Matching Items (37)
Description
Olfaction is an important sensory modality for behavior since odors inform animals of the presence of food, potential mates, and predators. The fruit fly, Drosophila melanogaster, is a favorable model organism for the investigation of the biophysical mechanisms that contribute to olfaction because its olfactory system is anatomically similar to but simpler than that of vertebrates. In the Drosophila olfactory system, sensory transduction takes place in olfactory receptor neurons housed in the antennae and maxillary palps on the front of the head. The first stage of olfactory processing resides in the antennal lobe, where the structural unit is the glomerulus. There are at least three classes of neurons in the antennal lobe - excitatory projection neurons, excitatory local neurons, and inhibitory local neurons. The arborizations of the local neurons are confined to the antennal lobe, and output from the antennal lobe is carried by projection neurons to higher regions of the brain. Different views exist of how circuits of the Drosophila antennal lobe translate input from the olfactory receptor neurons into projection neuron output. We construct a conductance based neuronal network model of the Drosophila antennal lobe with the aim of understanding possible mechanisms within the antennal lobe that account for the variety of projection neuron activity observed in experimental data. We explore possible outputs obtained from olfactory receptor neuron input that mimic experimental recordings under different connectivity paradigms. First, we develop realistic minimal cell models for the excitatory local neurons, inhibitory local neurons, and projections neurons based on experimental data for Drosophila channel kinetics, and explore the firing characteristics and mathematical structure of these models. We then investigate possible interglomerular and intraglomerular connectivity patterns in the Drosophila antennal lobe, where olfactory receptor neuron input to the antennal lobe is modeled with Poisson spike trains, and synaptic connections within the antennal lobe are mediated by chemical synapses and gap junctions as described in the Drosophila antennal lobe literature. Our simulation results show that inhibitory local neurons spread inhibition among all glomeruli, where projection neuron responses are decreased relatively uniformly for connections of synaptic strengths that are homogeneous. Also, in the case of homogeneous excitatory synaptic connections, the excitatory local neuron network facilitates odor detection in the presence of weak stimuli. Excitatory local neurons can spread excitation from projection neurons that receive more input from olfactory receptor neurons to projection neurons that receive less input from olfactory receptor neurons. For the parameter values for the network models associated with these results, eLNs decrease the ability of the network to discriminate among single odors.
ContributorsLuli, Dori (Author) / Crook, Sharon (Thesis advisor) / Baer, Steven (Committee member) / Castillo-Chavez, Carlos (Committee member) / Smith, Brian (Committee member) / Arizona State University (Publisher)
Created2013
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
The phycologist, M. R. Droop, studied vitamin B12 limitation in the flagellate Monochrysis lutheri and concluded that its specific growth rate depended on the concentration of the vitamin within the cell; i.e. the cell quota of the vitamin B12. The Droop model provides a mathematical expression to link growth rate to the intracellular concentration of a limiting nutrient. Although the Droop model has been an important modeling tool in ecology, it has only recently been applied to study cancer biology. Cancer cells live in an ecological setting, interacting and competing with normal and other cancerous cells for nutrients and space, and evolving and adapting to their environment. Here, the Droop equation is used to model three cancers.
First, prostate cancer is modeled, where androgen is considered the limiting nutrient since most tumors depend on androgen for proliferation and survival. The model's accuracy for predicting the biomarker for patients on intermittent androgen deprivation therapy is tested by comparing the simulation results to clinical data as well as to an existing simpler model. The results suggest that a simpler model may be more beneficial for a predictive use, although further research is needed in this field prior to implementing mathematical models as a predictive method in a clinical setting.
Next, two chronic myeloid leukemia models are compared that consider Imatinib treatment, a drug that inhibits the constitutively active tyrosine kinase BCR-ABL. Both models describe the competition of leukemic and normal cells, however the first model also describes intracellular dynamics by considering BCR-ABL as the limiting nutrient. Using clinical data, the differences in estimated parameters between the models and the capacity for each model to predict drug resistance are analyzed.
Last, a simple model is presented that considers ovarian tumor growth and tumor induced angiogenesis, subject to on and off anti-angiogenesis treatment. In this environment, the cell quota represents the intracellular concentration of necessary nutrients provided through blood supply. Mathematical analysis of the model is presented and model simulation results are compared to pre-clinical data. This simple model is able to fit both on- and off-treatment data using the same biologically relevant parameters.
First, prostate cancer is modeled, where androgen is considered the limiting nutrient since most tumors depend on androgen for proliferation and survival. The model's accuracy for predicting the biomarker for patients on intermittent androgen deprivation therapy is tested by comparing the simulation results to clinical data as well as to an existing simpler model. The results suggest that a simpler model may be more beneficial for a predictive use, although further research is needed in this field prior to implementing mathematical models as a predictive method in a clinical setting.
Next, two chronic myeloid leukemia models are compared that consider Imatinib treatment, a drug that inhibits the constitutively active tyrosine kinase BCR-ABL. Both models describe the competition of leukemic and normal cells, however the first model also describes intracellular dynamics by considering BCR-ABL as the limiting nutrient. Using clinical data, the differences in estimated parameters between the models and the capacity for each model to predict drug resistance are analyzed.
Last, a simple model is presented that considers ovarian tumor growth and tumor induced angiogenesis, subject to on and off anti-angiogenesis treatment. In this environment, the cell quota represents the intracellular concentration of necessary nutrients provided through blood supply. Mathematical analysis of the model is presented and model simulation results are compared to pre-clinical data. This simple model is able to fit both on- and off-treatment data using the same biologically relevant parameters.
ContributorsEverett, Rebecca Anne (Author) / Kuang, Yang (Thesis advisor) / Nagy, John (Committee member) / Milner, Fabio (Committee member) / Crook, Sharon (Committee member) / Jackiewicz, Zdzislaw (Committee member) / Arizona State University (Publisher)
Created2015
Description
Cell morphology and the distribution of voltage gated ion channels play a major role in determining a neuron's firing behavior, resulting in the specific processing of spatiotemporal synaptic input patterns. Although many studies have provided insight into the computational properties arising from neuronal structure as well as from channel kinetics, no comprehensive theory exists which explains how the interaction of these features shapes neuronal excitability. In this study computational models based on the identified Drosophila motoneuron (MN) 5 are developed to investigate the role of voltage gated ion channels, the impact of their densities and the effects of structural features.
First, a spatially collapsed model is used to develop voltage gated ion channels to study the excitability of the model neuron. Changing the channel densities reproduces different in situ observed firing patterns and induces a switch from resonator to integrator properties. Second, morphologically realistic multicompartment models are studied to investigate the passive properties of MN5. The passive electrical parameters fall in a range that is commonly observed in neurons, MN5 is spatially not compact, but for the single subtrees synaptic efficacy is location independent. Further, different subtrees are electrically independent from each other. Third, a continuum approach is used to formulate a new cable theoretic model to study the output in a dendritic cable with many subtrees, both analytically and computationally. The model is validated, by comparing it to a corresponding model with discrete branches. Further, the approach is demonstrated using MN5 and used to investigate spatially distributions of voltage gated ion channels.
First, a spatially collapsed model is used to develop voltage gated ion channels to study the excitability of the model neuron. Changing the channel densities reproduces different in situ observed firing patterns and induces a switch from resonator to integrator properties. Second, morphologically realistic multicompartment models are studied to investigate the passive properties of MN5. The passive electrical parameters fall in a range that is commonly observed in neurons, MN5 is spatially not compact, but for the single subtrees synaptic efficacy is location independent. Further, different subtrees are electrically independent from each other. Third, a continuum approach is used to formulate a new cable theoretic model to study the output in a dendritic cable with many subtrees, both analytically and computationally. The model is validated, by comparing it to a corresponding model with discrete branches. Further, the approach is demonstrated using MN5 and used to investigate spatially distributions of voltage gated ion channels.
ContributorsBerger, Sandra (Author) / Crook, Sharon (Thesis advisor) / Baer, Steven (Committee member) / Hamm, Thomas (Committee member) / Smith, Brian (Committee member) / Arizona State University (Publisher)
Created2014
Description
Tobacco and alcohol are the most commonly abused drugs worldwide. Many people smoke and drink together, but the mechanisms of this nicotine (NIC) -ethanol (EtOH) dependence are not fully known. EtOH has been shown to affect some nicotinic acetylcholine receptors (nAChRs), which potentially underlies NIC-EtOH codependence. Ventral Tegmental Area (VTA) dopamine (DA) and γ-aminobutyric acid (GABA) neurons express different nAChR subtypes, whose net activation results in enhancement of DA release in the Prefrontal Cortex (PFC) and Nucleus Accumbens (NAc). Enhancement of DA transmission in this mesocorticolimbic system is thought to lead to rewarding properties of EtOH and NIC, clarification of which is relevant to public health and clinical diseases. The aim of this study was to elucidate pharmacological mechanisms of action employed by both NIC and EtOH through nAChRs in VTA neurons by evaluating behavioral, network, synaptic and receptor functions therein. It was hypothesized that VTA GABA neurons are controlled by α7 nAChRs on presynaptic GLUergic terminals and α6 nAChRs on presynaptic GABAergic terminals. NIC and EtOH, via these nAChRs, modulate VTA GABA neuronal function. This modulation may underlie NIC and EtOH reward and reinforcement, while pharmacological manipulation of these nAChRs may be a therapeutic strategy to treat NIC or EtOH dependence. This data demonstrates that in VTA GABA neurons, α7 nAChRs on GLUergic terminals play a key role in the mediation of local NIC-induced firing increase. α6*-nAChRs on GABA terminals enhances presynaptic GABA release, and leads to greater inhibition to VTA GABA neurons, which results in an increase VTA DA neuron firing via a disinhibition mechanism. Genetic knockout of these nAChRs significantly prevents EtOH-induced animal conditioned place preference (CPP). Furthermore, levo-tetrahydropalmadine (l-THP), a compound purified from natural Chinese herbs, blocks nAChRs, prevents NIC-induced DA neuronal firing, and eliminates NIC CPP, suggesting it as a promising candidate in a new generation of interventions for smoking cessation. Improved understanding of underlying mechanisms and development of new drugs will increase the number of successful quitters each year and dramatically improve the quality of life for millions suffering from addiction, as well as those around them.
ContributorsTaylor, Devin (Author) / Wu, Jie (Committee member) / Olive, M F (Committee member) / Whiteaker, Paul (Committee member) / Vu, Eric (Committee member) / Hammer, Ronald (Committee member) / Arizona State University (Publisher)
Created2015
Description
Advances in experimental techniques have allowed for investigation of molecular dynamics at ever smaller temporal and spatial scales. There is currently a varied and growing body of literature which demonstrates the phenomenon of \emph{anomalous diffusion} in physics, engineering, and biology. In particular many diffusive type processes in the cell have been observed to follow a power law $\left \propto t^\alpha$ scaling of the mean square displacement of a particle. This contrasts with the expected linear behavior of particles undergoing normal diffusion. \emph{Anomalous sub-diffusion} ($\alpha<1$) has been attributed to factors such as cytoplasmic crowding of macromolecules, and trap-like structures in the subcellular environment non-linearly slowing the diffusion of molecules. Compared to normal diffusion, signaling molecules in these constrained spaces can be more concentrated at the source, and more diffuse at longer distances, potentially effecting the signalling dynamics. As diffusion at the cellular scale is a fundamental mechanism of cellular signaling and additionally is an implicit underlying mathematical assumption of many canonical models, a closer look at models of anomalous diffusion is warranted. Approaches in the literature include derivations of fractional differential diffusion equations (FDE) and continuous time random walks (CTRW). However these approaches are typically based on \emph{ad-hoc} assumptions on time- and space- jump distributions. We apply recent developments in asymptotic techniques on collisional kinetic equations to develop a FDE model of sub-diffusion due to trapping regions and investigate the nature of the space/time probability distributions assosiated with trapping regions. This approach both contrasts and compliments the stochastic CTRW approach by positing more physically realistic underlying assumptions on the motion of particles and their interactions with trapping regions, and additionally allowing varying assumptions to be applied individually to the traps and particle kinetics.
ContributorsHoleva, Thomas Matthew (Author) / Ringhofer, Christian (Thesis advisor) / Baer, Steve (Thesis advisor) / Crook, Sharon (Committee member) / Gardner, Carl (Committee member) / Taylor, Jesse (Committee member) / Arizona State University (Publisher)
Created2014
Description
Patients with Alzheimer's disease (AD) exhibit a significantly higher incidence of unprovoked seizures compared to age-matched non-AD controls, and animal models of AD (i.e., transgenic human amyloid precursor protein, hAPP mice) display neural hyper-excitation and epileptic seizures. Hyperexcitation is particularly important because it contributes to the high incidence of epilepsy in AD patients as well as AD-related synaptic deficits and neurodegeneration. Given that there is significant amyloid-β (Aβ) accumulation and deposition in AD brain, Aβ exposure ultimately may be responsible for neural hyper-excitation in both AD patients and animal models. Emerging evidence indicates that α7 nicotinic acetylcholine receptors (α7-nAChR) are involved in AD pathology, because synaptic impairment and learning and memory deficits in a hAPPα7-/- mouse model are decreased by nAChR α7 subunit gene deletion. Given that Aβ potently modulates α7-nAChR function, that α7-nAChR expression is significantly enhanced in both AD patients and animal models, and that α7-nAChR play an important role in regulating neuronal excitability, it is reasonable that α7-nAChRs may contribute to Aβ-induced neural hyperexcitation. We hypothesize that increased α7-nAChR expression and function as a consequence of Aβ exposure is important in Aβ-induced neural hyperexcitation. In this project, we found that exposure of Aβ aggregates at a nanomolar range induces neuronal hyperexcitation and toxicity via an upregulation of α7-nAChR in cultured hippocampus pyramidal neurons. Aβ up-regulates α7-nAChRs function and expression through a post translational mechanism. α7-nAChR up-regulation occurs prior to Aβ-induced neuronal hyperexcitation and toxicity. Moreover, inhibition of α7-nAChR or deletion of α7-nAChR prevented Aβ induced neuronal hyperexcitation and toxicity, which suggests that α7-nAChRs are required for Aβ induced neuronal hyperexcitation and toxicity. These results reveal a profound role for α7-nAChR in mediating Aβ-induced neuronal hyperexcitation and toxicity and predict that Aβ-induced up-regulation of α7-nAChR could be an early and critical event in AD etiopathogenesis. Drugs targeting α7-nAChR or seizure activity could be viable therapies for AD treatment.
ContributorsLiu, Qiang (Author) / Wu, Jie (Thesis advisor) / Lukas, Ronald J (Committee member) / Chang, Yongchang (Committee member) / Sierks, Michael (Committee member) / Smith, Brian (Committee member) / Vu, Eric (Committee member) / Arizona State University (Publisher)
Created2011
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
Predicting resistant prostate cancer is critical for lowering medical costs and improving the quality of life of advanced prostate cancer patients. I formulate, compare, and analyze two mathematical models that aim to forecast future levels of prostate-specific antigen (PSA). I accomplish these tasks by employing clinical data of locally advanced prostate cancer patients undergoing androgen deprivation therapy (ADT). I demonstrate that the inverse problem of parameter estimation might be too complicated and simply relying on data fitting can give incorrect conclusions, since there is a large error in parameter values estimated and parameters might be unidentifiable. I provide confidence intervals to give estimate forecasts using data assimilation via an ensemble Kalman Filter. Using the ensemble Kalman Filter, I perform dual estimation of parameters and state variables to test the prediction accuracy of the models. Finally, I present a novel model with time delay and a delay-dependent parameter. I provide a geometric stability result to study the behavior of this model and show that the inclusion of time delay may improve the accuracy of predictions. Also, I demonstrate with clinical data that the inclusion of the delay-dependent parameter facilitates the identification and estimation of parameters.
ContributorsBaez, Javier (Author) / Kuang, Yang (Thesis advisor) / Kostelich, Eric (Committee member) / Crook, Sharon (Committee member) / Gardner, Carl (Committee member) / Nagy, John (Committee member) / Arizona State University (Publisher)
Created2017
Description
Mathematical models are important tools for addressing problems that exceed experimental capabilities. In this work, I present ordinary and partial differential equation (ODE, PDE) models for two problems: Vicodin abuse and impact cratering.
The prescription opioid Vicodin is the nation's most widely prescribed pain reliever. The majority of Vicodin abusers are first introduced via prescription, distinguishing it from other drugs in which the most common path to abuse begins with experimentation. I develop and analyze two mathematical models of Vicodin use and abuse, considering only those patients with an initial Vicodin prescription. Through adjoint sensitivity analysis, I show that focusing efforts on prevention rather than treatment has greater success at reducing the total population of abusers. I prove that solutions to each model exist, are unique, and are non-negative. I also derive conditions for which these solutions are asymptotically stable.
Verification and Validation (V&V) are necessary processes to ensure accuracy of computational methods. Simulations are essential for addressing impact cratering problems, because these problems often exceed experimental capabilities. I show that the Free Lagrange (FLAG) hydrocode, developed and maintained by Los Alamos National Laboratory, can be used for impact cratering simulations by verifying FLAG against two analytical models of aluminum-on-aluminum impacts at different impact velocities and validating FLAG against a glass-into-water laboratory impact experiment. My verification results show good agreement with the theoretical maximum pressures, and my mesh resolution study shows that FLAG converges at resolutions low enough to reduce the required computation time from about 28 hours to about 25 minutes.
Asteroid 16 Psyche is the largest M-type (metallic) asteroid in the Main Asteroid Belt. Radar albedo data indicate Psyche's surface is rich in metallic content, but estimates for Psyche's composition vary widely. Psyche has two large impact structures in its Southern hemisphere, with estimated diameters from 50 km to 70 km and estimated depths up to 6.4 km. I use the FLAG hydrocode to model the formation of the largest of these impact structures. My results indicate an oblique angle of impact rather than a vertical impact. These results also support previous claims that Psyche is metallic and porous.
The prescription opioid Vicodin is the nation's most widely prescribed pain reliever. The majority of Vicodin abusers are first introduced via prescription, distinguishing it from other drugs in which the most common path to abuse begins with experimentation. I develop and analyze two mathematical models of Vicodin use and abuse, considering only those patients with an initial Vicodin prescription. Through adjoint sensitivity analysis, I show that focusing efforts on prevention rather than treatment has greater success at reducing the total population of abusers. I prove that solutions to each model exist, are unique, and are non-negative. I also derive conditions for which these solutions are asymptotically stable.
Verification and Validation (V&V) are necessary processes to ensure accuracy of computational methods. Simulations are essential for addressing impact cratering problems, because these problems often exceed experimental capabilities. I show that the Free Lagrange (FLAG) hydrocode, developed and maintained by Los Alamos National Laboratory, can be used for impact cratering simulations by verifying FLAG against two analytical models of aluminum-on-aluminum impacts at different impact velocities and validating FLAG against a glass-into-water laboratory impact experiment. My verification results show good agreement with the theoretical maximum pressures, and my mesh resolution study shows that FLAG converges at resolutions low enough to reduce the required computation time from about 28 hours to about 25 minutes.
Asteroid 16 Psyche is the largest M-type (metallic) asteroid in the Main Asteroid Belt. Radar albedo data indicate Psyche's surface is rich in metallic content, but estimates for Psyche's composition vary widely. Psyche has two large impact structures in its Southern hemisphere, with estimated diameters from 50 km to 70 km and estimated depths up to 6.4 km. I use the FLAG hydrocode to model the formation of the largest of these impact structures. My results indicate an oblique angle of impact rather than a vertical impact. These results also support previous claims that Psyche is metallic and porous.
ContributorsCaldwell, Wendy K (Author) / Wirkus, Stephen (Thesis advisor) / Asphaug, Erik (Committee member) / Camacho, Erika T (Committee member) / Crook, Sharon (Committee member) / Plesko, Catherine S (Committee member) / Smith, Hal (Committee member) / Arizona State University (Publisher)
Created2019