Matching Items (22)
Description
Glioblastoma (GBM) is the most common primary brain tumor with an incidence of approximately 11,000 Americans. Despite decades of research, average survival for GBM patients is a modest 15 months. Increasing the extent of GBM resection increases patient survival. However, extending neurosurgical margins also threatens the removal of eloquent brain. For this reason, the infiltrative nature of GBM is an obstacle to its complete resection. We hypothesize that targeting genes and proteins that regulate GBM motility, and developing techniques that safely enhance extent of surgical resection, will improve GBM patient survival by decreasing infiltration into eloquent brain regions and enhancing tumor cytoreduction during surgery. Chapter 2 of this dissertation describes a gene and protein we identified; aquaporin-1 (aqp1) that enhances infiltration of GBM. In chapter 3, we describe a method for enhancing the diagnostic yield of GBM patient biopsies which will assist in identifying future molecular targets for GBM therapies. In chapter 4 we develop an intraoperative optical imaging technique that will assist identifying GBM and its infiltrative margins during surgical resection. The topic of this dissertation aims to target glioblastoma infiltration from molecular and cellular biology and neurosurgical disciplines. In the introduction we; 1. Provide a background of GBM and current therapies. 2. Discuss a protein we found that decreases GBM survival. 3. Describe an imaging modality we utilized for improving the quality of accrued patient GBM samples. 4. We provide an overview of intraoperative contrast agents available for neurosurgical resection of GBM, and discuss a new agent we studied for intraoperative visualization of GBM.
ContributorsGeorges, Joseph F (Author) / Feuerstein, Burt G (Thesis advisor) / Smith, Brian H. (Thesis advisor) / Van Keuren-Jensen, Kendall (Committee member) / Deviche, Pierre (Committee member) / Bennett, Kevin (Committee member) / Arizona State University (Publisher)
Created2014
Description
Spatiotemporal processing in the mammalian olfactory bulb (OB), and its analog, the invertebrate antennal lobe (AL), is subject to plasticity driven by biogenic amines. I study plasticity using honey bees, which have been extensively studied with respect to nonassociative and associative based olfactory learning and memory. Octopamine (OA) release in the AL is the functional analog to epinephrine in the OB. Blockade of OA receptors in the AL blocks plasticity induced changes in behavior. I have now begun to test specific hypotheses related to how this biogenic amine might be involved in plasticity in neural circuits within the AL. OA acts via different receptor subtypes, AmOA1, which gates calcium release from intracellular stores, and AmOA-beta, which results in an increase of cAMP. Calcium also enters AL interneurons via nicotinic acetylcholine receptors, which are driven by acetylcholine release from sensory neuron terminals, as well as through voltage-gated calcium channels. I employ 2-photon excitation (2PE) microscopy using fluorescent calcium indicators to investigate potential sources of plasticity as revealed by calcium fluctuations in AL projection neuron (PN) dendrites in vivo. PNs are analogous to mitral cells in the OB and have dendritic processes that show calcium increases in response to odor stimulation. These calcium signals frequently change after association of odor with appetitive reinforcement. However, it is unclear whether the reported plasticity in calcium signals are due to changes intrinsic to the PNs or to changes in other neural components of the network. My studies were aimed toward understanding the role of OA for establishing associative plasticity in the AL network. Accordingly, I developed a treatment that isolates intact, functioning PNs in vivo. A second study revealed that cAMP is a likely component of plasticity in the AL, thus implicating the AmOA-beta; receptors. Finally, I developed a method for loading calcium indicators into neural components of the AL that have yet to be studied in detail. These manipulations are now revealing the molecular mechanisms contributing to associative plasticity in the AL. These studies will allow for a greater understanding of plasticity in several neural components of the honey bee AL and mammalian OB.
ContributorsProtas, Danielle (Author) / Smith, Brian H. (Thesis advisor) / Neisewander, Janet (Committee member) / Anderson, Trent (Committee member) / Tyler, William (Committee member) / Vu, Eric (Committee member) / Arizona State University (Publisher)
Created2014
Description
During attempted fixation, the eyes are not still but continue to produce so called "fixational eye movements", which include microsaccades, drift, and tremor. Microsaccades are thought to help prevent and restore vision loss during fixation, and to correct fixation errors, but how they contribute to these functions remains a matter of debate. This dissertation presents the results of four experiments conducted to address current controversies concerning the role of microsaccades in visibility and oculomotor control.
The first two experiments set out to correlate microsaccade production with the visibility of foveal and peripheral targets of varied spatial frequencies, during attempted fixation. The results indicate that microsaccades restore the visibility of both peripheral targets and targets presented entirely within the fovea, as a function of their spatial frequency characteristics.
The last two experiments set out to determine the role of microsaccades and drifts on the correction of gaze-position errors due to blinks in human and non-human primates, and to characterize microsaccades forming square-wave jerks (SWJs) in non-human primates. The results showed that microsaccades, but not drifts, correct gaze-position errors due to blinks, and that SWJ production and dynamic properties are equivalent in human and non-human primates.
These combined findings suggest that microsaccades, like saccades, serve multiple and non-exclusive functional roles in vision and oculomotor control, as opposed to having a single specialized function.
The first two experiments set out to correlate microsaccade production with the visibility of foveal and peripheral targets of varied spatial frequencies, during attempted fixation. The results indicate that microsaccades restore the visibility of both peripheral targets and targets presented entirely within the fovea, as a function of their spatial frequency characteristics.
The last two experiments set out to determine the role of microsaccades and drifts on the correction of gaze-position errors due to blinks in human and non-human primates, and to characterize microsaccades forming square-wave jerks (SWJs) in non-human primates. The results showed that microsaccades, but not drifts, correct gaze-position errors due to blinks, and that SWJ production and dynamic properties are equivalent in human and non-human primates.
These combined findings suggest that microsaccades, like saccades, serve multiple and non-exclusive functional roles in vision and oculomotor control, as opposed to having a single specialized function.
ContributorsCostela, Francisco M (Author) / Crook, Sharon M (Committee member) / Martinez-Conde, Susana (Committee member) / Macknik, Stephen L. (Committee member) / Baer, Stephen (Committee member) / McCamy, Michael B (Committee member) / Arizona State University (Publisher)
Created2014
Description
Warning coloration deters predators from attacking prey that are defended, usually by being distasteful, toxic, or otherwise costly for predators to pursue and consume. Predators may have an innate response to warning colors or learn to associate them with a defense through trial and error. In general, predators should select for warning signals that are easy to learn and recognize. Previous research demonstrates long-wavelength colors (e.g. red and yellow) are effective because they are readily detected and learned. However, a number of defended animals display short-wavelength coloration (e.g. blue and violet), such as the pipevine swallowtail butterfly (Battus philenor). The role of blue coloration in warning signals had not previously been explicitly tested. My research showed in laboratory experiments that curve-billed thrashers (Toxostoma curvirostre) and Gambel's quail (Callipepla gambelii) can learn and recognize the iridescent blue of B. philenor as a warning signal and that it is innately avoided. I tested the attack rates of these colors in the field and blue was not as effective as orange. I concluded that blue colors may function as warning signals, but the effectiveness is likely dependent on the context and predator.
Blue colors are often iridescent in nature and the effect of iridescence on warning signal function was unknown. I reared B. philenor larvae under varied food deprivation treatments. Iridescent colors did not have more variation than pigment-based colors under these conditions; variation which could affect predator learning. Learning could also be affected by changes in appearance, as iridescent colors change in both hue and brightness as the angle of illuminating light and viewer change in relation to the color surface. Iridescent colors can also be much brighter than pigment-based colors and iridescent animals can statically display different hues. I tested these potential effects on warning signal learning by domestic chickens (Gallus gallus domesticus) and found that variation due to the directionality of iridescence and a brighter warning signal did not influence learning. However, blue-violet was learned more readily than blue-green. These experiments revealed that the directionality of iridescent coloration does not likely negatively affect its potential effectiveness as a warning signal.
Blue colors are often iridescent in nature and the effect of iridescence on warning signal function was unknown. I reared B. philenor larvae under varied food deprivation treatments. Iridescent colors did not have more variation than pigment-based colors under these conditions; variation which could affect predator learning. Learning could also be affected by changes in appearance, as iridescent colors change in both hue and brightness as the angle of illuminating light and viewer change in relation to the color surface. Iridescent colors can also be much brighter than pigment-based colors and iridescent animals can statically display different hues. I tested these potential effects on warning signal learning by domestic chickens (Gallus gallus domesticus) and found that variation due to the directionality of iridescence and a brighter warning signal did not influence learning. However, blue-violet was learned more readily than blue-green. These experiments revealed that the directionality of iridescent coloration does not likely negatively affect its potential effectiveness as a warning signal.
ContributorsPegram, Kimberly Vann (Author) / Rutowski, Ronald L (Thesis advisor) / Hoelldobler, Berthold (Committee member) / Liebig, Juergen (Committee member) / McGraw, Kevin (Committee member) / Smith, Brian H. (Committee member) / Arizona State University (Publisher)
Created2015
Description
Dendrites are the structures of a neuron specialized to receive input signals and to provide the substrate for the formation of synaptic contacts with other cells. The goal of this work is to study the activity-dependent mechanisms underlying dendritic growth in a single-cell model. For this, the individually identifiable adult motoneuron, MN5, in Drosophila melanogaster was used. This dissertation presents the following results. First, the natural variability of morphological parameters of the MN5 dendritic tree in control flies is not larger than 15%, making MN5 a suitable model for quantitative morphological analysis. Second, three-dimensional topological analyses reveals that different parts of the MN5 dendritic tree innervate spatially separated areas (termed "isoneuronal tiling"). Third, genetic manipulation of the MN5 excitability reveals that both increased and decreased activity lead to dendritic overgrowth; whereas decreased excitability promoted branch elongation, increased excitability enhanced dendritic branching. Next, testing the activity-regulated transcription factor AP-1 for its role in MN5 dendritic development reveals that neural activity enhanced AP-1 transcriptional activity, and that AP-1 expression lead to opposite dendrite fates depending on its expression timing during development. Whereas overexpression of AP-1 at early stages results in loss of dendrites, AP-1 overexpression after the expression of acetylcholine receptors and the formation of all primary dendrites in MN5 causes overgrowth. Fourth, MN5 has been used to examine dendritic development resulting from the expression of the human gene MeCP2, a transcriptional regulator involved in the neurodevelopmental disease Rett syndrome. Targeted expression of full-length human MeCP2 in MN5 causes impaired dendritic growth, showing for the first time the cellular consequences of MeCP2 expression in Drosophila neurons. This dendritic phenotype requires the methyl-binding domain of MeCP2 and the chromatin remodeling protein Osa. In summary, this work has fully established MN5 as a single-neuron model to study mechanisms underlying dendrite development, maintenance and degeneration, and to test the behavioral consequences resulting from dendritic growth misregulation. Furthermore, this thesis provides quantitative description of isoneuronal tiling of a central neuron, offers novel insight into activity- and AP-1 dependent developmental plasticity, and finally, it establishes Drosophila MN5 as a model to study some specific aspects of human diseases.
ContributorsVonhoff, Fernando Jaime (Author) / Duch, Carsten J (Thesis advisor) / Smith, Brian H. (Committee member) / Vu, Eric (Committee member) / Crook, Sharon (Committee member) / Arizona State University (Publisher)
Created2012
Description
In vertebrate outer retina, changes in the membrane potential of horizontal cells affect the calcium influx and glutamate release of cone photoreceptors via a negative feedback. This feedback has a number of important physiological consequences. One is called background-induced flicker enhancement (BIFE) in which the onset of dim background enhances the center flicker response of horizontal cells. The underlying mechanism for the feedback is still unclear but competing hypotheses have been proposed. One is the GABA hypothesis, which states that the feedback is mediated by gamma-aminobutyric acid (GABA), an inhibitory neurotransmitter released from horizontal cells. Another is the ephaptic hypothesis, which contends that the feedback is non-GABAergic and is achieved through the modulation of electrical potential in the intersynaptic cleft between cones and horizontal cells. In this study, a continuum spine model of the cone-horizontal cell synaptic circuitry is formulated. This model, a partial differential equation system, incorporates both the GABA and ephaptic feedback mechanisms. Simulation results, in comparison with experiments, indicate that the ephaptic mechanism is necessary in order for the model to capture the major spatial and temporal dynamics of the BIFE effect. In addition, simulations indicate that the GABA mechanism may play some minor modulation role.
ContributorsChang, Shaojie (Author) / Baer, Steven M. (Thesis advisor) / Gardner, Carl L (Thesis advisor) / Crook, Sharon M (Committee member) / Kuang, Yang (Committee member) / Ringhofer, Christian (Committee member) / Arizona State University (Publisher)
Created2012
Description
Dopamine (DA) is a neurotransmitter involved in attention, goal oriented behavior, movement, reward learning, and short term and working memory. For the past four decades, mathematical and computational modeling approaches have been useful in DA research, and although every modeling approach has limitations, a model is an efficient way to generate and explore hypotheses. This work develops a model of DA dynamics in a representative, single DA neuron by integrating previous experimental, theoretical and computational research. The model consists of three compartments: the cytosol, the vesicles, and the extracellular space and forms the basis of a new mathematical paradigm for examining the dynamics of DA synthesis, storage, release and reuptake. The model can be driven by action potentials generated by any model of excitable membrane potential or even from experimentally induced depolarization voltage recordings. Here the model is forced by a previously published model of the excitable membrane of a mesencephalic DA neuron in order to study the biochemical processes involved in extracellular DA production. After demonstrating that the model exhibits realistic dynamics resembling those observed experimentally, the model is used to examine the functional changes in presynaptic mechanisms due to application of cocaine. Sensitivity analysis and numerical studies that focus on various possible mechanisms for the inhibition of DAT by cocaine provide insight for the complex interactions involved in DA dynamics. In particular, comparing numerical results for a mixed inhibition mechanism to those for competitive, non-competitive and uncompetitive inhibition mechanisms reveals many behavioral similarities for these different types of inhibition that depend on inhibition parameters and levels of cocaine. Placing experimental results within this context of mixed inhibition provides a possible explanation for the conflicting views of uptake inhibition mechanisms found in experimental neuroscience literature.
ContributorsTello-Bravo, David (Author) / Crook, Sharon M (Thesis advisor) / Greenwood, Priscilla E (Thesis advisor) / Baer, Steven M. (Committee member) / Castaneda, Edward (Committee member) / Castillo-Chavez, Carlos (Committee member) / Arizona State University (Publisher)
Created2012
Description
Many behaviors are organized into bouts – brief periods of responding punctuated by pauses. This dissertation examines the operant bouts of the lever pressing rat. Chapter 1 provides a brief history of operant response bout analyses. Chapters 2, 3, 5, and 6 develop new probabilistic models to identify changes in response bout parameters. The parameters of those models are demonstrated to be uniquely sensitive to different experimental manipulations, such as food deprivation (Chapters 2 and 4), response requirements (Chapters 2, 4, and 5), and reinforcer availability (Chapters 2 and 3). Chapter 6 reveals the response bout parameters that underlie the operant hyperactivity of a common rodent model of attention deficit hyperactivity disorder (ADHD), the spontaneously hypertensive rat (SHR). Chapter 6 then ameliorates the SHR’s operant hyperactivity using training procedures developed from findings in Chapters 2 and 4. Collectively, this dissertation provides new tools for the assessment of response bouts and demonstrates their utility for discerning differences between experimental preparations and animal strains that may be otherwise indistinguishable with more primitive methods.
ContributorsBrackney, Ryan J (Author) / Sanabria, Federico (Thesis advisor) / Smith, Brian H. (Thesis advisor) / Neisewander, Janet (Committee member) / Killeen, Peter (Committee member) / Arizona State University (Publisher)
Created2015
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
The ability to detect and appropriately respond to chemical stimuli is important for many organisms, ranging from bacteria to multicellular animals. Responses to these stimuli can be plastic over multiple time scales. In the short-term, the synaptic strengths of neurons embedded in neural circuits can be modified and result in various forms of learning. In the long-term, the overall developmental trajectory of the olfactory network can be altered and synaptic strengths can be modified on a broad scale as a direct result of long-term (chronic) stimulus experience. Over evolutionary time the olfactory system can impose selection pressures that affect the odorants used in communication networks. On short time scales, I measured the effects of repeated alarm pheromone exposure on the colony-level defense behaviors in a social bee. I found that the responses to the alarm pheromone were plastic. This suggests that there may be mechanisms that affect individual plasticity to pheromones and regulate how these individuals act in groups to coordinate nest defense. On longer time scales, I measured the behavioral and neural affects of bees given a single chronic odor experience versus bees that had a natural, more diverse olfactory experience. The central brains of bees with a deprived odor experience responded more similarly to odorants in imaging studies, and did not develop a fully mature olfactory network. Additionally, these immature networks showed behavioral deficits when recalling odor mixture components. Over evolutionary time, signals need to engage the attention of and be easily recognized by bees. I measured responses of bees to a floral mixture and its constituent monomolecular components. I found that natural floral mixtures engage the orientation of bees’ antennae more strongly than single-component odorants and also provide more consistent central brain responses between stimulations. Together, these studies highlight the importance of olfactory experience on different scales and how the nervous system might impose pressures to select the stimuli used as signals in communication networks.
ContributorsJernigan, Christopher (Author) / Smith, Brian H. (Thesis advisor) / Newbern, Jason (Committee member) / Harrisoin, Jon (Committee member) / Rutowski, Ronald (Committee member) / Pratt, Stephen (Committee member) / Arizona State University (Publisher)
Created2018