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- All Subjects: Bioengineering
- All Subjects: Microparticles
- Creators: Stabenfeldt, Sarah
Description
The research question explored in this thesis is how CRISPR mediated editing is influenced by artificially opened chromatin in cells. Closed chromatin poses a barrier to Cas9 binding and editing at target genes. Synthetic pioneer factors (PFs) are a promising new approach to artificially open condensed heterochromatin allowing greater access of target DNA to Cas9. The Haynes lab has constructed fusions of enzymatic chromatin-modifying domains designed to remodel chromatin and increase Cas9 editing efficiency. With a library of PFs available, this research focuses on analyzing the behavior of Cas9 in chromatin that has been artificially opened by PFs. The types and frequency of INDELs (insertions & deletions) were determined after non-homologous end joining (NHEJ) in PF and Cas9-treated cells using quantitative Sanger sequencing and Synthego’s ICE software. Furthermore, NOME-seq analysis was carried out to map nucleosome position in PF and Cas9 treated cells. Although this experiment was unsuccessful, the heat map generated with data obtained from Synthego ICE predicts a possible presence of nucleosome in the vicinity suggesting that perhaps a fully open chromatin state was not achieved. Linear Regression analysis with certain assumptions confirms that with the increase in distance downstream of cut-site, the editing frequency decreases exponentially. Nevertheless, further experimental work should be carried out to investigate this hypothesis.
ContributorsHamna, Syeda Fatima (Author) / Haynes, Karmella A (Thesis advisor) / Stabenfeldt, Sarah (Thesis advisor) / Tian, Xiaojun (Committee member) / Arizona State University (Publisher)
Created2019
Description
Myocardial infarction (MI) remains the leading cause of mortality and morbidity in the U.S., accounting for nearly 140,000 deaths per year. Heart transplantation and implantation of mechanical assist devices are the options of last resort for intractable heart failure, but these are limited by lack of organ donors and potential surgical complications. In this regard, there is an urgent need for developing new effective therapeutic strategies to induce regeneration and restore the loss contractility of infarcted myocardium. Over the past decades, regenerative medicine has emerged as a promising strategy to develop scaffold-free cell therapies and scaffold-based cardiac patches as potential approaches for MI treatment. Despite the progress, there are still critical shortcomings associated with these approaches regarding low cell retention, lack of global cardiomyocytes (CMs) synchronicity, as well as poor maturation and engraftment of the transplanted cells within the native myocardium. The overarching objective of this dissertation was to develop two classes of nanoengineered cardiac patches and scaffold-free microtissues with superior electrical, structural, and biological characteristics to address the limitations of previously developed tissue models. An integrated strategy, based on micro- and nanoscale technologies, was utilized to fabricate the proposed tissue models using functionalized gold nanomaterials (GNMs). Furthermore, comprehensive mechanistic studies were carried out to assess the influence of conductive GNMs on the electrophysiology and maturity of the engineered cardiac tissues. Specifically, the role of mechanical stiffness and nano-scale topographies of the scaffold, due to the incorporation of GNMs, on cardiac cells phenotype, contractility, and excitability were dissected from the scaffold’s electrical conductivity. In addition, the influence of GNMs on conduction velocity of CMs was investigated in both coupled and uncoupled gap junctions using microelectrode array technology. Overall, the key contributions of this work were to generate new classes of electrically conductive cardiac patches and scaffold-free microtissues and to mechanistically investigate the influence of conductive GNMs on maturation and electrophysiology of the engineered tissues.
ContributorsNavaei, Ali (Author) / Nikkhah, Mehdi (Thesis advisor) / Brafman, David (Committee member) / Migrino, Raymond Q. (Committee member) / Stabenfeldt, Sarah (Committee member) / Vernon, Brent (Committee member) / Arizona State University (Publisher)
Created2018
Description
Monitoring complex diseases and their comorbidities requires accurate and convenient measurements of multiple biomarkers. However, many state-of-the-art bioassays not only require complicated and time-consuming procedures, but also measure only one biomarker at a time. This noncomprehensive single-biomarker monitoring, as well as the cost and complexity of these bioassays advocate for a simple, rapid multi-marker sensing platform suitable for point-of-care or self-monitoring settings. To address this need, diabetes mellitus was selected as the example complex disease, with dry eye disease and cardiovascular disease as the example comorbidities. Seven vital biomarkers from these diseases were selected to investigate the platform technology: lactoferrin (Lfn), immunoglobulin E (IgE), insulin, glucose, lactate, low density lipoprotein (LDL), and high density lipoprotein (HDL). Using electrochemical techniques such as amperometry and electrochemical impedance spectroscopy (EIS), various single- and dual-marker sensing prototypes were studied. First, by focusing on the imaginary impedance of EIS, an analytical algorithm for the determination of optimal frequency and signal deconvolution was first developed. This algorithm helped overcome the challenge of signal overlapping in EIS multi-marker sensors, while providing a means to study the optimal frequency of a biomarker. The algorithm was then applied to develop various single- and dual-marker prototypes by exploring different kinds of molecular recognition elements (MRE) while studying the optimal frequencies of various biomarkers with respect to their biological properties. Throughout the exploration, 5 single-marker biosensors (glucose, lactate, insulin, IgE, and Lfn) and one dual-marker (LDL and HDL) biosensor were successfully developed. With the aid of nanoparticles and the engineering design of experiments, the zeta potential, conductivity, and molecular weight of a biomarker were found to be three example factors that contribute to a biomarker’s optimal frequency. The study platforms used in the study did not achieve dual-enzymatic marker biosensors (glucose and lactate) due to signal contamination from localized accumulation of reduced electron mediators on self-assembled monolayer. However, amperometric biosensors for glucose and lactate with disposable test strips and integrated samplers were successfully developed as a back-up solution to the multi-marker sensing platform. This work has resulted in twelve publications, five patents, and one submitted manuscripts at the time of submission.
ContributorsLin, Chi En (Author) / La Belle, Jeffrey T (Thesis advisor) / Caplan, Michael (Committee member) / Cook, Curtiss B (Committee member) / Stabenfeldt, Sarah (Committee member) / Spano, Mark (Committee member) / Arizona State University (Publisher)
Created2018
Description
The primary objective of this research project is to develop dual layered polymeric microparticles with a tunable delayed release profile. Poly(L-lactic acid) (PLA) and poly(lactic-co-glycolic acid) (PLGA) phase separate in a double emulsion process due to differences in hydrophobicity, which allows for the synthesis of double-walled microparticles with a PLA shell surrounding the PLGA core. The microparticles were loaded with bovine serum albumin (BSA) and different volumes of ethanol were added to the PLA shell phase to alter the porosity and release characteristics of the BSA. Different amounts of ethanol varied the total loading percentage of the BSA, the release profile, surface morphology, size distribution, and the localization of the protein within the particles. Scanning electron microscopy images detailed the surface morphology of the different particles. Loading the particles with fluorescently tagged insulin and imaging the particles through confocal microscopy supported the localization of the protein inside the particle. The study suggest that ethanol alters the release characteristics of the loaded BSA encapsulated in the microparticles supporting the use of a polar, protic solvent as a tool for tuning the delayed release profile of biological proteins.
ContributorsFauer, Chase Alexander (Author) / Stabenfeldt, Sarah (Thesis director) / Ankeny, Casey (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2015-05
Description
With microspheres growing in popularity as viable systems for targeted drug therapeutics, there exist a host of diseases and pathology induced side effects which could be treated with poly(lactic-co-glycolic acid) [PLGA] microparticle systems [6,10,12]. While PLGA systems are already applied in a wide variety the clinical setting [11], microparticles still have some way to go before they are viable systems for drug delivery. One of the main reasons for this is a lack of fabrication processes and systems which produce monodisperse particles while also being feasible for industrialization [10]. This honors thesis investigates various microparticle fabrication techniques \u2014 two using mechanical agitation and one using fluid dynamics \u2014 with the long term goal of incorporating norepinephrine and adenosine into the particles for metabolic stimulatory purposes. It was found that mechanical agitation processes lead to large values for dispersity and the polydispersity index while fluid dynamics methods have the potential to create more uniform and predictable outcomes. The research concludes by needing further investigation into methods and prototype systems involving fluid dynamics methods; however, these systems yield promising results for fabricating monodisperse particles which have the potential to encapsulate a wide variety of therapeutic drugs.
ContributorsRiley, Levi Louis (Author) / Vernon, Brent (Thesis director) / VanAuker, Michael (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
Description
Traumatic brain injury (TBI) is a leading cause of death in individuals under the age of 45, resulting in over 50,000 deaths each year. Over 80,000 TBI patients report long-term deficits consisting of motor or cognitive dysfunctions due to TBI pathophysiology. The biochemical secondary injury triggers a harmful inflammatory cascade, gliosis, and astrocyte activation surrounding the injury lesion, and no current treatments exist to alleviate these underlying pathologies. In order to mitigate the negative inflammatory effects of the secondary injury, we created a hydrogel comprised of hyaluronic acid (HA) and laminin, and we hypothesized that the anti-inflammatory properties of HA will decrease astrocyte activation and inflammation after TBI. C57/BL6 mice were subjected to mild-to-moderate CCI. Three days following injury, mice were treated with injection of vehicle or HA-Laminin hydrogel. Mice were sacrificed at three and seven days post injection and analyzed for astrocyte and inflammatory responses. In mice treated with vehicle injections, astrocyte activation was significantly increased at three days post-transplantation in the injured cortex and injury lesion. However, mice treated with the HA-Laminin hydrogel experienced significantly reduced acute astrocyte activation at the injury site three days post transplantation. Interestingly, there were no significant differences in astrocyte activation at seven days post treatment in either group. Although the microglial and macrophage response remains to be investigated, our data suggest that the HA-Laminin hydrogel demonstrates potential for TBI therapeutics targeting inflammation, including acute modulation of the astrocyte, microglia, and macrophage response to TBI.
ContributorsGoddery, Emma Nicole (Author) / Stabenfeldt, Sarah (Thesis director) / Addington, Caroline (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Polymer drug delivery system offers a key to a glaring issue in modern administration routes of drugs and biologics. Poly(lactic-co-glycolic acid) (PLGA) can be used to encapsulate drugs and biologics and deliver them into the patient, which allows high local concentration (compared to current treatment methods), protection of the cargo from the bodily environment, and reduction in systemic side effects. This experiment used a single emulsion technique to encapsulate L-tyrosine in PLGA microparticles and UV spectrophotometry to analyze the drug release over a period of one week. The release assay found that for the tested samples, the released amount is distinct initially, but is about the same after 4 days, and they generally follow the same normalized percent released pattern. The experiment could continue with testing more samples, test the same samples for a longer duration, and look into higher w/w concentrations such as 20% or 50%.
ContributorsSeo, Jinpyo (Author) / Vernon, Brent (Thesis director) / Pal, Amrita (Committee member) / Dean, W.P. Carey School of Business (Contributor) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
The goal of this research project is to create a Mathcad template file capable of statistically modelling the effects of mean and standard deviation on a microparticle batch characterized by the log normal distribution model. Such a file can be applied during manufacturing to explore tolerances and increase cost and time effectiveness. Theoretical data for the time to 60% drug release and the slope and intercept of the log-log plot were collected and subjected to statistical analysis in JMP. Since the scope of this project focuses on microparticle surface degradation drug release with no drug diffusion, the characteristic variables relating to the slope (n = diffusional release exponent) and the intercept (k = kinetic constant) do not directly apply to the distribution model within the scope of the research. However, these variables are useful for analysis when the Mathcad template is applied to other types of drug release models.
ContributorsHan, Priscilla (Author) / Vernon, Brent (Thesis director) / Nickle, Jacob (Committee member) / Harrington Bioengineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Neurodegenerative diseases such as Alzheimer’s disease, Parkinson’s disease, or amyotrophic lateral sclerosis are defined by the loss of several types of neurons and glial cells within the central nervous system (CNS). Combatting these diseases requires a robust population of relevant cell types that can be employed in cell therapies, drug screening, or patient specific disease modeling. Human induced pluripotent stem cells (hiPSC)-derived neural progenitor cells (hNPCs) have the ability to self-renew indefinitely and differentiate into the various neuronal and glial cell types of the CNS. In order to realize the potential of hNPCs, it is necessary to develop a xeno-free scalable platform for effective expansion and differentiation. Previous work in the Brafman lab led to the engineering of a chemically defined substrate—vitronectin derived peptide (VDP), which allows for the long-term expansion and differentiation of hNPCs. In this work, we use this substrate as the basis for a microcarrier (MC)-based suspension culture system. Several independently derived hNPC lines were cultured on MCs for multiple passages as well as efficiently differentiated to neurons. Finally, this MC-based system was used in conjunction with a low shear rotating wall vessel (RWV) bioreactor for the integrated, large-scale expansion and neuronal differentiation of hNPCs. Finally, VDP was shown to support the differentiation of hNPCs into functional astrocytes. Overall, this fully defined and scalable biomanufacturing system will facilitate the generation of hNPCs and their derivatives in quantities necessary for basic and translational applications.
ContributorsMorgan, Daylin (Author) / Brafman, David (Thesis advisor) / Stabenfeldt, Sarah (Committee member) / Wang, Xiao (Committee member) / Arizona State University (Publisher)
Created2018
Description
Calcium imaging is a well-established, non-invasive or minimally technique designed to study the electrical signaling neurons. Calcium regulates the release of gliotransmitters in astrocytes. Analyzing astrocytic calcium transients can provide significant insights into mechanisms such as neuroplasticity and neural signal modulation.
In the past decade, numerous methods have been developed to analyze in-vivo calcium imaging data that involves complex techniques such as overlapping signals segregation and motion artifact correction. The hypothesis used to detect calcium signal is the spatiotemporal sparsity of calcium signal, and these methods are unable to identify the passive cells that are not actively firing during the time frame in the video. Statistics regarding the percentage of cells in each frame of view can be critical for the analysis of calcium imaging data for human induced pluripotent stem cells derived neurons and astrocytes.
The objective of this research is to develop a simple and efficient semi-automated pipeline for analysis of in-vitro calcium imaging data. The region of interest (ROI) based image segmentation is used to extract the data regarding intensity fluctuation caused by calcium concentration changes in each cell. It is achieved by using two approaches: basic image segmentation approach and a machine learning approach. The intensity data is evaluated using a custom-made MATLAB that generates statistical information and graphical representation of the number of spiking cells in each field of view, the number of spikes per cell and spike height.
In the past decade, numerous methods have been developed to analyze in-vivo calcium imaging data that involves complex techniques such as overlapping signals segregation and motion artifact correction. The hypothesis used to detect calcium signal is the spatiotemporal sparsity of calcium signal, and these methods are unable to identify the passive cells that are not actively firing during the time frame in the video. Statistics regarding the percentage of cells in each frame of view can be critical for the analysis of calcium imaging data for human induced pluripotent stem cells derived neurons and astrocytes.
The objective of this research is to develop a simple and efficient semi-automated pipeline for analysis of in-vitro calcium imaging data. The region of interest (ROI) based image segmentation is used to extract the data regarding intensity fluctuation caused by calcium concentration changes in each cell. It is achieved by using two approaches: basic image segmentation approach and a machine learning approach. The intensity data is evaluated using a custom-made MATLAB that generates statistical information and graphical representation of the number of spiking cells in each field of view, the number of spikes per cell and spike height.
ContributorsBhandarkar, Siddhi Umesh (Author) / Brafman, David (Thesis advisor) / Stabenfeldt, Sarah (Committee member) / Tian, Xiaojun (Committee member) / Arizona State University (Publisher)
Created2019