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Beta-Amyloid(Aβ) plaques and tau protein tangles in the brain are now widely recognized as the defining hallmarks of Alzheimer’s disease (AD), followed by structural atrophy detectable on brain magnetic resonance imaging (MRI) scans. However, current methods to detect Aβ/tau pathology are either invasive (lumbar puncture) or quite costly and not

Beta-Amyloid(Aβ) plaques and tau protein tangles in the brain are now widely recognized as the defining hallmarks of Alzheimer’s disease (AD), followed by structural atrophy detectable on brain magnetic resonance imaging (MRI) scans. However, current methods to detect Aβ/tau pathology are either invasive (lumbar puncture) or quite costly and not widely available (positron emission tomography (PET)). And one of the particular neurodegenerative regions is the hippocampus to which the influence of Aβ/tau on has been one of the research projects focuses in the AD pathophysiological progress. In this dissertation, I proposed three novel machine learning and statistical models to examine subtle aspects of the hippocampal morphometry from MRI that are associated with Aβ /tau burden in the brain, measured using PET images. The first model is a novel unsupervised feature reduction model to generate a low-dimensional representation of hippocampal morphometry for each individual subject, which has superior performance in predicting Aβ/tau burden in the brain. The second one is an efficient federated group lasso model to identify the hippocampal subregions where atrophy is strongly associated with abnormal Aβ/Tau. The last one is a federated model for imaging genetics, which can identify genetic and transcriptomic influences on hippocampal morphometry. Finally, I stated the results of these three models that have been published or submitted to peer-reviewed conferences and journals.
ContributorsWu, Jianfeng (Author) / Wang, Yalin (Thesis advisor) / Li, Baoxin (Committee member) / Liang, Jianming (Committee member) / Wang, Junwen (Committee member) / Wu, Teresa (Committee member) / Arizona State University (Publisher)
Created2022
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Description
Transorbital surgery has gained recent notoriety due to its incorporation into endoscopic skull base surgery. The body of published literature on the field is cadaveric and observation. The pre-clinical studies are focused on the use of the endoscope only. Furthermore the methodology utilised in the published literature is inconsistent and

Transorbital surgery has gained recent notoriety due to its incorporation into endoscopic skull base surgery. The body of published literature on the field is cadaveric and observation. The pre-clinical studies are focused on the use of the endoscope only. Furthermore the methodology utilised in the published literature is inconsistent and does not embody the optimal principles of scientific experimentation. This body of work evaluates a minimally invasive novel surgical corridor - the transorbital approach - its validity in neurosurgical practice, as well as both qualitatively and quantitatively assessing available technological advances in a robust experimental fashion. While the endoscope is an established means of visualisation used in clinical transorbital surgery, the microscope has never been assessed with respect to the transorbital approach. This question is investigated here and the anatomical and surgical benefits and limitations of microscopic visualisation demonstrated. The comparative studies provide increased knowledge on specifics pertinent to neurosurgeons and other skull base specialists when planning pre-operatively, such as pathology location, involved anatomical structures, instrument maneuvrability and the advantages and disadvantages of the distinct visualisation technologies. This is all with the intention of selecting the most suitable surgical approach and technology, specific to the patient, pathology and anatomy, so as to perform the best surgical procedure. The research findings illustrated in this body of work are diverse, reproducible and applicable. The transorbital surgical corridor has substantive potential for access to the anterior cranial fossa and specific surgical target structures. The neuroquantitative metrics investigated confirm the utility and benefits specific to the respective visualisation technologies i.e. the endoscope and microscope. The most appropriate setting wherein the approach should be used is also discussed. The transorbital corridor has impressive potential, can utilise all available technological advances, promotes multi-disciplinary co-operation and learning amongst clinicians and ultimately, is a means of improving operative patient care.
ContributorsHoulihan, Lena Mary (Author) / Preul, Mark C. (Thesis advisor) / Vernon, Brent (Thesis advisor) / O' Sullivan, Michael G.J. (Committee member) / Lawton, Michael T. (Committee member) / Santarelli, Griffin (Committee member) / Smith, Brian (Committee member) / Arizona State University (Publisher)
Created2021
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Description
A description of numerical and analytical work pertaining to models that describe the growth and progression of glioblastoma multiforme (GBM), an aggressive form of primary brain cancer. Two reaction-diffusion models are used: the Fisher-Kolmogorov-Petrovsky-Piskunov equation and a 2-population model that divides the tumor into actively proliferating and quiescent (or necrotic)

A description of numerical and analytical work pertaining to models that describe the growth and progression of glioblastoma multiforme (GBM), an aggressive form of primary brain cancer. Two reaction-diffusion models are used: the Fisher-Kolmogorov-Petrovsky-Piskunov equation and a 2-population model that divides the tumor into actively proliferating and quiescent (or necrotic) cells. The numerical portion of this work (chapter 2) focuses on simulating GBM expansion in patients undergoing treatment for recurrence of tumor following initial surgery. The models are simulated on 3-dimensional brain geometries derived from magnetic resonance imaging (MRI) scans provided by the Barrow Neurological Institute. The study consists of 17 clinical time intervals across 10 patients that have been followed in detail, each of whom shows significant progression of tumor over a period of 1 to 3 months on sequential follow up scans. A Taguchi sampling design is implemented to estimate the variability of the predicted tumors to using 144 different choices of model parameters. In 9 cases, model parameters can be identified such that the simulated tumor contains at least 40 percent of the volume of the observed tumor. In the analytical portion of the paper (chapters 3 and 4), a positively invariant region for our 2-population model is identified. Then, a rigorous derivation of the critical patch size associated with the model is performed. The critical patch (KISS) size is the minimum habitat size needed for a population to survive in a region. Habitats larger than the critical patch size allow a population to persist, while smaller habitats lead to extinction. The critical patch size of the 2-population model is consistent with that of the Fisher-Kolmogorov-Petrovsky-Piskunov equation, one of the first reaction-diffusion models proposed for GBM. The critical patch size may indicate that GBM tumors have a minimum size depending on the location in the brain. A theoretical relationship between the size of a GBM tumor at steady-state and its maximum cell density is also derived, which has potential applications for patient-specific parameter estimation based on magnetic resonance imaging data.
ContributorsHarris, Duane C. (Author) / Kuang, Yang (Thesis advisor) / Kostelich, Eric J. (Thesis advisor) / Preul, Mark C. (Committee member) / Crook, Sharon (Committee member) / Gardner, Carl (Committee member) / Arizona State University (Publisher)
Created2023
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Description
In this thesis, I present the study of nucleon structure from distinct perspectives. I start by elaborating the motivations behind the endeavors and then introducing the key concept, namely the generalized parton distribution functions (GPDs), which serves as the frame- work describing hadronic particles in terms of their fundamental constituents.

In this thesis, I present the study of nucleon structure from distinct perspectives. I start by elaborating the motivations behind the endeavors and then introducing the key concept, namely the generalized parton distribution functions (GPDs), which serves as the frame- work describing hadronic particles in terms of their fundamental constituents. The second chapter is then devoted to a detailed phenomenological study of the Virtual Compton Scattering (VCS) process, where a more comprehensive parametrization is suggested. In the third chapter, the renormalization kernels that enters the QCD evolution equations at twist- 4 accuracy are computed in terms of Feynman diagrams in momentum space, which can be viewed as an extension of the work by Bukhvostov, Frolov, Lipatov, and Kuraev (BKLK). The results can be used for determining the QCD background interaction for future precision measurements.
ContributorsJi, Yao, Ph. D (Author) / Belitsky, Andrei (Thesis advisor) / Lebed, Richard (Committee member) / Schmidt, Kevin E (Committee member) / Vachaspati, Tanmay (Committee member) / Arizona State University (Publisher)
Created2016
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Description
The work presented in this dissertation examines three different nonequilibrium particle physics processes that could play a role in answering the question “how was the particle content of today’s universe produced after the big bang?” Cosmic strings produced from spontaneous breaking of a hidden sector $U(1)_{\rm X}$ symmetry could couple

The work presented in this dissertation examines three different nonequilibrium particle physics processes that could play a role in answering the question “how was the particle content of today’s universe produced after the big bang?” Cosmic strings produced from spontaneous breaking of a hidden sector $U(1)_{\rm X}$ symmetry could couple to Standard Model fields through Higgs Portal or Kinetic Mixing operators and radiate particles that contribute to the diffuse gamma ray background. In this work we calculate the properties of these strings, including finding effective couplings between the strings and Standard Model fields. Explosive particle production after inflation, known as preheating, would have produced a stochastic background of gravitational waves (GW). This work shows how the presence of realistic additional fields and interactions can affect this prediction dramatically. Specifically, it considers the inflaton to be coupled to a light scalar field, and shows that even a very small quartic self-interaction term will reduce the amplitude of the gravitational wave spectrum. For self-coupling $\lambda_{\chi} \gtrsim g^2$, where $g^2$ is the inflaton-scalar coupling, the peak energy density goes as $\Omega_{\rm GW}^{(\lambda_{\chi})} / \Omega_{\rm GW}^{(\lambda_{\chi}=0)} \sim (g^2/\lambda_{\chi})^{2}$. Finally, leptonic charge-parity (CP) violation could be an important clue to understanding the origin of our universe's matter-antimatter asymmetry, and long-baseline neutrino oscillation experiments in the coming decade may uncover this. The CP violating effects of a possible fourth ``sterile" neutrino can interfere with the usual three neutrinos; this work shows how combinations of various measurements can help break those degeneracies.
ContributorsHyde, Jeffrey Morgan (Author) / Vachaspati, Tanmay (Thesis advisor) / Easson, Damien (Committee member) / Belitsky, Andrei (Committee member) / Comfort, Joseph (Committee member) / Arizona State University (Publisher)
Created2016
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Description
With the discovery of the Higgs Boson in 2012, particle physics has decidedly moved beyond the Standard Model into a new epoch. Though the Standard Model particle content is now completely accounted for, there remain many theoretical issues about the structure of the theory in need of resolution. Among these

With the discovery of the Higgs Boson in 2012, particle physics has decidedly moved beyond the Standard Model into a new epoch. Though the Standard Model particle content is now completely accounted for, there remain many theoretical issues about the structure of the theory in need of resolution. Among these is the hierarchy problem: since the renormalized Higgs mass receives quadratic corrections from a higher cutoff scale, what keeps the Higgs boson light? Many possible solutions to this problem have been advanced, such as supersymmetry, Randall-Sundrum models, or sub-millimeter corrections to gravity. One such solution has been advanced by the Lee-Wick Standard Model. In this theory, higher-derivative operators are added to the Lagrangian for each Standard Model field, which result in propagators that possess two physical poles and fall off more rapidly in the ultraviolet regime. It can be shown by an auxiliary field transformation that the higher-derivative theory is identical to positing a second, manifestly renormalizable theory in which new fields with opposite-sign kinetic and mass terms are found. These so-called Lee-Wick fields have opposite-sign propagators, and famously cancel off the quadratic divergences that plague the renormalized Higgs mass. The states in the Hilbert space corresponding to Lee-Wick particles have negative norm, and implications for causality and unitarity are examined.

This dissertation explores a variant of the theory called the N = 3 Lee-Wick

Standard Model. The Lagrangian of this theory features a yet-higher derivative operator, which produces a propagator with three physical poles and possesses even better high-energy behavior than the minimal Lee-Wick theory. An analogous auxiliary field transformation takes this higher-derivative theory into a renormalizable theory with states of alternating positive, negative, and positive norm. The phenomenology of this theory is examined in detail, with particular emphasis on the collider signatures of Lee-Wick particles, electroweak precision constraints on the masses that the new particles can take on, and scenarios in early-universe cosmology in which Lee-Wick particles can play a significant role.
ContributorsTerBeek, Russell Henry (Author) / Lebed, Richard F (Thesis advisor) / Alarcon, Ricardo (Committee member) / Belitsky, Andrei (Committee member) / Chamberlin, Ralph (Committee member) / Parikh, Maulik (Committee member) / Arizona State University (Publisher)
Created2015
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Description
This dissertation presents three novel algorithms with real-world applications to genomic oncology. While the methodologies presented here were all developed to overcome various challenges associated with the adoption of high throughput genomic data in clinical oncology, they can be used in other domains as well. First, a network informed feature

This dissertation presents three novel algorithms with real-world applications to genomic oncology. While the methodologies presented here were all developed to overcome various challenges associated with the adoption of high throughput genomic data in clinical oncology, they can be used in other domains as well. First, a network informed feature ranking algorithm is presented, which shows a significant increase in ability to select true predictive features from simulated data sets when compared to other state of the art graphical feature ranking methods. The methodology also shows an increased ability to predict pathological complete response to preoperative chemotherapy from genomic sequencing data of breast cancer patients utilizing domain knowledge from protein-protein interaction networks. Second, an algorithm that overcomes population biases inherent in the use of a human reference genome developed primarily from European populations is presented to classify microsatellite instability (MSI) status from next-generation-sequencing (NGS) data. The methodology significantly increases the accuracy of MSI status prediction in African and African American ancestries. Finally, a single variable model is presented to capture the bimodality inherent in genomic data stemming from heterogeneous diseases. This model shows improvements over other parametric models in the measurements of receiver-operator characteristic (ROC) curves for bimodal data. The model is used to estimate ROC curves for heterogeneous biomarkers in a dataset containing breast cancer and cancer-free specimen.
ContributorsSaul, Michelle (Author) / Dinu, Valentin (Thesis advisor) / Liu, Li (Committee member) / Wang, Junwen (Committee member) / Arizona State University (Publisher)
Created2021
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Description

Introduction: The ketogenic diet (KD) is a high-fat, low-carbohydrate diet that alters metabolism by increasing the level of ketone bodies in the blood. KetoCal® (KC) is a nutritionally complete, commercially available 4∶1 (fat∶ carbohydrate+protein) ketogenic formula that is an effective non-pharmacologic treatment for the management of refractory pediatric epilepsy. Diet-induced ketosis

Introduction: The ketogenic diet (KD) is a high-fat, low-carbohydrate diet that alters metabolism by increasing the level of ketone bodies in the blood. KetoCal® (KC) is a nutritionally complete, commercially available 4∶1 (fat∶ carbohydrate+protein) ketogenic formula that is an effective non-pharmacologic treatment for the management of refractory pediatric epilepsy. Diet-induced ketosis causes changes to brain homeostasis that have potential for the treatment of other neurological diseases such as malignant gliomas.

Methods: We used an intracranial bioluminescent mouse model of malignant glioma. Following implantation animals were maintained on standard diet (SD) or KC. The mice received 2×4 Gy of whole brain radiation and tumor growth was followed by in vivo imaging.

Results: Animals fed KC had elevated levels of β-hydroxybutyrate (p = 0.0173) and an increased median survival of approximately 5 days relative to animals maintained on SD. KC plus radiation treatment were more than additive, and in 9 of 11 irradiated animals maintained on KC the bioluminescent signal from the tumor cells diminished below the level of detection (p<0.0001). Animals were switched to SD 101 days after implantation and no signs of tumor recurrence were seen for over 200 days.

Conclusions: KC significantly enhances the anti-tumor effect of radiation. This suggests that cellular metabolic alterations induced through KC may be useful as an adjuvant to the current standard of care for the treatment of human malignant gliomas.

ContributorsAbdelwahab, Mohammed G. (Author) / Fenton, Kathryn E. (Author) / Preul, Mark C. (Author) / Rho, Jong M. (Author) / Lynch, Andrew (Author) / Stafford, Phillip (Author) / Scheck, Adrienne C. (Author) / Biodesign Institute (Contributor)
Created2012-05-01
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Description

Background: The successful treatment of malignant gliomas remains a challenge despite the current standard of care, which consists of surgery, radiation and temozolomide. Advances in the survival of brain cancer patients require the design of new therapeutic approaches that take advantage of common phenotypes such as the altered metabolism found in

Background: The successful treatment of malignant gliomas remains a challenge despite the current standard of care, which consists of surgery, radiation and temozolomide. Advances in the survival of brain cancer patients require the design of new therapeutic approaches that take advantage of common phenotypes such as the altered metabolism found in cancer cells. It has therefore been postulated that the high-fat, low-carbohydrate, adequate protein ketogenic diet (KD) may be useful in the treatment of brain tumors. We have demonstrated that the KD enhances survival and potentiates standard therapy in a mouse model of malignant glioma, yet the mechanisms are not fully understood.

Methods: To explore the effects of the KD on various aspects of tumor growth and progression, we used the immunocompetent, syngeneic GL261-Luc2 mouse model of malignant glioma.

Results: Tumors from animals maintained on KD showed reduced expression of the hypoxia marker carbonic anhydrase 9, hypoxia inducible factor 1-alpha, and decreased activation of nuclear factor kappa B. Additionally, tumors from animals maintained on KD had reduced tumor microvasculature and decreased expression of vascular endothelial growth factor receptor 2, matrix metalloproteinase-2 and vimentin. Peritumoral edema was significantly reduced in animals fed the KD and protein analyses showed altered expression of zona occludens-1 and aquaporin-4.

Conclusions: The KD directly or indirectly alters the expression of several proteins involved in malignant progression and may be a useful tool for the treatment of gliomas.

ContributorsWoolf, Eric (Author) / Curley, Kara L. (Author) / Liu, Qingwei (Author) / Turner, Gregory H. (Author) / Charlton, Julie A. (Author) / Preul, Mark C. (Author) / Scheck, Adrienne C. (Author) / College of Liberal Arts and Sciences (Contributor)
Created2015-06-17
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Description

Background: Malignant brain tumors affect people of all ages and are the second leading cause of cancer deaths in children. While current treatments are effective and improve survival, there remains a substantial need for more efficacious therapeutic modalities. The ketogenic diet (KD) - a high-fat, low-carbohydrate treatment for medically refractory epilepsy

Background: Malignant brain tumors affect people of all ages and are the second leading cause of cancer deaths in children. While current treatments are effective and improve survival, there remains a substantial need for more efficacious therapeutic modalities. The ketogenic diet (KD) - a high-fat, low-carbohydrate treatment for medically refractory epilepsy - has been suggested as an alternative strategy to inhibit tumor growth by altering intrinsic metabolism, especially by inducing glycopenia.

Methods: Here, we examined the effects of an experimental KD on a mouse model of glioma, and compared patterns of gene expression in tumors vs. normal brain from animals fed either a KD or a standard diet.

Results: Animals received intracranial injections of bioluminescent GL261-luc cells and tumor growth was followed in vivo. KD treatment significantly reduced the rate of tumor growth and prolonged survival. Further, the KD reduced reactive oxygen species (ROS) production in tumor cells. Gene expression profiling demonstrated that the KD induces an overall reversion to expression patterns seen in non-tumor specimens. Notably, genes involved in modulating ROS levels and oxidative stress were altered, including those encoding cyclooxygenase 2, glutathione peroxidases 3 and 7, and periredoxin 4.

Conclusions: Our data demonstrate that the KD improves survivability in our mouse model of glioma, and suggests that the mechanisms accounting for this protective effect likely involve complex alterations in cellular metabolism beyond simply a reduction in glucose.

ContributorsStafford, Phillip (Author) / Abdelwahab, Mohammed G. (Author) / Kim, Do Young (Author) / Preul, Mark C. (Author) / Rho, Jong M. (Author) / Scheck, Adrienne C. (Author) / Biodesign Institute (Contributor)
Created2010-09-10