VictorJuiz/thesis huggingface dataset:
Defining non-canonical modes of gene regulation in budding yeast meiosis

Gene regulation in budding yeast meiosis is incredibly complex, involving a number of non-canonical strategies. Defining the different modes of regulation is key to fully understanding how the cell functions, especially under changing conditions. Here, we examined two non-canonical gene regulation strategies employed by yeast during meiosis: alternative translation initiation and regulated turnover of ribosomal proteins./nIn chapter two, we investigated the role of alternative translation initiation site choice in yeast. Genomic analyses in budding yeast have helped define the foundational principles of eukaryotic gene expression. However, in the absence of empirical methods for defining coding regions, these analyses have historically excluded specific classes of possible coding regions, such as those initiating at non-AUG start codons. We applied an experimental approach to globally annotate translation initiation sites in yeast and identified 149 genes with alternative N-terminally extended protein isoforms initiating from near-cognate codons upstream of annotated AUG start codons. These isoforms are produced in concert with canonical isoforms and translated with high specificity, resulting from initiation at only a small subset of possible start codons. The non-AUG initiation driving their production is enriched during meiosis and induced by low eIF5A, which is seen in this context. These findings reveal widespread production of non-canonical protein isoforms and unexpected complexity to the rules by which even a simple eukaryotic genome is decoded./nIn chapter three, we evaluated the role of protein degradation during yeast meiosis, and found that ribosomes are degraded and resynthesized in spores, revealing an interesting mode of regulation of an important molecular machine. Protein degradation is known to be a key component of expression regulation for individual genes, but its global impact on gene expression has been difficult to determine. We analyzed a parallel gene expression dataset of yeast meiotic differentiation, identifying instances of coordinated protein-level decreases to identify new cases of regulated meiotic protein degradation, including degradation of ribosomes. Comparison of protein and translation measurements over time revealed that ribosomes are degraded and resynthesized in spores, making the biological purpose of ribosome resetting an interesting area of follow-up.

Advisor: Brar, Gloria A
Coming Home: The Western, Media, and Masculinity

In its analysis of four postwar Westerns (the films The Last Sunset and Gunman’s Walk, and the television Westerns Have Gun—Will Travel and The Rifleman), this dissertation finds a contradictory ideological strain intrinsic to the genre’s frontier legacy, as well as a critical semiosis specific to its production era. By centralizing the postwar era’s domestic concerns over and against the genre’s typical emphasis on the frontier mythos associated with Theodore Roosevelt, these Westerns subvert the stereotypical frontier/civilization dyad. By reconceiving the genre in a way that privileges “civilization” over “frontier,” this dissertation shows that the crucible of “savage” Nature, which formerly determined the exceptionality of the Westerner’s masculine character (as a synecdoche for an exceptional national one), is a cultural production that turns against civilization itself. Denuded of their naturalizing origin, and depicted as social productions within the dramatic action, the gunmen protagonists of each of these four Westerns additionally appear as complex gender constructions. By juxtaposing allusions from each Western to the ideological and aesthetic history of the genre and the socio-political context of the postwar era, the dissertation approaches the Cold War era as similarly mythological, constructed, and contradictory. I demonstrate that the conventions of the genre correspond with the conventions of domestication and nuclearization specific to the postwar era. In the process, this dissertation locates and defines a semiotic function for, and of, each Western that highlights the distinct narrative modalities respective of their mediums. In this sense, Coming Home: The Western, Media, and Masculinity continues a scholarly tradition suited for American studies and gender studies, while approaching the genre via the modalities of comparative media studies and television studies.

Advisor: Whissel, Kristen
Constraining Consciousness

Many philosophers hold that there’s a fundamental difference in conceiving of the mind first-personally, in a how-it-feels way vs. conceiving of the mind third-personally, in a how-it-works way. This is a mistake. And the quickest way to see this mistake is with an example./nIn that widely held view, we have two separate ways of thinking about consciousness. We can think of mental states as phenomenally conscious—as feeling a certain way or as having certain qualitative aspects—or we can think of mental states as conscious in functional sense—as being available for arbitrary use in a cognitive system. We’re supposed to find a sharp contrast in concepts here: simply reflecting these different senses of “consciousness” won’t reveal anything about how they actually overlap. But I think we have good reason to reject this view: we cannot conceive of an experience that is functionally isolated from the subject for whom it is an experience. If this is right, it looks like the phenomenal and functional senses of “consciousness” aren’t totally distinct after all, since there are a priori functional constraints on phenomenal experience./nBecause conceptual dualists draw a sharp distinction between thinking about the mind in a first-personal, how-it-feels way and a third-personal, how-it-works way, they run into a scary epistemological problem: the specter of phenomenal overflow. Each and every attempt to mark off the boundary between a subject's cognitive access and phenomenal experience, a skeptical challenge will arise in the form of phenomenal overflow. Conceptual dualists are themselves responsible for this, because of their conceptual commitments, which bar them from the sorts of a priori resources that might have helped them to avoid such a situation. And so they end up saddled with a feeble, grossly- underpowered epistemology, which can't possible match the picture most of us have of our own epistemological situation. If you're sufficiently spooked-out by that epistemological fate, then you're be better off abandoning conceptual dualism./nAre phenomenal concepts functional concepts? For evidence that they aren't, many have looked towards absent qualia and inverted qualia cases (which, respectively, involve 'subtracting' and 'inverting' the phenomenal consciousness of 'normal' subjects). Such/ni/ncases have been thought to demonstrate the conceptual independence of the phenomenal from the physical. This is a mistake. While the phenomenal cannot be conceptually reduced to the functional, neither can it be conceptually isolated from the functional. A modest version of conceptual functionalism is laid out, its advantages and disadvantages considered.

Advisor: Lee, Geoffrey
Campbell, John
Uncertainty, Inequality, and Global Climate Policy

Despite decades of research on the science and potential impacts of climate change, considerable disagreement remains over how to balance the upfront costs of reducing greenhouse gas emissions with the benefits of avoiding future negative impacts. This disagreement persists, in part, because deep uncertainties in the climate system limit our understanding of how temperature and sea level will evolve over the coming centuries. The global nature and long timescales of climate change provide an additional challenge, as climate policy analysis requires difficult ethical judgments on how to value the well-being of individuals at different income levels and across generations. In this dissertation, I address these issues by using integrated assessment models (IAMs) to analyze how distributional equity concerns and previously neglected climate uncertainties affect climate policy design. In the first part, I calculate the optimal carbon dioxide mitigation policy when society accounts for the trade-off between mitigation costs, climate damages, and the climate and localized health consequences of changes in air pollutant co-emissions. The presence of health “co-benefits” leads to increased mitigation levels that may be consistent with a 2 °C target, but the magnitude of this effect crucially depends on independent air quality policies and the value society assigns to improvements in human health. In the second part, I use a Bayesian calibration framework and an ensemble of IAMs to quantify how parametric climate uncertainties affect the social cost of methane (SC-CH4). Despite accounting for the recent 25% upward revision to methane radiative forcing, the constrained models produce a mean SC-CH4 estimate 23% lower than the value recently used by the U.S. federal government. I also provide the first probabilistic equity-weighted SC-CH4 estimates and find that the U.S. value is more than an order of magnitude higher than sub-Saharan Africa’s. The third part of my dissertation focuses on low-probability, high-impact upper tail estimates of the social cost of carbon (SCC). In this analysis, I first show that the simple climate models from the IAMs used to calculate official U.S. SCC estimates do not pass relatively simple out-of-sample hindcast tests and exhibit impulse response behaviors that are inconsistent with current scientific understanding. I then couple the non-climate components of each IAM to a reduced complexity Earth system model and quantify how different treatments of parametric uncertainties affect 95th percentile SCC estimates. While failing to account for interactions between the uncertain parameters increases the 95th percentile SCC by more than 20%, following the official U.S. SCC climate uncertainty framework nearly doubles it.

Advisor: Anthoff, David
In vivo assembly and evolution of artificial metalloenzymes towards new-to-nature metabolism

This dissertation presents the development of artificial metalloenzymes (ArMs) for unnatural reactions, the in vivo engineering and catalysis of ArMs, and the integration of ArMs with a natural biosynthetic pathway to produce products previously inaccessible by nature in a microbial host.Chapter 1 provides an overview of ArMs that are generated from incorporation of abiotic metal complexes into protein scaffolds. Assembly strategies and non-natural reactivity of this class of biohybrid catalysts are presented in detail. While a majority of work in this field has focused on the design and application of ArMs in vitro, the overview discusses the emerging trend towards integrating ArMs into whole-cell systems and metabolic networks and the challenges associated with the development of ArMs that function in vivo. Chapter 2 describes the directed evolution of an artificial iridium-containing P450 that catalyzed the cyclopropanation of monocyclic terpenes and their derivatives with diastereoselectivities that are complementary to those attained with chiral transition metal catalysts. The combination of the broad reactivity of iridium porphyrin and the exquisite selectivity provided by proteins generates catalysts with activity and selectivity previously unattainable with natural enzymes or transition metal complexes alone. Chapter 3 describes the application of a nonpathogenic Escherichia coli (E. coli) strain, Nissle 1917, for recombinant expression of P450s containing artificial cofactors. The outer-membrane receptor in Nissle 1917 transports iridium porphyrin into cells for binding to the apo-CYP119 expressed in the cytoplasm. We show that the Ir-CYP119 (CYP119 containing iridium porphyrin) assembled in vivo catalyzes carbene insertions into benzylic C-H bonds with remarkable enantioselectivity and site-selectivity. The application of Nissle 1917 as a whole-cell screening platform eliminates the need for laborious processing procedures, drastically increases the throughput of screening, and accelerates the development of Ir-CYP119 with improved catalytic properties. Chapter 4 describes the integration of artificial metalloenzymes that catalyze unnatural reactions into metabolic networks that could broaden the cache of molecules produced biosynthetically by microorganisms. We report the assembly of an artificial P450 containing an iridium-porphyrin complex in the cytoplasm of an E. coli that produces a terpene by heterologous expression and insertion of this ArM into the biosynthetic pathway to produce an unnatural terpenoid. This work shows that synthetic biology and synthetic chemistry, incorporated together in whole cells, can produce molecules previously inaccessible by natural metabolic pathways.

Advisor: Hartwig, John
Printed, Flexible Electrochemical Sensors

Chemicals are ubiquitous, from the food we eat to the composition of our own bodies. Different chemicals can give us information about ourselves or our surroundings. For example, chemicals in the body can give information about the state of a person's health, while chemicals in the atmosphere can give information about pollution. Chemical sensors are necessary to gain this information. Electrochemical sensors can use electrical signal output to indicate the presence and amount of chemicals. This is done two ways: amperometric sensors output current, and potentiometric sensors output potential. The magnitude of the signal indicates the amount of chemical present. Printing is useful for fabricating these sensors in flexible form factors and for disposable uses./nThis thesis discusses the development of several different printed electrochemical sensors. An overview is first given of the developments in printed electrochemical sensors which enabled this work. Printed amperometric sensors for determination of lactate in sweat are optimized for sensing the transition from aerobic to anaerobic metabolism. These sensors are printed to accommodate form factors closely matching that of skin. These sensors have a sensitivity of 4.8 uA/mM and a linear range up to 25 mM lactate. However, an investigation into the selectivity of these sensors determines they are susceptible to interference from the salt present in sweat, making them less useful as sensors and more useful as indicators. Potentiometric sensors are proposed as an alternative for sensing metabolites in sweat, due to their selectivity in sweat. Potentiometric sensors cannot be made for sensing lactate, but ammonium sensors are demonstrated instead for determining levels of carbohydrates and metabolic condition. Potentiometric ammonium sensors show a near-Nernstian response of 57.5 mV/decade +/- 0.3 mV/decade. Sweat is not the only application for printed sensors. Printed potentiometric sensors for nitrate in soil are also demonstrated, where printing enables the use of degradable materials. The nitrate sensors have near-Nernstian sensitivity of -53.3 mV/decade +/- 1.1 mV/decade, and the printed reference developed shows relative insensitivity to nitrate in solution. The work discussed here indicates a step toward distributed networks of sensors.

Advisor: Arias, Ana C
Analysis of Dictionary Learning and Random Forest under Data-inspired Models

Many algorithms in Machine Learning have demonstrated powerful empirical performance in terms of prediction accuracy and ability to extract knowledge from data. Inspired by the empirical success, researchers study the behavior of those algorithms under theoretical models. Two challenges must be addressed when one {tries} to understand those algorithms from a theoretical perspective. First, a sound theoretical model should be considered. A good model should reflect key properties of the real data. If the models do not capture important aspects of the real data, the observations and/or conclusions made on those theoretical models {may not be relevant} to practice. Thus, theoretical models that reflect certain properties of real data are required so that the insights obtained from those models are convincing to practitioners. Second, many of these algorithms are hard to analyze via traditional techniques. Therefore, novel techniques are required to analyze those algorithms under new theoretical models. In this thesis, we analyze two problems under novel real-data inspired theoretical models: $\ell_1$-minimization for dictionary learning and seeking important features and feature interactions from {Random Forest} (RF). Both analyses give unique insights into the problem by studying a novel data generative model. For dictionary learning, we propose two novel theoretical models: exact sparse model and Bernoulli-type models. Unlike most previous {analyses} that assume the data is {generated from} Gaussian distributions with sparsity constraints, these new models can capture non-Gaussian data distributions and allow us to analyze the algorithms under novel data properties such as non-negativity and heavy-tail. We show that $\ell_1$-minimization model in Dictionary Learning does not satisfy the classic global identifiability condition under the new model. However, the reference dictionary still enjoys some global property across all the feasible dictionaries. Our theoretical analysis leads to a novel algorithm called Dictionary Learning Block Coordinate Descent (DL-BCD). For RF, we start off with analyzing the feature importance bias for noisy features when using Mean Decrease Impurity (MDI). Then, we study the feature interaction recovery problem and analyzed the data-inspired Local-Spiky Sparse (LSS) model without Lipschitz assumptions that are often present in the previous literature. We show that the depth-weighted-prevalence of a true feature interaction in the decision paths of trees does not depend on the model coefficients but only on the size of the interaction. The theoretical analysis leads to a novel feature ranking method called LSSrank. We examine the performance of LSSrank on simulated data and it has high probability to rank true interactions at the top under the LSS model.

Advisor: Yu, Bin
Relationships between sleep physiology and Alzheimer’s disease in the aging brain

Impaired sleep is a frequent symptom affecting patients with Alzheimer’s disease (AD). Recent work has shown that sleep disruption occurs very early in the progression of AD, before the presence of significant cognitive decline. The accumulation of tau neurofibrillary tangles and β-amyloid (Aβ) plaques, the hallmark pathologies of AD, have been shown to impact sleep electrophysiology in rodent models. Furthermore, experimental disruption of sleep accelerates AD progression, suggesting that this relationship is bi-directional. With the recent advent of PET radiotracers that bind to in vivo tau and Aβ in the human brain, it is now possible to study how the presence of these proteins affect sleep physiology in healthy older people. Is disrupted sleep an early marker of the pathogenesis of AD? In this dissertation, I address this question by investigating associations between a diverse set of sleep metrics and PET-measured tau and Aβ burden in cognitively healthy older adults. Chapter 1 demonstrates that greater tau and Aβ are associated with distinct impairments in sleep oscillatory signatures, and that self-reported changes in sleep across the lifespan are predictive of pathological burden in late-life. Chapter 2 utilizes a longitudinal design to establish that impairments in both micro-electrophysiological and macro-architectural measures of sleep predict the subsequent rate of Aβ accumulation. Chapter 3 describes associations between tau and Aβ and real life patterns of sleep behavior, and shows that individuals with greater pathological burden are worse at estimating their own sleep quality. Together, these data illustrate the ways that sleep, measured objectively and subjectively, in the sleep lab and at home, is affected in the earliest stages of AD. These findings indicate the sensitivity of human sleep physiology to AD, and suggest that sleep may provide a non-invasive biomarker of tau and Aβ burden in cognitively normal older adults. Most importantly, while more work is needed to confirm these findings, these relationships offer the possibility that improving sleep quality may slow the progression of AD.

Advisor: Walker, Matthew P
Short-range Order and its Impact on the Deformation Behaviors of Alloys

Chemical short-range order (SRO) of atoms within a nominally single-phase solid solution is known to significantly impact the mechanical properties of alloys. While associated phenomena have been indirectly revealed, direct observation of the SRO microstructure at the nanoscale remains unexplored. In the current dissertation we show the development of methods to directly observe SRO in several model alloys using energy-filtered Transmission Electron Microscopy (TEM). Our observations reveal the distribution of SRO domains and verified that the degree of SRO could be tailored by the thermomechanical history of the alloys. The SRO distribution is discussed in light of the deformation features formed both ex-situ and in-situ in the TEM. The ability to conduct quantitative analysis of SRO should give us a new method to engineer desirable performance of structural alloys. A synergistic study of the mechanical properties of Ti-Al and CrCoNi alloys were carried out to examine their correlations to the degree of SRO. The SRO induced deformation features, including SRO hardening, wavy to planar slip transition, diffuse anti phase boundary and planar slip assisted deformation twinning, were observed from bulk to nanometer scales. We demonstrated that with the presence of SRO, the dislocation dynamics during the deformation would exhibit a tendency of planar configuration with subsequent deformation localization and reduced work-hardening ability. Additionally, in the CrCoNi alloy, the local stacking fault energy (SFE), which is directly related to the deformation behaviors of alloys, could be significantly altered by changing the SRO state. Subsequent impact on the competition of dislocation and deformation twinning is probed in terms of the microstructures and density functional theory calculations. Novel characterization techniques based on nanobeam electron diffraction were developed to enable full strain tensor analysis. In summary, the current dissertation presents a set of methods to image SRO in alloys and correlate the SRO to mechanical properties. The results provide insight into future alloy development. The techniques developed could be potentially applied to the broader materials science community to facilitate materials characterization in emerging topics like high-entropy ceramics.

Advisor: Minor, Andrew A.