Matching Items (36)
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- All Subjects: Biomedical Engineering
- Creators: Stabenfeldt, Sarah
- Creators: Wang, Xiao
- Resource Type: Text
Description
Specificity and affinity towards a given ligand/epitope limit target-specific delivery. Companies can spend between $500 million to $2 billion attempting to discover a new drug or therapy; a significant portion of this expense funds high-throughput screening to find the most successful target-specific compound available. A more recent addition to discovering highly specific targets is the application of phage display utilizing single chain variable fragment antibodies (scFv). The aim of this research was to employ phage display to identify pathologies related to traumatic brain injury (TBI), particularly astrogliosis. A unique biopanning method against viable astrocyte cultures activated with TGF-β achieved this aim. Four scFv clones of interest showed varying relative affinities toward astrocytes. One of those four showed the ability to identify reactive astroctyes over basal astrocytes through max signal readings, while another showed a statistical significance in max signal reading toward basal astrocytes. Future studies will include further affinity characterization assays. This work contributes to the development of targeting therapeutics and diagnostics for TBI.
ContributorsMarsh, William (Author) / Stabenfeldt, Sarah (Thesis advisor) / Caplan, Michael (Committee member) / Sierks, Michael (Committee member) / Arizona State University (Publisher)
Created2013
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 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
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). 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
Description
The objective of this small animal pre-clinical research project was to study quantitatively the long-term micro- and macro- structural brain changes employing multiparametric MRI (Magnetic Resonance Imaging) techniques. Two separate projects make up the basis of this thesis. The first part focuses on obtaining prognostic information at early stages in the case of Traumatic Brain Injury (TBI) in rat animal model using imaging data acquired at 24-hours and 7-days post injury. The obtained parametric T2 and diffusion values from DTI (Diffusion Tensor Imaging) showed significant deviations in the signal intensities from the control and were potentially useful as an early indicator of the severity of post-traumatic injury damage. DTI was especially critical in distinguishing between the cytotoxic and vasogenic edema and in identification of injury regions resolving to normal control values by day-7. These results indicate the potential of quantitative MRI as a clinical marker in predicting prognosis following TBI. The second part of this thesis focuses on studying the effect of novel therapeutic strategies employing dendritic cell (DC) based vaccinations in mice glioma model. The treatment cohorts included comparing a single dose of Azacytidine drug vs. mice getting three doses of drug per week. Another cohort was used as an untreated control group. The MRI results did not show any significant changes in between the two treated cohorts with no reduction in tumor volumes compared to the control group. The future studies would be focused on issues regarding the optimal dose for the application of DC vaccine. Together, the quantitative MRI plays an important role in the prognosis and diagnosis of the above mentioned pathologies, providing essential information about the anatomical location, micro-structural tissue environment, lesion volume and treatment response.
ContributorsAnnaldas, Bharat (Author) / Kodibagkar, Vikram (Thesis advisor) / Stabenfeldt, Sarah (Committee member) / Bhardwaj, Ratan (Committee member) / Arizona State University (Publisher)
Created2014
Description
Modern medical conditions, including cancer, traumatic brain injury, and cardiovascular disease, have elicited the need for cell therapies. The ability to non-invasively track cells in vivo in order to evaluate these therapies and explore cell dynamics is necessary. Magnetic Resonance Imaging provides a platform to track cells as a non-invasive modality with superior resolution and soft tissue contrast. A new methodology for cellular labeling and imaging uses Nile Red doped hexamethyldisiloxane (HMDSO) nanoemulsions as dual modality (Magnetic Resonance Imaging/Fluorescence), dual-functional (oximetry/ detection) nanoprobes. While Gadolinium chelates and super paramagnetic iron oxide-based particles have historically provided contrast enhancement in MRI, newer agents offer additional advantages. A technique using 1H MRI in conjunction with an oxygen reporter molecule is one tool capable of providing these benefits, and can be used in neural progenitor cell and cancer cell studies. Proton Imaging of Siloxanes to Map Tissue Oxygenation Levels (PISTOL) provides the ability to track the polydimethylsiloxane (PDMS) labeled cells utilizing the duality of the nanoemulsions. 1H MRI based labeling of neural stem cells and cancer cells was successfully demonstrated. Additionally, fluorescence labeling of the nanoprobes provided validation of the MRI data and could prove useful for quick in vivo verification and ex vivo validation for future studies.
ContributorsCusick, Alex (Author) / Kodibagkar, Vikram D. (Thesis advisor) / Stabenfeldt, Sarah (Committee member) / Kleim, Jeff (Committee member) / Arizona State University (Publisher)
Created2014
Description
Magnetic Resonance Imaging (MRI) is an efficient non-invasive imaging tool widely used in medical field to produce high quality images. The MRI signal is detected with specifically developed radio frequency (RF) systems or "coils". There are several key parameters to evaluate the performance of RF coils: signal-to-noise ratio (SNR), homogeneity, quality factor (Q factor), sensitivity, etc. The choice of coil size and configuration depends on the object to be imaged. While surface coils have better sensitivity, volume coils are often employed to image a larger region of interest (ROI) as they display better spatial homogeneity. For the cell labeling and imaging studies using the newly developed siloxane based nanoemulsions as 1H MR reporter probes, the first step is to determine the sensitivity of signal detection under controlled conditions in vitro. In this thesis, a novel designed 7 Tesla RF volume coil was designed and tested for detection of small quantities of siloxane probe as well as for imaging of labeled tumor spheroid. The procedure contains PCB circuit design, RF probe design, test and subsequent modification. In this report, both theory and design methodology will be discussed.
ContributorsWang, Haiqing (Author) / Kodibagkar, Vikram (Thesis advisor) / Stabenfeldt, Sarah (Committee member) / Sadleir, Rosalind (Committee member) / Arizona State University (Publisher)
Created2014
Description
Alzheimer's disease (AD) is the most common form of dementia leading to cognitive dysfunction and memory loss as well as emotional and behavioral disorders. It is the 6th leading cause of death in United States, and the only one among top 10 death causes that cannot be prevented, cured or slowed. An estimated 5.4 million Americans live with AD, and this number is expected to triple by year 2050 as the baby boomers age. The cost of care for AD in the US is about $200 billion each year. Unfortunately, in addition to the lack of an effective treatment or AD, there is also a lack of an effective diagnosis, particularly an early diagnosis which would enable treatment to begin before significant neuronal damage has occurred.
Increasing evidence implicates soluble oligomeric forms of beta-amyloid and tau in the onset and progression of AD. While many studies have focused on beta-amyloid, soluble oligomeric tau species may also play an important role in AD pathogenesis. Antibodies that selectively identify and target specific oligomeric tau variants would be valuable tools for both diagnostic and therapeutic applications and also to study the etiology of AD and other neurodegenerative diseases.
Recombinant human tau (rhTau) in monomeric, dimeric, trimeric and fibrillar forms were synthesized and purified to perform LDH assay on human neuroblastoma cells, so that trimeric but not monomeric or dimeric rhTau was identified as extracellularly neurotoxic to neuronal cells. A novel biopanning protocol was designed based on phage display technique and atomic force microscopy (AFM), and used to isolate single chain antibody variable domain fragments (scFvs) that selectively recognize the toxic tau oligomers. These scFvs selectively bind tau variants in brain tissue of human AD patients and AD-related tau transgenic rodent models and have potential value as early diagnostic biomarkers for AD and as potential therapeutics to selectively target toxic tau aggregates.
Increasing evidence implicates soluble oligomeric forms of beta-amyloid and tau in the onset and progression of AD. While many studies have focused on beta-amyloid, soluble oligomeric tau species may also play an important role in AD pathogenesis. Antibodies that selectively identify and target specific oligomeric tau variants would be valuable tools for both diagnostic and therapeutic applications and also to study the etiology of AD and other neurodegenerative diseases.
Recombinant human tau (rhTau) in monomeric, dimeric, trimeric and fibrillar forms were synthesized and purified to perform LDH assay on human neuroblastoma cells, so that trimeric but not monomeric or dimeric rhTau was identified as extracellularly neurotoxic to neuronal cells. A novel biopanning protocol was designed based on phage display technique and atomic force microscopy (AFM), and used to isolate single chain antibody variable domain fragments (scFvs) that selectively recognize the toxic tau oligomers. These scFvs selectively bind tau variants in brain tissue of human AD patients and AD-related tau transgenic rodent models and have potential value as early diagnostic biomarkers for AD and as potential therapeutics to selectively target toxic tau aggregates.
ContributorsTian, Huilai (Author) / Sierks, Michael R (Thesis advisor) / Dai, Lenore (Committee member) / Tillery, Stephen H (Committee member) / Nielsen, David R (Committee member) / Stabenfeldt, Sarah (Committee member) / Arizona State University (Publisher)
Created2014
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 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.
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
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 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
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