Matching Items (133)
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 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
Description
Antibodies are the immunoglobulins which are secreted by the B cells after a microbial invasion. They are stable and stays in the serum for a long time which makes them an excellent biomarker for disease diagnosis. Inflammatory bowel disease is a type of autoimmune disease where the immune system mistakenly attacks the commensal bacteria and leads to inflammation. We studied antibody response of 100 Crohn’s disease (CD), 100 ulcerative colitis (UC) and 100 healthy controls against 1,173 bacterial and 397 viral proteins. We found some anti-bacterial antibodies higher in CD compared to controls while some antibodies lower in UC compared to controls. We were able to build biomarker panels with AUCs of 0.81, 0.87, and 0.82 distinguishing CD vs. control, UC vs. control, and CD vs. UC, respectively. Subgroup analysis based on the Montreal classification revealed that penetrating CD behavior (B3), colonic CD location (L2), and extensive UC (E3) exhibited highest antibody reactivity among all patients. We also wanted to study the reason for the presence of autoantibodies in the sera of healthy individuals. A meta-analysis of 9 independent biomarker study was performed to find 77 common autoantibodies shared by healthy individuals. There was no gender bias; however, the number of autoantibodies increased with age, plateauing around adolescence. Molecular mimicry likely contributed to the elicitation of a subset of these common autoantibodies as 21 common autoantigens had 7 or more ungapped amino acid matches with viral proteins. Intrinsic properties of protein like hydrophilicity, basicity, aromaticity, and flexibility were enriched for common autoantigens. Subcellular localization and tissue expression analysis indicated the sequestration of some autoantigens from circulating autoantibodies can explain the absence of autoimmunity in these healthy individuals.
ContributorsShome, Mahasish (Author) / LaBaer, Joshua (Thesis advisor) / Borges, Chad (Committee member) / Stephanopoulos, Nicholas (Committee member) / Arizona State University (Publisher)
Created2021
Description
Exposure of liquid biospecimens like plasma and serum (P/S) to improper handling and storage can impact the integrity of biomolecules, potentially leading to apparent quantitative changes of important clinical proteins. An accurate and quick estimate of the quality of biospecimens employed in biomarker discovery and validation studies is essential to facilitating accurate conclusions. ΔS-Cys-Albumin is a marker of blood P/S exposure to thawed conditions that can quantitatively track the exposure of P/S to temperatures greater than their freezing point of -30 C. Reported here are studies carried out to evaluate the potential of ΔS-Cys-Albumin to track the stability of clinically important analytes present in P/S upon their exposure to thawed conditions. P/S samples obtained from both cancer-free donors and cancer patients were exposed to 23 C (room temperature), 4 C and -20 C degrees, and the degree to which the apparent concentrations of clinically relevant biomolecules present in P/S were impacted during the time it took ΔS-Cys-Albumin to reach zero was measured. Analyte concentrations measured by molecular interaction-based assays were significantly impacted when samples were exposed to the point where average ΔS-Cys-Albumin fell below 12% at each temperature. Furthermore, the percentage of proteins that became unstable with time under thawed conditions exhibited a strong inverse linear relationship to ΔS-Cys-Albumin, indicating that ΔS-Cys-Albumin can serve as an effective surrogate marker to track the stability of other clinically relevant proteins in plasma as well as to estimate the fraction of proteins that have been destabilized by exposure to thawed conditions, regardless of what the exposure temperature(s) may have been. These results indicated that P/S exposure to thawed conditions disrupts epitopes required for clinical protein quantification via molecular interaction-based assays. In continuation of this theme, a spurious binding event between two clinically important proteins, Apolipoprotein E (ApoE) and Interferon- (IFN) present in human plasma under in vitro experimental conditions is also reported. The interaction was confirmed to be evident only when ApoE was expressed in vitro with a Glutathione-S-Transferase (GST) fusion tag. Future steps required to find the exact manner in which the GST fusion tag facilitated the association between ApoE and IFNγ are discussed with emphasis on the possible pitfalls associated with using fusion proteins for studying novel protein-protein interactions.
ContributorsKapuruge, Erandi Prasadini (Author) / Borges, Chad R (Thesis advisor) / LaBaer, Joshua (Committee member) / Van Horn, Wade (Committee member) / Arizona State University (Publisher)
Created2021
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 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
Description
Osteocalcin (Oc) is the most abundant non-collagen protein found in the bone, but its precise function is still not completely understood. Three glutamic acid (Glu) residues within its sequence are sites for vitamin K-dependent post-translational modification, replacing a hydrogen with a carboxylate located at the γ-carbon position, converting these to γ-carboxyglutamic acid (Gla) residues. This modification confers increased binding of Oc to Ca2+ and hydroxyapatite matrix. Presented here, novel metal binding partners Mn2+, Fe3+, and Cr3+ of human Oc were determined, while the previously identified binders to (generally) non-human Oc, Ca2+, Mg2+, Pb2+ and Al3+ were validated as binders to human Oc by direct infusion mass spectrometry with all metals binding with higher affinity to the post-translationally modified form (Gla-Oc) compared to the unmodified form (Glu-Oc). Oc was also found to form pentamer (Gla-Oc) and pentamer and tetramer (Glu-Oc) homomeric self-assemblies in the absence of NaCl, which disassembled to monomers in the presence of near physiological Na+ concentrations. Additionally, Oc was found to form filamentous structures in vitro by negative stain TEM in the presence of increased Ca2+ titrations in a Gla- and pH-dependent manner. Finally, by combining circular dichroism spectroscopy to determine the fraction of Gla-Oc bound, and inductively-coupled plasma mass spectrometry to quantify total Al concentrations, the data were fit to a single-site binding model and the equilibrium dissociation constant for Al3+ binding to human Gla-Oc was determined (Kd = 1.0 ± 0.12 nM). Including citrate, a known competitive binder of Al3+, maintained Al in solution and enabled calculation of free Al3+ concentrations using a Matlab script to solve the complex set of linear equations. To further improve Al solubility limits, the pH of the system was lowered to 4.5, the pH during bone resorption. Complementary binding experiments with Glu-Oc were not possible due to the observed precipitation of Glu-Oc at pH 4.5, although qualitatively if Glu-Oc binds Al3+, it is with much lower affinity compared to Gla-Oc. Taken together, the results presented here further support the importance of post-translational modification, and thus adequate nutritional intake of vitamin K, on the binding and self-assembly properties of human Oc.
ContributorsThibert, Stephanie (Author) / Borges, Chad R (Thesis advisor) / LaBaer, Joshua (Committee member) / Chiu, Po-Lin (Committee member) / Arizona State University (Publisher)
Created2021
Description
The 5-year survival rate for late-stage metastatic melanoma is only ~30%. A major reason for this low survival rate is that one of the most commonly mutated genes in melanoma, NRAS, has no FDA-approved targeted therapies. Because the RAS protein does not have any targeted therapies, patients with RAS mutant tumors have an ongoing need for treatments that indirectly target RAS. This thesis project aims to identify expression and phosphorylation levels of proteins downstream of RAS in melanoma cell lines with the most common driver mutations. By analyzing the protein-level differences between these genetic mutants, we hope to identify additional indirect RAS protein targets for the treatment of NRAS mutant melanoma. RAS has several downstream effector proteins involved in oncogenic signaling pathways including FAK, Paxillin, AKT, and ERK. 5 melanoma cell lines (2 BRAF mutant, 2 NRAS mutant, and 1 designated wildtype) were analyzed using western bloting for FAK, Paxillin, AKT, and ERK phosphorylation and total expression levels. The results of western blot analysis showed that NRAS mutant cell lines had increased expression of phosphorylated Paxillin. Increased Paxillin phosphorylation corresponds to increased Paxillin binding at the FAT domain of FAK. Therefore, cell lines with increased FAK FAT – Paxillin interaction would be more sensitive to FAK FAT domain inhibition. The data presented provide an an explanation for the reduction in cell viability in NRAS mutant cell lines infected with Ad-FRNK. This information also has significant clinical relevance as researchers work to develop synthetic FAK FAT domain inhibitors, such as cyclic peptides. Additionally, cell lines with high levels of phosphorylated AKT showed a significant reduction in the amount of phosphorylated ERK. The identification of this inverse relationship may help to explain why BRAF and NRAS mutations are mutually exclusive. To conclude, NRAS mutant cell lines have increased expression of phosphorylated Paxillin and AKT which may explain why NRAS mutant cell lines are more sensitive to FAK FAT domain inhibition.
ContributorsSherwood, Nicole (Author) / Gould, Ian (Thesis director) / LaBaer, Joshua (Committee member) / Marlowe, Timothy (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2022-05
Description
In this research, I surveyed existing methods of characterizing Epilepsy from Electroencephalogram (EEG) data, including the Random Forest algorithm, which was claimed by many researchers to be the most effective at detecting epileptic seizures [7]. I observed that although many papers claimed a detection of >99% using Random Forest, it was not specified “when” the detection was declared within the 23.6 second interval of the seizure event. In this research, I created a time-series procedure to detect the seizure as early as possible within the 23.6 second epileptic seizure window and found that the detection is effective (> 92%) as early as the first few seconds of the epileptic episode. I intend to use this research as a stepping stone towards my upcoming Masters thesis research where I plan to expand the time-series detection mechanism to the pre-ictal stage, which will require a different dataset.
ContributorsBou-Ghazale, Carine (Author) / Lai, Ying-Cheng (Thesis director) / Berisha, Visar (Committee member) / Barrett, The Honors College (Contributor) / Electrical Engineering Program (Contributor)
Created2022-05
Description
Emerging pathogens present several challenges to medical diagnostics. Primarily, the exponential spread of a novel pathogen through naïve populations require a rapid and overwhelming diagnostic response at the site of outbreak. While point-of-care (PoC) platforms have been developed for detection of antigens, serologic responses, and pathogenic genomes, only nucleic acid diagnostics currently have the potential to be developed and manufactured within weeks of an outbreak owing to the speed of next-generation sequencing and custom DNA synthesis. Among nucleic acid diagnostics, isothermal amplification strategies are uniquely suited for PoC implementation due to their simple instrumentation and lack of thermocycling requirement. Unfortunately, isothermal strategies are currently prone to spurious nonspecific amplification, hindering their specificity and necessitating extensive empirical design pipelines that are both time and resource intensive. In this work, isothermal amplification strategies are extensively compared for their feasibility of implementation in outbreak response scenarios. One such technology, Loop-mediated Amplification (LAMP), is identified as having high-potential for rapid development and PoC deployment. Various approaches to abrogating nonspecific amplification are described including a novel in silico design tool based on coarse-grained simulation of interactions between thermophilic DNA polymerase and DNA strands in isothermal reaction conditions. Nonspecific amplification is shown to be due to stabilization of primer secondary structures by high concentrations of Bst DNA polymerase and a mechanism of micro-complement-mediated cross-priming is demonstrated as causal via nanopore sequencing of nonspecific reaction products. The resulting computational model predicts primer set background in 64% of 67 test assays and its usefulness is illustrated further by determining problematic primers in a West Nile Virus-specific LAMP primer set and optimizing primer 3’ nucleotides to eliminate micro-complements within the reaction, resulting in inhibition of background accumulation. Finally, the emergence of Orthopox monkeypox (MPXV) as a recurring threat is discussed and SimCycle is utilized to develop a novel technique for clade-specific discrimination of MPXV based on bridging viral genomic rearrangements (Bridging LAMP). Bridging LAMP is implemented in a 4-plex microfluidic format and demonstrates 100% sensitivity in detection of 100 copies of viral lysates and 45 crude MPXV-positive patient samples collected during the 2022 Clade IIb outbreak.
ContributorsKnappenberger, Mark Daniel (Author) / Anderson, Karen S (Thesis advisor) / LaBaer, Joshua (Committee member) / Roberson, Robert (Committee member) / Lindsay, Stuart (Committee member) / Arizona State University (Publisher)
Created2023
Description
Predicting nonlinear dynamical systems has been a long-standing challenge in science. This field is currently witnessing a revolution with the advent of machine learning methods. Concurrently, the analysis of dynamics in various nonlinear complex systems continues to be crucial. Guided by these directions, I conduct the following studies. Predicting critical transitions and transient states in nonlinear dynamics is a complex problem. I developed a solution called parameter-aware reservoir computing, which uses machine learning to track how system dynamics change with a driving parameter. I show that the transition point can be accurately predicted while trained in a sustained functioning regime before the transition. Notably, it can also predict if the system will enter a transient state, the distribution of transient lifetimes, and their average before a final collapse, which are crucial for management. I introduce a machine-learning-based digital twin for monitoring and predicting the evolution of externally driven nonlinear dynamical systems, where reservoir computing is exploited. Extensive tests on various models, encompassing optics, ecology, and climate, verify the approach’s effectiveness. The digital twins can extrapolate unknown system dynamics, continually forecast and monitor under non-stationary external driving, infer hidden variables, adapt to different driving waveforms, and extrapolate bifurcation behaviors across varying system sizes. Integrating engineered gene circuits into host cells poses a significant challenge in synthetic biology due to circuit-host interactions, such as growth feedback. I conducted systematic studies on hundreds of circuit structures exhibiting various functionalities, and identified a comprehensive categorization of growth-induced failures. I discerned three dynamical mechanisms behind these circuit failures. Moreover, my comprehensive computations reveal a scaling law between the circuit robustness and the intensity of growth feedback. A class of circuits with optimal robustness is also identified. Chimera states, a phenomenon of symmetry-breaking in oscillator networks, traditionally have transient lifetimes that grow exponentially with system size. However, my research on high-dimensional oscillators leads to the discovery of ’short-lived’ chimera states. Their lifetime increases logarithmically with system size and decreases logarithmically with random perturbations, indicating a unique fragility. To understand these states, I use a transverse stability analysis supported by simulations.
ContributorsKong, Lingwei (Author) / Lai, Ying-Cheng (Thesis advisor) / Tian, Xiaojun (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Alkhateeb, Ahmed (Committee member) / Arizona State University (Publisher)
Created2023
Description
MicroRNAs (miRNAs) are 17-22 nucleotide non-coding RNAs that regulate gene expression by targeting non-complementary elements in the 3’ untranslated regions (3’UTRs) of mRNAs. miRNAs, which form complex networks of interaction that differ by tissue and developmental stage, display conservation in their function across metazoan species. Yet much remains unknown regarding their biogenesis, localization, strand selection, and their absolute abundance due to the difficulty of detecting and amplifying such small molecules. Here, I used an updated HT qPCR-based methodology to follow miRNA expression of 5p and 3p strands for all 190 C. elegans miRNAs described in miRBase throughout all six developmental stages in triplicates (total of 9,708 experiments), and studied their expression levels, tissue localization, and the rules underlying miRNA strand selection. My study validated previous findings and identified novel, conserved patterns of miRNA strand expression throughout C. elegans development, which at times correlate with previously observed developmental phenotypes. Additionally, my results highlighted novel structural principles underlying strand selection, which can be applied to higher metazoans.
Though optimized for use in C. elegans, this method can be easily adapted to other eukaryotic systems, allowing for more scalable quantitative investigation of miRNA biology and/or miRNA diagnostics.
ContributorsMeadows, Dalton Alexander (Author) / Mangone, Marco (Thesis advisor) / LaBaer, Joshua (Committee member) / Murugan, Vel (Committee member) / Wilson-Rawls, Jeanne (Committee member) / Arizona State University (Publisher)
Created2023