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Title: DETERMINING CELL STIFFNESS USING MICROFLUIDICS
Creator: Penumarthy, Vineet Shyam
Date: 2019
Description: Sorting healthy cells from diseased cells is critical to detecting diseases and treating them before damage is done to a patient. These...
Show moreSorting healthy cells from diseased cells is critical to detecting diseases and treating them before damage is done to a patient. These diseases can be characterized based upon proteins, cytokines, DNA, pathology, blood tests, etc. However, another way of detecting them is using the mechanical properties of a cell, specifically the cell stiffness. In this study, a long microfluidic channel was designed, fabricated, and tested for flow using 6.7 µm polystyrene beads. Following this, Caco-2 cells and preadipocytes were flown through the channel and the travel time each cell took to flow through the channel was recorded, along with its cell diameter. The cells were then treated with blebbistatin, a myosin-II inhibitor, in order to soften the cell actin cytoskeleton and reduce the cell stiffness and were then flown through the channel again and the times taken to flow through were again recorded. We hypothesized that the stiffer a cell, the longer it would take to flow through the channel. From the results obtained using Caco-2 cells, we found that the blebbistatin treated cell times were much lower than the untreated cells, thus indicating that our hypothesis is true.
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Title: EXPRESSION OF PPAR-γ AND PGC-1α TO INFLAMMATION IN HEPATOCYTES
Creator: HE, QIFAN
Date: 2019
Description: In this study, we examined that Proliferator-Activated Receptor γ (PPAR-γ) and Peroxisome Proliferator-Activated Receptor γ Coactivator 1-α ...
Show moreIn this study, we examined that Proliferator-Activated Receptor γ (PPAR-γ) and Peroxisome Proliferator-Activated Receptor γ Coactivator 1-α (PGC1α) protein expression in hepatocytes have different degrees of expression to Tumor Necrosis Factor α (TNFα) and rosiglitazone. To verify this objective, we employed lentivirus, instead of traditional plasmids, to transfect human hepatocytes (HepG2). Fluorescence-related protein of PPAR-γ and PGC-1α were delivered to hepatocytes, and inflammation was induced by adding TNFα and rosiglitazone to the medium. We successfully designed and created the lentivirus with high delivery efficiency, and determined that the test was true, indicating that PPAR-γ and PGC-1α proteins have different expression to inflammation in human hepatocytes.
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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: Ultrasensitive protein quantification using Rolling Circle Amplification
Creator: Hetzel, Laura Ann
Date: 2019
Description: There are several protein biomarkers that can aid in diagnosing and evaluating the progression of Alzheimer’s Disease (AD), including Amyloid...
Show moreThere are several protein biomarkers that can aid in diagnosing and evaluating the progression of Alzheimer’s Disease (AD), including Amyloid Beta-42 (Aβ42), Amyloid Beta-40 (Aβ40), and Tau proteins. The proteins are most prevalent in the brain and cerebral spinal fluid, becoming more diluted in the bloodstream. Since diagnosis and progression would require evaluating and comparing protein levels over time and identifying miniscule changes, an assay with high sensitivity is paramount. Similarly, evaluating how a drug treatment affects the levels of protein requires a highly sensitive assay. Currently, enzyme-linked immunosorbent assay (ELISA) is accepted as the most sensitive assay for protein detection and quantification. However, in the case of Aβ40 and Aβ42 proteins, oftentimes the levels of the proteins in patients are very close to the sensitivity of the commercial ELISA. The uncertainty in these measurements is very high, which results in reporting of conflicting outcomes. One of the challenges of quantifying proteins is that proteins, unlike nucleic acids, cannot be amplified. To overcome this limitation, we have cleverly pseudo-amplified proteins using rolling circle amplification (RCA). By doing so, we have demonstrated a ten to forty times improvement in sensitivity over ELISA and radioimmunoassays. In previous experiments, C-peptide has been used as the protein of interest, and ELISA reports the smallest detectable quantity is 0.01 ng in buffer. Using RCA, we have found that as little as 0.00075 ng C-peptide in buffer could be quantified, and 0.004 ng in 10% serum could be quantified. The same process can be applied to other proteins such as Aβ40 and Aβ42, and the results are expected to be similar. In fact, we have measured Type I Diabetes autoantibodies with approximately forty times improvement over the gold standard radioimmunoassay. With excellent results in buffer and 10% serum, expansion to human samples holds great potential. If the human experiments are as successful as anticipated, RCA could be used to precisely evaluate the effect of a drug on protein levels, contributing to the overall evaluation of the success of the drug.
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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: IMPACT OF DATA SHAPE, FIDELITY, AND INTER-OBSERVER REPRODUCIBILITY ON CARDIAC MAGNETIC RESONANCE IMAGE PIPELINES
Creator: Obioma, Blessing Ngozi
Date: 2020
Description: Artificial Intelligence (AI) holds a great promise in the healthcare. It provides a variety of advantages with its application in clinical...
Show moreArtificial Intelligence (AI) holds a great promise in the healthcare. It provides a variety of advantages with its application in clinical diagnosis, disease prediction, and treatment, with such interests intensifying in the medical image field. AI can automate various cumbersome data processing techniques in medical imaging such as segmentation of left ventricular chambers and image-based classification of diseases. However, full clinical implementation and adaptation of emerging AI-based tools face challenges due to the inherently opaque nature of such AI algorithms based on Deep Neural Networks (DNN), for which computer-trained bias is not only difficult to detect by physician users but is also difficult to safely design in software development. In this work, we examine AI application in Cardiac Magnetic Resonance (CMR) using an automated image classification task, and thereby propose an AI quality control framework design that differentially evaluates the black-box DNN via carefully prepared input data with shape and fidelity variations to probe system responses to these variations. Two variants of the Visual Geometric Graphics with 19 neural layers (VGG19) was used for classification, with a total of 60,000 CMR images. Findings from this work provides insights on the importance of quality training data preparation and demonstrates the importance of data shape variability. It also provides gateway for computation performance optimization in training and validation time.
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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: SUSTAINED RELEASE OF PHOSPHATE-BASED THERAPEUTICS FOR ATTENUATION OF PATHOGEN-INDUCED PROTEOLYTIC MATRIX DEGRADATION
Creator: Bittencourt Pimentel, Marja
Date: 2019
Description: Loss of the normal intestinal microbiome community structure and its replacement by pathogenic microbes contributes to severe persistent...
Show moreLoss of the normal intestinal microbiome community structure and its replacement by pathogenic microbes contributes to severe persistent inflammation in diseases such as ulcerative colitis and inflammatory bowel disease. While host-derived proteases are known to contribute to this pathogenesis, the role of increased production of microbial-secreted proteases due to virulent phenotypes remains unclear. Following surgical removal of diseased intestinal tract, increased bacterial protease expression is a key phenotype involved in intestinal healing impairment. Antibiotic administration is ineffective for treating these complications as it inadvertently eliminates normal flora while allowing pathogenic bacteria to acquire antibiotic resistance. Prior research has shown that intestinal phosphate depletion in the surgically stressed host triggers bacterial virulence which is suppressed under phosphate abundant conditions. To address this issue our previous work has demonstrated that the use of free monophosphate (-Pi) and polyphosphate (-PPi), as well as post-loaded PPi nanoparticles (NP-PPi) attenuate collagenase production of gram-negative (Pseudomonas aeruginosa and Serratia marcescens) but not gram-positive (Enterococcus faecalis) pathogens expressing high collagenolytic activity. Due to the variation in phosphate metabolism among microbial species we investigated the in vitro efficacy of a combination treatment of phosphates delivered in a sustained release format using NP-PPi and NP-Pi on collagenase and biofilm attenuation across gram-positive and gram-negative test pathogens.Collagenase screening was assessed using two in vitro models. The first in vitro assay involved culturing pathogens in the presence and absence of NP-Pi and/or NP-PPi treatment using two-dimensional (2D) commercially available fluorogenic protease-sensitive peptide substrates. Although these substrates are among the most commonly used for screening protease activity and inhibition in vitro, their application does not translate to three-dimensional (3D) matrix degradation. Additionally, the addition of drug-loaded nanoparticles directly in bacterial culture does not recapitulate the in vivo sustained release of phosphates due to nanoparticles embedded within tissue. Thus, the second model involved the development of a novel cell culture platform which utilized a proteolytically degradable hydrogel scaffold and a non-degradable nanocomposite hydrogel scaffold. In this assay NP-Pi and NP-PPi were entrapped in a non-degradable poly(ethylene) glycol (PEG) hydrogel to form of a nanocomposite matrix which served as a reservoir for sustained release of phosphates. Bacteria producing high levels of proteases were cultured in the presence of the nanocomposite phosphate releasing reservoir and the proteolytically degradable PEG hydrogel scaffold to determine the efficacy of sustained release of phosphates in attenuating proteolytic hydrogel degradation. To correlate matrix degradation with bacterial enzymes secreted in the culture medium, we also developed a method to efficiently measure hydrogel degradation rate until complete material degradation with a greater degree of accuracy compared to the commonly employed method utilizing gravimetric measurements in gel wet weight. Combined, the in vitro platform and our proposed degradation assay provide a novel approach for screening the effect of therapeutics for attenuation of bacterial protease-induced matrix degradation.The 2D in vitro study demonstrated that the combination treatment (NP-PPi + NP-Pi) confers broad spectrum efficacy for suppression of collagenase and biofilm production across test pathogens. Conversely, the 3D in vitro model demonstrated that the combination treatment (NP-PPi + NP-Pi) attenuated protease production for gram-negative pathogens, while the gram-positive test pathogen exhibited significant decreases in protease levels only in the presence of NP-Pi. Finally, our novel Sirius red absorbance assay for quantifying hydrogel degradation was found to provide greater accuracy when compared to gravimetric measurements in gel wet weight. It also enabled real-time monitoring of 3D matrix degradation kinetics as well as the time required for complete material dissolution in the presence of bacterial proteases and active human MMP-9 enzyme solutions. These findings highlight the importance of designing relevant in vitro platforms for screening therapeutic efficacy in the presence of cells and nanomaterials.
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Title: Wireless Body Sensor Network for Tracking Human Mobility using Long Short-Term Memory Neural Network for Classification
Creator: Gupta, Saumya
Date: 2019
Description: A large number of sensors are used without justification of the number chosen or placement choice. Many papers about body sensor networks...
Show moreA large number of sensors are used without justification of the number chosen or placement choice. Many papers about body sensor networks explore how to capture a type or types of motion, but all their sensors are placed in different locations; making their algorithms very specific to that movement. In this research, we explore the enhancement of human activity classification algorithm using long short-term memory (LSTM) neural network and wearable sensor network. There are five identical nodes used in the body sensor network to collect data. Each node incorporates an ESP8266 Microcontroller with Wi-Fi which is connected to an inertial measurement unit consisting of triple axis accelerometer and gyroscope sensor board. An analysis on the accuracy that each sensor node provides separately and in different combinations has been conducted to allow future research to focus their positioning in optimal positions. A Robot Operating System (ROS) central node is used to illustrate the in-built multi-threading capability. For demonstration, the positions chosen are waist, ankles and wrists. The raw sensor data can be observed on screen while it is being labelled live to create fitting dataset for developing an artificial neural network. Expectation is that increasing the number of sensors should raise the overall accuracy of the output but that isn’t the case observed, positioning of the sensor is pertinent to improvement. These platforms can be further extended to understand different motions and different sensor positions, also expanded to include other sensors.
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