Treatment for middle cerebral artery bifurcation aneurysms: in silico comparison of the novel Contour device and conventional flow-diverters.

Endovascular treatment has become the standard therapy for cerebral aneurysms, while the effective treatment for middle cerebral artery (MCA) bifurcation aneurysms remains a challenge. Current flow-diverting techniques with endovascular coils cover the aneurysm orifice as well as adjacent vessel branches, which may lead to branch occlusion. Novel endovascular flow disruptors, such as the Contour device (Cerus Endovascular), are of great potential to eliminate the risk of branch occlusion. However, there is a lack of valid comparison between novel flow disruptors and conventional (intraluminal) flow-diverters. In this study, two in silico MCA bifurcation aneurysm models were treated by specific Contour devices and flow-diverters using fast-deployment algorithms. Computational fluid dynamic simulations were used to examine the performance and efficiency of deployed devices. Hemodynamic parameters, including aneurysm inflow and wall shear stress, were compared among each Contour device, conventional flow-diverter, and untreated condition. Our results show that the placement of devices can effectively reduce the risk of aneurysm rupture, while the deployment of a Contour device causes more flow reduction than using flow-diverters (e.g. Silk Vista Baby). Besides, the Contour device presents the flow diversion capability of targeting the aneurysm neck without occluding the daughter vessel. In summary, the in silico aneurysm models presented in this study can serve as a powerful pre-planning tool for testing new treatment techniques, optimising device deployment, and predicting the performance in patient-specific aneurysm cases. Contour device is proved to be an effective treatment of MCA bifurcation aneurysms with less daughter vessel occlusion.

Role of blood flow in endothelial functionality: a review.

Endothelial cells, located on the surface of blood vessel walls, are constantly stimulated by mechanical forces from the blood flow. The mechanical forces, i.e., fluid shear stress, induced by the blood flow play a pivotal role in controlling multiple physiological processes at the endothelium and in regulating various pathways that maintain homeostasis and vascular function. In this review, research looking at different blood fluid patterns and fluid shear stress in the circulation system is summarized, together with the interactions between the blood flow and the endothelial cells. This review also highlights the flow profile as a response to the configurational changes of the endothelial glycocalyx, which is less revisited in previous reviews. The role of endothelial glycocalyx in maintaining endothelium health and the strategies for the restoration of damaged endothelial glycocalyx are discussed from the perspective of the fluid shear stress. This review provides a new perspective regarding our understanding of the role that blood flow plays in regulating endothelial functionality.

A computational study of fluid transport characteristics in the brain parenchyma of dementia subtypes.

The cerebral environment is a complex system consisting of parenchymal tissue and multiple fluids. Dementia is a common class of neurodegenerative diseases, caused by structural damages and functional deficits in the cerebral environment. In order to better understand the pathology of dementia from a cerebral fluid transport angle and provide clearer evidence that could help differentiate between dementia subtypes, such as Alzheimer's disease and vascular dementia, we conducted fluid-structure interaction modelling of the brain using a multiple-network poroelasticity model, which considers both neuropathological and cerebrovascular factors. The parenchyma was further subdivided and labelled into parcellations to obtain more localised and detailed data. The numerical results were converted to computed functional images by an in-house workflow. Different cerebral blood flow (CBF) and cerebrospinal fluid (CSF) clearance abnormalities were identified in the modelling results, when comparing Alzheimer's disease and vascular dementia. This paper presents our preliminary results as a proof of concept for a novel clinical diagnostic tool, and paves the way for a larger clinical study.

A CT-based predictive model for stent-induced vessel damage: application to type B aortic dissection.

OBJECTIVES: The distal stent-induced new entry (distal SINE) is a life-threatening device-related complication after thoracic endovascular aortic repair (TEVAR). However, risk factors for distal SINE are not fully determined, and prediction models are lacking. This study aimed to establish a predictive model for distal SINE based on the preoperative dataset. METHODS: Two hundred and six patients with Stanford type B aortic dissection (TBAD) that experienced TEVAR were involved in this study. Among them, thirty patients developed distal SINE. Pre-TEVAR morphological parameters were measured based on the CT-reconstructed configurations. Virtual post-TEVAR morphological and mechanical parameters were computed via the virtual stenting algorithm (VSA). Two predictive models (PM-1 and PM-2) were developed and presented as nomograms to help risk evaluation of distal SINE. The performance of the proposed predictive models was evaluated and internal validation was conducted. RESULTS: Machine-selected variables for PM-1 included key pre-TEVAR parameters, and those for PM-2 included key virtual post-TEVAR parameters. Both models showed good calibration in both development and validation subsamples, while PM-2 outperformed PM-1. The discrimination of PM-2 was better than PM-1 in the development subsample, with an optimism-corrected area under the curve (AUC) of 0.95 and 0.77, respectively. Application of PM-2 in the validation subsample presented good discrimination with an AUC of 0.9727. The decision curve demonstrated that PM-2 was clinically useful. CONCLUSION: This study proposed a predictive model for distal SINE incorporating the CT-based VSA. This predictive model could efficiently predict the risk of distal SINE and thus might contribute to personalized intervention planning. CLINICAL RELEVANCE STATEMENT: This study established a predictive model to evaluate the risk of distal SINE based on the pre-stenting CT dataset and planned device information. With an accurate VSA tool, the predictive model could help to improve the safety of the endovascular repair procedure. KEY POINTS: • Clinically useful prediction models for distal stent-induced new entry are still lacking, and the safety of the stent implantation is hard to guarantee. • Our proposed predictive tool based on a virtual stenting algorithm supports different stenting planning rehearsals and real-time risk evaluation, guiding clinicians to optimize the presurgical plan when necessary. • The established prediction model provides accurate risk evaluation for vessel damage, improving the safety of the intervention procedure.

A Computational Framework to Predict Calvarial Growth: Optimising Management of Sagittal Craniosynostosis.

The neonate skull consists of several bony plates, connected by fibrous soft tissue called sutures. Premature fusion of sutures is a medical condition known as craniosynostosis. Sagittal synostosis, caused by premature fusion of the sagittal suture, is the most common form of this condition. The optimum management of this condition is an ongoing debate in the craniofacial community while aspects of the biomechanics and mechanobiology are not well understood. Here, we describe a computational framework that enables us to predict and compare the calvarial growth following different reconstruction techniques for the management of sagittal synostosis. Our results demonstrate how different reconstruction techniques interact with the increasing intracranial volume. The framework proposed here can be used to inform optimum management of different forms of craniosynostosis, minimising the risk of functional consequences and secondary surgery.

Should friction losses be included in an electromechanical model of a bioinspired flapping-wing micro aerial vehicle to estimate the flight energetic requirements?

The paper aims to examine the effects of mechanical losses on the performance of a bioinspired flapping-wing micro aerial vehicle (FWMAV) and ways to mitigate them by introducing a novel electromechanical model. The mathematical model captures the effect of a DC gear motor, slider-crank, flapping-wings aerodynamics, and frictional losses. The aerodynamic loads are obtained using a quasi-steady flow model. The parameters of the flight mechanism are estimated using published experimental data which are also used to validate the mathematical model. Incorporating the flapping mechanism friction losses into the mathematical model enables capturing the physics of the problem with higher accuracy, which is not possible with simpler models. It also makes it possible to estimate the aerodynamic energetic requirements. Moreover, the model enabled evaluations of the effects of adding bioinspired elastic elements on the efficiency of the system. Although it is established through experimental studies that the addition of a bioinspired elastic element can improve system efficiency and increase lift generation, the existing mathematical models fail to model and predict such effects. It has been demonstrated that the addition of an elastic element can reduce friction losses in the system by decreasing the internal forces. Optimised parameters for a FWMAV incorporating elastic elements are also obtained.

Molecular dynamics simulation: A new way to understand the functionality of the endothelial glycocalyx.

Endothelial glycocalyx (EG) is a carbohydrate-rich layer which lines the lumen side of blood vessel walls. The EG layer is directly exposed to blood flow. The unique physiological location and its strongly coupled interaction with blood flow allow the EG layer to modulate microvascular mass transport and to sense and transmit mechanical signals from the passing blood. Molecular dynamics (MD) simulation is a computational method which focuses on atomic/molecular behavior at the microscale. The last two decades have witnessed a substantial increase in number and a broadening in scope regarding applications of MD in a wide spectrum of areas, including EG-related research. In this mini-review, MD works which solve EG-related problems and provide new insights into the functionality of EG are considered. Challenges of the MD method in EG research are articulated, and the future of MD in solving EG-related problems is also evaluated.

Virtual Flow-T Stenting for Two Patient-Specific Bifurcation Aneurysms.

The effective treatment of wide necked cerebral aneurysms located at vessel bifurcations (WNBAs) remains a significant challenge. Such aneurysm geometries have typically been approached with Y or T stenting configurations of stents and/or flow diverters, often with the addition of endovascular coils. In this study, two WNBAs were virtually treated by a novel T-stenting technique (Flow-T) with a number of braided stents and flow-diverter devices. Multiple possible device deployment configurations with varying device compression levels were tested, using fast-deployment algorithms, before a steady state computational hemodynamic simulation was conducted to examine the efficacy and performance of each scenario. The virtual fast deployment algorithm based on a linear and torsional spring analogy is used to accurately deploy nine stents in two WNBAs geometries. The devices expand from the distal to proximal side of the devices with respect to aneurysm sac. In the WNBAs modelled, all configurations of Flow-T device placement were shown to reduce factors linked with increased aneurysm rupture risk including aneurysm inflow jets and high aneurysm velocity, along with areas of flow impingement and elevated wall shear stress (WSS). The relative position of the flow-diverting device in the secondary daughter vessel in the Flow-T approach was found to have a negligible effect on overall effectiveness of the procedure in the two geometries considered. The level of interventionalist-applied compression in the braised stent that forms the other arm of the Flow-T approach was shown to impact the aneurysm inflow reduction and aneurysm flow pattern more substantially. In the Flow-T approach the relative position of the secondary daughter vessel flow-diverter device (the SVB) was found to have a negligible effect on inflow reduction, aneurysm flow pattern, or WSS distribution in both aneurysm geometries. This suggests that the device placement in this vessel may be of secondary importance. By contrast, substantially more variation in inflow reduction and aneurysm flow pattern was seen due to variations in braided stent (LVIS EVO or Baby Leo) compression at the aneurysm neck. As such we conclude that the success of a Flow-T procedure is primarily dictated by the level of compression that the interventionalist applies to the braided stent. Similar computationally predicted outcomes for both aneurysm geometries studied suggest that adjunct coiling approach taken in the clinical intervention of the second geometry may have been unnecessary for successful aneurysm isolation. Finally, the computational modelling framework proposed offers an effective planning platform for complex endovascular techniques, such as Flow-T, where the scope of device choice and combination is large and selecting the best strategy and device combination from several candidates is vital.

Understanding the Role of Endothelial Glycocalyx in Mechanotransduction via Computational Simulation: A Mini Review.

Endothelial glycocalyx (EG) is a forest-like structure, covering the lumen side of blood vessel walls. EG is exposed to the mechanical forces of blood flow, mainly shear, and closely associated with vascular regulation, health, diseases, and therapies. One hallmark function of the EG is mechanotransduction, which means the EG senses the mechanical signals from the blood flow and then transmits the signals into the cells. Using numerical modelling methods or in silico experiments to investigate EG-related topics has gained increasing momentum in recent years, thanks to tremendous progress in supercomputing. Numerical modelling and simulation allows certain very specific or even extreme conditions to be fulfilled, which provides new insights and complements experimental observations. This mini review examines the application of numerical methods in EG-related studies, focusing on how computer simulation contributes to the understanding of EG as a mechanotransducer. The numerical methods covered in this review include macroscopic (i.e., continuum-based), mesoscopic [e.g., lattice Boltzmann method (LBM) and dissipative particle dynamics (DPD)] and microscopic [e.g., molecular dynamics (MD) and Monte Carlo (MC) methods]. Accounting for the emerging trends in artificial intelligence and the advent of exascale computing, the future of numerical simulation for EG-related problems is also contemplated.

Using Sensitivity Analysis to Develop a Validated Computational Model of Post-operative Calvarial Growth in Sagittal Craniosynostosis.

Craniosynostosis is the premature fusion of one or more sutures across the calvaria, resulting in morphological and health complications that require invasive corrective surgery. Finite element (FE) method is a powerful tool that can aid with preoperative planning and post-operative predictions of craniosynostosis outcomes. However, input factors can influence the prediction of skull growth and the pressure on the growing brain using this approach. Therefore, the aim of this study was to carry out a series of sensitivity studies to understand the effect of various input parameters on predicting the skull morphology of a sagittal synostosis patient post-operatively. Preoperative CT images of a 4-month old patient were used to develop a 3D model of the skull, in which calvarial bones, sutures, cerebrospinal fluid (CSF), and brain were segmented. Calvarial reconstructive surgery was virtually modeled and two intracranial content scenarios labeled "CSF present" and "CSF absent," were then developed. FE method was used to predict the calvarial morphology up to 76 months of age with intracranial volume-bone contact parameters being established across the models. Sensitivity tests with regards to the choice of material properties, methods of simulating bone formation and the rate of bone formation across the sutures were undertaken. Results were compared to the in vivo data from the same patient. Sensitivity tests to the choice of various material properties highlighted that the defined elastic modulus for the craniotomies appears to have the greatest influence on the predicted overall skull morphology. The bone formation modeling approach across the sutures/craniotomies had a considerable impact on the level of contact pressure across the brain with minimum impact on the overall predicated morphology of the skull. Including the effect of CSF (based on the approach adopted here) displayed only a slight reduction in brain pressure outcomes. The sensitivity tests performed in this study set the foundation for future comparative studies using FE method to compare outcomes of different reconstruction techniques for the management of craniosynostosis.

Thrombin-Fibrinogen In Vitro Flow Model of Thrombus Growth in Cerebral Aneurysms.

Cerebral aneurysms are balloon-like structures that develop on weakened areas of cerebral artery walls, with a significant risk of rupture. Thrombi formation is closely associated with cerebral aneurysms and has been observed both before and after intervention, leading to a wide variability of outcomes in patients with the condition. The attempt to manage the outcomes has led to the development of various computational models of cerebral aneurysm thrombosis. In the current study, we developed a simplified thrombin-fibrinogen flow system, based on commercially available purified human-derived plasma proteins, which enables thrombus growth and tracking in an idealized cerebral aneurysm geometry. A three-dimensional printed geometry of an idealized cerebral aneurysm and parent vessel configuration was developed. An unexpected outcome was that this phantom-based flow model allowed us to track clot growth over a period of time, by using optical imaging to record the progression of the growing clot into the flow field. Image processing techniques were subsequently used to extract important quantitative metrics from the imaging dataset, such as end point intracranial thrombus volume. The model clearly demonstrates that clot formation, in cerebral aneurysms, is a complex interplay between mechanics and biochemistry. This system is beneficial for verifying computational models of cerebral aneurysm thrombosis, particularly those focusing on initial angiographic occlusion outcomes, and will also assist manufacturers in optimizing interventional device designs.

Multi-stage learning for segmentation of aortic dissections using a prior aortic anatomy simplification.

Aortic dissection (AD) is a life-threatening cardiovascular disease with a high mortality rate. The accurate and generalized 3-D reconstruction of AD from CT-angiography can effectively assist clinical procedures and surgery plans, however, is clinically unavaliable due to the lacking of efficient tools. In this study, we presented a novel multi-stage segmentation framework for type B AD to extract true lumen (TL), false lumen (FL) and all branches (BR) as different classes. Two cascaded neural networks were used to segment the aortic trunk and branches and to separate the dual lumen, respectively. An aortic straightening method was designed based on the prior vascular anatomy of AD, simplifying the curved aortic shape before the second network. The straightening-based method achieved the mean Dice scores of 0.96, 0.95 and 0.89 for TL, FL, and BR on a multi-center dataset involving 120 patients, outperforming the end-to-end multi-class methods and the multi-stage methods without straightening on the dual-lumen segmentation, even using different network architectures. Both the global volumetric features of the aorta and the local characteristics of the primary tear could be better identified and quantified based on the straightening. Comparing to previous deep learning methods dealing with AD segmentations, the proposed framework presented advantages in segmentation accuracy.

Exploring neurodegenerative disorders using a novel integrated model of cerebral transport: Initial results.

The neurovascular unit (NVU) underlines the complex and symbiotic relationship between brain cells and the cerebral vasculature, and dictates the need to consider both neurodegenerative and cerebrovascular diseases under the same mechanistic umbrella. Importantly, unlike peripheral organs, the brain was thought not to contain a dedicated lymphatics system. The glymphatic system concept (a portmanteau of glia and lymphatic) has further emphasized the importance of cerebrospinal fluid transport and emphasized its role as a mechanism for waste removal from the central nervous system. In this work, we outline a novel multiporoelastic solver which is embedded within a high precision, subject specific workflow that allows for the co-existence of a multitude of interconnected compartments with varying properties (multiple-network poroelastic theory, or MPET), that allow for the physiologically accurate representation of perfused brain tissue. This novel numerical template is based on a six-compartment MPET system (6-MPET) and is implemented through an in-house finite element code. The latter utilises the specificity of a high throughput imaging pipeline (which has been extended to incorporate the regional variation of mechanical properties) and blood flow variability model developed as part of the VPH-DARE@IT research platform. To exemplify the capability of this large-scale consolidated pipeline, a cognitively healthy subject is used to acquire novel, biomechanistically inspired biomarkers relating to primary and derivative variables of the 6-MPET system. These biomarkers are shown to capture the sophisticated nature of the NVU and the glymphatic system, paving the way for a potential route in deconvoluting the complexity associated with the likely interdependence of neurodegenerative and cerebrovascular diseases. The present study is the first, to the best of our knowledge, that casts and implements the 6-MPET equations in a 3D anatomically accurate brain geometry.

Sodium ion transport across the endothelial glycocalyx layer under electric field conditions: A molecular dynamics study.

In the present research, the sodium ion transport across the endothelial glycocalyx layer (EGL) under an imposed electric field is investigated, for the first time, using a series of molecular dynamics simulations. The electric field is perpendicularly imposed on the EGL with varying strengths. The sodium ion molarity difference between the inner and outer layers of EGL, Δc, is used to quantify the sodium transport in the presence of the negatively charged glycocalyx sugar chains. Results suggest that a weak electric field increases Δc, regardless of whether the electric field is imposed perpendicularly inward or outward. By contrast, a strong electric field drives sodium ions to travel in the same orientation as the electric field. Scrutiny of the charge distribution of the glycocalyx sugar chains suggests that the electric field modifies the spatial layouts of glycocalyx atoms as it drives the transport of sodium ions. The modification in glycocalyx layouts further changes the inter-molecular interactions between glycocalyx sugar chains and sodium ions, thereby limiting the electric field control of ion transport. The sodium ions, in turn, alter the apparent bending stiffness of glycocalyx. Moreover, the negative charges of the glycocalyx sugar chains play an important role in maintaining structural stability of endothelial glycocalyx. Based on the findings, a hypothesis is proposed regarding the existence of a strength threshold of the electric field in controlling charged particles in the endothelium, which offers an alternative explanation for contrasting results in previous experimental observations.

Finite element evaluations of the mechanical properties of polycaprolactone/hydroxyapatite scaffolds by direct ink writing: Effects of pore geometry.

Osteochondral (OC) defects usually involve the damage of both the cartilage and its underneath subchondral bone. In recent years, tissue engineering (TE) has become the most promising method that combines scaffolds, growth factors, and cells for the repair of OC defects. An ideal OC scaffold should have a gradient structure to match the hierarchical mechanical properties of natural OC tissue. To satisfy such requirements, 3D printing, e.g., direct ink writing (DIW), has emerged as a technology for precise and customized scaffold fabrication with optimized structures and mechanical properties. In this study, finite element simulations were applied to investigate the effects of pore geometry on the mechanical properties of 3D printed scaffolds. Scaffold specimens with different lay-down angles, filament diameters, inter-filament spacing, and layer overlaps were simulated in compressive loading conditions. The results showed that Young's moduli of scaffolds decreased linearly with increasing scaffold porosity. The orthotropic characteristics increased as the lay-down angle decreased from 90° to 15°. Moreover, gradient transitions within a wide range of strain magnitudes were achieved in a single construct by assembling layers with different lay-down angles. The results provide quantitative relationships between pore geometry and mechanical properties of lattice scaffolds, and demonstrate that the hierarchical mechanical properties of natural OC tissue can be mimicked by tuning the porosity and local lay-down angles in 3D printed scaffolds.

Principal mode of Syndecan-4 mechanotransduction for the endothelial glycocalyx is a scissor-like dimer motion.

AIM: Endothelial glycocalyx (EG) plays a pivotal role in a plethora of diseases, like cardiovascular and renal diseases. One hallmark function of the EG as a mechanotransducer which transmits mechanical signals into cytoplasm has been documented for decades. However, the basic question - how the glycocalyx transmits the flow shear stress- is unanswered so far. Our aim is to shed light on the fundamental mode of signal transmission from flow to the endothelial cytoskeleton. METHODS: We conduct a series of large-scale molecular dynamics computational experiments to investigate the dynamics of glycocalyx under varying conditions (changing blood flow velocities and shedding of glycocalyx sugar chains). RESULTS: We have identified that the main pathway of signal transmission in this system manifests as a scissors-like motion of the Syndecan-4 core protein. Results have suggested that the force transmitted into the cytoskeleton with an order of 10 ~ 100 pN, and the main function of sugar chains of a glycocalyx element is to protect the core proteins from severe conformational changes thereby maintaining the functionality of the EG. CONCLUSION: This research provides a reconciling explanation for a longstanding debate about the force transmission threshold based on our findings. A new explanation has also been provided to relate the role of the EG as a mechanotransducer to its function as a microvascular barrier: the EG regulates the mechanotransduction by altering the median value and variation range of the scissor angle, and the EG governs the microvascular barrier via controlling the scissor angle which will affect the intercellular cleft.

Membrane Deformation of Endothelial Surface Layer Interspersed with Syndecan-4: A Molecular Dynamics Study.

The lipid membrane of endothelial cells plays a pivotal role in maintaining normal circulatory system functions. To investigate the response of the endothelial cell membrane to changes in vascular conditions, an atomistic model of the lipid membrane interspersed with Syndecan-4 core protein was established based on experimental observations and a series of molecular dynamics simulations were undertaken. The results show that flow results in continuous deformation of the lipid membrane, and the degree of membrane deformation is not in monotonic relationship with the environmental changes (either the changes in blood velocity or the alteration of the core protein configuration). An explanation for such non-monotonic relationship is provided, which agrees with previous experimental results. The elevation of the lipid membrane surface around the core protein of the endothelial glycocalyx was also observed, which can be mainly attributed to the Coulombic interactions between the biomolecules therein. The present study demonstrates that the blood flow can deform the lipid membrane directly via the interactions between water molecules and lipid membrane atoms thereby affecting mechanosensing; it also presents an additional force transmission pathway from the flow to the lipid membrane via the glycocalyx core protein, which complements previous mechanotransduction hypothesis.

On the Validation of a Multiple-Network Poroelastic Model Using Arterial Spin Labeling MRI Data.

The Multiple-Network Poroelastic Theory (MPET) is a numerical model to characterize the transport of multiple fluid networks in the brain, which overcomes the problem of conducting separate analyses on individual fluid compartments and losing the interactions between tissue and fluids, in addition to the interaction between the different fluids themselves. In this paper, the blood perfusion results from MPET modeling are partially validated using cerebral blood flow (CBF) data obtained from arterial spin labeling (ASL) magnetic resonance imaging (MRI), which uses arterial blood water as an endogenous tracer to measure CBF. Two subjects-one healthy control and one patient with unilateral middle cerebral artery (MCA) stenosis are included in the validation test. The comparison shows several similarities between CBF data from ASL and blood perfusion results from MPET modeling, such as higher blood perfusion in the gray matter than in the white matter, higher perfusion in the periventricular region for both the healthy control and the patient, and asymmetric distribution of blood perfusion for the patient. Although the partial validation is mainly conducted in a qualitative way, it is one important step toward the full validation of the MPET model, which has the potential to be used as a testing bed for hypotheses and new theories in neuroscience research.

Microvascular ion transport through endothelial glycocalyx layer: new mechanism and improved Starling principle.

Ion transport through the endothelial glycocalyx layer is closely associated with many vascular diseases. Clarification of ion behaviors around the endothelial glycocalyx layer under varying circumstances will benefit pathologies related to cardiovascular and renal diseases. In this research, a series of large-scale molecular dynamics simulations are conducted to study the response of ion transport to the changing blood flow velocity and the shedding of endothelial glycocalyx sugar chains. Results indicate that blood flow promotes the outward Na+ transport from the near-membrane region to the lumen via the endothelial glycocalyx layer. Scrutiny of sugar-chain dynamics and their interactions with Na+ suggests that corner conformation of endothelial glycocalyx sugar chains confines the movement of the Na+, whereas stretching conformation facilitates the motion of Na+ ions. The flow impact on ion transport of Na+ is nonlinear. Based on the findings, the Starling principle and its revised version, which are prevailingly used to predict the ion transport of the endothelial glycocalyx layer, are further improved. An estimation based on the further revised Starling principle indicates that physiological flow changes the osmotic part of transendothelial water flux by 8% compared with the stationary situation. NEW & NOTEWORTHY The biophysical roles of negatively charged oligosaccharides of the endothelial glycocalyx have gained increasing attention due to their importance in regulating microvascular fluid exchange. The Starling principle and its revisions are at the heart of the understanding of fluid homeostasis in the periphery. Here, the blood flow changes the conformations of glycocalyx sugar chains, thereby influencing availability of Na+ for transport. Based on the findings, the Starling principle and its revision are further improved.

Effect of the Mixing Region Geometry and Collector Distance on Microbubble Formation in a Microfluidic Device Coupled with ac-dc Electric Fields.

In this work, we report a significant advance in the preparation of monodisperse microbubbles using a combination of microfluidic and electric field technologies. Microbubbles have been employed in various fields such as biomedical engineering, water purification, and food engineering. Many techniques have been investigated for their preparation. Of these, the microfluidic T-junction has shown great potential because of the high degree of control it has over processing parameters and the ability to produce monodisperse microbubbles. Two main lines of investigation were conducted in this work-the effect of varying the mixing region distance (Mx) and the influence of altering the tip-to-collector distance (Dx) when an ac-dc field is applied. It was found that when Mx was decreased from 200 to 100 µm, the microbubble diameter also decreased from 128 ± 3 to 88 ± 5 µm due to an increase in shear stress as a result of a reduction in surface area. Similarly, decreasing the tip-to-collector distance results in an increase in the electric field strength experienced at the nozzle, facilitating further reduction of the bubble diameter from 111 ± 1 to 86 ± 1 µm at an ac voltage of 6 kV P-P and an applied dc voltage of 6 kV. Experiments conducted with the optimal parameters identified from these previous experiments enabled further reduction of the microbubble diameter to 18 ± 2 µm. These results suggest that a unique combination of parameters can be employed to achieve particular microbubble diameters to suit various applications.