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Revisiting U-Pb and ²⁶Al-²⁶Mg Systematics of Calcium Aluminum-Rich Inclusions: Applications on Early Solar System Chronology and Evolution History
No full textStable isotope systematics are powerful tools for understanding the evolution history of the earth and Solar system. In this thesis, I present applications of uranium (U) and magnesium (Mg) isotopes in both geochemistry and cosmochemistry.
Uranium is a redox-sensitive to the dissolved oxygen level in aqueous environment, and these redox reactions are associated with resolvable isotopic fractionation. Thus, U isotopes are widely used in paleo-environment reconstruction as a proxy of marine anoxia. For this application, the work presented in this thesis includes (1) exploration of the potential of bioapatite as a novel paleoredox proxy. and (2) re-calibrate the U isotope composition of seawater. The U-Pb and Al-Mg systematics provide constraints on the time sequence and composition of the early Solar System. For this application, the work presented in this thesis includes (1) combined Pb-Pb and Al-Mg systematics on calcium-aluminum-rich inclusions (CAIs) to resolve the discrepancies between these two chronometers (2) Al-Mg systematics of bulk CAIs to understand their precursors. This thesis also presents the analytical techniques developed for the studies above and the development of a comprehensive uranium isotope database.</p
Bridging Sensory Perception to Developmental Decision Making in Caenorhabditis elegans
Get PDFAmidst uncertain environmental flux, organisms must be able to appropriately adapt their physiology in response to or in preparation for harsh conditions. To accomplish this task, organisms need to accurately perceive current environmental cues, make informed decisions about how the future environmental landscape might unfold, and execute the genetic programs to manifest the proper physiological changes. As a prime example, the roundworm Caenorhabditis elegans makes multiple developmental decisions during its life cycle in response to environmental cues. During larval growth, C. elegans can forego reproductive growth and instead enter diapause (also called dauer), a developmentally arrested state resistant to environmental stress, in response to unfavorable growth conditions. The decisions to enter and exit dauer involve complex neurogenetic computations that integrate environmental cues, yet despite decades of research in the field of C. elegans dauer biology, we still do not fully understand how such sensory integration occurs. Furthermore, how the dauer entry and exit decisions compare and contrast to one another remains unclear.
In this thesis, I comprehensively analyze the C. elegans dauer exit decision using behavioral analyses, neuronal imaging, and gene reporter technologies. In Chapter Two, I I demonstrate how, during dauer exit, the ASJ chemosensory neurons integrate food availability and population density at both the levels of neuronal calcium dynamics and gene expression. I show that expression of the insulin-like peptide encoding gene ins 6 within the ASJ neurons is responsive to dauer-relevant cues, dependent on ASJ neuronal activity, and participates in an autoregulatory feedback mechanism that enforces decision commitment. In Chapter Three, I analyze how steroid hormones are essential for the dauer exit decision, and I illustrate how the spatiotemporal dynamics of steroid hormone regulation during dauer exit compares with that of dauer entry. Taken together, this thesis significantly advances our knowledge of the C. elegans dauer exit decision and helps us better understand how animals coordinate decisions over long timescales in response to changing environments.</p
Creating the Electric and Magnetic Fields for the nEDM@SNS Experiment
Get PDFThe neutron’s electric dipole moment (nEDM) remains one of the most important quantities to measure due to its sensitivity to new sources of CP violation. The nEDM@SNS Collaboration aims to improve this measurement by 2 orders of magnitude by using a novel measurement technique. This thesis focuses on two of the key challenges that this ambitious experiment must address, electrostatically and magnetostatically, respectively: the production of high voltage for the nEDM measurement using a Cavallo multiplier, and the magnetic environment created for the polarization and transmission of the cold neutron beam through the many nested components of the experimental apparatus. A series of Cavallo prototypes is developed, including a room-temperature apparatus and a cryogenic apparatus with two sets of electrodes. The created high voltage will be monitored without physical contact using a designed and prototyped field mill. Transmission and polarization measurements of the cold neutron beam through the nested components of the experimental apparatus are discussed
I. Dynamics of Subduction Initiation and II. Constraining Sedimentary Basin Structure with Seismic Ambient Noise
No full textSubduction initiation, the inception of a subduction zone, heralds dramatic changes in tectonic plate kinematics and dynamics. In the first half of the thesis, I focus on understanding the dynamics of the subduction initiation process through a synthesis of numerical computations and theoretical frameworks. In Chapter 2, we employ force balance analysis and 2D geodynamic models to yield an analytical solution on the force evolution of the subducting plate. This formulation illuminates a pivotal phase in subduction initiation —- the compression-to-extension transition of plate forces -— as a defining milestone. In Chapter 3, we extend this analytical framework into a sliced 3D context (2.5D) while incorporating the influence of strike-slip motion. Modified from Chapter 2, the analytical solution validates that strike-slip motion facilitates subduction initiation by accelerating the process of weakening. Chapter 4 ventures into 3D geodynamic modeling, focusing on the Puysegur trench -— a living example of subduction initiation. The models demonstrate a capability to match multiple geophysical and geological observations quantitatively with mechanical models. With a parametric search, we discover the best-fitting models require a relatively fast strain weakening rate, which can be explained by pore-pressure weakening at shallow depths and grain-size reduction at greater depths.
The second part of this thesis transitions to ambient seismic noise correlation. In Chapter 5, we conduct an ambient noise tomography in northern Los Angeles basins with a newly obtained, dense seismic data set. The new shear wave velocity model exhibits a lower velocity in the basins than previous community models, which can potentially resolve the inconsistency between observed and calculated ground motions. In Chapter 6, we introduce a new method to identify the near-field noise sources from the spurious arrivals in ambient noise correlations. The correlation between the inverted noise sources and geological features in northern LA basins suggests the viability of this technique as a novel means of identifying geological structures, including faults.</p
Design and Construction of Bacterial Genomes at the Megabase-Scale
No full textBuilding genomic chimeras would enable melding of the diverse functions and properties of life. However, prior arts in genome synthesis are limited to reconstituting functions within singular genomes rather than combining diverse genomic functions across multiple distinct genomes. Existing methods are also prohibitively expensive, laborious, time-consuming, and not scalable for creating large genomes. Addressing these limitations, the author invented Additive Conjugative-CAST Engineering (ACE) combining conjugation with CRISPR-associated transposition (CAST) to deliver and integrate up to half a genome per step from a donor into a precisely defined position in the recipient’s genome. This work demonstrates ACE’s engineering capacities integrating a 2-megabase donor genomic segment in a single step and at least three megabase in two steps. Importantly, ACE’s generality is confirmed through the creation of genomic chimeras across species, genus, order, and class barriers. With ACE, this work further showcases that such chimeric organisms, denoted genome expanded organisms (GEOs), can be forged from at least three starting bacterial strains, and are stably maintained to express all acquired genomic parts. Principles confounding ACE are expanded onto genome editing technologies, such as Prime Editing, and further explored for the megabase-scale transfer of DNA into eukaryotes. ACE and derivative technologies thereof offer a new paradigm of creating artificial lifeforms to combine and potentially create novel functions beyond the constraints of nature, while probing and elucidating genome plasticity, architecture, and expression patterns of GEOs.</p
Taking the Pulse of Life: Intramolecular and Clumped Isotopic Perspectives on the Origins and Evolution of Hydrocarbons in Geological and Prebiotic Systems
Get PDFLife’s origins and fate are tightly intertwined. All life as we know it is composed of proteins, carbohydrates, lipids, and nucleic acids. These biomolecules are synthesized today by cellular machinery made of the same components, leaving open questions about the origins of life and prebiotic chemistry. After death, organic remnants are buried in sediments, undergoing microbial reworking, consolidation, and transformation into kerogen. As temperature and pressure increase with depth, kerogen matures, releasing oil and gas before ultimately transforming into graphite. The question remains: can we decipher the traces of life (and non-life) from somewhat altered organic matter from the past or on other planets? This thesis explores the origins and evolution of one of the most fundamental classes of compounds—hydrocarbons—across geological and prebiotic settings through novel applications of intramolecular and clumped isotope analysis.
Chapter 2 delves into the evolution of isotopic signatures in methane, the simplest hydrocarbon, during the maturation process. By studying the clumped isotope effects of thermogenic methane formation through pyrolysis experiments, this chapter challenges previously held assumptions about abiotic and microbial signatures. The findings offer new opportunities to constrain the thermal maturation of sedimentary organic matter and have implications for the search for extraterrestrial life.
To facilitate high-precision measurements of hydrocarbon isotopic structures, Chapter 3 presents hardware and software developments enabling automated, high-throughput analysis using Orbitrap mass spectrometry. Chapter 4 then introduces a novel method coupling gas chromatography and Orbitrap MS to simultaneously measure intramolecular ¹³C and ²H distributions in n-alkanes, validating the technique for forensic fingerprinting and natural sample characterization.
Turning to the impact of thermal maturation, Chapter 5 examines how n-alkane intramolecular isotope patterns evolve through pyrolysis experiments. Kinetic isotope effects control residual n-alkane isotopic compositions, with minimal alteration to intramolecular distributions under the studied conditions, suggesting preservation of primitive signatures.
Chapter 6 brings together these analytical developments to compare intramolecular isotope compositions of n-nonadecane from sedimentary, abiotic, and biological sources. Distinctive isotopic fingerprints are established for each source, with implications for interpreting organic matter histories and detecting potential signatures of extraterrestrial life.
Collectively, this thesis expands the "molecular detective" toolkit for tracing hydrocarbon origins across diverse environments, from deep petroleum systems to potential prebiotic reaction pathways. The findings illuminate key processes governing isotopic biosignatures and their preservation through geological time.</p
Towards a Synthetic Nucleus: Separating Transcription and Translation in Cell-Free Protein Expression Systems
Get PDFSynthetic cells represent the culmination of decades of research aimed at deciphering the intricacies of life at its most basic level. The result of the fusion of biology, chemistry, physics, and engineering, synthetic cells promise to revolutionize biotechnology, medicine, and beyond. This thesis focuses on the ramifications of incorporating a synthetic nucleus within a synthetic cell.
To experimentally study transcription and translation, we use a commercially available cell-free protein expression system comprising all the purified proteins essential for protein production (PURE), along with a fluorescent RNA aptamer--malachite green aptamer (MGapt), and a green fluorescent protein (deGFP). We observed that the chemical composition of the PURE system significantly impacts MGapt fluorescence, leading to inaccurate RNA calculations. We identify the reducing agent, dithiothreitol (DTT), to address this challenge as a crucial chemical affecting MGapt fluorescence. We propose a model that can reliably model MGapt measurements in commercial PURE. This investigation illuminates the intricate dynamics of MGapt in PURE and emphasizes the necessity of accounting for environmental factors in RNA measurements employing aptamers.
Subsequently, to advance our understanding of a synthetic nucleus and analyze the effects of separating transcription and translation in a cell-free protein expression, we propose and validate a chemical reaction network model for transcription (TX) in PURE. Additionally, we used open-source software to expand an existing translation (TL) model for any arbitrary DNA sequence to create a nearly complete model of TX-TL in PURE. Leveraging this model, we investigate the effect of introducing a synthetic nucleus by modulating the RNA diffusion rate and resource allocation. This detailed model showcases our capability to comprehensively model protein expression in PURE, enabling insights into the efficacy of segregating transcription and translation processes within the artificial cell environment. Lastly, we provide a perspective on the future of synthetic cells with an artificial nucleus and propose further steps to develop the proposed synthetic nucleus model.</p
Low-Energy Plasma–Surface Interactions at Airless Icy Bodies
Get PDFLow-energy plasma surface interactions occur in many solar system environments and are especially important in the magnetospheres of gas giants. Within these magnetospheres orbit a catalogue of icy moons, some of which famously host interior liquid-water oceans. They are continuously exposed to a cold, corotating plasma “wind,” resulting in bombardment by heavy reactive ions, with peak number fluxes in the hyperthermal energy regime (10s to 100s of eV). Despite their abundance, these low-energy ions have been mostly overlooked in planetary science because they are poor drivers of radiolysis. In this thesis we take a combined experimental-theoretical approach to understanding the interaction of hyperthermal water group molecules/ions with relevant surfaces, motivated by some specific solar system observations, mostly from the Saturn system.
We begin with experimental case studies of water-group ion scattering on carbonaceous (Chapter 2) and chloride-salt surfaces (Chapter 3), focusing on the emission of secondary negative ions. For carbonaceous surfaces, we detect surprisingly energetic carbon fragments, apparently emitted by near-threshold sputtering processes. The most abundant products (O⁻, C2⁻, C2H⁻) are consistent with mass range for negative PUIs of unknown origin observed near Dione and Rhea. The reported mass ranges, however, have been estimated for pick-up of initially stationary ions, which is a poor assumption for the products we observe. Our experiments with chloride salts (relevant to Jupiter’s moon Europa) are complicated by surface charging but provide kinematic evidence of reactive scattering and single knock-on sputter processes. Specifically, we observe abstraction of Cl from Pt to form chlorine monoxide anions. We then describe a modification of our scattering apparatus to enable exposure of ice targets, developing a one-of-a-kind experimental facility (Chapter 6). Some limited and preliminary results for Ar⁺ and O⁺ bombardment of amorphous water ice follow, which are more revealing of experimental challenges than of surface chemistry and dynamics.
Our theoretical efforts include Reactive Molecular Dynamics simulations of collision-induced chemistry in ices using the ReaxFF formalism. These reveal a novel non-radiolytic process (an Eley-Rideal reaction) for formation of molecular oxygen in low-energy (2−50 eV) water-group molecule bombardment of crystalline water ice, relevant to the maintenance of O₂ exospheres at Saturn’s moons Dione and Rhea (Chapter 4). With the addition of CH₄ to the ice (as a clathrate), bombardment results in formation of methanol and formaldehyde at yields as great as 10% and 5%, respectively (Chapter 5). Two mechanisms are observed for methanol synthesis: one a typical radiolysis process and the second a two-step non-radiolytic mechanism. We provide preliminary results for an HCN/CH₄/H₂O ice target in Chapter 8 to motivate further study of the role that hyperthermal reactive ions play in synthesis of prebiotic organics. Finally, in Chapter 7, we describe a Monte-Carlo model for the production and transport of H₂ in the Enceladus due to plasma-surface interactions. Radiolysis by suprathermal electrons is the primary contributor, but the calculated mixing ratio falls several orders of magnitude short of the reported ~1%, which lends credibility to the notion that H₂ is being emitted from Enceladus’ internal ocean.</p
Kernel Methods for Learning About Complex Dynamical Systems
Get PDFThe ubiquitous spread of machine learning tools in natural sciences in recent years has seen trully exponential growth. What sounded like an expression from a sci-fi novel mere 7 years ago, "solving PDEs with machine learning" is hardly surprising to anyone today. The variety of methods is very large, but most of them revolve around the artificial neural networks. Despite tremendous success of applications to problems in natural sciences, and despite many strides towards a fundamental theory of neural networks, they still often lack interpretability and robustness of the results. An alternative, much narrower class of machine learning algorithms is comprised of the kernel methods. These methods, in contrast, offer deep analytical theory, with many approximation results and interpretable components. The firm foundation of the kernel methods, however, is offset by the practical difficulties, such as high computational cost, the burden of high-dimensional optimization and the necessity to manually choose kernel parametrization. This thesis explores a few applications of the kernel methods to dynamical systems, with the goal to address some of those issues. The comparison between the kernel analog forecasting and the plain Gaussian process regression is made, both from theoretical and practical sides, and a parametric extension of the former is proposed. An application of kernel methods to closures of dynamical systems is showcased. Finally, an application of data assimilation machinery to an epidemiological model is shown.</p