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Caracals (Caracal caracal) are a felid species native to regions of southern Africa and western and central Asia. Despite their relatively high prevalence, the majority of research conducted on caracals has been undertaken on captive individuals, which encounter significantly different environments and exhibit different behaviors in comparison to caracals in

Caracals (Caracal caracal) are a felid species native to regions of southern Africa and western and central Asia. Despite their relatively high prevalence, the majority of research conducted on caracals has been undertaken on captive individuals, which encounter significantly different environments and exhibit different behaviors in comparison to caracals in the wild. Thereby, they likely have a vastly different virome. The goal of this study was to identify known and unknown DNA viruses associated with free-ranging caracals. Caracal fecal and organ samples were obtained from a caracal surveillance study undertaken in the Western Cape region of South Africa. Parasitic ticks found feeding on caracals were also obtained. Using a viral metagenomic informed approach, a novel circovirus (family Circoviridae) was detected and characterized in caracal fecal, kidney, spleen, and liver samples, as well as in ticks feeding on the caracals. To our knowledge, this is the first circovirus identified in caracals. The novel circovirus was determined to be closely related to a canine circovirus. These findings expand the knowledge of viral diversity and caracals and are greatly important to caracal conservation efforts as well as conservation efforts of other animals within their ecosystem.

ContributorsCollins, Courtney (Author) / Varsani, Arvind (Thesis director) / Dolby, Greer (Committee member) / Kraberger, Simona (Committee member) / Barrett, The Honors College (Contributor) / School of Molecular Sciences (Contributor)
Created2022-05
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Computational models have long been used to describe and predict the outcome of complex immunological processes. The dissertation work described here centers on the construction of multiscale computational immunology models that derives biological insights at the population, systems, and atomistic levels. First, SARS-CoV-2 mortality is investigated through the lens of

Computational models have long been used to describe and predict the outcome of complex immunological processes. The dissertation work described here centers on the construction of multiscale computational immunology models that derives biological insights at the population, systems, and atomistic levels. First, SARS-CoV-2 mortality is investigated through the lens of the predicted robustness of CD8+ T cell responses in 23 different populations. The robustness of CD8+ T cell responses in a given population was modeled by predicting the efficiency of endemic MHC-I protein variants to present peptides derived from SARS-CoV-2 proteins to circulating T cells. To accomplish this task, an algorithm, called EnsembleMHC, was developed to predict viral peptides with a high probability of being recognized by CD T cells. It was discovered that there was significant variation in the efficiency of different MHC-I protein variants to present SARS-CoV-2 derived peptides, and countries enriched with variants with high presentation efficiency had significantly lower mortality rates. Second, a biophysics-based MHC-I peptide prediction algorithm was developed. The MHC-I protein is the most polymorphic protein in the human genome with polymorphisms in the peptide binding causing striking changes in the amino acid compositions, or binding motifs, of peptide species capable of stable binding. A deep learning model, coined HLA-Inception, was trained to predict peptide binding using only biophysical properties, namely electrostatic potential. HLA-Inception was shown to be extremely accurate and efficient at predicting peptide binding motifs and was used to determine the peptide binding motifs of 5,821 MHC-I protein variants. Finally, the impact of stalk glycosylations on NL63 protein dynamics was investigated. Previous data has shown that coronavirus crown glycans play an important role in immune evasion and receptor binding, however, little is known about the role of the stalk glycans. Through the integration of computational biology, experimental data, and physics-based simulations, the stalk glycans were shown to heavily influence the bending angle of spike protein, with a particular emphasis on the glycan at position 1242. Further investigation revealed that removal of the N1242 glycan significantly reduced infectivity, highlighting a new potential therapeutic target. Overall, these investigations and associated innovations in integrative modeling.
ContributorsWilson, Eric Andrew (Author) / Anderson, Karen (Thesis advisor) / Singharoy, Abhishek (Thesis advisor) / Woodbury, Neal (Committee member) / Sulc, Petr (Committee member) / Arizona State University (Publisher)
Created2022
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Description
Scientists are entrusted with developing novel molecular strategies for effective prophylactic and therapeutic interventions. Antivirals are indispensable tools that can be targeted at viral domains directly or at cellular domains indirectly to obstruct viral infections and reduce pathogenicity. Despite their transformative potential in healthcare, to date, antivirals have been clinically

Scientists are entrusted with developing novel molecular strategies for effective prophylactic and therapeutic interventions. Antivirals are indispensable tools that can be targeted at viral domains directly or at cellular domains indirectly to obstruct viral infections and reduce pathogenicity. Despite their transformative potential in healthcare, to date, antivirals have been clinically approved to treat only 10 out of the greater than 200 known pathogenic human viruses. Additionally, as obligate intracellular parasites, many virus functions are intimately coupled with host cellular processes. As such, the development of a clinically relevant antiviral is challenged by the limited number of clear targets per virus and necessitates an extensive insight into these molecular processes. Compounding this challenge, many viral pathogens have evolved to evade effective antivirals. Therefore, a means to develop virus- or strain-specific antivirals without detailed insight into each idiosyncratic biochemical mechanism may aid in the development of antivirals against a larger swath of pathogens. Such an approach will tremendously benefit from having the specific molecular recognition of viral species as the lowest barrier. Here, I modify a nanobody (anti-green fluorescent protein) that specifically recognizes non-essential epitopes (glycoprotein M-pHluorin chimera) presented on the extra virion surface of a virus (Pseudorabies virus strain 486). The nanobody switches from having no inhibitory properties (tested up to 50 μM) to ∼3 nM IC50 in in vitro infectivity assays using porcine kidney (PK15) cells. The nanobody modifications use highly reliable bioconjugation to a three-dimensional wireframe deoxyribonucleic acid (DNA) origami scaffold. Mechanistic studies suggest that inhibition is mediated by the DNA origami scaffold bound to the virus particle, which obstructs the internalization of the viruses into cells, and that inhibition is enhanced by avidity resulting from multivalent virus and scaffold interactions. The assembled nanostructures demonstrate negligible cytotoxicity (<10 nM) and sufficient stability, further supporting their therapeutic potential. If translatable to other viral species and epitopes, this approach may open a new strategy that leverages existing infrastructures – monoclonal antibody development, phage display, and in vitro evolution - for rapidly developing novel antivirals in vivo.
ContributorsPradhan, Swechchha (Author) / Hariadi, Rizal (Thesis advisor) / Hogue, Ian (Committee member) / Varsani, Arvind (Committee member) / Chen, Qiang (Committee member) / Arizona State University (Publisher)
Created2022
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Description
Monkeypox virus (MPXV) is an orthopoxvirus that causes smallpox-like disease and has up to a 10% mortality rate, depending on the infectious strain. The global eradication of the smallpox virus has led to the decrease in smallpox vaccinations, which has led to a drastic increase in the number of human

Monkeypox virus (MPXV) is an orthopoxvirus that causes smallpox-like disease and has up to a 10% mortality rate, depending on the infectious strain. The global eradication of the smallpox virus has led to the decrease in smallpox vaccinations, which has led to a drastic increase in the number of human MPXV cases. MPXV has been named the most important orthopoxvirus to infect humans since the eradication of smallpox and has been the causative agent of the 2022 world-wide MPXV outbreak. Despite being highly pathogenic, MPXV contains a natural truncation at the N-terminus of its E3 homologue. Vaccinia virus (VACV) E3 protein has two domains: an N- terminus Z-form nucleic acid binding domain (Z-BD) and a C-terminus double stranded RNA binding domain (dsRBD). Both domains are required for pathogenesis, interferon (IFN) resistance, and protein kinase R (PKR) inhibition. The N-terminus is required for evasion of Z-DNA binding protein 1 (ZBP1)-dependent necroptosis. ZBP1 binding to Z- form deoxyribonucleic acid/ribonucleic acid (Z-DNA/RNA) leads to activation of receptor-interacting protein kinase 3 (RIPK3) leading to mixed lineage kinase domain- like (MLKL) phosphorylation, aggregation and cell death. This study investigated how different cell lines combat MPXV infection and how MPXV has evolved ways to circumvent the host response. MPXV is shown to inhibit necroptosis in L929 cells by degrading RIPK3 through the viral inducer of RIPK3 degradation (vIRD) and by inhibiting MLKL aggregation. Additionally, the data shows that IFN treatment efficiently inhibits MPXV replication in a ZBP1-, RIPK3-, and MLKL- dependent manner, but independent of necroptosis. Also, the data suggests that an IFN inducer with a pancaspase or proteasome inhibitor could potentially be a beneficial treatment against MPXV infections. Furthermore, it reveals a link between PKR and pathogen-induced necroptosis that has not been previously described.
ContributorsWilliams, Jacqueline (Author) / Jacobs, Bertram (Thesis advisor) / Langland, Jeffrey (Committee member) / Lake, Douglas (Committee member) / Varsani, Arvind (Committee member) / Arizona State University (Publisher)
Created2022
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Description
A remarkable phenomenon in contemporary physics is quantum scarring in classically chaoticsystems, where the wave functions tend to concentrate on classical periodic orbits. Quantum scarring has been studied for more than four decades, but the problem of efficiently detecting quantum scars has remained to be challenging, relying mostly on human visualization of wave

A remarkable phenomenon in contemporary physics is quantum scarring in classically chaoticsystems, where the wave functions tend to concentrate on classical periodic orbits. Quantum scarring has been studied for more than four decades, but the problem of efficiently detecting quantum scars has remained to be challenging, relying mostly on human visualization of wave function patterns. This paper develops a machine learning approach to detecting quantum scars in an automated and highly efficient manner. In particular, this paper exploits Meta learning. The first step is to construct a few-shot classification algorithm, under the requirement that the one-shot classification accuracy be larger than 90%. Then propose a scheme based on a combination of neural networks to improve the accuracy. This paper shows that the machine learning scheme can find the correct quantum scars from thousands images of wave functions, without any human intervention, regardless of the symmetry of the underlying classical system. This will be the first application of Meta learning to quantum systems. Interacting spin networks are fundamental to quantum computing. Data-based tomography oftime-independent spin networks has been achieved, but an open challenge is to ascertain the structures of time-dependent spin networks using time series measurements taken locally from a small subset of the spins. Physically, the dynamical evolution of a spin network under time-dependent driving or perturbation is described by the Heisenberg equation of motion. Motivated by this basic fact, this paper articulates a physics-enhanced machine learning framework whose core is Heisenberg neural networks. This paper demonstrates that, from local measurements, not only the local Hamiltonian can be recovered but the Hamiltonian reflecting the interacting structure of the whole system can also be faithfully reconstructed. Using Heisenberg neural machine on spin networks of a variety of structures. In the extreme case where measurements are taken from only one spin, the achieved tomography fidelity values can reach about 90%. The developed machine learning framework is applicable to any time-dependent systems whose quantum dynamical evolution is governed by the Heisenberg equation of motion.
ContributorsHan, Chendi (Author) / Lai, Ying-Cheng (Thesis advisor) / Yu, Hongbin (Committee member) / Dasarathy, Gautam (Committee member) / Seo, Jae-Sun (Committee member) / Arizona State University (Publisher)
Created2022
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Description
Traditional public health strategies for assessing human behavior, exposure, and activity are considered resource-exhaustive, time-consuming, and expensive, warranting a need for alternative methods to enhance data acquisition and subsequent interventions. This dissertation critically evaluated the use of wastewater-based epidemiology (WBE) as an inclusive and non-invasive tool for conducting near real-time

Traditional public health strategies for assessing human behavior, exposure, and activity are considered resource-exhaustive, time-consuming, and expensive, warranting a need for alternative methods to enhance data acquisition and subsequent interventions. This dissertation critically evaluated the use of wastewater-based epidemiology (WBE) as an inclusive and non-invasive tool for conducting near real-time population health assessments. A rigorous literature review was performed to gauge the current landscape of WBE to monitor for biomarkers indicative of diet, as well as exposure to estrogen-mimicking endocrine disrupting (EED) chemicals via route of ingestion. Wastewater-derived measurements of phytoestrogens from August 2017 through July 2019 (n = 156 samples) in a small sewer catchment revealed seasonal patterns, with highest average per capita consumption rates in January through March of each year (2018: 7.0 ± 2.0 mg d-1; 2019: 8.2 ± 2.3 mg d-1) and statistically significant differences (p = 0.01) between fall and winter (3.4 ± 1.2 vs. 6.1 ± 2.9 mg d-1; p ≤ 0.01) and spring and summer (5.6 ± 2.1 vs. 3.4 ± 1.5 mg d-1; p ≤ 0.01). Additional investigations, including a human gut microbial composition analysis of community wastewater, were performed to support a methodological framework for future implementation of WBE to assess population-level dietary behavior. In response to the COVID-19 global pandemic, a high-frequency, high-resolution sample collection approach with public data sharing was implemented throughout the City of Tempe, Arizona, and analyzed for SARS-CoV-2 (E gene) from April 2020 through March 2021 (n = 1,556 samples). Results indicate early warning capability during the first wave (June 2020) compared to newly reported clinical cases (8.5 ± 2.1 days), later transitioning to a slight lagging indicator in December/January 2020-21 (-2.0 ± 1.4 days). A viral hotspot from within a larger catchment area was detected, prompting targeted interventions to successfully mitigate community spread; reinforcing the importance of sample collection within the sewer infrastructure. I conclude that by working in tandem with traditional approaches, WBE can enlighten a comprehensive understanding of population health, with methods and strategies implemented in this work recommended for future expansion to produce timely, actionable data in support of public health.
ContributorsBowes, Devin Ashley (Author) / Halden, Rolf U (Thesis advisor) / Krajmalnik-Brown, Rosa (Thesis advisor) / Conroy-Ben, Otakuye (Committee member) / Varsani, Arvind (Committee member) / Whisner, Corrie (Committee member) / Arizona State University (Publisher)
Created2022
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Description
Few-layer black phosphorous (FLBP) is one of the most important two-dimensional (2D) materials due to its strongly layer-dependent quantized bandstructure, which leads to wavelength-tunable optical and electrical properties. This thesis focuses on the preparation of stable, high-quality FLBP, the characterization of its optical properties, and device applications.Part I presents an

Few-layer black phosphorous (FLBP) is one of the most important two-dimensional (2D) materials due to its strongly layer-dependent quantized bandstructure, which leads to wavelength-tunable optical and electrical properties. This thesis focuses on the preparation of stable, high-quality FLBP, the characterization of its optical properties, and device applications.Part I presents an approach to preparing high-quality, stable FLBP samples by combining O2 plasma etching, boron nitride (BN) sandwiching, and subsequent rapid thermal annealing (RTA). Such a strategy has successfully produced FLBP samples with a record-long lifetime, with 80% of photoluminescence (PL) intensity remaining after 7 months. The improved material quality of FLBP allows the establishment of a more definitive relationship between the layer number and PL energies. Part II presents the study of oxygen incorporation in FLBP. The natural oxidation formed in the air environment is dominated by the formation of interstitial oxygen and dangling oxygen. By the real-time PL and Raman spectroscopy, it is found that continuous laser excitation breaks the bonds of interstitial oxygen, and free oxygen atoms can diffuse around or form dangling oxygen under low heat. RTA at 450 °C can turn the interstitial oxygen into dangling oxygen more thoroughly. Such oxygen-containing samples show similar optical properties to the pristine BP samples. The bandgap of such FLBP samples increases with the concentration of the incorporated oxygen. Part III deals with the investigation of emission natures of the prepared samples. The power- and temperature-dependent measurements demonstrate that PL emissions are dominated by excitons and trions, with a combined percentage larger than 80% at room temperature. Such measurements allow the determination of trion and exciton binding energies of 2-, 3-, and 4-layer BP, with values around 33, 23, 15 meV for trions and 297, 276, 179 meV for excitons at 77K, respectively. Part IV presents the initial exploration of device applications of such FLBP samples. The coupling between photonic crystal cavity (PCC) modes and FLBP's emission is realized by integrating the prepared sandwich structure onto 2D PCC. Electroluminescence has also been achieved by integrating such materials onto interdigital electrodes driven by alternating electric fields.
ContributorsLi, Dongying (Author) / Ning, Cun-Zheng (Thesis advisor) / Vasileska, Dragica (Committee member) / Lai, Ying-Cheng (Committee member) / Yu, Hongbin (Committee member) / Arizona State University (Publisher)
Created2022
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Description

Cities in the Global South face rapid urbanization challenges and often suffer an acute lack of infrastructure and governance capacities. Smart Cities Mission, in India, launched in 2015, aims to offer a novel approach for urban renewal of 100 cities following an area‐based development approach, where the use of ICT

Cities in the Global South face rapid urbanization challenges and often suffer an acute lack of infrastructure and governance capacities. Smart Cities Mission, in India, launched in 2015, aims to offer a novel approach for urban renewal of 100 cities following an area‐based development approach, where the use of ICT and digital technologies is particularly emphasized. This article presents a critical review of the design and implementation framework of this new urban renewal program across selected case‐study cities. The article examines the claims of the so‐called “smart cities” against actual urban transformation on‐ground and evaluates how “inclusive” and “sustainable” these developments are. We quantify the scale and coverage of the smart city urban renewal projects in the cities to highlight who the program includes and excludes. The article also presents a statistical analysis of the sectoral focus and budgetary allocations of the projects under the Smart Cities Mission to find an inherent bias in these smart city initiatives in terms of which types of development they promote and the ones it ignores. The findings indicate that a predominant emphasis on digital urban renewal of selected precincts and enclaves, branded as “smart cities,” leads to deepening social polarization and gentrification. The article offers crucial urban planning lessons for designing ICT‐driven urban renewal projects, while addressing critical questions around inclusion and sustainability in smart city ventures.`

ContributorsPraharaj, Sarbeswar (Author)
Created2021-05-07
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Description
Poxviruses such as monkeypox virus (MPXV) are emerging zoonotic diseases. Compared to MPXV, Vaccinia virus (VACV) has reduced pathogenicity in humans and can be used as a partially protective vaccine against MPXV. While most orthopoxviruses have E3 protein homologues with highly similar N-termini, the MPXV homologue, F3, has a start

Poxviruses such as monkeypox virus (MPXV) are emerging zoonotic diseases. Compared to MPXV, Vaccinia virus (VACV) has reduced pathogenicity in humans and can be used as a partially protective vaccine against MPXV. While most orthopoxviruses have E3 protein homologues with highly similar N-termini, the MPXV homologue, F3, has a start codon mutation leading to an N-terminal truncation of 37 amino acids. The VACV protein E3 consists of a dsRNA binding domain in its C-terminus which must be intact for pathogenicity in murine models and replication in cultured cells. The N-terminus of E3 contains a Z-form nucleic acid (ZNA) binding domain and is also required for pathogenicity in murine models. Poxviruses produce RNA transcripts that extend beyond the transcribed gene which can form double-stranded RNA (dsRNA). The innate immune system easily recognizes dsRNA through proteins such as protein kinase R (PKR). After comparing a vaccinia virus with a wild-type E3 protein (VACV WT) to one with an E3 N-terminal truncation of 37 amino acids (VACV E3Δ37N), phenotypic differences appeared in several cell lines. In HeLa cells and certain murine embryonic fibroblasts (MEFs), dsRNA recognition pathways such as PKR become activated during VACV E3Δ37N infections, unlike VACV WT. However, MPXV does not activate PKR in HeLa or MEF cells. Additional investigation determined that MPXV produces less dsRNA than VACV. VACV E3Δ37N was made more similar to MPXV by selecting mutants that produce less dsRNA. By producing less dsRNA, VACV E3Δ37N no longer activated PKR in HeLa or MEF cells, thus restoring the wild-type phenotype. Furthermore, in other cell lines such as L929 (also a murine fibroblast) VACV E3Δ37N, but not VACV WT infection leads to activation of DNA-dependent activator of IFN-regulatory factors (DAI) and induction of necroptotic cell death. The same low dsRNA mutants demonstrate that DAI activation and necroptotic induction is independent of classical dsRNA. Finally, investigations of spread in an animal model and replication in cell lines where both the PKR and DAI pathways are intact determined that inhibition of both pathways is required for VACV E3Δ37N to replicate.
ContributorsCotsmire, Samantha (Author) / Jacobs, Bertram L (Thesis advisor) / Varsani, Arvind (Committee member) / Hogue, Brenda (Committee member) / Haydel, Shelley (Committee member) / Arizona State University (Publisher)
Created2021
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Description

Bats are a highly diverse mammal species with a dense virome and fascinating immune system. The following project utilizes metagenomics in order to identify DNA viruses present in populations of silver-haired bats and Mexican free-tailed bats from southern Arizona. A significant number of DNA viruses and novel viruses were identified

Bats are a highly diverse mammal species with a dense virome and fascinating immune system. The following project utilizes metagenomics in order to identify DNA viruses present in populations of silver-haired bats and Mexican free-tailed bats from southern Arizona. A significant number of DNA viruses and novel viruses were identified in the Cressdnaviricota phylum and Microvirdae family.

ContributorsHarding, Ciara (Author) / Varsani, Arvind (Thesis director) / Dolby, Greer (Committee member) / Kraberger, Simona (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor) / Watts College of Public Service & Community Solut (Contributor)
Created2022-05