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Description
The object of this study is to charac terize the effect of focused ultrasound stimulation (FUS) on the rat ce rvix which has been observed to speed its ripening during pregnancy. Ce rvical ripening is required for successful fetal delivery. Timed-pregnant Sprague-Dawley rats (n=36) were used. On day 14 of

The object of this study is to charac terize the effect of focused ultrasound stimulation (FUS) on the rat ce rvix which has been observed to speed its ripening during pregnancy. Ce rvical ripening is required for successful fetal delivery. Timed-pregnant Sprague-Dawley rats (n=36) were used. On day 14 of gestation, the FUS system was placed on the body surface of the rat over the cervix and ultrasound energy was applied to cervix for variable times up to 1 hour in the control group, the FUS system was placed on rats but no energy was applied. Daily measurement of cervix light-induced florescence (LIF, photon counts of collagen x-bridge fluorescence) were made on days 16 of gestation and daily until spont-aneous delivery (day22) to estimate changes in cervical ripening. We found that pulses of 680 KHz ultrasound at 25 Hertz, 1 millisecond pulse duration at 1W/cm^2 applied for as little as 30 minutes would immediately afterwards show the cervix to hav e ripened to the degree seen just before delivery on day 22. Delivery times, fetal weights and viability were unaffected in the FUS-treated animals.
ContributorsLuo, Daishen (Author) / Towe, Bruce C (Thesis advisor) / Wang, Xiao (Committee member) / Caplan, Michael (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Sensitivity is a fundamental challenge for in vivo molecular magnetic resonance imaging (MRI). Here, I improve the sensitivity of metal nanoparticle contrast agents by strategically incorporating pure and doped metal oxides in the nanoparticle core, forming a soluble, monodisperse, contrast agent with adjustable T2 or T1 relaxivity (r2 or r1).

Sensitivity is a fundamental challenge for in vivo molecular magnetic resonance imaging (MRI). Here, I improve the sensitivity of metal nanoparticle contrast agents by strategically incorporating pure and doped metal oxides in the nanoparticle core, forming a soluble, monodisperse, contrast agent with adjustable T2 or T1 relaxivity (r2 or r1). I first developed a simplified technique to incorporate iron oxides in apoferritin to form "magnetoferritin" for nM-level detection with T2- and T2* weighting. I then explored whether the crystal could be chemically modified to form a particle with high r1. I first adsorbed Mn2+ ions to metal binding sites in the apoferritin pores. The strategic placement of metal ions near sites of water exchange and within the crystal oxide enhance r1, suggesting a mechanism for increasing relaxivity in porous nanoparticle agents. However, the Mn2+ addition was only possible when the particle was simultaneously filled with an iron oxide, resulting in a particle with a high r1 but also a high r2 and making them undetectable with conventional T1-weighting techniques. To solve this problem and decrease the particle r2 for more sensitive detection, I chemically doped the nanoparticles with tungsten to form a disordered W-Fe oxide composite in the apoferritin core. This configuration formed a particle with a r1 of 4,870mM-1s-1 and r2 of 9,076mM-1s-1. These relaxivities allowed the detection of concentrations ranging from 20nM - 400nM in vivo, both passively injected and targeted to the kidney glomerulus. I further developed an MRI acquisition technique to distinguish particles based on r2/r1, and show that three nanoparticles of similar size can be distinguished in vitro and in vivo with MRI. This work forms the basis for a new, highly flexible inorganic approach to design nanoparticle contrast agents for molecular MRI.
ContributorsClavijo Jordan, Maria Veronica (Author) / Bennett, Kevin M (Thesis advisor) / Kodibagkar, Vikram (Committee member) / Sherry, A Dean (Committee member) / Wang, Xiao (Committee member) / Yarger, Jeffery (Committee member) / Arizona State University (Publisher)
Created2012
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Description
While techniques for reading DNA in some capacity has been possible for decades,

the ability to accurately edit genomes at scale has remained elusive. Novel techniques

have been introduced recently to aid in the writing of DNA sequences. While writing

DNA is more accessible, it still remains expensive, justifying the increased interest in

in

While techniques for reading DNA in some capacity has been possible for decades,

the ability to accurately edit genomes at scale has remained elusive. Novel techniques

have been introduced recently to aid in the writing of DNA sequences. While writing

DNA is more accessible, it still remains expensive, justifying the increased interest in

in silico predictions of cell behavior. In order to accurately predict the behavior of

cells it is necessary to extensively model the cell environment, including gene-to-gene

interactions as completely as possible.

Significant algorithmic advances have been made for identifying these interactions,

but despite these improvements current techniques fail to infer some edges, and

fail to capture some complexities in the network. Much of this limitation is due to

heavily underdetermined problems, whereby tens of thousands of variables are to be

inferred using datasets with the power to resolve only a small fraction of the variables.

Additionally, failure to correctly resolve gene isoforms using short reads contributes

significantly to noise in gene quantification measures.

This dissertation introduces novel mathematical models, machine learning techniques,

and biological techniques to solve the problems described above. Mathematical

models are proposed for simulation of gene network motifs, and raw read simulation.

Machine learning techniques are shown for DNA sequence matching, and DNA

sequence correction.

Results provide novel insights into the low level functionality of gene networks. Also

shown is the ability to use normalization techniques to aggregate data for gene network

inference leading to larger data sets while minimizing increases in inter-experimental

noise. Results also demonstrate that high error rates experienced by third generation

sequencing are significantly different than previous error profiles, and that these errors can be modeled, simulated, and rectified. Finally, techniques are provided for amending this DNA error that preserve the benefits of third generation sequencing.
ContributorsFaucon, Philippe Christophe (Author) / Liu, Huan (Thesis advisor) / Wang, Xiao (Committee member) / Crook, Sharon M (Committee member) / Wang, Yalin (Committee member) / Sarjoughian, Hessam S. (Committee member) / Arizona State University (Publisher)
Created2017
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Description
Recombinases are powerful tools for genome engineering and synthetic biology, however recombinases are limited by a lack of user-programmability and often require complex directed-evolution experiments to retarget specificity. Conversely, CRISPR systems have extreme versatility yet can induce off-target mutations and karyotypic destabilization. To address these constraints we developed an RNA-guided

Recombinases are powerful tools for genome engineering and synthetic biology, however recombinases are limited by a lack of user-programmability and often require complex directed-evolution experiments to retarget specificity. Conversely, CRISPR systems have extreme versatility yet can induce off-target mutations and karyotypic destabilization. To address these constraints we developed an RNA-guided recombinase protein by fusing a hyperactive mutant resolvase from transposon TN3 to catalytically inactive Cas9. We validated recombinase-Cas9 (rCas9) function in model eukaryote Saccharomyces cerevisiae using a chromosomally integrated fluorescent reporter. Moreover, we demonstrated cooperative targeting by CRISPR RNAs at spacings of 22 or 40bps is necessary for directing recombination. Using PCR and Sanger sequencing, we confirmed rCas9 targets DNA recombination. With further development we envision rCas9 becoming useful in the development of RNA-programmed genetic circuitry as well as high-specificity genome engineering.
ContributorsStandage-Beier, Kylie S (Author) / Wang, Xiao (Thesis advisor) / Brafman, David A (Committee member) / Tian, Xiao-jun (Committee member) / Arizona State University (Publisher)
Created2018
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Description
Synthetic biology is an emerging field which melds genetics, molecular biology, network theory, and mathematical systems to understand, build, and predict gene network behavior. As an engineering discipline, developing a mathematical understanding of the genetic circuits being studied is of fundamental importance. In this dissertation, mathematical concepts for understanding, predicting,

Synthetic biology is an emerging field which melds genetics, molecular biology, network theory, and mathematical systems to understand, build, and predict gene network behavior. As an engineering discipline, developing a mathematical understanding of the genetic circuits being studied is of fundamental importance. In this dissertation, mathematical concepts for understanding, predicting, and controlling gene transcriptional networks are presented and applied to two synthetic gene network contexts. First, this engineering approach is used to improve the function of the guide ribonucleic acid (gRNA)-targeted, dCas9-regulated transcriptional cascades through analysis and targeted modification of the RNA transcript. In so doing, a fluorescent guide RNA (fgRNA) is developed to more clearly observe gRNA dynamics and aid design. It is shown that through careful optimization, RNA Polymerase II (Pol II) driven gRNA transcripts can be strong enough to exhibit measurable cascading behavior, previously only shown in RNA Polymerase III (Pol III) circuits. Second, inherent gene expression noise is used to achieve precise fractional differentiation of a population. Mathematical methods are employed to predict and understand the observed behavior, and metrics for analyzing and quantifying similar differentiation kinetics are presented. Through careful mathematical analysis and simulation, coupled with experimental data, two methods for achieving ratio control are presented, with the optimal schema for any application being dependent on the noisiness of the system under study. Together, these studies push the boundaries of gene network control, with potential applications in stem cell differentiation, therapeutics, and bio-production.
ContributorsMenn, David J (Author) / Wang, Xiao (Thesis advisor) / Kiani, Samira (Committee member) / Haynes, Karmella (Committee member) / Nielsen, David (Committee member) / Marshall, Pamela (Committee member) / Arizona State University (Publisher)
Created2018
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Description
Synthetic biology is a novel method that reengineers functional parts of natural genes of interest to build new biomolecular devices able to express as designed. There is increasing interest in synthetic biology due to wide potential applications in various fields such as clinics and fuel production. However, there are still

Synthetic biology is a novel method that reengineers functional parts of natural genes of interest to build new biomolecular devices able to express as designed. There is increasing interest in synthetic biology due to wide potential applications in various fields such as clinics and fuel production. However, there are still many challenges in synthetic biology. For example, many natural biological processes are poorly understood, and these could be more thoroughly studied through model synthetic gene networks. Additionally, since synthetic biology applications may have numerous design constraints, more inducer systems should be developed to satisfy different requirements for genetic design.

This thesis covers two topics. First, I attempt to generate stochastic resonance (SR) in a biological system. Synthetic bistable systems were chosen because the inducer range in which they exhibit bistability can satisfy one of the three requirements of SR: a weak periodic force is unable to make the transition between states happen. I synthesized several different bistable systems, including toggle switches and self-activators, to select systems matching another requirement: the system has a clear threshold between the two energy states. Their bistability was verified and characterized. At the same time, I attempted to figure out the third requirement for SR – an effective noise serving as the stochastic force – through one of the most widespread toggles, the mutual inhibition toggle, in both yeast and E. coli. A mathematic model for SR was written and adjusted.

Secondly, I began work on designing a new genetic system capable of responding to pulsed magnetic fields. The operators responding to pulsed magnetic stimuli in the rpoH promoter were extracted and reorganized. Different versions of the rpoH promoter were generated and tested, and their varying responsiveness to magnetic fields was recorded. In order to improve efficiency and produce better operators, a directed evolution method was applied with the help of a CRISPR-dCas9 nicking system. The best performing promoters thus far show a five-fold difference in gene expression between trials with and without the magnetic field.
ContributorsHu, Hao (Author) / Wang, Xiao (Thesis advisor) / Stabenfeldt, Sarah (Committee member) / Brafman, David (Committee member) / Arizona State University (Publisher)
Created2016
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Description
An in vitro model of Alzheimer’s disease (AD) is required to study the poorly understood molecular mechanisms involved in the familial and sporadic forms of the disease. Animal models have previously proven to be useful in studying familial Alzheimer’s disease (AD) by the introduction of AD related mutations in the

An in vitro model of Alzheimer’s disease (AD) is required to study the poorly understood molecular mechanisms involved in the familial and sporadic forms of the disease. Animal models have previously proven to be useful in studying familial Alzheimer’s disease (AD) by the introduction of AD related mutations in the animal genome and by the overexpression of AD related proteins. The genetics of sporadic Alzheimer’s is however too complex to model in an animal model. More recently, AD human induced pluripotent stem cells (hiPSCs) have been used to study the disease in a dish. However, AD hiPSC derived neurons do not faithfully reflect all the molecular characteristics and phenotypes observed in the aged cells with neurodegenerative disease. The truncated form of nuclear protein Lamin-A, progerin, has been implicated in premature aging and is found in increasing concentrations as normal cells age. We hypothesized that by overexpressing progerin, we can cause cells to ‘age’ and display the neurodegenerative effects observed with aging in both diseased and normal cells. To answer this hypothesis, we first generated a retrovirus that allows for the overexpression of progerin in AD and non-demented control (NDC) hiPSC derived neural progenitor cells(NPCs). Subsequently, we generated a pure population of hNPCs that overexpress progerin and wild type lamin. Finally, we analyzed the presence of various age related phenotypes such as abnormal nuclear structure and the loss of nuclear lamina associated proteins to characterize ‘aging’ in these cells.
ContributorsRaman, Sreedevi (Author) / Brafman, David (Thesis advisor) / Stabenfeldt, Sarah (Committee member) / Wang, Xiao (Committee member) / Arizona State University (Publisher)
Created2017
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Description
Neurodegenerative diseases such as Alzheimer’s Disease, Parkinson’s Disease and Amyotrophic Lateral Sclerosis are marked by the loss of different types of neurons and glial cells in the central nervous system (CNS). Human Pluripotent Stem Cell (hPSC)-derived Neural Progenitor Cells (hNPCs) have the ability to self-renew indefinitely and to differentiate into

Neurodegenerative diseases such as Alzheimer’s Disease, Parkinson’s Disease and Amyotrophic Lateral Sclerosis are marked by the loss of different types of neurons and glial cells in the central nervous system (CNS). Human Pluripotent Stem Cell (hPSC)-derived Neural Progenitor Cells (hNPCs) have the ability to self-renew indefinitely and to differentiate into various cell types of the CNS. HNPCs can be used in cell based therapies and have the potential to reverse or arrest neurodegeneration and to replace lost neurons and glial cells. However, the lack of completely defined, scalable systems to culture these cells, limits their therapeutic and clinical applications. In a previous study, a completely defined, robust, synthetic peptide- a Vitronectin Derived Peptide (VDP) that supports the long term expansion and differentiation of various embryonic and induced pluripotent stem cell (hESC/hIPSC) derived hNPC lines on two dimensional (2D) tissue culture plates was identified. In this study, the culture of hNPCs was scaled up using VDP coated microcarriers (MC). VDP MC were able to support the long term expansion of hESC and hiPSC derived hNPCs over multiple passages and supported higher fold changes in cell densities, compared to VDP coated 2D surfaces. VDP MC also showed the ability to support the neuronal differentiation of hNPCs, and produced mature neurons expressing several neuronal, neurotransmitter and cortical markers. Additionally, alzheimer’s disease (AD) relevant phenotypes were studied in patient hIPSC derived hNPCs cultured on laminin MC to assess if the MC culture system could be used for disease modelling and drug screening. Finally, a microcarrier based bioreactor system was developed for the large scale expansion of hNPCs, exhibiting more than a five-fold change in cell density and supporting more than 100 million hNPCs in culture. Thus, the development of a xeno-free, scalable system allows hNPC culture under standard and reproducible conditions in quantities required for therapeutic and clinical applications.
ContributorsRajaram Srinivasan, Gayathri (Author) / Brafman, David (Thesis advisor) / Wang, Xiao (Committee member) / Haynes, Karmella (Committee member) / Arizona State University (Publisher)
Created2017
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Description
Alzheimer’s disease (AD), despite over a century of research, does not have a clearly defined pathogenesis for the sporadic form that makes up the majority of disease incidence. A variety of correlative risk factors have been identified, including the three isoforms of apolipoprotein E (ApoE), a cholesterol transport protein in

Alzheimer’s disease (AD), despite over a century of research, does not have a clearly defined pathogenesis for the sporadic form that makes up the majority of disease incidence. A variety of correlative risk factors have been identified, including the three isoforms of apolipoprotein E (ApoE), a cholesterol transport protein in the central nervous system. ApoE ε3 is the wild-type variant with no effect on risk. ApoE ε2, the protective and most rare variant, reduces risk of developing AD by 40%. ApoE ε4, the risk variant, increases risk by 3.2-fold and 14.9-fold for heterozygous and homozygous representation respectively. Study of these isoforms has been historically complex, but the advent of human induced pluripotent stem cells (hiPSC) provides the means for highly controlled, longitudinal in vitro study. The effect of ApoE variants can be further elucidated using this platform by generating isogenic hiPSC lines through precise genetic modification, the objective of this research. As the difference between alleles is determined by two cytosine-thymine polymorphisms, a specialized CRISPR/Cas9 system for direct base conversion was able to be successfully employed. The base conversion method for transitioning from the ε3 to ε2 allele was first verified using the HEK293 cell line as a model with delivery via electroporation. Following this verification, the transfection method was optimized using two hiPSC lines derived from ε4/ε4 patients, with a lipofection technique ultimately resulting in successful base conversion at the same site verified in the HEK293 model. Additional research performed included characterization of the pre-modification genotype with respect to likely off-target sites and methods of isolating clonal variants.
ContributorsLakers, Mary Frances (Author) / Brafman, David (Thesis advisor) / Haynes, Karmella (Committee member) / Wang, Xiao (Committee member) / Arizona State University (Publisher)
Created2017
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Description
The blood-brain-barrier (BBB) is a significant obstacle for treating many neurological disorders. Bubble-assisted focused ultrasound (BAFUS) medicated BBB disruption is a promising technology that enables the delivery of large drug doses at targeted locations across the BBB. However, the current lack of an in vitro model of this process hinders

The blood-brain-barrier (BBB) is a significant obstacle for treating many neurological disorders. Bubble-assisted focused ultrasound (BAFUS) medicated BBB disruption is a promising technology that enables the delivery of large drug doses at targeted locations across the BBB. However, the current lack of an in vitro model of this process hinders the full understanding of BAFUS BBB disruption for better translation into clinics. In this work, a US-transparent organ-on-chip device has been fabricated that can be critical for the in vitro modeling of the BAFUS BBB disruption. The transparency of the device window to focused ultrasound (FUS) was calculated theoretically and demonstrated by experiments. Nanobubbles were fabricated, characterized by cryogenic transmission electron microscopy (cryo-TEM), and showed bubble cavitation under FUS. Human colorectal adenocarcinoma (Caco-2) cells were used to form a good cellular barrier for BAFUS barrier disruption, as suggested by the measured permeability and transepithelial electrical resistance (TEER). Finally, barrier disruption and recovery were observed in BAFUS disrupted US-transparent organ-on-chips with Caco-2 barriers, showing great promise of the platform for future modeling BAFUS BBB disruption in vitro.
ContributorsAkkad, Adam Rifat (Author) / Gu, Jian (Thesis advisor) / Nikkhah, Mehdi (Thesis advisor) / Belohlavek, Marek (Committee member) / Wang, Xiao (Committee member) / Arizona State University (Publisher)
Created2022