Matching Items (102)
Description
Effectively modeling Alzheimer’s disease will lend to a more comprehensive
understanding of the disease pathology, more efficacious drug development and
regenerative medicine as a form of treatment. There are limitations with current
transgenic mouse models of Alzheimer’s disease and the study of post mortem brain tissue of Alzheimer’s diseases patients. Stem cell models can overcome the lack of clinical relevance and impracticality associated with current models. Ideally, the use of stem cell models provides the foundation to study the biochemical and physiological aspects of Alzheimer’s disease, but at the cellular level. Moreover, the future of drug development and disease modeling can be improved by developing a reproducible and well-characterized model of AD that can be scaled up to meet requirements for basic and translational applications. Characterization and analysis of a heterogenic neuronal culture developed from induced pluripotent stem cells calls for the understanding of single cell identity and cell viability. A method to analyze RNA following intracellular sorting was developed in order to analyze single cell identity of a heterogenic population
of human induced pluripotent stem cells and neural progenitor cells. The population was intracellularly stained and sorted for Oct4. RNA was isolated and analyzed with qPCR, which demonstrated expected expression profiles for Oct4+ and Oct4- cells. In addition, a protocol to label cells with pO2 sensing nanoprobes was developed to assess cell viability. Non-destructive nanoprobe up-take by neural progenitor cells was assessed with fluorescent imaging and flow cytometry. Nanoprobe labeled neurons were cultured long-term and continued to fluoresce at day 28. The proof of concept experiments demonstrated will be further expanded upon and utilized in developing a more clinically relevant and cost-effective model of Alzheimer’s disease with downstream applications
in drug development and regenerative medicine.
understanding of the disease pathology, more efficacious drug development and
regenerative medicine as a form of treatment. There are limitations with current
transgenic mouse models of Alzheimer’s disease and the study of post mortem brain tissue of Alzheimer’s diseases patients. Stem cell models can overcome the lack of clinical relevance and impracticality associated with current models. Ideally, the use of stem cell models provides the foundation to study the biochemical and physiological aspects of Alzheimer’s disease, but at the cellular level. Moreover, the future of drug development and disease modeling can be improved by developing a reproducible and well-characterized model of AD that can be scaled up to meet requirements for basic and translational applications. Characterization and analysis of a heterogenic neuronal culture developed from induced pluripotent stem cells calls for the understanding of single cell identity and cell viability. A method to analyze RNA following intracellular sorting was developed in order to analyze single cell identity of a heterogenic population
of human induced pluripotent stem cells and neural progenitor cells. The population was intracellularly stained and sorted for Oct4. RNA was isolated and analyzed with qPCR, which demonstrated expected expression profiles for Oct4+ and Oct4- cells. In addition, a protocol to label cells with pO2 sensing nanoprobes was developed to assess cell viability. Non-destructive nanoprobe up-take by neural progenitor cells was assessed with fluorescent imaging and flow cytometry. Nanoprobe labeled neurons were cultured long-term and continued to fluoresce at day 28. The proof of concept experiments demonstrated will be further expanded upon and utilized in developing a more clinically relevant and cost-effective model of Alzheimer’s disease with downstream applications
in drug development and regenerative medicine.
ContributorsKnittel, Jacob James (Author) / Brafman, David (Thesis director) / Salvatore, Oddo (Committee member) / School of Life Sciences (Contributor) / Dean, W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Cell fate is a complex and dynamic process with many genetic components. It has often been likened to “multistable” mathematical systems because of the numerous possible “stable” states, or cell types, that cells may end up in. Due to its complexity, understanding the process of cell fate and differentiation has proven challenging. A better understanding of cell differentiation has applications in regenerative stem cell therapies, disease pathologies, and gene regulatory networks.
A variety of different genes have been associated with cell fate. For example, the Nanog/Oct-4/Sox2 network forms the core interaction of a gene network that maintains stem cell pluripotency, and Oct-4 and Sox2 also play a role in the tissue types that stem cells eventually differentiate into. Using the CRISPR/cas9 based homology independent targeted integration (HITI) method developed by Suzuki et al., we can integrate fluorescent tags behind genes with reasonable efficiency via the non-homologous end joining (NHEJ) DNA repair pathway. With human embryonic kidney (HEK) 293T cells, which can be transfected with high efficiencies, we aim to create a three-parameter reporter cell line with fluorescent tags for three different genes related to cell fate. This cell line would provide several advantages for the study of cell fate, including the ability to quantitatively measure cell state, observe expression heterogeneity among a population of genetically identical cells, and easily monitor fluctuations in expression patterns.
The project is partially complete at this time. This report discusses progress thus far, as well as the challenges faced and the future steps for completing the reporter line.
A variety of different genes have been associated with cell fate. For example, the Nanog/Oct-4/Sox2 network forms the core interaction of a gene network that maintains stem cell pluripotency, and Oct-4 and Sox2 also play a role in the tissue types that stem cells eventually differentiate into. Using the CRISPR/cas9 based homology independent targeted integration (HITI) method developed by Suzuki et al., we can integrate fluorescent tags behind genes with reasonable efficiency via the non-homologous end joining (NHEJ) DNA repair pathway. With human embryonic kidney (HEK) 293T cells, which can be transfected with high efficiencies, we aim to create a three-parameter reporter cell line with fluorescent tags for three different genes related to cell fate. This cell line would provide several advantages for the study of cell fate, including the ability to quantitatively measure cell state, observe expression heterogeneity among a population of genetically identical cells, and easily monitor fluctuations in expression patterns.
The project is partially complete at this time. This report discusses progress thus far, as well as the challenges faced and the future steps for completing the reporter line.
ContributorsLoveday, Tristan Andre (Author) / Wang, Xiao (Thesis director) / Brafman, David (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Chronic Traumatic Encephalopathy (CTE) is a neurodegenerative brain disease that results from repetitive brain trauma causing brain structure, personality, behavioral, and cognitive changes. CTE is currently undiagnosable and untreatable in living patients. This thesis investigates research surrounding CTE and presents a comparative discussion of the advantages and disadvantages of current diagnostic methods used for other neurodegenerative diseases that may be useful for the diagnosis of CTE.
ContributorsBlair, Sierra (Co-author) / Blair, Taylor (Co-author) / Brafman, David (Thesis director) / Stabenfeldt, Sarah (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Alzheimer’s Disease (AD) affects over 5 million individuals in the U.S. and has a direct cost estimated in excess of $200 billion per year. Broadly speaking, there are two forms of AD—early-onset, familial AD (FAD) and late-onset-sporadic AD (SAD). Animal models of AD, which rely on the overexpression of FAD-related mutations, have provided important insights into the disease. However, these models do not display important disease-related pathologies and have been limited in their ability to model the complex genetics associated with SAD.
Advances in cellular reprogramming, have enabled the generation of in vitro disease models that can be used to dissect disease mechanisms and evaluate potential therapeutics. To that end, efforts by many groups, including the Brafman laboratory, to generated patient-specific hiPSCs have demonstrated the promise of studying AD in a simplified and accessible system. However, neurons generated from these hiPSCs have shown some, but not all, of the early molecular and cellular hallmarks associated with the disease. Additionally, phenotypes and pathological hallmarks associated with later stages of the human disease have not been observed with current hiPSC-based systems. Further, disease relevant phenotypes in neurons generated from SAD hiPSCs have been highly variable or largely absent. Finally, the reprogramming process erases phenotypes associated with cellular aging and, as a result, iPSC-derived neurons more closely resemble fetal brain rather than adult brain.
It is well-established that in vivo cells reside within a complex 3-D microenvironment that plays a significant role in regulating cell behavior. Signaling and other cellular functions, such as gene expression and differentiation potential, differ in 3-D cultures compared with 2-D substrates. Nonetheless, previous studies using AD hiPSCs have relied on 2-D neuronal culture models that do not reflect the 3-D complexity of native brain tissue, and therefore, are unable to replicate all aspects of AD pathogenesis. Further, the reprogramming process erases cellular aging phenotypes. To address these limitations, this project aimed to develop bioengineering methods for the generation of 3-D organoid-based cultures that mimic in vivo cortical tissue, and to generate an inducible gene repression system to recapitulate cellular aging hallmarks.
Advances in cellular reprogramming, have enabled the generation of in vitro disease models that can be used to dissect disease mechanisms and evaluate potential therapeutics. To that end, efforts by many groups, including the Brafman laboratory, to generated patient-specific hiPSCs have demonstrated the promise of studying AD in a simplified and accessible system. However, neurons generated from these hiPSCs have shown some, but not all, of the early molecular and cellular hallmarks associated with the disease. Additionally, phenotypes and pathological hallmarks associated with later stages of the human disease have not been observed with current hiPSC-based systems. Further, disease relevant phenotypes in neurons generated from SAD hiPSCs have been highly variable or largely absent. Finally, the reprogramming process erases phenotypes associated with cellular aging and, as a result, iPSC-derived neurons more closely resemble fetal brain rather than adult brain.
It is well-established that in vivo cells reside within a complex 3-D microenvironment that plays a significant role in regulating cell behavior. Signaling and other cellular functions, such as gene expression and differentiation potential, differ in 3-D cultures compared with 2-D substrates. Nonetheless, previous studies using AD hiPSCs have relied on 2-D neuronal culture models that do not reflect the 3-D complexity of native brain tissue, and therefore, are unable to replicate all aspects of AD pathogenesis. Further, the reprogramming process erases cellular aging phenotypes. To address these limitations, this project aimed to develop bioengineering methods for the generation of 3-D organoid-based cultures that mimic in vivo cortical tissue, and to generate an inducible gene repression system to recapitulate cellular aging hallmarks.
ContributorsBounds, Lexi Rose (Author) / Brafman, David (Thesis director) / Wang, Xiao (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Genetic manipulation of human cell lines has widespread applications in biomedical research ranging from disease modeling to therapeutic development. Human cells are generally difficult to genetically engineer, but exogenous nucleic acids can be expressed by viral, chemical, or nonchemical means. Chemical transfections are simpler in practice than both viral and nonchemical delivery of genetic material, but often suffer from cytotoxicity and low efficiency. Novel aminoglycoside antibiotic-derived lipopolymers have been synthesized to mediate transgene delivery to human cells. These polymers are comprised of either paromomycin or apramycin crosslinked with glycerol diglycidylether and derivatized with stearoyl chloride in varying molar ratios. In this work, three previously identified target lipopolymers were screened against a library of human embryonic and induced pluripotent stem cell lines. Cells were transfected with a plasmid encoding green fluorescent protein (GFP) and expression was quantified with flow cytometry 48 hours after transfection. Transfection efficiency was evaluated between three distinct lipopolymers and four lipopolymer:DNA mass ratios. GFP expression was compared to that of cells transfected with commercially available chemical gene delivery reagent controls\u2014JetPEI, Lipofectamine, and Fugene\u2014at their recommended reagent:DNA ratios. Improved transgene expression in stem cell lines allows for improved research methods. Human stem cell-derived neurons that have been genetically manipulated to express phenotypic characteristics of aging can be utilized to model neurodegenerative diseases, elucidating information about these diseases that would be inaccessible in unmanipulated tissue.
ContributorsMehta, Frea (Author) / Brafman, David (Thesis director) / Rege, Kaushal (Committee member) / Chemical Engineering Program (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Open source image analytics and data mining software are widely available but can be overly-complicated and non-intuitive for medical physicians and researchers to use. The ASU-Mayo Clinic Imaging Informatics Lab has developed an in-house pipeline to process medical images, extract imaging features, and develop multi-parametric models to assist disease staging and diagnosis. The tools have been extensively used in a number of medical studies including brain tumor, breast cancer, liver cancer, Alzheimer's disease, and migraine. Recognizing the need from users in the medical field for a simplified interface and streamlined functionalities, this project aims to democratize this pipeline so that it is more readily available to health practitioners and third party developers.
ContributorsBaer, Lisa Zhou (Author) / Wu, Teresa (Thesis director) / Wang, Yalin (Committee member) / Computer Science and Engineering Program (Contributor) / W. P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
the project led by Professor Emma Frow, researching of stem cell clinics focused on stem cell applications, adherence to FDA guidelines, and characterization of information available and physician credentials. Regenerative medicine clinics commonly offered stem cell therapy, but introduced platelet rich plasma (PRP) and prolotherapy as regenerative therapies.
PRP and Prolotherapy are individual treatments that were even suggested and used in combination with stem cell therapies. Prolotherapy predates PRP as a chemical irritant therapy originally used to sclerose tissues. Prolotherapy is meant to stimulate platelet derived growth factors release to improve tissue healing response. Prolotherapy shows negligible efficacy improvements over corticosteroids, but may have underlying side effects from being an irritant. PRP is a more modern therapy for improved healing. Speculations state initial use was in an open heart surgery to improve healing post-surgery. PRP is created via centrifugation of patient blood to isolate growth factors by removing serum and other biological components to increase platelet concentration. PRP is comparable to corticosteroid injections in efficacy, but as an autologous application, there are no side effects making it more advantageous. Growth factors induce healing response and reduce inflammation. Growth factors stimulate cell growth, proliferation, differentiation, and stimulate cellular response mechanism such as angiogenesis and mitogenesis. The growth factor stimulation of PRP and prolotherapy both assist stem cell proliferation. Additional research is needed to determine differential capacity to ensure multipotent stem cells regenerate the correct cell type from the increased differential capacity offered by growth factor recruitment. The application of combination therapy for stem cells is unsubstantiated and applications violate FDA ‘minimal manipulation’ guidelines.
PRP and Prolotherapy are individual treatments that were even suggested and used in combination with stem cell therapies. Prolotherapy predates PRP as a chemical irritant therapy originally used to sclerose tissues. Prolotherapy is meant to stimulate platelet derived growth factors release to improve tissue healing response. Prolotherapy shows negligible efficacy improvements over corticosteroids, but may have underlying side effects from being an irritant. PRP is a more modern therapy for improved healing. Speculations state initial use was in an open heart surgery to improve healing post-surgery. PRP is created via centrifugation of patient blood to isolate growth factors by removing serum and other biological components to increase platelet concentration. PRP is comparable to corticosteroid injections in efficacy, but as an autologous application, there are no side effects making it more advantageous. Growth factors induce healing response and reduce inflammation. Growth factors stimulate cell growth, proliferation, differentiation, and stimulate cellular response mechanism such as angiogenesis and mitogenesis. The growth factor stimulation of PRP and prolotherapy both assist stem cell proliferation. Additional research is needed to determine differential capacity to ensure multipotent stem cells regenerate the correct cell type from the increased differential capacity offered by growth factor recruitment. The application of combination therapy for stem cells is unsubstantiated and applications violate FDA ‘minimal manipulation’ guidelines.
ContributorsKrum, Logan (Author) / Frow, Emma (Thesis director) / Brafman, David (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Current research into live-cell dynamics, particularly those relating to chromatin structure and remodeling, are limited. The tools that are used to detect state changes in chromatin, such as Chromatin Immunoprecipitation and qPCR, require that the cell be killed off. This limits the ability of researchers to pinpoint changes in live cells over a longer period of time. As such, there is a need for a live-cell sensor that can detect chromatin state changes. The Chromometer is a transgenic chromatin state sensor designed to better understand human cell fate and the chromatin changes that occur. HOXD11.12, a DNA sequence that attracts repressive Polycomb group (PCG) proteins, was placed upstream of a core promoter-driven fluorescent reporter (AmCyan fluorescent protein, CFP) to link chromatin repression to a CFP signal. The transgene was stably inserted at an ectopic site in U2-OS (osteosarcoma) cells. Expression of CFP should reflect the epigenetic state at the HOXD locus, where several genes are regulated by Polycomb to control cell differentiation. U2-OS cells were transfected with the transgene and grown under selective pressure. Twelve colonies were identified as having integrated parts from the transgene into their genomes. PCR testing verified 2 cell lines that contain the complete transgene. Flow cytometry indicated mono-modal and bimodal populations in all transgenic cell colonies. Further research must be done to determine the effectiveness of this device as a sensor for live cell state change detection.
ContributorsBarclay, David (Co-author) / Simper, Jan (Co-author) / Haynes, Karmella (Thesis director) / Brafman, David (Committee member) / School of Life Sciences (Contributor) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Video object segmentation (VOS) is an important task in computer vision with a lot of applications, e.g., video editing, object tracking, and object based encoding. Different from image object segmentation, video object segmentation must consider both spatial and temporal coherence for the object. Despite extensive previous work, the problem is still challenging. Usually, foreground object in the video draws more attention from humans, i.e. it is salient. In this thesis we tackle the problem from the aspect of saliency, where saliency means a certain subset of visual information selected by a visual system (human or machine). We present a novel unsupervised method for video object segmentation that considers both low level vision cues and high level motion cues. In our model, video object segmentation can be formulated as a unified energy minimization problem and solved in polynomial time by employing the min-cut algorithm. Specifically, our energy function comprises the unary term and pair-wise interaction energy term respectively, where unary term measures region saliency and interaction term smooths the mutual effects between object saliency and motion saliency. Object saliency is computed in spatial domain from each discrete frame using multi-scale context features, e.g., color histogram, gradient, and graph based manifold ranking. Meanwhile, motion saliency is calculated in temporal domain by extracting phase information of the video. In the experimental section of this thesis, our proposed method has been evaluated on several benchmark datasets. In MSRA 1000 dataset the result demonstrates that our spatial object saliency detection is superior to the state-of-art methods. Moreover, our temporal motion saliency detector can achieve better performance than existing motion detection approaches in UCF sports action analysis dataset and Weizmann dataset respectively. Finally, we show the attractive empirical result and quantitative evaluation of our approach on two benchmark video object segmentation datasets.
ContributorsWang, Yilin (Author) / Li, Baoxin (Thesis advisor) / Wang, Yalin (Committee member) / Cleveau, David (Committee member) / Arizona State University (Publisher)
Created2013
Description
Learning from high dimensional biomedical data attracts lots of attention recently. High dimensional biomedical data often suffer from the curse of dimensionality and have imbalanced class distributions. Both of these features of biomedical data, high dimensionality and imbalanced class distributions, are challenging for traditional machine learning methods and may affect the model performance. In this thesis, I focus on developing learning methods for the high-dimensional imbalanced biomedical data. In the first part, a sparse canonical correlation analysis (CCA) method is presented. The penalty terms is used to control the sparsity of the projection matrices of CCA. The sparse CCA method is then applied to find patterns among biomedical data sets and labels, or to find patterns among different data sources. In the second part, I discuss several learning problems for imbalanced biomedical data. Note that traditional learning systems are often biased when the biomedical data are imbalanced. Therefore, traditional evaluations such as accuracy may be inappropriate for such cases. I then discuss several alternative evaluation criteria to evaluate the learning performance. For imbalanced binary classification problems, I use the undersampling based classifiers ensemble (UEM) strategy to obtain accurate models for both classes of samples. A small sphere and large margin (SSLM) approach is also presented to detect rare abnormal samples from a large number of subjects. In addition, I apply multiple feature selection and clustering methods to deal with high-dimensional data and data with highly correlated features. Experiments on high-dimensional imbalanced biomedical data are presented which illustrate the effectiveness and efficiency of my methods.
ContributorsYang, Tao (Author) / Ye, Jieping (Thesis advisor) / Wang, Yalin (Committee member) / Davulcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2013