstrate that by transforming plant proteins into physically cross-linked microgels, it is possible to improve their lubricity remarkably, dependent on their volume fractions, as evidenced by combining tribology using biomimetic tongue-like surface with atomic force microscopy, dynamic light scattering, rheology and adsorption measurements. Experimental findings which are fully supported by numerical modelling reveal that these non-lipidic microgels not only decrease boundary friction by an order of magnitude as compared to native protein but also replicate the lubrication performance of a 20:80 oil/water emulsion. These plant protein microgels offer a much-needed platform to design the next-generation of healthy, palatable and sustainable foods.

Sedation strategies for pulsed-field ablation of atrial fibrillation: focus on deep sedation with intravenous ketamine in spontaneous respiration.

AIMS: A standardized sedation protocol for pulsed-field ablation (PFA) of atrial fibrillation (AF) through irreversible cellular electroporation has not been well established. We report our experience of a protocol for deep sedation with ketamine in spontaneous respiration during the PFA of AF. METHODS AND RESULTS: All consecutive patients undergoing PFA for AF at our center were included. Our sedation protocol involves the intravenous administration of fentanyl (1.5 mcg/kg) and midazolam (2 mg) at low doses before local anesthesia with lidocaine. A ketamine adjunct (1 mg/kg) was injected about 5 minutes before the first PFA delivery. We enrolled 66 patients (age = 59 ± 9 years, 78.8% males, body mass index = 28.8 ± 5 kg/m2, fluoroscopy time = 21[15-30] min, skin-to-skin time = 75[60-100] min and PFA LA dwell time = 25[22-28] min). By the end of the procedure, PVI had been achieved in all patients by means of PFA alone. The mean time under sedation was 56.4 ± 6 min, with 50 (76%) patients being sedated for less than 1 hour. A satisfactory Ramsey Sedation Scale level before ketamine infusion was achieved in all patients except one (78.8% of the patients with rank 3; 19.7% with rank 2). In all procedures, the satisfaction level was found to be acceptable by both the patient and the primary operator (Score = 0 in 98.5% of cases). All patients reported none or mild pain. No major procedure or anesthesia-related complications were reported. CONCLUSION: Our standardized sedation protocol with the administration of drugs with rapid onset and pharmacological offset at low doses was safe and effective, with an optimal degree of patient and operator satisfaction. CLINICAL TRIAL REGISTRATION: Advanced TecHnologies For SuccEssful AblatioN of AF in Clinical Practice (ATHENA). URL: http://clinicaltrials.gov/Identifier: NCT05617456.

Non-equilibrium molecular simulations of thin film rupture.

The retraction of thin films, as described by the Taylor-Culick (TC) theory, is subject to widespread debate, particularly for films at the nanoscale. We use non-equilibrium molecular dynamics simulations to explore the validity of the assumptions used in continuum models by tracking the evolution of holes in a film. By deriving a new mathematical form for the surface shape and considering a locally varying surface tension at the front of the retracting film, we reconcile the original theory with our simulation to recover a corrected TC speed valid at the nanoscale.

Nanoscale friction of biomimetic hair surfaces.

We investigate the nanoscale friction between biomimetic hair surfaces using chemical colloidal probe atomic force microscopy experiments and nonequilibrium molecular dynamics simulations. In the experiments, friction is measured between water-lubricated silica surfaces functionalised with monolayers formed from either octadecyl or sulfonate groups, which are representative of the surfaces of virgin and ultimately bleached hair, respectively. In the simulations, friction is monitored between coarse-grained model hair surfaces with different levels of chemical damage, where a specified amount of grafted octadecyl groups are randomly replaced with sulfonate groups. The sliding velocity dependence of friction in the simulations can be described using an extended stress-augmented thermally activation model. As the damage level increases in the simulations, the friction coefficient generally increases, but its sliding velocity-dependence decreases. At low sliding velocities, which are closer to those encountered experimentally and physiologically, we observe a monotonic increase of the friction coefficient with damage ratio, which is consistent with our new experiments using biomimetic surfaces and previous ones using real hair. This observation demonstrates that modified surface chemistry, rather than roughness changes or subsurface damage, control the increase in nanoscale friction of bleached or chemically damaged hair. We expect the methods and biomimetic surfaces proposed here to be useful to screen the tribological performance of hair care formulations both experimentally and computationally.

Linking fluid-axons interactions to the macroscopic fluid transport properties of the brain.

Many brain disorders, including Alzheimer's Disease and Parkinson's Disease, and drug delivery procedures are linked to fluid transport in the brain; yet, while neurons are extremely soft and can be easily deformed, how the microscale channel flow interacts with the neuronal structures (especially axons) deformation and how these interactions affect the macroscale tissue function and transport properties is poorly understood. Misrepresenting these relationships may lead to the erroneous prediction of e.g. disease spread, drug delivery, and nerve injury in the brain. However, understanding fluid-neuron interactions is an outstanding challenge because the behaviours of both phases are not only dynamic but also occur at an extremely small length scale (the width of the flow channel is ∼100 nm), which cannot be captured by state-of-the-art experimental techniques. Here, by explicitly simulating the dynamics of the flow and axons at the microstructural level, we, for the first time, establish the link between micromechanical tissue response to the physical laws governing the macroscopic transport property of the brain white matter. We found that interactions between axons and the interstitial flow are very strong, thus playing an essential role in the brain fluid/mass transport. Furthermore, we proposed the first anisotropic pressure-dependent permeability tensor informed by microstructural dynamics for more accurate brain modelling at the macroscale, and analysed the effect of the variation of the microstructural parameters that influence such tensor. These findings will shed light on some unsolved issues linked to brain functions and medical treatments relying on intracerebral transport, and the mathematical model provides a framework to more realistically model the brain and design brain-tissue-like biomaterials. STATEMENT OF SIGNIFICANCE: This study reveals how neurons interact with the fluid flowing around them and how these microscale interactions affect macroscale transport behaviour of the brain tissue. The findings provide unprecedented insights into some unsolved issues linked to brain functions and medical treatments relying on intracerebral fluid transport. Furthermore, we, for the first time, established a microstructure-informed permeability tensor as a function of local hydraulic pressure and pressure gradient for the brain tissue, which inherently captures the dynamic transport property of the brain. This study is a cornerstone to advance the predicting accuracy of brain tissue transport property and neural tissue engineering.

Mathematical Optimisation of Magnetic Nanoparticle Diffusion in the Brain White Matter.

Magnetic nanoparticles (MNPs) are a promising drug delivery system to treat brain diseases, as the particle transport trajectory can be manipulated by an external magnetic field. However, due to the complex microstructure of brain tissues, particularly the arrangement of nerve fibres in the white matter (WM), how to achieve desired drug distribution patterns, e.g., uniform distribution, is largely unknown. In this study, by adopting a mathematical model capable of capturing the diffusion trajectories of MNPs, we conducted a pilot study to investigate the effects of key parameters in the MNP delivery on the particle diffusion behaviours in the brain WM microstructures. The results show that (i) a uniform distribution of MNPs can be achieved in anisotropic tissues by adjusting the particle size and magnetic field; (ii) particle size plays a key role in determining MNPs' diffusion behaviours. The magnitude of MNP equivalent diffusivity is reversely correlated to the particle size. The MNPs with a dimension greater than 90 nm cannot reach a uniform distribution in the brain WM even in an external magnitude field; (iii) axon tortuosity may lead to transversely anisotropic MNP transport in the brain WM; however, this effect can be mitigated by applying an external magnetic field perpendicular to the local axon track. This study not only advances understanding to answer the question of how to optimise MNP delivery, but also demonstrates the potential of mathematical modelling to help achieve desired drug distributions in biological tissues with a complex microstructure.

Polymer brushes for friction control: Contributions of molecular simulations.

When polymer chains are grafted to solid surfaces at sufficiently high density, they form brushes that can modify the surface properties. In particular, polymer brushes are increasingly being used to reduce friction in water-lubricated systems close to the very low levels found in natural systems, such as synovial joints. New types of polymer brush are continually being developed to improve with lower friction and adhesion, as well as higher load-bearing capacities. To complement experimental studies, molecular simulations are increasingly being used to help to understand how polymer brushes reduce friction. In this paper, we review how molecular simulations of polymer brush friction have progressed from very simple coarse-grained models toward more detailed models that can capture the effects of brush topology and chemistry as well as electrostatic interactions for polyelectrolyte brushes. We pay particular attention to studies that have attempted to match experimental friction data of polymer brush bilayers to results obtained using molecular simulations. We also critically look at the remaining challenges and key limitations to overcome and propose future modifications that could potentially improve agreement with experimental studies, thus enabling molecular simulations to be used predictively to modify the brush structure for optimal friction reduction.

Reconstruction of ovine axonal cytoarchitecture enables more accurate models of brain biomechanics.

There is an increased need and focus to understand how local brain microstructure affects the transport of drug molecules directly administered to the brain tissue, for example in convection-enhanced delivery procedures. This study reports a systematic attempt to characterize the cytoarchitecture of commissural, long association and projection fibres, namely the corpus callosum, the fornix and the corona radiata, with the specific aim to map different regions of the tissue and provide essential information for the development of accurate models of brain biomechanics. Ovine samples are imaged using scanning electron microscopy combined with focused ion beam milling to generate 3D volume reconstructions of the tissue at subcellular spatial resolution. Focus is placed on the characteristic cytological feature of the white matter: the axons and their alignment in the tissue. For each tract, a 3D reconstruction of relatively large volumes, including a significant number of axons, is performed and outer axonal ellipticity, outer axonal cross-sectional area and their relative perimeter are measured. The study of well-resolved microstructural features provides useful insight into the fibrous organization of the tissue, whose micromechanical behaviour is that of a composite material presenting elliptical tortuous tubular axonal structures embedded in the extra-cellular matrix. Drug flow can be captured through microstructurally-based models using 3D volumes, either reconstructed directly from images or generated in silico using parameters extracted from the database of images, leading to a workflow to enable physically-accurate simulations of drug delivery to the targeted tissue.

Digitally-enhanced lubricant evaluation scheme for hot stamping applications.

Digitally-enhanced technologies are set to transform every aspect of manufacturing. Networks of sensors that compute at the edge (streamlining information flow from devices and providing real-time local data analysis), and emerging Cloud Finite Element Analysis technologies yield data at unprecedented scales, both in terms of volume and precision, providing information on complex processes and systems that had previously been impractical. Cloud Finite Element Analysis technologies enable proactive data collection in a supply chain of, for example the metal forming industry, throughout the life cycle of a product or process, which presents revolutionary opportunities for the development and evaluation of digitally-enhanced lubricants, which requires a coherent research agenda involving the merging of tribological knowledge, manufacturing and data science. In the present study, data obtained from a vast number of experimentally verified finite element simulation results is used for a metal forming process to develop a digitally-enhanced lubricant evaluation approach, by precisely representing the tribological boundary conditions at the workpiece/tooling interface, i.e., complex loading conditions of contact pressures, sliding speeds and temperatures. The presented approach combines the implementation of digital characteristics of the target forming process, data-guided lubricant testing and mechanism-based accurate theoretical modelling, enabling the development of data-centric lubricant limit diagrams and intuitive and quantitative evaluation of the lubricant performance.

Quantifying Wetting Dynamics with Triboelectrification.

Wetting is often perceived as an intrinsic surface property of materials, but determining its evolution is complicated by its complex dependence on roughness across the scales. The Wenzel (W) state, where liquids have intimate contact with the rough surfaces, and the Cassie-Baxter (CB) state, where liquids sit onto air pockets formed between asperities, are only two states among the plethora of wetting behaviors. Furthermore, transitions from the CB to the Wenzel state dictate completely different surface performance, such as anti-contamination, anti-icing, drag reduction etc.; however, little is known about how transition occurs during time between the several wetting modes. In this paper, wetting dynamics can be accurately quantified and tracked using solid-liquid triboelectrification. Theoretical underpinning reveals how surface micro-/nano-geometries regulate stability/infiltration, also demonstrating the generality of the authors' theoretical approach in understanding wetting transitions. It can clarify the functioning behavior of materials in real environment.

On the microstructurally driven heterogeneous response of brain white matter to drug infusion pressure.

Delivering therapeutic agents into the brain via convection-enhanced delivery (CED), a mechanically controlled infusion method, provides an efficient approach to bypass the blood-brain barrier and deliver drugs directly to the targeted focus in the brain. Mathematical methods based on Darcy's law have been widely adopted to predict drug distribution in the brain to improve the accuracy and reduce the side effects of this technique. However, most of the current studies assume that the hydraulic permeability and porosity of brain tissue are homogeneous and constant during the infusion process, which is less accurate due to the deformability of the axonal structures and the extracellular matrix in brain white matter. To solve this problem, a multiscale model was established in this study, which takes into account the pressure-driven deformation of brain microstructure to quantify the change of local permeability and porosity. The simulation results were corroborated using experiments measuring hydraulic permeability in ovine brain samples. Results show that both hydraulic pressure and drug concentration in the brain would be significantly underestimated by classical Darcy's law, thus highlighting the great importance of the present multiscale model in providing a better understanding of how drugs transport inside the brain and how brain tissue responds to the infusion pressure. This new method can assist the development of both new drugs for brain diseases and preoperative evaluation techniques for CED surgery, thus helping to improve the efficiency and precision of treatments for brain diseases.

Slip and stress from low shear rate nonequilibrium molecular dynamics: The transient-time correlation function technique.

We derive the transient-time correlation function (TTCF) expression for the computation of phase variables of inhomogenous confined atomistic fluids undergoing boundary-driven planar shear (Couette) flow at constant pressure. Using nonequilibrium molecular dynamics simulations, we then apply the TTCF formalism to the computation of the shear stress and the slip velocity for atomistic fluids at realistic low shear rates, in systems under constant pressure and constant volume. We show that, compared to direct averaging of multiple trajectories, the TTCF method dramatically improves the accuracy of the results at low shear rates and that it is suitable to investigate the tribology and rheology of atomistically detailed confined fluids at realistic flow rates.

The Intrinsic Fragility of the Liquid-Vapor Interface: A Stress Network Perspective.

The evolution of the liquid-vapor interface of a Lennard-Jones fluid is examined with molecular dynamics simulations using the intrinsic sampling method. Results suggest clear damping of the intrinsic profiles with increasing temperature. Investigating the surface stress distribution, we have identified a linear variation of the space-filling nature (fractal dimension) of the stress clusters at the intrinsic surface with increasing surface tension or, equivalently, with decreasing temperature. A percolation analysis of these stress networks indicates that the stress field is more disjointed at higher temperatures. This leads to more fragile (or poorly connected) interfaces which result in a reduction in surface tension.