Organizational Unit:

Wallace H. Coulter Department of Biomedical Engineering

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https://hdl.handle.net/1853/70757

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https://ror.org/02j15s898

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Organizational Unit

College of Engineering

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https://finding-aids.library.gatech.edu/agents/corporate_entities/1129

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Publication Search Results

Now showing 1 - 10 of 1199

Epigenetic regulation of inflammation and fibrotic signaling

(Georgia Institute of Technology, 2024-05-03) Bogle, Jasmine Yvonne

Volumetric muscle loss stands as a debilitating condition resulting from substantial skeletal muscle tissue loss, often stemming from traumatic injury or disease. Unfortunately, the modern treatment options for VML remain limited and frequently yield suboptimal functional recovery, underscoring the critical need for innovative therapeutic approaches. Among these, the pursuit of epigenetic mechanisms governing muscle regeneration and inflammation emerges as a promising avenue of research. Recent studies have demonstrated the significance of chromatin architecture in muscle regeneration. Alterations in chromatin structure can significantly impact gene expression, consequently affecting muscle cell function and regeneration. Epigenetic regulation plays a crucial role in muscle regeneration and myogenesis by exerting control over the expression of genes that are pivotal to muscle cell proliferation, differentiation and regeneration. Furthermore, epigenetic regulation influences the function and behavior of muscle stem cells, which are vital for muscle regeneration post injury. The regenerative process triggered by muscle tissue in response to damage can be delineated into five interconnected and time dependent waves. Immunomodulation proves essential in attenuating damage induced inflammation and establishing a conducive immune microenvironment for successful progression through each stage. Both pro-inflammatory and pro-resolving phases play critical roles in muscle repair, thereby potentially impacting VML treatment outcomes. The intricate interplay between muscle tissue and the immune system fundamentally dictates proper regeneration following trauma, emphasizing the importance of understanding the underlying regeneration mechanisms. Given these insights, there is a bourgeoning interest in exploring the potential of epigenetic modulators to regulate the inflammatory response, diminish fibrotic signaling, and enhance muscle stem cell expansion and differentiation. This approach holds tremendous promise for promoting muscle regeneration and facilitating functional recovery following VML, offering a novel therapeutic strategy for addressing this challenging condition.
Biophysical characterization of 53-6.7 antibody binding to CD8 immunoreceptor

(Georgia Institute of Technology, 2024-04-30) Srinivasan, Shreyaa

Expressing on CD8+ T cells, the CD8 co-receptor binds the membrane-proximal domain of the MHC-I molecule away from the membrane-distal domains that present the peptide for the TCR binding. CD8 contributes to antigen recognition and T cell signaling. While CD8 is widely recognized as a co-stimulatory molecule for conventional CD8+ αβ T cells, recent reports highlight its multifaceted role in both adaptive and innate immune responses. Recognizing CD8’s increasing role in immune response underscores the significance of modulating its function, which delves into finding new strategies that can influence CD8 to augment or repress T-cell signaling. Monoclonal antibodies have been deeply explored as crucial immunomodulators, particularly with T-cell receptors. While there have been few observations about the impact of these antibodies on T-cell signaling and immune regulation via CD8, the biophysical interactions between antibodies and CD8 have not been extensively studied, prompting the investigation into this important area. To address this knowledge gap, my thesis research aimed to conduct phylogenetic analysis, generate recombinant CD8 protein, and perform biophysical characterization of therapeutically relevant CD8/monoclonal antibody (mAB) complexes. Recombinant expression constructs for CD8α and CD8β ectodomains and ectodomain-hinges were designed and expressed in E. coli cells. Proteins were expressed in insoluble inclusion bodies after induction, which required solubilization and in vitro refolding to prepare a properly conformed CD8 homodimer and heterodimeric proteins. Successful refolding of CD8αα was confirmed via circular dichroism spectroscopy. Surface plasmon resonance revealed high-affinity interactions between CD8αα and antibodies 53-6.7 and YTS 169.4, but not antibody OKT8. Refolding attempts for CD8αβ and CD8αβ linker constructs failed, indicating different structural dynamics between CD8αβ and CD8αα, and potential requirement of using eukaryotic expressions. I also wrote and submitted a Review Article (to Frontiers in Immunology – Chapters 1 – 3) that outlines the unique structure and function of different CD8 domains (ectodomain, hinge, transmembrane and cytoplasmic tail), in addition to various ways of harnessing CD8 as an immunomodulator through engineering CD8 mutations and utilizing monoclonal antibodies binding to CD8 for venturing potential medical applications. Overall, these studies serve as a useful resource, guiding both fundamental research in CD8-related immunology and translational efforts towards targeted immunotherapy.
Small Extracellular Vesicle Loaded 3D Bioprinted Cardiac Patch for Tissue Repair Post Myocardial Infarction

(Georgia Institute of Technology, 2024-04-29) Rajurkar, Pranshu Parimal

Myocardial infarction is a leading cause of morbidity worldwide, often leading to heart failure and death caused by severe damage to the cardiac tissue. While stem cells therapies have been explored to regenerate the injured tissue, they suffer from tumorigenicity, immune rejection, low engraftment rates and poor translation overall. Recently, small extracellular vesicles (sEVs), the mediators of paracrine signaling for stem cells, have emerged as cell-free therapies and have been shown to possess cardioprotective and regenerative potential. However, sEV therapies suffer from poor tissue targeting and fast clearance from the circulation when injected intravenously or locally. To overcome these shortcomings, the goal of this study was to fabricate a sEV loaded 3D bioprinted cardiac patch. We hypothesized that once implanted on the injured heart tissue, the patch will be able to control the release of the encapsulated sEVs and retain them on-site for better regenerative outcomes. We isolated sEVs from cardiac progenitor cells (CPC) and successfully fabricated a 3D bioprinted cardiac patch which sustained the release of the encapsulated sEVs for over two weeks. We showed that the CPC sEVs had a strong angiogenic, pro-proliferative and pro-migratory effect on endothelial cells and this functionality was retained by the sEV loaded patch in vitro. Taken together, this study demonstrates the potential of 3D bioprinted sEVs for cardiac tissue regeneration and sets a strong foundation for in vivo studies in the future.
4D Flow Magnetic Resonance Imaging and Computational Fluid Dynamics for the Study of Complex Blood Flow Patterns in Carotid Webs

(Georgia Institute of Technology, 2024-04-29) El Sayed, Retta

Carotid webs (CaW) contribute to cryptogenic strokes in young patients aged 30-48 years, even in the absence of traditional risk factors for vascular disease. CaW poses a challenge in clinical management as it is often resistant to traditional antiplatelet therapy. Understanding the complex flow alterations induced by CaW that lead to thrombus formation and subsequent stroke is crucial to improve clinical outcomes. To characterize flow patterns associated with CaW, advanced imaging techniques such as three-dimensional, three-directional, ECG-gated, time-resolved, phase-contrast magnetic resonance imaging (4D flow MRI) as well as computational fluid dynamics (CFD) are employed in this study. First, the spatio-temporal parameters of 4D flow magnetic resonance imaging were optimized using a patient-derived phantom model and CFD. This optimization is crucial for resolving complex flow patterns in the regions immediately distal to CaW within a clinically acceptable scan time. Subsequently, the study enrolled participants to measure hemodynamics in the carotid artery bulb in three groups: patients with CaW, patients with mild atherosclerosis with a comparable degree of narrowing, and healthy subjects. This was achieved using both 4D flow MRI and CFD. The results suggest that CaW is associated with lower time-averaged wall shear stress (TAWSS) and higher oscillatory shear index (OSI) than both mild atherosclerosis and carotid bifurcations in healthy subjects. Finally, we used a dataset where subjects had images with and without a clot to determine hemodynamic metrics in the location where a thrombus was observed in patients with CaW. This enables us to identify patients with CaW at risk for stroke by pinpointing the shear rate responsible for thrombus formation downstream of regions with blood stasis. This research aimed to deepen our understanding of the hemodynamic mechanisms linked to stroke risk in patients with CaW. These insights may lead to enhanced diagnostic and preventive strategies tailored to subjects with CaW, potentially improving outcomes.
A 3D Bioprinted model to examine the effect of stiffness on cortical organoids

(Georgia Institute of Technology, 2024-04-29) Sridhar, Vani

The human brain development is an intricate, dynamic, and highly regulated process that begins in the prenatal period and continues through adulthood. This process involves several complex mechanisms including differentiation, proliferation, migration, and maturation of neural progenitor cells into various types of neurons and glial cells, forming the intricate neural circuits that underlie cognition, behavior, and sensory processing. Intensive study of the neurobiology of brain development is essential because of its direct impact on human behavior and furthermore, to fully understand the pathophysiology and etiology of neurodevelopmental disorders (NDDs), which in turn are disruptive to human brain development. Due to the obvious limitation of studying a developing human brain, researchers rely on bioengineered in vitro models to accurately recapitulate the physiological conditions of brain tissue. Current bioengineering efforts encompass using biomaterials and stem cells to establish the models, incorporate vasculature, and induce the necessary physical and chemical cues using external additives and factors. One such extracellular matrix (ECM) cue of high importance is the mechanical stiffness (i.e., elastic modulus) of the tissue. The brain is one of the softest tissues in our body; although, as the brain tissue matures, its stiffness gradually increases. This study aims to investigate the effect of varying stiffnesses on human cortical organoids in a 3D bioprinted hydrogel model. The organoids are embedded into these models and co-cultured with endothelial cells. At different time points, the cell viability, growth, and other developmental markers were studied to assess the contribution of ECM stiffness to the developing brain.
Development of synnotch platform for sensing receptor force and investigation of receptor-mediated mechanotransduction

(Georgia Institute of Technology, 2024-04-26) Lyu, Jintian

B cell lymphoma, a malignancy stemming from B lymphocytes, is a dynamic disease marked by the uncontrolled growth of B cells and their accumulation in various organs, presenting a complex health challenge. This dissertation interrogates the multifaceted interplay of genetic mutations that contributes to the pathogenesis and progression of B cell lymphoma, with particular focus on how it shapes mechano-transduction of CD40 in B cell. We explored the germinal center (GC) origin of Diffuse Large B-cell Lymphoma (DLBCL), examining the role of epigenetic modulations and mutations in the EZH2 gene, a histone methyltransferase, which impact B cell functionality and development. Particularly, we consider how EZH2 mutations can initiate lymphomagenesis by altering the dependency of GC B cells on T follicular helper (Tfh) cells. By harnessing the mechano-sensitive properties of the Notch receptor, we have engineered a synthetic version of the Notch receptor (SynNotch) by substituting its native ligand-binding domain with an antibody's single-chain variable fragment, enabling targeted receptor interaction, and modifying its signaling pathway to trigger a detectable response, such as the production of green fluorescence protein (GFP) or luciferase. When a target cell applies force to the receptor, which then gets relayed to the SynNotch, this interaction prompts the signal for GFP or luciferase production, visible through flow cytometry or microscopy. By introducing cells equipped with this SynNotch construct into living organisms, we can trace their journey to locate and engage with cells that express the intended receptor, monitoring the subsequent reporter signals. This approach permits the quantification of the exerted forces on the receptor by the target cells in a living context. We demonstrated the design, in vitro validation, and in vivo application of this system using T cells as sensor cells and B cells as targets, focusing on the CD40 receptor. Our research confirms the practicality and value of our platform, offering a novel method for future mechanobiological studies. Through this, we demonstrate that the EZH2Y641 mutation alters the mechanical interaction between B cells and the CD40-CD40L interface—a critical point in immunoregulation—disrupting the downstream signaling and epigenetics that ordinarily extinguish the pseudo-malignant phenotype of GC B cells. Our results also reveal that the EZH2Y641 mutation reduces in situ CD40–CD40L affinity, a discrepancy that can be corrected by EZH2 inhibition. Further investigations show that mechanical forces influence the phosphorylation of key signaling molecules and can modulate the spreading of B cells on CD40L presenting surfaces, impacting B cell signaling. The utilization of the SynNotch platform to compare the mechanical behavior of B cells in vivo, between those with wild-type EZH2 and the EZH2Y641 mutant, underscores the utility of our technology. Collectively, this dissertation elucidates the mechanobiological mechanisms at play in the malignant transformation of B cells and validates a new technology to study them, thus contributing valuable insights into the underpinnings of B cell lymphomas and establishing a groundwork for potential therapeutic interventions. In the end of the thesis, we extended our investigation into other biological system and show the important role of mechano-transduction.
Quantitative Imaging Techniques to Guide Clinical Decision Making and Treatment of Glioblastoma

(Georgia Institute of Technology, 2024-04-17) Ramesh, Karthik

Treatment of glioblastoma (GBM), a grade IV brain tumor, is complex and challenging. Despite an aggressive treatment protocol of surgery, radiation treatment, and chemotherapy, patient outcomes are poor. Throughout a patient’s treatment timeline, imaging is central to clinical decision making. The gold standard imaging for treatment of GBM is magnetic resonance imaging (MRI). While clinical MRIs show some extent of tumor infiltration, they do not capture the entire extent and further, can struggle to define tumor margins. Spectroscopic MRI (sMRI) measures the endogenous metabolites in the brain and in particular, a ratio of two metabolites (choline and N-acetyl aspartate) shows tumor margins that extend well past what’s seen in the clinic. To that end, we first present our efforts to guide GBM treatment with sMRI. Next, we analyze whether pre-treatment insights from sMRI correlate with patient survival and outcomes. Finally, GBM patients are tracked with clinical imaging after completing surgery and chemoradiation. To improve objectivity and robustness in post-treatment patient tracking, we have developed deep learning algorithms to quantify patient lesions and provide assistive suggestions to physicians for whether tumor recurrence has occurred. By utilizing sMRI during treatment and the latest deep learning algorithms after treatment, we have improved GBM patient survival and provided insights that can help physicians treat patients more proactively. Further, all our algorithms are housed in software that fit seamlessly into clinician workflows as the integration of quantitative tools and imaging into the clinic is vital towards affecting patient lives directly. Future plans involve translating sMRI and our quantitative software into the clinic to assist clinicians and improve patient livelihood.
Studying the Effects of Noradrenergic Neuromodulation on the BOLD Global Signal and Quasi-Periodic Patterns in Rat rs-fMRI

(Georgia Institute of Technology, 2024-04-15) Anumba, Nmachi

The study of dynamically changing resting-state fMRI (rs-fMRI) signals that span multiple brain regions provides an opportunity to better understand the intrinsic contexts of large-scale communication across the brain. Two prominent examples of these whole-brain spatiotemporal patterns are the blood oxygen level dependent (BOLD) global signal and quasi-periodic patterns (QPPs). The BOLD global signal is defined as the averaged activity of the brain during a scan and its use as a nuisance regressor has been a contentious topic for years. QPPs are propagating waves of anticorrelated activity that alternate between two prominent resting-state brain networks, though their origin is unknown. Both of these signals have been shown to exhibit notable relationships with measures of arousal and vigilance. Activity of the locus coeruleus (LC), a brainstem nucleus responsible for the synthesis and release of norepinephrine, is known to play a significant role in arousal. Speculation that QPPs may originate from the activity of brainstem nuclei, in addition to findings that link the global signal to levels of arousal, led us to believe that the widespread nature of LC influence could have a significant effect on these two signals. In this work we studied the direct effects of LC activity on the BOLD global signal and QPPs in rats. This was done by first identifying a neural global signal component in a noise-controlled environment that could consequently be affected by LC neuromodulation (Aim 1). Secondly, we used optogenetic-fMRI to stimulate the LC at different frequencies and study how these varying levels of LC activity affected both the global signal and QPPs in rats (Aim 2). Both spatiotemporal signals were analyzed both through traditional methods and through the employment of complex principal component analysis (CPCA). Our findings show evidence for a neural global signal component that is distinct from noise. We also report spatially specific changes in global signal distribution under tonic LC stimulation as well as regional changes in QPP involvement under 5 Hz and 15 Hz phasic stimulation. Given that the LC is also strongly implicated in Alzheimer's disease (AD), we also used the AD rat model TgF344-AD to investigate the effects of the disease on whole-brain dynamics using CPCA, for which we show age-specific AD effects. These results show that the neuromodulatory effects of the LC norepinephrine system on large-scale spatiotemporal patterns may be small in scale and more regionally specific than initially thought.
Improving Brain Sensitivity of Cerebral Blood Flow Measurements With Continuous-Wave Diffuse Correlation Spectroscopy

(Georgia Institute of Technology, 2024-04-04) Zhao, Hongting

Adequate cerebral blood flow is critical for the delivery of oxygen and nutrients necessary to maintain neuronal health and function. Diffuse correlation spectroscopy (DCS) is an emerging optical modality for measuring cerebral blood flow non-invasively at the bedside. DCS measures the temporal intensity autocorrelation of multiply scattered light that has traveled from the source to the tissue surface. As the decay rate of correlation curve is related to the motion of red blood cells in the underlying tissue, DCS measures an index of blood flow. Due to the noninvasive nature of the technology, the detected signal at tissue surface contains signal contributions from both cerebral and extracerebral layers, i.e., scalp, skull, and cerebrospinal fluid. These extracerebral contributions can be particularly appreciable in adults wherein the total scalp and skull thickness can exceed 1 cm. Thus, limited brain sensitivity is one of the remaining challenges for applications of DCS to the study of the human brain. This thesis focuses on exploring advanced modeling methods that aim to improve brain sensitivity of DCS measurements by isolating the contribution of the signal that arises from the brain. Specifically, this thesis investigates an analytical model that treats the head as a series of slabs emulating the scalp, skull, and brain layers, dubbed the three-layer model. This model has been touted as a solution to the limited brain sensitivity problem with DCS, although little work has been done to rigorously investigate the accuracy of the model and to demonstrate its utility in vivo. Thus, through a series of in silico and in-vivo experiments, I demonstrated that accurate estimation of absolute values of brain blood flow with this model is subject to numerous sources of error given its sensitivity to layer optical properties, layer thickness, head curvature, and the presence of cerebrospinal fluid. However, I show that estimations of relative changes in brain blood flow with this model are more accurate than traditional analytical approaches and less sensitive to above-mentioned confounding factors. In vivo, I demonstrate that the model is susceptible to errors as extracerebral layer thickness increases. Overall, this work demonstrates significant limitations to multi-layered modeling approaches in general that must be considered before the approach is widely used.
Machine Learning in Digital Neuropathology: Towards a Large-Scale Analysis Platform for Federated Cohorts

(Georgia Institute of Technology, 2024-02-01) Vizcarra, Juan Carlos

Millions of people suffer from neurodegenerative diseases, including Alzheimer’s disease, Parkinson’s disease, and related disorders. Post-mortem analysis of brain tissue is essential in improving our understanding of the underlying biological mechanisms of neurodegeneration. Modern techniques allow digitization of brain tissue glass slides into large images that are rich in data for computational analysis. Developing effective image analysis tools for these datasets is challenging because datasets vary widely, are rarely reported completely, and need to be developed with the expert user, neuropathologist, in mind. To address these concerns, this work aimed at investigating the intersection between neuropathology, modern computational analysis and data management. In Aim 1, an inter-rater and inter-annotator study was conducted to measure the variability amongst experts and novices in two important tasks related to Alzheimer’s disease pathology. Aim 2 explored the ability to utilize modern computational approaches in machine learning to perform the tasks in Aim 1 and show that even with imperfect ground truth, computational approaches can mimic and perform similar to experts in the field. Finally in Aim 3, a suite of tools, including the NeuroTK platform, were developed to provide all the necessary tools for neuropathologists to run novel large scale image analysis studies. The results of this work highlight the impact of machine learning in neuropathology and provide a suite of powerful open-source tools that will open up large scale computational analysis of digital imaging datasets.