Surface acoustic waves induced micropatterning of cells in gelatin methacryloyl (GelMA) hydrogels

Acoustic force patterning is an emerging technology that provides a platform to control the spatial location of cells in a rapid, accurate, yet contactless manner. However, very few studies have been reported on the usage of acoustic force patterning for the rapid arrangement of biological objects, such as cells, in a three-dimensional (3D) environment. In this study, we report on a bio-acoustic force patterning technique, which uses surface acoustic waves (SAWs) for the rapid arrangement of cells within an extracellular matrix-based hydrogel such as gelatin methacryloyl (GelMA). A proof-of-principle was achieved through both simulations and experiments based on the in-house fabricated piezoelectric SAW transducers, which enabled us to explore the effects of various parameters on the performance of the built construct. The SAWs were applied in a fashion that generated standing SAWs (SSAWs) on the substrate, the energy of which subsequently was transferred into the gel, creating a rapid, and contactless alignment of the cells (<10 s, based on the experimental conditions). Following ultraviolet radiation induced photo-crosslinking of the cell encapsulated GelMA pre-polymer solution, the patterned cardiac cells readily spread after alignment in the GelMA hydrogel and demonstrated beating activity in 5–7 days. The described acoustic force assembly method can be utilized not only to control the spatial distribution of the cells inside a 3D construct, but can also preserve the viability and functionality of the patterned cells (e.g. beating rates of cardiac cells). This platform can be potentially employed in a diverse range of applications, whether it is for tissue engineering, in vitro cell studies, or creating 3D biomimetic tissue structures

Unidirectional brain-computer interface: Artificial neural network encoding natural images to fMRI response in the visual cortex

While significant advancements in artificial intelligence (AI) have catalyzed progress across various domains, its full potential in understanding visual perception remains underexplored. We propose an artificial neural network dubbed VISION, an acronym for "Visual Interface System for Imaging Output of Neural activity," to mimic the human brain and show how it can foster neuroscientific inquiries. Using visual and contextual inputs, this multimodal model predicts the brain's functional magnetic resonance imaging (fMRI) scan response to natural images. VISION successfully predicts human hemodynamic responses as fMRI voxel values to visual inputs with an accuracy exceeding state-of-the-art performance by 45%. We further probe the trained networks to reveal representational biases in different visual areas, generate experimentally testable hypotheses, and formulate an interpretable metric to associate these hypotheses with cortical functions. With both a model and evaluation metric, the cost and time burdens associated with designing and implementing functional analysis on the visual cortex could be reduced. Our work suggests that the evolution of computational models may shed light on our fundamental understanding of the visual cortex and provide a viable approach toward reliable brain-machine interfaces

Surface acoustic waves induced micropatterning of cells in gelatin methacryloyl (GelMA) hydrogels

Acoustic force patterning is an emerging technology that provides a platform to control the spatial location of cells in a rapid, accurate, yet contactless manner. However, very few studies have been reported on the usage of acoustic force patterning for the rapid arrangement of biological objects, such as cells, in a three-dimensional (3D) environment. In this study, we report on a bio-acoustic force patterning technique, which uses surface acoustic waves (SAWs) for the rapid arrangement of cells within an extracellular matrix-based hydrogel such as gelatin methacryloyl (GelMA). A proof-of-principle was achieved through both simulations and experiments based on the in-house fabricated piezoelectric SAW transducers, which enabled us to explore the effects of various parameters on the performance of the built construct. The SAWs were applied in a fashion that generated standing SAWs (SSAWs) on the substrate, the energy of which subsequently was transferred into the gel, creating a rapid, and contactless alignment of the cells (<10 s, based on the experimental conditions). Following ultraviolet radiation induced photo-crosslinking of the cell encapsulated GelMA pre-polymer solution, the patterned cardiac cells readily spread after alignment in the GelMA hydrogel and demonstrated beating activity in 5-7 days. The described acoustic force assembly method can be utilized not only to control the spatial distribution of the cells inside a 3D construct, but can also preserve the viability and functionality of the patterned cells (e.g. beating rates of cardiac cells). This platform can be potentially employed in a diverse range of applications, whether it is for tissue engineering, in vitro cell studies, or creating 3D biomimetic tissue structures

A computational and experimental study inside microfluidic systems: the role of shear stress and flow recirculation in cell docking

Abstract In this paper, microfluidic devices containing microwells that enabled cell docking were investigated. We theoretically assessed the effect of geometry on recirculation areas and wall shear stress patterns within microwells and studied the relationship between the computational predictions and experimental cell docking. We used microchannels with 150 μm diameter microwells that had either 20 or 80 μm thickness. Flow within 80 μm deep microwells was subject to extensive recirculation areas and low shear stresses (&lt;0.5 mPa) near the well base; whilst these were only presented within a 10 μm peripheral ring in 20 μm thick microwells. We also experimentally demonstrated that cell docking was significantly higher (p&lt;0.01) in 80 μm thick microwells as compared to 20 μm thick microwells. Finally, a computational tool which correlated physical and geometrical parameters of microwells with their fluid dynamic environment was developed and was also experimentally confirmed

Expert recommendations on the assessment of wall shear stress in human coronary arteries : existing methodologies, technical considerations, and clinical applications

The aim of this manuscript is to provide guidelines for appropriate use of CFD to obtain reproducible and reliable wall shear stress maps in native and instrumented human coronary arteries. The outcome of CFD heavily depends on the quality of the input data, which include vessel geometrical data, proper boundary conditions, and material models. Available methodologies to reconstruct coronary artery anatomy are discussed in ‘Imaging coronary arteries: a brief review’ section. Computational procedures implemented to simulate blood flow in native coronary arteries are presented in ‘Wall shear stress in native arteries’ section. The effect of including different geometrical scales due to the presence of stent struts in instrumented arteries is highlighted in ‘Wall shear stress in stents’ section. The clinical implications are discussed in ‘Clinical applications’ section, and concluding remarks are presented in ‘Concluding remarks’ section

Smart Grid Adaptive Volt-VAR Optimization in Distribution Networks

The electrical distribution networks across the world are witnessing a steady infusion of smart grid technologies into every aspect of their infrastructure and operations. Technologies such as Energy Management Systems (EMS), Distribution Management Systems (DMS) and Advanced Metering Infrastructure (AMI) have partially addressed the needs of the distribution networks for automation, control, monitoring and optimization. Many utilities intend to explore the capabilities of advanced AMI systems for other functionalities within their grids. AMI systems produce an extensive amount of data that can be collected from termination points, for various optimization, control and energy conservation functions. Moreover, deployment of smart grid assets and smart system utilizations provide unprecedented opportunities for network operators and planners to adopt more efficient and reliable strategies for the technical/economic issues of their grids. Accordingly, new smart grid adaptive optimization and control techniques can be constituent components of future distribution grids. The present thesis aims to propose a novel smart grid adaptive solution for one of the well-known techniques typically employed for distribution network voltage and reactive power optimization called Volt-VAR Optimization (VVO). Proposed VVO engine enables capturing AMI data to solve the VVO problem through its comprehensive objective function in quasi real-time intervals. Furthermore, this thesis investigates the impacts of disparate smart grid components such as Distributed Generation (DGs), Electric Vehicles (EVs) and Distributed Energy Resources (DERs) on proposed smart grid adaptive VVO. Solving maintenance scheduling problem of Volt-VAR Control Components (VVCCs), proposing a new solution for VVCC number of switching per day issue, offering a quasi-real-time load modeling approach to enhance the accuracy of energy conservation calculations, presenting a predictive VVO solution and considering Conservation Voltage Reduction (CVR) as a part of VVO objective to save the energy consumption of loads are some of the novel VVO studies presented in this thesis. This thesis examines proposed VVO performance and applicability through a real-time co-simulation platform using advanced communication protocols/standards such as DNP3 and IEC 61850. The results of thesis studies prove that applying proposed VVO engine could considerably enhance smart distribution system levels of accuracy, efficiency and reliability

Characterization of Common Cartoid Artery Geometry and its Impact on Velocity Profile Shape

Clinical and engineering studies of carotid artery disease typically assume that the common carotid artery (CCA), proximal to the bifurcation, is relatively straight enough to assume fully-developed flow. However, a recent study from our group (Ford et al) showed the surprising presence, in vivo, of strongly skewed velocity profiles in mildly curved CCAs. In this thesis we aim to understand how CCA geometry affects velocity profile skewing. The left and right normal CCAs of 32 participants (62±13 yrs), randomly chosen from NIH’s VALIDATE study (N~450) were digitally segmented from aortic root to bifurcation. It was shown that each segmented CCA could be divided into nominal cervical and thoracic region and that each region could be approximated by planar circular arches. Subsequent CFD simulations of CCA parametric models suggested strong velocity profile skewing both at the inlet and outlet of cervical segment and the effect of various geometric parameters were investigated.MAS

On the Development of a 2MHz Radial Imaging Ultrasound Array for Potential Use in Guiding Pedicle Screw Insertion

Spinal fusion surgeries often require the insertion of screw implants into the pedicle bone. Although the procedure is somewhat routine, there is an inherent error rate when surgeons employ manual feedback techniques in the operating room. An alternative image guidance technique to reduce the error rate is an ultrasound transducer, which could be incorporated with the surgical toolkit to image the pedicle bone from within. This allows for real-time, non-radiating visualization of the anatomy and bone boundaries relative to the tip of the toolkit. The primary objective of this thesis is to describe the design and fabrication of 2MHz ultrasound probes for pedicle screw guidance. Three single-element transducer designs (3.5mm diameter) are explored in order to arrive at an acoustic design (backing, active, matching layer) that enables intra-pedicular imaging. To eliminate the need for manual rotation of the transducer, we have successfully designed and fabricated a 2MHz radial array that consists of 32 elements (3.2mm outer diameter). Using a commercial platform, we have obtained radial images from successive groupings of four array elements, when the array was placed in various fluids. Although this work has not demonstrated intra-pedicular imaging, we believe that it represents an important step in this direction. A secondary objective of this work is to investigate the directionality distribution in the pedicle's trabecular bone. This stems from the need to better understand the manner in which it can affect ultrasound propagation. In this thesis, we have estimated the direction distribution of pedicle trabecular bone from micro-CT images using Gabor filters. The Gabor filter was tested for suitability in detecting trabecular structures first through simulated 2-D line tests then through 3-D bone models. When applied to micro-CT images of six human pedicle bones, the final results are an estimation of the main directions of trabecular structures in both the coronal and sagittal planes. However, since the pedicles tested were from just one cadaver, more general conclusions cannot be drawn concerning the directionality distribution. Nonetheless, a reliable quantitative method has been developed that should have considerable potential in a variety of applications.Ph.D