A. James Clark School of Engineering

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The collections in this community comprise faculty research works, as well as graduate theses and dissertations.

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Subject: search.filters.subject.inflammation

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Now showing 1 - 6 of 6
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    Combinatorial microRNA Loading into Extracellular Vesicles for Increased Anti-Inflammatory Efficacy
    (MDPI, 2022-10-21) Pottash, Alex Eli; Levy, Daniel; Jeyaram, Anjana; Kuo, Leo; Kronstadt, Stephanie M.; Chao, Wei; Jay, Steven M.
    Extracellular vesicles (EVs) have emerged as promising therapeutic entities in part due to their potential to regulate multiple signaling pathways in target cells. This potential is derived from the broad array of constituent and/or cargo molecules associated with EVs. Among these, microRNAs (miRNAs) are commonly implicated as important and have been associated with a wide variety of EV-induced biological phenomena. While controlled loading of single miRNAs is a well-documented approach for enhancing EV bioactivity, loading of multiple miRNAs has not been fully leveraged to maximize the potential of EV-based therapies. Here, an established approach to extrinsic nucleic acid loading of EVs, sonication, was utilized to load multiple miRNAs in HEK293T EVs. Combinations of miRNAs were compared to single miRNAs with respect to anti-inflammatory outcomes in assays of increasing stringency, with the combination of miR-146a, miR-155, and miR-223 found to have the most potential amongst the tested groups.
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    Induced Pluripotent Stem Cell-Derived Extracellular Vesicles Promote Wound Repair in a Diabetic Mouse Model via an Anti-Inflammatory Immunomodulatory Mechanism
    (Wiley, 2023-06-19) Levy, Daniel; Abadchi, Sanaz Nourhammadi; Shababi, Niloufar; Ravari, Mohsen Rouhani; Pirolli, Nicholas H.; Bergeron, Cade; Obiorah, Angel; Mokhtari-Esbuie, Farzad; Gheshlaghi, Shayan; Abraham, John M.; Smith, Ian M.; Powsner, Emily H.; Solomon, Talia J.; Harmon, John W.; Jay, Steven M.
    Extracellular vesicles (EVs) derived from mesenchymal stem/stromal cells (MSCs) have recently been explored in clinical trials for treatment of diseases with complex pathophysiologies. However, production of MSC EVs is currently hampered by donor-specific characteristics and limited ex vivo expansion capabilities before decreased potency, thus restricting their potential as a scalable and reproducible therapeutic. Induced pluripotent stem cells (iPSCs) represent a self-renewing source for obtaining differentiated iPSC-derived MSCs (iMSCs), circumventing both scalability and donor variability concerns for therapeutic EV production. Thus, it is initially sought to evaluate the therapeutic potential of iMSC EVs. Interestingly, while utilizing undifferentiated iPSC EVs as a control, it is found that their vascularization bioactivity is similar and their anti-inflammatory bioactivity is superior to donor-matched iMSC EVs in cell-based assays. To supplement this initial in vitro bioactivity screen, a diabetic wound healing mouse model where both the pro-vascularization and anti-inflammatory activity of these EVs would be beneficial is employed. In this in vivo model, iPSC EVs more effectively mediate inflammation resolution within the wound bed. Combined with the lack of additional differentiation steps required for iMSC generation, these results support the use of undifferentiated iPSCs as a source for therapeutic EV production with respect to both scalability and efficacy.
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    Strategies for small RNA loading into extracellular vesicles
    (2022) Pottash, Alex; Jay, Steven M; Bioengineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Small RNAs are an exciting class of therapeutics with significant untapped therapeutic potential, due to their ability to affect cell behavior at the RNA level. However, delivery of RNA is a challenge due to its size and labile nature. Extracellular vesicles (EVs) are promising as delivery vehicles due to their natural role as physiological intercellular microRNA transporters, and research has shown that EVs have significant advantages compared to competing technologies such as lipid nanoparticles. Specifically, EVs more readily transport through biological barriers, deliver RNA more efficiently, and are less immunogenic. However, intrinsic microRNA content in EVs is low and thus active small RNA loading strategies are needed to enable therapeutic use. Consequently, a variety of small RNA loading methods for EVs have been developed. These include endogenous and exogenous approaches. Exogenous approaches, in which EVs are loaded directly, have been shown to enable loading of hundreds to thousands of small RNAs per EV, but they are not readily amenable to scalable production processes. Endogenous approaches, in which EVs are loaded by upstream manipulation of the producer cell, are compatible with large scale EV production, but loading by these approaches is inconsistent and has scarcely been quantitatively analyzed. The work in this dissertation is focused on enabling small RNA therapeutics via EV delivery. The lack of an ideal small RNA loading approach for EVs is addressed by tackling important issues of both endogenous and exogenous loading. First, the loading capacity of several common endogenous loading methods was optimized and quantitatively analyzed. Additionally, new approaches to endogenous small RNA loading involving genetic manipulation of the RNA structure and the microRNA cellular processing pathway were developed and evaluated. Finally, exogenous loading via sonication was applied to enable delivery of a novel microRNA combination that was identified via a rational selection process. This combination of miR-146a, miR-155, and miR-223 was found to have potentially synergistic anti-inflammatory activity, and EV-mediated delivery of the combination opens the possibility for therapeutic application in inflammatory diseases and conditions such as sepsis. Overall, this work both improves understanding of current techniques for small RNA loading into EVs and opens new opportunities for advanced strategies, bringing EV-based small RNA therapeutics closer to clinical application.
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    HIGH PERFORMANCE AGENT-BASED MODELS WITH REAL-TIME IN SITU VISUALIZATION OF INFLAMMATORY AND HEALING RESPONSES IN INJURED VOCAL FOLDS
    (2019) Seekhao, Nuttiiya; JaJa, Joseph; Li-Jessen, Nicole Y. K.; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    The introduction of clusters of multi-core and many-core processors has played a major role in recent advances in tackling a wide range of new challenging applications and in enabling new frontiers in BigData. However, as the computing power increases, the programming complexity to take optimal advantage of the machine's resources has significantly increased. High-performance computing (HPC) techniques are crucial in realizing the full potential of parallel computing. This research is an interdisciplinary effort focusing on two major directions. The first involves the introduction of HPC techniques to substantially improve the performance of complex biological agent-based models (ABM) simulations, more specifically simulations that are related to the inflammatory and healing responses of vocal folds at the physiological scale in mammals. The second direction involves improvements and extensions of the existing state-of-the-art vocal fold repair models. These improvements and extensions include comprehensive visualization of large data sets generated by the model and a significant increase in user-simulation interactivity. We developed a highly-interactive remote simulation and visualization framework for vocal fold (VF) agent-based modeling (ABM). The 3D VF ABM was verified through comparisons with empirical vocal fold data. Representative trends of biomarker predictions in surgically injured vocal folds were observed. The physiologically representative human VF ABM consisted of more than 15 million mobile biological cells. The model maintained and generated 1.7 billion signaling and extracellular matrix (ECM) protein data points in each iteration. The VF ABM employed HPC techniques to optimize its performance by concurrently utilizing the power of multi-core CPU and multiple GPUs. The optimization techniques included the minimization of data transfer between the CPU host and the rendering GPU. These transfer minimization techniques also reduced transfers between peer GPUs in multi-GPU setups. The data transfer minimization techniques were executed with a scheduling scheme that aims to achieve load balancing, maximum overlap of computation and communication, and a high degree of interactivity. This scheduling scheme achieved optimal interactivity by hyper-tasking the available GPUs (GHT). In comparison to the original serial implementation on a popular ABM framework, NetLogo, these schemes have shown substantial performance improvements of 400x and 800x for the 2D and 3D model, respectively. Furthermore, the combination of data footprint and data transfer reduction techniques with GHT achieved high-interactivity visualization with an average framerate of 42.8 fps. This performance enabled the users to perform real-time data exploration on large simulated outputs and steer the course of their simulation as needed.
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    Of Mice and Math: A Systems Biology Model for Alzheimer's disease
    (2011) Kyrtsos, Christina Rose; Baras, John S; Lee, Hey-Kyoung; Bioengineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder in the US, affecting over 1 in 8 people over the age of 65. There are several well-known pathological changes in the brains of AD patients, namely: the presence of diffuse beta amyloid plaques derived from the amyloid precursor protein (APP), hyper-phosphorylated tau protein, neuroinflammation and mitochondrial dysfunction. Recent studies have shown that cholesterol levels in both the plasma and the brain may play a role in disease pathogenesis, however, this exact role is not well understood. Additional proteins of interest have also been identified (ApoE, LRP-1, IL-1) as possible contributors to AD pathogenesis. To help understand these roles better, a systems biology mathematical model was developed. Basic principles from graph theory and control analysis were used to study the effect of altered cholesterol, ApoE, LRP and APP on the system as a whole. Negative feedback regulation and the rate of cholesterol transfer between astrocytes and neurons were identified as key modulators in the level of beta amyloid. Experiments were run concurrently to test whether decreasing plasma and brain cholesterol levels with simvastatin altered the expression levels of beta amyloid, ApoE, and LRP-1, to ascertain the edge directions in the network model and to better understand whether statin treatment served as a viable treatment option for AD patients. The work completed herein represents the first attempt to create a systems-level mathematical model to study AD that looks at intercellular interactions, as well as interactions between metabolic and inflammatory pathways.
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    Defining Critical Parameters for Producing and Modulating Inflammation Caused by Cell Encapsulating Alginate Microspheres
    (2007-09-11) Breger, Joyce Catherine; Wang, Nam Sun; Lyle, Dan B; Chemical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Minimizing induced inflammation, particularly nitric oxide (NO) production, is critical to optimal function or failure of implanted encapsulated cells. The purpose of this study is to define critical factors that affect toxic NO production from the macrophage cell line RAW264.7 in response to alginate microcapsules. The effects of the following were determined: 1) concentration of endotoxin (LPS) contamination; 2) presence of interferon-gamma (IFN-γ); 3) bead diameter and alginate volume; and 4) anti-inflammatory drugs in the alginate. A higher concentration (5 X) of LPS was required in alginate to produce the effect seen by LPS free in medium, sensitivity was enhanced by IFN-γ, bead diameter was inversely proportional to NO2 under low inflammatory conditions, and parthenolide in alginate significantly reduced inflammation. These results suggest that survival of implanted encapsulated cells may be improved by using highly purified alginate, avoiding ancillary inflammation, controlling surface area presentation, and incorporating anti-inflammatory drugs into the capsule matrix.