Browsing by Author "Royse, Madison K."

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    A 3D printable perfused hydrogel vascular model to assay ultrasound-induced permeability
    (Royal Society of Chemistry, 2022) Royse, Madison K.; Means, A. Kristen; Calderon, Gisele A.; Kinstlinger, Ian S.; He, Yufang; Durante, Marc R.; Procopio, Adam T.; Veiseh, Omid; Xu, Jun; Bioengineering
    The development of an in vitro model to study vascular permeability is vital for clinical applications such as the targeted delivery of therapeutics. This work demonstrates the use of a perfusion-based 3D printable hydrogel vascular model as an assessment for endothelial permeability and its barrier function. Aside from providing a platform that more closely mimics the dynamic vascular conditions in vivo, this model enables the real-time observation of changes in the endothelial monolayer during the application of ultrasound to investigate the downstream effect of ultrasound-induced permeability. We show an increase in the apparent permeability coefficient of a fluorescently labeled tracer molecule after ultrasound treatment via a custom MATLAB algorithm, which implemented advanced features such as edge detection and a dynamic region of interest, thus supporting the use of ultrasound as a non-invasive method to enhance vascular permeability for targeted drug therapies. Notably, live-cell imaging with VE-cadherin-GFP HUVECs provides some of the first real-time acquisitions of the dynamics of endothelial cell–cell junctions under the application of ultrasound in a 3D perfusable model. This model demonstrates potential as a new scalable platform to investigate ultrasound-assisted delivery of therapeutics across a cellular barrier that more accurately mimics the physiologic matrix and fluid dynamics.
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    Development of a 3D printable in vitro vascular model for therapeutic applications
    (2022-08-08) Royse, Madison K.; Veiseh, Omid
    The process of drug discovery and development is long and costly, often resulting in limited or expensive treatment options for patients. The translation of drug candidates and therapeutic strategies from preclinical screening to clinical studies is a substantial hurdle in the field and has underscored the need for technologies that can accurately predict therapeutic outcomes in vitro before translation to clinical studies. Recent advances in 3D printing have enabled the fabrication of in vitro models that more accurately recapitulate physiologic forces and material composition in comparison to traditional in vitro methods such as 2D cell culture and microfluidic devices. Here, we demonstrate the development of a 3D-printed perfusable gelatin-based hydrogel as an in vitro vascular model for screening therapeutics in an accelerated and cost-effective manner. Biocompatible hydrogels of gelatin methacrylate (GelMA) and poly(ethylene glycol) diacrylate (PEGDA) with hollow vascular architectures were fabricated via projection stereolithography, endothelialized with human umbilical vein endothelial cells (HUVECs), and subjected to fluid flow with varying biochemical stimuli to promote endothelial maturation and stability. The ability of these endothelialized channels to respond to external barrier-disrupting stimuli was validated by showing a significant increase in vascular permeability after ultrasound treatment, demonstrating the utility of this model in assessing therapeutic strategies targeting vasculature. Finally, this model was adapted to recreate the highly restrictive vasculature of the central nervous system, the blood-brain barrier (BBB), via incorporation of human brain microvascular endothelial cells, human brain microvascular pericytes, and human brain astrocytes. The presence of essential blood-brain barrier junctional complexes and transporters were confirmed, and pilot work demonstrated the capacity of this in vitro BBB model to be used as a tool for evaluating the transport of therapeutics across the blood-brain barrier. This 3D printed perfusable vascular model offers an alternative route to assess vascular-focused therapies, providing a preclinical model that bridges less physiologic in vitro methods and more complex, costly in vivo animal studies.
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    Development of an automated biomaterial platform to study mosquito feeding behavior
    (Frontiers Media S.A., 2023) Janson, Kevin D.; Carter, Brendan H.; Jameson, Samuel B.; de Verges, Jane E.; Dalliance, Erika S.; Royse, Madison K.; Kim, Paul; Wesson, Dawn M.; Veiseh, Omid; Bioengineering
    Mosquitoes carry a number of deadly pathogens that are transmitted while feeding on blood through the skin, and studying mosquito feeding behavior could elucidate countermeasures to mitigate biting. Although this type of research has existed for decades, there has yet to be a compelling example of a controlled environment to test the impact of multiple variables on mosquito feeding behavior. In this study, we leveraged uniformly bioprinted vascularized skin mimics to create a mosquito feeding platform with independently tunable feeding sites. Our platform allows us to observe mosquito feeding behavior and collect video data for 30–45 min. We maximized throughput by developing a highly accurate computer vision model (mean average precision: 92.5%) that automatically processes videos and increases measurement objectivity. This model enables assessment of critical factors such as feeding and activity around feeding sites, and we used it to evaluate the repellent effect of DEET and oil of lemon eucalyptus-based repellents. We validated that both repellents effectively repel mosquitoes in laboratory settings (0% feeding in experimental groups, 13.8% feeding in control group, p < 0.0001), suggesting our platform’s use as a repellent screening assay in the future. The platform is scalable, compact, and reduces dependence on vertebrate hosts in mosquito research.