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Probing the Influence of Cx43 and Glucose on Endothelial Biomechanics
Title
Probing the Influence of Cx43 and Glucose on Endothelial Biomechanics.
Creator
Islam, Md Mydul, Steward, Robert, Kassab, Alain, Mansy, Hansen, Willenberg, Bradley, University of Central Florida
Abstract / Description
Endothelial cells (ECs) form the innermost layer of all vasculature and constantly receive both biochemical and biomechanical signals, yielding a plethora of biomechanical responses. In response to various biochemical or biomechanical cues, ECs have been documented to generate biomechanical responses such as tractions and intercellular stresses between the cell and substrate and between adjacent cells in a confluent monolayer, respectively. Thus far, the ability of endothelial tight junctions...
Show moreEndothelial cells (ECs) form the innermost layer of all vasculature and constantly receive both biochemical and biomechanical signals, yielding a plethora of biomechanical responses. In response to various biochemical or biomechanical cues, ECs have been documented to generate biomechanical responses such as tractions and intercellular stresses between the cell and substrate and between adjacent cells in a confluent monolayer, respectively. Thus far, the ability of endothelial tight junctions and adherens junctions to transmit intercellular stresses has been actively investigated, but the role of gap junctions is currently unknown. In addition, there is no report of the independent influence of hyperglycemia on endothelial biomechanics present in the literature. To fill these gaps, we conducted a two-fold study where we investigated the influence of endothelial gap junction Cx43 and hyperglycemia in endothelial tractions and intercellular stress generation. In the first study, we selectively disrupted and enhanced EC gap junction Cx43 by using 2',5'-dihydroxychalcone and retinoic acid, respectively and in the second study, we cultured ECs in both normal glucose and hyperglycemic condition for 10 days. In both studies, tractions and intercellular stresses were calculated using traction force microscopy (TFM) and monolayer stress microscopy (MSM), respectively. Our results reveal that Cx43 downregulation increased as well as decreased endothelial avg. normal intercellular stresses in response to a low (0.83 (&)#181;M) and a high dose (8.3 (&)#181;M) chalcone treatment, respectively, while Cx43 upregulation decreases avg. normal intercellular stresses in both treatment conditions (2.5 (&)#181;M and 25 (&)#181;M) compared to control. In addition, we observed a decrease in intercellular stresses with hyperglycemic condition compared to control. The results we present here represent, for the first time, detailed and comprehensive biomechanical analysis of endothelial cells under the influence of glucose and the gap junction Cx43. We believe our results will provide valuable insights into endothelial permeability, barrier strength as well as leading to a greater understanding of overall endothelial mechanics.
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Date Issued
2019
Identifier
CFE0007819, ucf:52805
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0007819
Task Focused Robotic Imitation Learning
Title
Task Focused Robotic Imitation Learning.
Creator
Abolghasemi, Pooya, Boloni, Ladislau, Sukthankar, Gita, Shah, Mubarak, Willenberg, Bradley, University of Central Florida
Abstract / Description
For many years, successful applications of robotics were the domain of controlled environments, such as industrial assembly lines. Such environments are custom designed for the convenience of the robot and separated from human operators. In recent years, advances in artificial intelligence, in particular, deep learning and computer vision, allowed researchers to successfully demonstrate robots that operate in unstructured environments and directly interact with humans. One of the major...
Show moreFor many years, successful applications of robotics were the domain of controlled environments, such as industrial assembly lines. Such environments are custom designed for the convenience of the robot and separated from human operators. In recent years, advances in artificial intelligence, in particular, deep learning and computer vision, allowed researchers to successfully demonstrate robots that operate in unstructured environments and directly interact with humans. One of the major applications of such robots is in assistive robotics. For instance, a wheelchair mounted robotic arm can help disabled users in the performance of activities of daily living (ADLs) such as feeding and personal grooming. Early systems relied entirely on the control of the human operator, something that is difficult to accomplish by a user with motor and/or cognitive disabilities. In this dissertation, we are describing research results that advance the field of assistive robotics. The overall goal is to improve the ability of the wheelchair / robotic arm assembly to help the user with the performance of the ADLs by requiring only high-level commands from the user. Let us consider an ADL involving the manipulation of an object in the user's home. This task can be naturally decomposed into two components: the movement of the wheelchair in such a way that the manipulator can conveniently grasp the object and the movement of the manipulator itself. This dissertation we provide an approach for addressing the challenge of finding the position appropriate for the required manipulation. We introduce the ease-of-reach score (ERS), a metric that quantifies the preferences for the positioning of the base while taking into consideration the shape and position of obstacles and clutter in the environment. As the brute force computation of ERS is computationally expensive, we propose a machine learning approach to estimate the ERS based on features and characteristics of the obstacles. This dissertation addresses the second component as well, the ability of the robotic arm to manipulate objects. Recent work in end-to-end learning of robotic manipulation had demonstrated that a deep learning-based controller of vision-enabled robotic arms can be thought to manipulate objects from a moderate number of demonstrations. However, the current state of the art systems are limited in robustness to physical and visual disturbances and do not generalize well to new objects. We describe new techniques based on task-focused attention that show significant improvement in the robustness of manipulation and performance in clutter.
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Date Issued
2019
Identifier
CFE0007771, ucf:52392
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0007771
Development of a Functional In Vitro 3D Model of the Peripheral Nerve
Title
Development of a Functional In Vitro 3D Model of the Peripheral Nerve.
Creator
Anderson, Wesley, Lambert, Stephen, Hickman, James, Fernandez-Valle, Cristina, Willenberg, Bradley, University of Central Florida
Abstract / Description
Peripheral neuropathies, affect approximately 20 million people in the United States and are often a complication of conditions such as diabetes that can result in amputation of affected areas such as the feet and toes. In vitro methodologies to facilitate the understanding and treatment of these disorders often lack the cellular and functional complexity required to accurately model peripheral neuropathies. In particular, they are often 2-D and functional readouts, such as electrical...
Show morePeripheral neuropathies, affect approximately 20 million people in the United States and are often a complication of conditions such as diabetes that can result in amputation of affected areas such as the feet and toes. In vitro methodologies to facilitate the understanding and treatment of these disorders often lack the cellular and functional complexity required to accurately model peripheral neuropathies. In particular, they are often 2-D and functional readouts, such as electrical activity, are limited to cell bodies thereby limiting the understanding of axonopathy which often characterizes these disorders. We have developed a functional 3-D model of peripheral nerves using a capillary alginate gel (Capgel(TM)), as a scaffold. We hypothesize that: 1) The unique microcapillary structure of Capgel(TM) allows for the modeling of the 3-D microstructure of the peripheral nerve, and 2) That axon bundling in the capillary allows for the detection of axonal electrical activity. In our initial studies, we demonstrate that culturing embryonic dorsal root ganglia (DRG) within the Capgel(TM) environment allows for the separation of cell bodies from axons and recreates many of the features of an in vivo peripheral nerve fascicle including myelinated axons and the formation of a rudimentary perineurium. To develop functionality for this model we have integrated the DRG Capgel(TM) culture with a microelectrode array to examine spontaneous activity in axon bundles, which we find demonstrates superiority to other widely used 2-D models of the same tissue. Furthermore, by analyzing the activity on individual electrodes, we were able to record action potentials from multiple axons within the same bundle indicating a functional complexity comparable to that observed in fascicles in vivo. This 3D model of the peripheral nerve can be used to study the functional complexities of peripheral neuropathies and nerve regeneration as well as being utilized in the development of novel therapeutics.
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Date Issued
2018
Identifier
CFE0007150, ucf:52303
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0007150