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Title: Pre-implant Brain Activation Modeling to Drive Placement of Depth Leads in White Matter for Direct Neurostimulation Therapy in Epilepsy
Creator: Cendejas Zaragoza, Leopoldo
Date: 2019
Description: A critical step towards applying direct brain stimulation therapy in focal onset epilepsy is to effectively interface with epileptogenic...
Show moreA critical step towards applying direct brain stimulation therapy in focal onset epilepsy is to effectively interface with epileptogenic neural circuits using a limited set of active contacts. This takes special relevance when interacting with networks that exhibit two or more foci. A strategy to influence the maximum extent of the epileptogenic circuit is to stimulate white matter pathways to enhance propagation to distant epileptic tissue.A significant number of elements must be considered in the clinical response to stimulation delivered directly to neuronal populations. These variables include: stimulation parameter settings, number and interdependence of anatomical targets, electrode number, electrode location and orientation, geometry or shape of the electrode contacts, contact polarity, biophysical properties of stimulated medium, andtrajectory of axonal bundles adjacent to the stimulation site.This document addresses the development of a computational model which takes into consideration all the mentioned variables to predict activation of distant sites via white matter pathways. A method to calculate the extracellular potential field, induced by the application of time-dependent stimulation waveforms, is discussed. Such a method considers both the anisotropic conductivity nature of neural tissue and the electrochemical phenomena of the electrode-tissue interface. The response of white matter fibers is then evaluated by solving a compartmental cable model based in the Hodgkin and Huxley membrane description.The model was integrated into a pre-surgical workflow and was used prospectively to guide stereotactic implantation of depth leads to apply direct neurostimulation therapy in four patients with refractory focal onset epilepsy.
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Title: Non-invasive quantification of cancer drug targets: Mathematical models for paired-agent molecular imaging
Creator: Sadeghipour, Negar
Date: 2017
Description: Cancer is among the leading causes of death worldwide. Incidence of cancer is rising at a rate that is almost completely nullifying...
Show moreCancer is among the leading causes of death worldwide. Incidence of cancer is rising at a rate that is almost completely nullifying improvements in cancer treatment and the heterogeneity of advanced disease poses significant complications for the development of effective therapies. With more aggressive cancers tending to display abnormally high expression of signaling receptors associated cell proliferation - receptors that tend to be expressed at very low levels by healthy cells in adulthood - many new cancer-specific “molecular therapies” have been developed to target and block these pathways. However, not all cancers overexpress the same proliferation pathways, so many have proposed molecular imaging as a non-invasive means of identifying on a patient-by-patient basis, which specific targets may be overexpressed to tailor therapies to the individual (“precision medicine”). The primary goal of this thesis was to develop and validate some of the first non-invasive means of measuring drug-target concentrations prior to therapy and the first measures of drug-target occupancy during therapy to ultimately predict and monitor the efficacy of cancer molecular therapy. All work was founded on paired-agent molecular imaging protocols that employ co-administration of two imaging agents: one agent that is targeted to the biomolecule of interest (e.g. a cell surface signaling receptor that may be overexpressed by a cancer), and a second, “control” (“untargeted”) agent that is as chemically similar to the targeted agent as possible, but that does not bind to the biomolecule of interest. In all paired-agent imaging strategies, the signal from the control agent is used to account for delivery and nonspecific retention effects that can confound the relationship between the targeted imaging agent concentration in a region-of-interest (ROI) and the targeted biomolecule concentration in that ROI.
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Title: Intraoperative tumor margin detection using nanoparticles: protocol optimization through kinetic modeling
Creator: Xu, Xiaochun
Date: 2018
Description: Clear margins (no tumor on the surface of the resected tissues) is essential to minimize tumor recurrence and prolong survival for wide local...
Show moreClear margins (no tumor on the surface of the resected tissues) is essential to minimize tumor recurrence and prolong survival for wide local excision cancer surgeries. However, standard methods of margin assessment cannot be carried out within the time frame of surgery (meaning patients with positive margins are suggested to undergo call-back surgeries). Intraoperative molecular imaging of cell surface receptors can offer a solution; however, substantial nonspecific diffusion and retention of imaging agents in resected tissues remains a significant challenge to identifying cancer reliably. Recently, “paired-agent” methods—which employ co-administration of a control-imaging agent with a targeting agent—have been applied to thick-sample staining and rinsing applications to account for background staining. This dissertation aimed to optimize paired-agent molecular imaging tumor-to-healthy tissue discrimination through mathematical modeling.Two simplified mathematical models—the rinsing paired-agent model (RPAM) and the serial staining model (SSM)—were derived and tested in accurate simulation models (also developed as a component of this dissertation,) and in preclinical cancer models. More specifically, RPAM was demonstrated to be capable of providing more accurate estimates of receptor concentration than more standard “ratiometric” methods (essentially dividing the targeted agent signal by the control agent signal), and the model was insensitive to the variability of rinsing time from one image to the next. Though it was noted in experiments, that regardless of the approach taken, a very large fraction of signal was removed upon the first rinse, leading to large “gaps” in the data that would be available to RPAM. The SSM, on the other hand, provided a model that could be applied to serial staining data, which yielded a more gradual change in signal between imaging.Considering the multidimensional complexity of paired-agent topical tissue molecular imaging (with diffusion, imaging agent chemical/binding properties, tissue staining, rinsing, imaging, and data analysis protocols all being subject to alteration), thorough optimization margin analysis imaging protocols is untractable using experiments alone. Therefore, a salient feature of this dissertation was the development and validation of a “forward” mathematical diffusion and binding model for in silico testing of proposed paired-agent staining and rinsing protocols in thick tissue.
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Title: A three-dimensional tissue molecular imaging system based on angular domain optical projection tomography: Applications in lymph node biopsy
Creator: Torres, Veronica Calliste
Date: 2020
Description: Sentinel lymph node biopsy is a good prognostic factor for several cancers as therapeutic decisions are often determined by the results....
Show moreSentinel lymph node biopsy is a good prognostic factor for several cancers as therapeutic decisions are often determined by the results. Despite this importance, false negatives remain common because of standard pathology procedures that aim only to detect macrometastases (> 2 mm diameter) and leave more than 99% of lymph node volumes unassessed. While it is possible to section tissue samples more thoroughly, a subsequent 10x increase in pathologist read time is undesirable. Therefore, a more sensitive and rapid approach for lymph node evaluation is warranted.Our proposed solution was the development of an angle-restricted optical projection tomography system to provide high resolution quantitative imaging of whole lymph nodes prior to conventional pathology. Two main strategies were employed: 1) early photon imaging achieved with angular restriction to minimize the number of detected multiply scattered photons that add to imaging blur; and 2) paired-agent molecular imaging, which can quantify targeted biomolecule concentrations through co-administration of targeted and control imaging agents.This thesis focused primarily on the first aspect; however, all work was performed with paired-agent imaging in mind, such that the technique can be implemented directly in future studies. The first chapter presents a proof-of-concept that verifies the utility of angle-domain imaging for evaluation of low scattering lymph nodes. Filtered backprojection and strict angle restriction for scatter rejection were sufficient to detect and localize clinically relevant metastases. In the second chapter, improvements were made to the system so that detection efficiency could be improved, and the system was more rigorously characterized in terms of reconstruction accuracy and limits of detection. Finally, the third chapter presents the investigation of alternate reconstruction techniques to push the limits of achievable resolution and image quality. The overall findings of this work demonstrate the potential for an angle-restricted tomography system to provide significant improvements of metastases detection sensitivity in excised lymph nodes compared to conventional pathology at a fraction of the time and cost.
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Title: AGENT-BASED MODELING OF IMMUNE RESPONSE IN THE DEVELOPMENT OF TYPE 1 DIABETES
Creator: Xu, Qian
Date: 2020
Description: Diabetes is a chronic disease that affects a large number of people around the world and cause many co-morbidities ranging from cardiovascular...
Show moreDiabetes is a chronic disease that affects a large number of people around the world and cause many co-morbidities ranging from cardiovascular diseases, neuropathy, retinopathy and blindness and kidney failure. The economic burden induced by diabetes is not only caused by the wage loss and medical burden, but also with the cost of treatment of diabetes and co-morbidities caused by diabetes. Clinical research for treatment and cure of diabetes is costly. Computer modeling and simulation studies provide an economical alternative to conduct preliminary evaluation of new hypotheses and alternatives in new therapies. The most promising results obtained from simulations can then be investigates experimentally, improving the efficiency of experiments and clinical studies. This work focuses on the development of an agent-based model to describe the destruction of islets and β cells and the development of Type 1 diabetes. The whole process of inflammation related to diabetes takes place in pancreatic lymph node, circulation, and pancreatic tissue with islets. The infiltration to islets and insulin-producing β cell damage happens in the pancreatic tissue with islets; the lymphocytes activation and antigen presentation majorly happened in the pancreatic lymph node. Therefore, the model described activities taking place in the islets in the pancreatic tissue section and pancreatic lymph nodes, the interactions among T cells, α/β cells, antigen presentation cells and immunosuppression cells. Cell behavior was obtained from the literature that published experiment results and used to develop the rules followed by the agents representing various types of cells and their interactions. The agent-based model provides a framework to describe relationship between lymphocytes and β cell through the trends of cell variations in the inflammation and demonstrates the effects of these cells in the disease development. Two different systems, a mouse model and a human model have been developed. The simulation results with the mouse model indicate that the different types of regulatory cells play different roles in suppressing inflammation. Among them, the regulatory T cells play the most important role in suppressing inflammation, but the B regulatory cell conversion is the key to induce the cascade of regulatory cell generation in inflammatory environment when there are no regulatory cytokines in the environment. The simulation results with the human model are mostly similar with mouse model, however, their effect of potential therapies such as addition of Tregs did not do as well as that in mouse model. The treatment method might be adjusted by combining other cytokines or immunosuppression cells in human assays.
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Title: Modeling the Glycemic Response to Physical Activity and Athletic Competition Anxiety in People with Type 1 Diabetes
Creator: Hobbs, Nicole B.
Date: 2021
Description: The first observational study of recreational athletes with T1D during a meaningful athletic competition and a non-competitive exercise...
Show moreThe first observational study of recreational athletes with T1D during a meaningful athletic competition and a non-competitive exercise session was conducted. Non-invasive wearable devices and surveys are used to identify the presence or absence of competition stress during physical activity and to estimate physical activity intensity. An elevated glycemic trend on the day of an athletic competition is a frequent complaint among people with T1D and this increase was consistently observed in our study population. The elevation in glycemia is impacted by the individual behavior related to diabetes management and this behavioral change is impacted by the individual’s duration of diabetes and other demographic traits. A physical activity-intensity dependent model of glucose-insulin dynamics was developed for a type 1 diabetes simulator as a basis for the development of multivariable artificial pancreas systems. Several potential model structures were compared to assess the influence of model terms related to endogenous glucose production, glucose utilization, and glucose transfer. The model including all three terms accurately describes the relation of plasma insulin and physical activity intensity upon glucose production and glucose utilization to generate the appropriate glucose response for each physical activity condition ranging from low to maximal intensity efforts. All artificial pancreas performance metrics have been determined based upon physician-defined metrics for success. An online survey was conducted to assess individual goals for diabetes management, and for many individuals, the ability to achieve personalized metrics is unnecessary as their goals match the general metrics. As individual targets may be set by the individual or their doctor, the ability to achieve those are still of interest. A framework to target the individual management goals with the multivariable artificial pancreas system is developed which increased the percentage of time spent in each individual target range in simulations.
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Title: DEVELOPMENT OF BIOMARKERS OF SMALL VESSEL DISEASE IN AGING
Creator: Makkinejad, Nazanin
Date: 2021
Description: Age-related neuropathologies including cerebrovascular and neurodegenerative diseases play a critical role in cognitive dysfunction, and...
Show moreAge-related neuropathologies including cerebrovascular and neurodegenerative diseases play a critical role in cognitive dysfunction, and development of dementia. Designing methodologies for early prediction of these diseases are much needed. Since multiple pathologies commonly coexist in brains of older adults, clinical diagnosis lacks the specificity to isolate the pathology of interest, and gold standard is determined only at autopsy. Magnetic resonance imaging (MRI) provides a non-invasive tool to study abnormalities in brain characteristics that is unique to each pathology. Utilizing ex-vivo MRI for brain imaging proves to be useful as it eliminates two important biases of in-vivo MRI. First, no additional pathology would develop between imaging and pathologic examination, and second, frail older adults would not be excluded from MRI.Hence, the aims of this dissertation were two-fold: to study brain correlates of age- related neuropathologies, and to develop and validate classifiers of small vessel diseases by combining ex-vivo MRI and pathology in a large community cohort of older adults. The structure of the project is as follows.First, the association of amygdala volume and shape with transactive response DNA-binding protein 43 (TDP-43) pathology was investigated. Using a regularized regression technique, higher TDP-43 was associated with lower amygdala volume. Also, shape analysis of amygdala showed unique patterns of spatial atrophy associated with TDP-43 independent of other pathologies. Lastly, using linear mixed effect models, amygdala volume was shown to explain an additional portion of variance in cognitive decline above and beyond what was explained by the neuropathologies and demographics.Second, the previous study was extended to analyze other subcortical regions including the hippocampus, thalamus, nucleus accumbens, caudate, and putamen, and was also conducted in a larger dataset. The results showed unique contribution of TDP-43, neurofibrillary tangles (hallmark characteristic of Alzheimer’s disease pathology), and atherosclerosis (a cerebrovascular pathology) to atrophy on the surface of subcortical structures. Understanding the independent effects of each pathology on volume and shape of different brain regions can form a basis for the development of classifiers of age-related neuropathologies.Third, an in-vivo classifier of arteriolosclerosis was developed and validated. Arteriolosclerosis is one of the main pathologies of small vessel disease, is associated with cognitive decline and dementia, and currently has no standard biomarker available. In this work, the classifier was developed ex-vivo using machine learning (ML) techniques and was then translated to in-vivo. The in-vivo classifier was packaged as a software called ARTS, which outputs a score that is the likelihood of arteriolosclerosis when the required input is given to the software. It was tested and validated in various cohorts and showed to have high performance in predicting the pathology. It was also shown that higher ARTS score was associated with greater cognitive decline in domains that are specific to small vessel disease.Fourth, motivated by current trends and superiority of deep learning (DL) techniques in classification tasks in computer vision and medical imaging, a preliminary study was designed to use DL for training an ex-vivo classifier of arteriolosclerosis. Specifically, convolutional neural networks (CNNs) were applied on 3 Tesla ex-vivo MR images directly without providing prior information of brain correlates of arteriolosclerosis. One interesting aspect of the results was that the network learnt that white matter hyperintense lesions contributed the most to classification of arteriolosclerosis. These results were encouraging, and more future work will exploit the capability of DL techniques alongside the traditional ML approaches for more automation and possibly better performance.Finally, a preliminary classifier of arteriolosclerosis and small vessel atherosclerosis was developed since the existence of both pathologies in brain have devastating effects on cognition. The methodology was similar to the one used for development of arteriolosclerosis classifier with minor differences. The classifier showed a good performance in-vivo, although the testing needs to be assessed in more cohorts.The comprehensive study of age-related neuropathologies and their contribution to abnormalities of subcortical brain structures offers a great potential to develop a biomarker of each pathology. Also, the finding that the MR-based classifier of arteriolosclerosis showed high performance in-vivo demonstrate the potential of ex-vivo studies for development of biomarkers that are precise (because they are based on autopsy, which is the gold standard) and are expected to work well in-vivo. The implications of this study include development of biomarkers that could potentially be used in refined participant selection and enhanced monitoring of the treatment response in clinical drug and prevention trials.
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Title: Assessment of Sleep Characteristics and Their Effects in People with Type 1 Diabetes for the Development of a Sleep Module for the Multivariable Artificial Pancreas System
Creator: Brandt, Rachel
Date: 2021
Description: his work is focused on the relationship between sleep and blood glucose control in people with Type 1 Diabetes and on the development of a...
Show morehis work is focused on the relationship between sleep and blood glucose control in people with Type 1 Diabetes and on the development of a sleep module incorporating new variables and rules for use in automated insulin delivery and advisory systems. Through this research, sleep effects were identified, quantified and incorporated into a multivariable artificial pancreas system (mvAP) that is currently being developed. The mvAP uses different physiological signals acquired through non-invasive wearable sensors along with a continuous glucose monitor (CGM) to detect the state of the user to predict future blood glucose values to aid in insulin dosing decisions. The overall objective of the research was to develop and add a module to further improve the successful mvAP by incorporating sleep related information while retaining the functionality and safety of the system and improving the effectiveness in maintaining good glycemic control. Two types of sleep effects were studied: effects of sleep characteristics and stages in real-time (during sleep) and effects of sleep on glucose metabolism the next day. It was found that poor sleep quality was related to higher glycemic variability overnight in adults with Type 1 Diabetes. However, in adults without diabetes, there were no consistent relationships found between sleep stages and changes in blood glucose levels overnight. For adults with Type 1 Diabetes, it was determined that Sleep Quality, Total Sleep Time, Wake After Sleep Onset (WASO), Number of Awakenings >5 minutes, and amount of Deep sleep could be used in conjunction with insulin on board and the amount of time that has passed since the user has woken up to predict how much more insulin may be needed at the first meal of the day. This Insulin Multiplier Algorithm was tested and validated in replay simulations. Finally, in order to incorporate these relationships into the mvAP, a sleep stage detection algorithm was developed using the Empatica E4 wristband.
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Title: A Biodegradable Microsphere-Hydrogel Ocular Drug Delivery System for Treatment of Choroidal Neovascularization
Creator: Liu, Wenqiang
Date: 2020
Description: Current standard of care for neovascular age-related macular degeneration (AMD) requires repeated intravitreal bolus injections of anti...
Show moreCurrent standard of care for neovascular age-related macular degeneration (AMD) requires repeated intravitreal bolus injections of anti-vascular endothelial growth factors (anti-VEGFs). This frequent repeated injection regimen present increased risks of potential complications including endophthalmitis, retinal detachment, intravitreal hemorrhage, and cataract. In addition, pharmacokinetic profiles of drugs are non-optimal, since the peak level of drug after bolus injections may cause potential toxic effect while the quick clearance later may render subtherapeutic concentration. Finally, the significant socioeconomic burden upon patients, family, and healthcare systems cannot be ignored. Therefore, a controlled delivery system for anti-VEGF drugs is in high demand to reduce injection frequencies, minimize potential risks, and improve efficacy.The overall goal of this study was to develop a biodegradable and injectable drug delivery system (DDS) capable of releasing therapeutic anti-VEGF (aflibercept) for six months. Based on our previous non-degradable DDS for anti-VEGFs, this work sought to introduce biodegradable polymeric crosslinker into the hydrogel matrix to make the DDS biodegradable. To accomplish this goal, three specific aims were pursued: (1) Development of a biodegradable and injectable microsphere-hydrogel DDS for controlled release of aflibercept for six months, important biomaterial parameters including thermoresponsive behavior, injectability, in vitro degradation and biocompatibility, release kinetics, and drug bioactivity were characterized to obtain the optimal DDS formulation; (2) Evaluation of long-term in vivo efficacy of aflibercept-loaded DDS in laser-induced CNV model; (3) Investigation of in vivo safety and biocompatibility of DDS injection and its degradation products.
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Title: Implementation of a multisensor wearable artificial pancreas platform: ensuring safety with communication robustness and cyber security
Creator: Lazaro Martinez, Carmen Caterina
Date: 2019
Description: Advances in IoT technologies and new sensor capabilities contributed to the rapid growth of wearable medical devices. Today, mobile sensor...
Show moreAdvances in IoT technologies and new sensor capabilities contributed to the rapid growth of wearable medical devices. Today, mobile sensor platforms can be effectively, cost efficiently integrated in healthcare applications. However, the increased risks of these devices, inherent vulnerabilities of mobile operating systems and open nature of the wireless protocols call for improved safety and security measures to prioritize patient's well-being. In the field of type 1 diabetes, blood glucose level management with insulin control algorithms are available in diabetes therapy systems, though none are fully automated and require extra announcements (such as meal and exercise) to operate. A mobile artificial pancreas (AP), based on Android smartphone, is developed: such a platform relies on off-the-shelf components and receives in real-time the physiological measurements from the wrist worn physical activity tracker and the glucose measurements, then used in a predictive control algorithm (originally developed and tested on a laptop), to compute the optimal amount of insulin to administer via an insulin pump. A dedicated remote server provides additional support for registration, authentication and data backup.The nature of the algorithm required a fast, reliable method to translate its inherent functions. Therefore, we implement a new semi-automatic conversion mechanism which ports MATLAB to Android as native C code. Validation tests of the mobile version confirm there are no deviations in the results.Moreover, in order to enhance safety guarantees for the patient, this cyber-physical system needs a robust implementation also resilient to attacks and failures. A central monitor module is introduced, wherein wireless devices and communications channels are integrated with complementary alarm and safety subsystems. The parameterization of the AP as a state machine demonstrates the efficiency to detect and react to possible errors, since any state change triggers the appropriate correcting response. The result is a protected and fail-safe environment, further expanded with security modules enforcing encryption, authenticated access and data-flow rules for intrusion detection.Overall, this research demonstrates, in the case of an AP, how challenges in diverse fields such as sensor fusion, control systems, wireless communications and cybersecurity can be addressed with a holistic approach for mobile health (mHealth).
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Title: An adaptive personalized multivariable, multimodule artificial pancreas system based on a plasma insulin cognizant model predictive control
Creator: Hajizadeh, Iman
Date: 2019
Description: An adaptive and personalized multivariable artificial pancreas system is proposed for effective glycemic control and disturbance rejection...
Show moreAn adaptive and personalized multivariable artificial pancreas system is proposed for effective glycemic control and disturbance rejection without manual user announcements for meals and exercise. Adaptive models identified through system identification techniques are integrated with a physiological compartment model to characterize the time-varying glucose-insulin dynamics. The real-time estimation of plasma insulin concentration to quantify the insulin in the bloodstream in patients with type 1 diabetes mellitus is presented. The identified time-varying models are employed for the design of an adaptive model predictive control formulation that is cognizant of the plasma insulin concentration. A feature extraction method based on glucose measurements is used to detect rapid deviations from the desired set-point caused by significant disturbances and subsequently modify the constraints of the optimization problem for negotiating between the aggressiveness and robustness of the controller to suggest the required amount of insulin. A predictive hypoglycemia module with carbohydrate suggestion is also designed to prevent any potential hypoglycemia events. A controller performance assessment algorithm is developed to analyze the closed-loop behavior and modify the parameters of the artificial pancreas control system. To this end, various performance indices are defined to quantitatively evaluate the controller efficacy in real-time. The controller assessment and modification module also incorporates on-line learning from historical data to anticipate impending disturbances and proactively counteract their effects.
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Title: ENGINEERING HUMAN ADIPOSE TISSUE WITHIN A MICROFLUIDIC DEVICE
Creator: Yang, Feipeng
Date: 2019
Description: Adipose tissue models can be used for in vitro drug screening of therapeutics designed for the treatment of obesity or adipose tissue-related...
Show moreAdipose tissue models can be used for in vitro drug screening of therapeutics designed for the treatment of obesity or adipose tissue-related diseases. This work aimed to engineer functional three-dimensional (3D) adipose microtissue models that could be incorporated within a microfluidic system. To support the on-chip 3D culture, a microfluidic device consisted of cell culture chambers flanked by two side channels was designed. The mold for the microfluidic device was manufactured using computer numeric control (CNC) micro-milling. Soft lithography with polydimethylsiloxane (PDMS) was used to construct the microchannels and chambers in the microfluidic device. A model was developed by the monoculture of adipocytes within the microfluidic device. Human adipose-derived stem cells (ADSCs) were differentiated toward adipocyte in the cell culture chambers and formed a 3D adipose microtissue. The effect of interstitial flow on the adipogenic differentiation of ADSCs was explored. Adipocytes showed decreased adiponectin secretion and increased lipolysis in response to increased interstitial shear stress. Meanwhile, multiple adipogenic genes were downregulated with the increase in shear stress.To engineer vascularized adipose tissue, a co-culture system with ADSCs, human umbilical vein endothelial cells (HUVECs) and normal human lung fibroblasts (NHLFs) was applied. Culture conditions (media, cell ratios, temporal conditions, etc.) for optimal differentiation of ADSCs and induction of network formation were identified. ADSCs were induced toward adipogenesis before mixed with HUVECs and NHLFs. The cell mixture was loaded into the microfluidic device and formed an adipose microtissue with a vessel network in a mixed culture media. An interconnected vascular network was established within 2 weeks and formed anastomoses with the side channels. Perfusion of fluorescent dextran confirmed the interconnections and lumen formation of the vascular network. Perfusion of fluorescently labeled fatty acid analog through vessels resulted in the accumulation of the fatty acid in adipocytes, confirming the functionality of the adipose microtissue. In conclusion, this work presented adipose tissue models within a microfluidic device that can potentially be utilized for on-chip drug screening, as well as provide insights into the engineering of complex tissues.
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Title: Gradient Hydrogels for Neovascularization of Engineered Tissues
Creator: He, Yusheng Jason
Date: 2020
Description: The inability to induce extensive and perfusable microvasculature within complex engineered tissues that possess spatial variations in...
Show moreThe inability to induce extensive and perfusable microvasculature within complex engineered tissues that possess spatial variations in mechanical properties, physical architecture and biochemical composition remains as a major hurdle to their clinical translation. Biomaterial strategies focused on designing scaffolds with physiologically relevant gradients provide a promising means for elucidating 3D vascular cell responses to spatial and temporal variations in matrix properties. This work developed a cell-laden hydrogel platform with tunable decoupled and combined gradients of multiple matrix properties critical for maintenance of long term-vascular cell viability, adhesion, migration and invasion outgrowth to elucidate the impact of gradient matrix cues on 3D neovascularization in culture. This was achieved through the completion of three specific aims. First, a novel ascending frontal polymerization (AFP) technique was developed to generate gradient-based PEG hydrogel scaffolds with tunable individual and combined matrix gradients. Using programmable syringe pumps to control the delivery of precursors with distinct composition during crosslinking, we were able to generate gradient scaffolds with decoupled spatial variations in the immobilized concentration of the RGD cell adhesion peptide ligand and elastic modulus. Using this approach, the slope and magnitude of the imposed RGD gradients were readily manipulated without inducing variations in elastic modulus. Vascular spheroids inserted into gradient hydrogel scaffolds supported 3D vascular sprout formation, while the immobilized RGD gradient promoted an increase in sprout length towards the imposed gradient. Next, to create cell-laden scaffolds photopolymerization conditions were optimized to enable viable cell encapsulation during scaffold fabrication. To achieve this, an experimental sensitivity analysis combined with the design of experiments (DOE) was implemented to design isotropic hydrogel scaffolds with a broad range of matrix properties (elastic modulus, immobilized RGD and proteolytic degradation) that supported vascular sprouting in 3D culture. We examined the individual and interaction effects of each matrix property and demonstrated that an optimal combination associated with increases in immobilized RGD and proteolytic degradation of mediate synergistic enhancements in 3D vascular sprouting. Based on the findings from this in vitro study with isotropic hydrogel scaffolds, we designed scaffolds with 5 types of gradient combinations in immobilized RGD, stiffness and protease-sensitivity and explored the impact of spatial variations these matrix cues on vascular sprouting within the constructs in 3D culture. Specifically, we created hydrogel scaffolds with gradients in immobilized RGD with (1) steep and (2) shallow slopes, (3) gradients in elastic modulus, (4) gradients in protease-sensitivityand and (5) opposing gradients of RGD and modulus and concurrent gradients of protease sensitivity and RGD. By encapsulating vascular spheroids in different regions of each gradient scaffold, we observed spatial variations in total sprout length within all gradient scaffolds. We also found that RGD gradient and combined gradient scaffolds induced biased vascular sprouting toward increased RGD concentration and that biased sprouting was enhanced by gradient magnitude and slopes of immobilized RGD concentration. Conversely, directional sprouting responses diminished in scaffolds possessing opposing gradients in RGD (with concurrent gradients of degradation) and modulus. The presented work is the first to demonstrate the use of a cell-laden biomaterial platform to explore the impact of gradients in RGD, proteolytic degradation, and stiffness on vascular sprouting responses in 3D culture. The presented platform and findings of this thesis work hold great potential in the fields of tissue engineering specifically for prevascularization of complex tissues that possess spatial variations in mechanical properties, degradation rate and adhesion ligand composition to facilitate their regeneration.
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Title: MULTIVARIABLE SIMULATION PLATFORM FOR TYPE 1 DIABETES AND AUTOMATIC MEAL HANDLING IN ARTIFICIAL PANCREAS SYSTEMS
Creator: Samadi, Sediqeh
Date: 2019
Description: Artificial pancreas (AP) systems are designed to automate the glucose control in type 1 diabetes mellitus (T1DM). Multivariable artificial...
Show moreArtificial pancreas (AP) systems are designed to automate the glucose control in type 1 diabetes mellitus (T1DM). Multivariable artificial pancreas systems have evolved to incorporate various additional physiological measurements beyond the conventional continuous glucose monitoring measurements to better integrate information on the metabolic state of the patients affecting the glycemic dynamics. The changes in the physiological measurements such as heart rate, energy expenditure, skin temperature, and skin conductance measured by wearable devices are indicative of the changes in the metabolic state. The controller receives the physiological measurements in the feed forward manner which accelerates the remedy control decision in response to the disturbances. Although various AP systems are proposed in the literature to accommodate these additional sources of information, the testing and evaluation of these advanced multivariable AP systems are hindered by the requirements of conducting time-consuming and expensive clinical trials. Development of a simulation platform for rapid prototyping and iterative development of AP systems is one of the main contributions of this study. Simulation platform for T1DM includes a compartmental model generating glucose concentration in response to physical activity in addition to meals and infused insulin. The proposed exercise-glucose-insulin model is an extension of the previously developed glucose-insulin model to derive transient variations in glycemic dynamics caused by physical activity and to improve the glucose prediction accuracy. Physiological variables affected by physical activity, such as heart rate, skin temperature, and blood volume pulse are generated in addition to the glucose concentration in the simulator. The simulation platform includes several virtual patients providing a reliable platform for in silico evaluation of different algorithms proposed for automation of glucose control in T1DM. The multivariable simulator will accelerate the development of next-generation artificial pancreas systems.The development of a disturbance detection algorithm is the other contribution of this study. Meals are major disturbances to the glucose homeostasis, and automated detection of meal consumption and carbohydrate estimation of the consumed meal are critical for fully automated artificial pancreas control systems. In this study, a detection algorithm integrating fuzzy logic classification and qualitative analysis is proposed. A fuzzy logic system estimates the carbohydrate content of the meal.
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Title: Incorporating Real-Time Estimates of Physiological States in Artificial Pancreas Systems
Creator: Sevil, Mert
Date: 2020
Description: Type-1 diabetes is a chronic disease that has a negative impact on the life of a person with diabetes causing other chronic diseases, reducing...
Show moreType-1 diabetes is a chronic disease that has a negative impact on the life of a person with diabetes causing other chronic diseases, reducing the quality of life, and the possibility of causing dangerous reductions in blood glucose levels that may lead to coma or death. More than 100 million U.S. adults are now living with diabetes or pre-diabetes. Diabetes is one of the most expensive public health problems in the U.S. at $327 billion in 2017. Thus, alternative solutions or novel proposals are crucial to more effective treatments and cure. Artificial pancreas systems are one of the common treatment techniques of Type-1 Diabetes, which reduce the risk of diabetes-related complications and make diabetics' lives easier and make it convenient. Artificial pancreas systems aim to maintain blood glucose concentrations in a tighter target blood glucose range, which is a challenging problem. Several factors affect blood glucose concentrations including intensity of exercise, type of exercise, acute psychological stress and the physical state of a person with diabetes. These factors are unknown disturbances for artificial pancreas control systems. In this project, a single non-invasive wrist-worn device is used to obtain different biosignals in-real time. Biosignals are utilized with the development energy expenditure estimation model, psychological stress detection and physical state classification models. Several machine learning methods are tested and validated until the best classification and estimation accuracy is achieved for each estimate. Obtained models are incorporated with the current artificial pancreas design to improve its glycemic control performance. The controller is aware of such measurable disturbances with the proposed method, which allows for providing accurate and timely control action. Additional estimates are utilized to improve blood glucose concentration prediction model accuracy. Clinical trials are used to test and validate the proposed work. In summary, the presented work illustrates different machine learning techniques and algorithms that can enhance automated insulin delivery by a multivariable artificial pancreas system and enhance the quality of life of people with Type 1 diabetes.
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Title: Quantification of Vascular Permeability in the Retina Using Fluorescein Videoangiography Data as a Biomarker for Early Diabetic Retinopathy
Creator: Kayaalp Nalbant, Elif
Date: 2023
Description: Diabetic retinopathy, which is the most common reason for blindness in the working-age population, affects over one-third of those who have...
Show moreDiabetic retinopathy, which is the most common reason for blindness in the working-age population, affects over one-third of those who have had diabetes for over ten years. High blood sugar level (hyperglycemia) in the blood damages blood vessels and tight junction at the blood-retinal barrier (BRB). Chronic inflammation leads to changes in vascular health, and over time blood vessels tend to get damaged and exhibit higher “leakage” or permeability. In the late stage of DR, hemorrhages can occur, leading to irreversible damage of neuronal tissue in the retina and vision loss. In the clinic, there are some biomarkers and imaging modalities used to diagnose DR based on some of the more severe products of DR (e.g., hemorrhage), but there is no non-invasive, highly sensitive method to detect diabetic retinopathy before clinical signs occur, when mitigating therapies could be more effective. In this thesis, indicator dilution theory was explored to modeling the temporal dynamics of fluorescein in the retina after intravenous injection, with an aim to quantitatively map subtle changes in retinal blood flow and vascular permeability that could preempt subsequent irreversible damage. Specifically, a simplified version of indicator dilution theory—namely the “adiabatic approximation in tissue homogeneity” (AATH) model—was used to estimate physiological parameters such as the blood flow (F) and the extraction fraction (E: a parameter coupled with vascular permeability) from retinal fluorescein videoangiography data. The AATH fitting protocol was optimized through simulations using a more complex model (the AATH-vascular heterogeneity model, AATH-VH). It was determined that a two-step least square fitting method was more sensitive than a single-step least square fitting of AATH to simulated data to evaluate vascular permeability in early diabetic retinopathy. The optimized data analysis protocol was then evaluated in an initial clinical study comparing healthy control subjects to those with moderate non-proliferative DR. Volumetric blood flow and retinal vascular permeability maps were compared between patient groups with clear increases in extraction fraction observed in the mild NPDR patients compared to control. These promising early data have been the foundation to an ongoing 5 year study tracking 100 Diabetic patients with no DR so see if early changes in vascular permeability can predict which patients are more likely to progress to DR.
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Title: Development of MIITRA T1w, DTI and FOD templates of the older adult brain in a common space
Creator: Wu, Yingjuan
Date: 2022
Description: Human brain atlases play an important role in neuroimaging studies and are commonly used as references for spatial normalization, tissue...
Show moreHuman brain atlases play an important role in neuroimaging studies and are commonly used as references for spatial normalization, tissue segmentation, automated brain parcellation, seed selection for functional connectivity analyses and fiber-tracking, or standards for algorithm evaluation. A brain atlas typically consists of brain templates of different imaging modalities in a common space and semantic labels that delineate brain regions according to the characteristics of the underlying tissue.High-quality T1-weighted (T1w) and diffusion tensor imaging (DTI) brain templates that are representative of the individuals under study enhance the accuracy of template-based neuroimaging investigations, and when they are also located in a common space they facilitate optimal integration of information on brain morphometry and diffusion characteristics. However, such multimodal templates have not been constructed for the brain of older adults. This thesis introduced an iterative method for construction of multimodal T1w and DTI templates that aims at maximizing the quality of each template separately as well as the spatial matching between templates. The performance of the proposed method was evaluated across iterations and was compared to the performance of state-of-the-art multimodal template construction approaches based on multichannel registration. Using the proposed method, along with other recently developed techniques, high-quality T1w and DTI templates of the older adult brain were developed in a common space at 0.5mm resolution for the MIITRA atlas. In this thesis, the new templates were compared to other available templates in terms of the image quality, inter-subject and inter-modality spatial normalization accuracy achieved when used as a reference, and the representativeness of the older adult brain. Furthermore, as fiber orientation distribution (FOD) model is capable of resolving intravoxel heterogeneity, which overcomes the limitations of the DTI model especially in regions with complex neuronal microarchitecture, FOD template is in high demand to facilitate FOD-based, fixel-based analyses, white matter connectivity studies and white matter parcellations. In this thesis, several FOD template construction methods were compared and a FOD template was developed at 0.5mm resolution for the MIITRA atlas. Overall, the present work brought new insights into multimodal template construction, conducted a thorough, quantitative evaluation of available multimodal template construction methods, and generated much-needed high quality T1w, DTI and FOD templates of the older adult brain in a common space with 0.5mm resolution.
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Title: SIMULTANEOUS RELEASE OF BIOACTIVE AFLIBERCEPT AND DEXAMETHASONE FROM A MICROSPHERE- AND NANOPARTICLE-HYDROGEL OCULAR DRUG DELIVERY SYSTEM FOR THE ENHANCED TREATMENT OF NON-RESPONSIVE PATIENTS WITH CHOROIDAL NEOVASCULARIZATION
Creator: Rudeen, Kayla M
Date: 2022
Description: There is a growing subset of wet age-related macular degeneration (AMD) patients who do not fully respond to standard of care treatment, which...
Show moreThere is a growing subset of wet age-related macular degeneration (AMD) patients who do not fully respond to standard of care treatment, which consists of bimonthly/monthly bolus intravitreal injections of anti-vascular endothelial growth factors (anti-VEGFs). Some of these patients may respond to a combination therapy of anti-VEGF and corticosteroids. One treatment option uses a dexamethasone implant that releases for six months. This regimen, however, requires both the bimonthly/monthly intravitreal injections of anti-VEGF and semiannual intravitreal injections of the dexamethasone implant. Combining the two treatments into a single drug delivery system (DDS) would reduce the total number of injections, reducing the risk of potential complications (endophthalmitis, retinal detachment, intravitreal hemorrhage, increased intraocular pressure, and cataract) as well as the socioeconomic burden of treatment.The overarching goal of this study was to develop a single DDS that simultaneously releases anti-VEGF (aflibercept) and corticosteroid (dexamethasone) for the treatment of non-responsive wet AMD patients. Our laboratory previously developed a thermoresponsive, biodegradable microparticle-hydrogel DDS that releases anti-VEGF over a period of six months. The aims of the study were to (1) modify this system to include dexamethasone-loaded nanoparticles, optimize release kinetics for both drugs, and characterize the DDS; (2) evaluate the in vivo treatment efficacy in a laser-induced choroidal neovascularization (CNV) model; and (3) investigate the impacts of temperature and storage on the DDS integrity.
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Title: DEVELOPMENT AND EVALUATION OF MRI TEMPLATES OF THE MIITRA ATLAS
Creator: RIDWAN, ABDUR RAQUIB
Date: 2021
Description: Digital human brain atlases play a pivotal role in conducting wide range of neuroimaging studies and are commonly used as references for...
Show moreDigital human brain atlases play a pivotal role in conducting wide range of neuroimaging studies and are commonly used as references for spatial normalization in voxel-wise analysis, region-of interest analyses, automated tissue-segmentation, functional connectivity analyses, etc. A brain atlas typically consists of MRI-based multi-modal templates and semantic labels delineating brain regions according to the characteristics of the underlying tissue. In recent times there has been a plethora of magnetic resonance imaging (MRI) studies on older adults without dementia to explore the role of brain characteristics associated with cognitive functions in old age with the ultimate goal to develop strategies for prevention of cognitive decline. Increasing the accuracy in terms of sensitivity and specificity of such neuroimaging studies require an atlas with a comprehensive set of high-quality templates representative of the brain characteristics typical of older adults and detailed labels accurately mapping brain regions of interest. However, such an atlas has not been constructed for older adults without dementia. Hence this thesis aims to build high quality MRI templates which are the cornerstone resources needed for the development of a comprehensive, high quality, multi-channel, longitudinal, probabilistic digital human brain atlas for older adults termed as Multi-channel Illinois Institute of Technology and Rush University Aging (MIITRA) atlas. This dissertation focuses on a) to develop and evaluate a high performing 1mm isotropic structural T1-weighted brain template, b) to investigate the development and evaluation of a spatio-temporally consistent longitudinal structural T1-weighted template of the older adult brain, c) to develop and evaluate an unbiased 0.5 mm isotropic super-resolved high resolution and detail-preserving structural T1 weighted template of the older adult brain, d) to develop an unbiased 0.5 mm super-resolved high resolution and detail-preserving structural PD weighted and T2-weighted template of the older adult brain, e) to investigate and provide future directions in the development of a 0.5 mm super-resolved high resolution DTI template of the older adult brain, and f) to construct a novel approach in the development of MRI templates using both space and frequency information of spatially normalized older adult data. The thesis based on the aforementioned foundational points was constructed as follows: Firstly, this thesis presents the development of a 1mm isotropic T1-weighted structural template of the older adult brain utilizing state of the art registration algorithm ANTs with parameters carefully optimized for older adults, in an iterative groupwise spatial normalization framework. The preprocessing steps were also thoroughly investigated to ensure high quality data. It was demonstrated through systematic comparison of this new template to several other standardized and study-specific T1-weighted templates that a) it exhibited high image sharpness, b) allowed for high spatial normalization accuracy and detection of smaller inter-group morphometric differences compared to other standardized templates, c) had similar performance to that of study-specific templates and d) was highly representative of the older adult brain. Secondly, with the acquired technical know-how from the aforementioned research findings a new method was introduced for the construction of a spatio-temporally consistent longitudinal template based on high quality cross-sectional older adult data from a large cohort. The new template was compared to templates generated with previously published methods in terms of spatio-temporal consistency and image quality and was shown to have superior performance. In addition, a novel approach was introduced for image quality enhancement of the longitudinal templates utilizing both space and frequency information. Thirdly, the thesis presents a method that involves a) thoroughly refining registration parameters, b) patch-based tissue-guided sparse-representation approach in a super-resolved unbiased minimum deformation space to construct and evaluate an unbiased 0.5 mm isotropic super-resolved high resolution and detail-preserving structural T1 weighted template of the older adult brain. This method accounts for misregistration specially in the cortical regions, ensuring sharp delineation of structures representative of the older adult brain. The new template developed using this approach maintained high anatomical consistency with sharp and detailed cortical features in the brain and exhibited higher image sharpness compared to other high-resolution standardized templates and allowed for high spatial normalization accuracy when used as a reference for normalization of older adult data. Additionally, this approach of template building was investigated on DTI tensors of older adult participants, and the constructed DTI template was shown to perform better than templates developed using the best approach currently present in the literature. Finally, the thesis presents the development of an unbiased 0.5 mm super-resolved high resolution and detail-preserving structural PD weighted and T2-weighted template of the older adult brain, from nonlocal super-resolution based upsampled PD and T2w older adult participant data, using this new template building approach.
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Title: DEVELOPMENT OF FULLY BIOCOMPATIBLE HYDROGEL NANOPARTICLE FORMULATIONS FOR CONTROLLED-RELEASE DELIVERY OF A WIDE VARIETY OF BIOMOLECULES
Creator: Borges, Fernando Tancredo Pereira
Date: 2020
Description: In recent years, our group has focused on the production of PEGDA-based hydrogel scaffolds and nanoparticles for drug delivery of small...
Show moreIn recent years, our group has focused on the production of PEGDA-based hydrogel scaffolds and nanoparticles for drug delivery of small molecules. However, with recent advances in modern therapeutic treatments, such as protein and genetic engineering, there is an increasing need for the development of drug delivery devices that would be able encapsulate larger molecules. Therefore, the goal of this thesis work was to develop a systematic way to produce fully biocompatible PEGDA-based hydrogel nanoparticle formulations that would be able to encapsulate any size molecule, ranging from small ionic molecules, to peptides and proteins, all the way to large nucleic acids, and deliver it in a controlled manner.The first of part of this work consisted of developing a stable and reproducible process for the production of hydrogel PPi-NPs. Initial studies were done in order to assess the influence of phosphate salts in the polymerization system and it was found that both monophosphate and polyphosphate salts significantly damper the NVP homo-polymerization kinetics, but do not affect the co-polymerization of NVP and PEGDA. Then, emulsion stability studies were done to determine whether phosphate salts affected the stability of the minimeulsion system used in the production of the nanoparticles. Cloud point measurements and droplet size screening measurements showed that by transitioning from a Pi-loaded emulsion system to a PPi-loaded emulsion system, the required HLB of the emulsion shifts by 1.5 points. Upon correction for that shift, a reproducible process for production of PPi-loaded nanoparticles was obtained. A parametric study was then performed to see how the different process parameters affected the different properties of the produced particles. The second part of the work consisted in developing a platform for encapsulation of large to very-large molecules within these hydrogel systems. A new set of equations was developed for better estimation of the interstitial space, available for encapsulation of molecules, of crosslinked polymers that used very high molecular weight crosslinkers and/or high amounts of crosslinker. Upon development of this new set of equations, hydrogel discs were made via photopolymerization in order to validate the equations. By introducing a third monomer, EGA, and varying the molecular weight and concentration of the crosslinker, hydrogels with a wide range of mesh dimensions from 25 to 700 were achieved. These gels were then used to encapsulate 4 different sample molecules of varying molecular weights and size. A new heuristic was developed for encapsulation of non-spherical molecules, where the aspect ratios of the molecule and of the polymer network are considered. By varying the size of the ratios of the dimensions of the hydrogel network to the dimensions of the molecule, significantly different release profiles of small molecules, peptides and oligonucleotides were obtained. Finally, in order to explore different administration routes, the process was transitioning into being fully biocompatible. The organic solvent previously used in the emulsion system was replaced by soybean oil and the surfactants were replaced by a food-grade surfactant, PGPR, to form Bio-Compatible Nanoparticle Emulsions (BCNEs). Qualitative release from the BCNEs was shown. A new method for quantitative measuring of release from BCNE was developed. Release from QK-BCNE was observed up to 46 days, which is unprecedented for sustained-release and revolutionary for the field. A BCNE spreadable ointment formulation was also developed.
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