VictorJuiz/thesis huggingface dataset:
A programmable alternative splicing platform for regulating protein diversity [electronic resource]

Nature offers enormous functional diversity that is largely untapped in engineered biological systems. Given its roots in bacterial transcriptional gene networks, synthetic biology has yet to develop a comprehensive set of tools that harness the complexity and biological regulation prevalent in mammalian cells. A critically important mechanism in mammalian cells, alternative splicing, increases the coding capacity of genomes to generate several proteins from an individual gene. Few engineered genetic devices utilizing alternative splicing mechanisms have been described, and existing approaches are limited to turning on or off the expression of a gene coupled to a splicing regulatory component. A novel alternative splicing platform has the potential to broaden the current regulatory capabilities of genetic devices by providing a strategy to program protein function. We describe the design and implementation of an intron framework for controlling the mutually exclusive alternative splicing of exons in a four exon-three intron system, wherein the exon sequences can be recoded. The coding capacity of the genetic device is increased by the mutually exclusive nature of the alternative splicing event, as one of two internal exons is incorporated into a mature mRNA, thereby resulting in multiple isoforms. RNA profiling and protein expression assays established that these devices effectively spliced to produce the expected dominant isoform. Systematic tuning of consensus sequence element activity in the intron framework revealed the ability to modify isoform profiles and favor alternate isoform production from a splicing device. Furthermore, we conducted an exploratory study of intronic regulatory elements for controlling and predicting mutually exclusive alternative splicing events within the context of the intron framework. Finally, we applied this intron framework to program transcription factor activity by encoding domains of modular transcription factors in synthetic RNA splicing devices, modifying domain functionality through alternative splicing, and producing precise transcription factor profiles that control downstream gene expression patterns. Our work highlights the first demonstration of an intron framework design that leverages a complex mode of alternative splicing to program protein diversity with synthetic RNA splicing devices. Continued development of such foundational frameworks in mammalian synthetic biology will enable increasingly sophisticated devices that expand the capabilities of genetic engineering for tackling critical global challenges in health and medicine.

Keywords: Bioengineering.
Advisor: Smolke Christina D. primary advisor. Thesis advisor
Fire Andrew Zachary advisor. Thesis advisor
Swartz James R. advisor. Thesis advisor
The programmed cell death protein 1 (PD-1) pathway in cancer [electronic resource] : engineering protein therapeutics and exploring a novel role for PD-1 on tumor-infiltrating macrophages

Programmed cell death protein 1 (PD-1) is an immune checkpoint receptor that is upregulated on activated T cells to induce tolerance.1,2 Tumor cells frequently overexpress the ligand for PD-1, programmed cell death ligand 1 (PD-L1), allowing escape from the immune system.3,4 Several monoclonal antibodies blocking PD-1/PD-L1 are clinically approved, and lead to remarkable efficacy in patients with a variety of cancers, including melanoma, colorectal cancer, non-small cell lung cancer, and Hodgkin's lymphoma.5-10 However, antibodies have inherent limitations that can curtail their efficacy in this setting, including poor tissue/tumor penetrance and detrimental Fc-effector functions that deplete immune cells. To determine if PD-1:PD-L1 directed immunotherapy could be improved with smaller, non-antibody therapeutics, I used directed-evolution by yeast-surface display to engineer the PD-1 ectodomain as a high-affinity (110 pM) competitive antagonist of PD-L1. In contrast to anti-PD-L1 monoclonal antibodies, high-affinity PD-1 demonstrated superior tumor penetration without inducing depletion of peripheral effector T cells. Consistent with these advantages, in syngeneic CT26 tumor models, high affinity PD-1 was effective in treating both small (50 mm3) and large tumors (150 mm3), whereas the activity of anti-PD-L1 antibodies was completely abrogated against large tumors. Furthermore, I found that high-affinity PD-1 could be radiolabeled and applied as a PET imaging tracer to efficiently distinguish between PD-L1-positive and PD-L1-negative tumors in living mice, providing an alternative to invasive biopsy and histological analysis. These results thus highlight the favorable pharmacology of small, non-antibody therapeutics for enhanced cancer immunotherapy and immune diagnostics. Although it is well-established that PD-1/PD-L1 blockade activates T cells, little is known about the role that this pathway may have on tumor-associated macrophages (TAMs). As such, I also investigate a functional role for PD-1 on TAMs. I show that both mouse and human TAMs express PD-1. TAM PD-1 expression increases over time in mouse models, and with increasing disease stage in primary human cancers. TAM PD-1 expression negatively correlates with phagocytic potency against tumor cells, and blockade of PD-1/PD-L1 in vivo increases macrophage phagocytosis, reduces tumor growth, and lengthens survival in mouse models of cancer in a macrophage-dependent fashion. My results suggest that PD-1/PD-L1 therapies may also function through a direct effect on macrophages, with significant implications for treatment with these agents.

Keywords: Molecular and Cellular Physiology.
Advisor: Weissman Irving L. primary advisor. Thesis advisor
Beachy Philip Arden advisor. Thesis advisor
Feng Liang
Majeti Ravindra
Programming heterogeneous systems from an image processing domain specific language [electronic resource]

The performance and energy efficiency of image processing tasks are becoming increasingly important as cameras become ubiquitous, and as our ability to extract information from images improves. These tasks are extremely computationally intensive, requiring trillions of operations per second to fulfill the performance requirements of applications in computer vision, computational photography, and augmented reality. Therefore, specialized hardware accelerators are necessary to deliver the performance and energy efficiency required by these important applications. However, creating, "programming, '' and integrating this hardware into a hardware/software system is difficult. We address this problem by extending the image processing language, Halide, so users can specify which portions of their applications should become hardware accelerators, and then provide a compiler that uses this code to automatically create the accelerator along with the "glue" code needed for the user's application to access this hardware. Starting with Halide not only provides a very high-level functional description of the hardware, but also allows our compiler to generate a complete software application, which accesses the hardware for acceleration when appropriate. This system also provides high-level semantics to explore different mappings of applications to a heterogeneous system, including the flexibility of being able to change the throughput rate of the generated hardware. We demonstrate our approach by mapping applications to a commercial Xilinx Zynq system. Using its FPGA with two low-power ARM cores, our design achieves up to 6x higher performance and 38x lower energy compared to the quad-core ARM CPU on an NVIDIA Tegra K1, and 3.5x higher performance with 12x lower energy compared to the K1's 192-core GPU.

Keywords: Electrical Engineering.
Advisor: Horowitz Mark
Hanrahan P. M. (Patrick Matthew) advisor. Thesis advisor
Olukotun Oyekunle Ayinde advisor. Thesis advisor
Propagation in multi-dimensional Fisher-KPP equations [electronic resource]

Advection-reaction-diffusion equations (ARD) are non-linear elliptic or parabolic equations that are used to model a variety of systems in natural sciences and engineering, ranging from biological (population dynamics) to chemical and astrophysical systems (reactions in a fluid). They describe the evolution of a normalized quantity, such as a local density of a population or a temperature, as a result of three processes: transport inside the domain (advection), creation or depletion due to an energy source (reaction), and spatial movement (diffusion). These equations exhibit interesting behaviors such as growth/decay, spreading and mixing. Over the past decades there has been significant progress towards understanding and quantifying the behavior of ARD equations. A great focus was shown in equations of biological invasions, more specifically in the phenomenon of spreading, which happens as a result of the invasion of an unstable equilibrium state by a positive stable one. There are two main threads of research in this field: (1) front-like spreading, which leads to the study of traveling fronts, their speeds of propagation and stability properties, and (2) multi-directional spreading, arising from initial data that have compact support or fast decay in every direction. In this thesis we study the problem of spreading rates for the Cauchy problem in multi-dimensional periodic Fisher-KPP equations. Localized initial data give rise to an invasion that will happen typically at different speeds and profiles in each unit direction, but independent on the size and distribution of the original mass. The main result will be on precise asymptotics for the location of level sets of solutions for these data. The trajectory of the thesis will be as follows: In the first part, after a brief introduction of the problem and past results, we study the linearized Dirichlet equation in a half space moving at a constant speed derived from the slowest traveling fronts. This provides intuition for the location of the fronts in the compactly supported case, as well as concrete bounds that can be compared to the solution of the original problem. In the second part we prove the main result by controlling the propagation of the Fisher-KPP solution using sub- and super-solutions constructed from the linearized fronts.

Keywords: Mathematics.
Advisor: Ryzhik Leonid primary advisor. Thesis advisor
Papanicolaou George advisor. Thesis advisor
Ying Lexing advisor. Thesis advisor
Public deliberation and participation through a comparative lens [electronic resource] : attitudes, behaviors, and institutions

Ordinary people have been increasingly engaging in policy deliberations around the world. This dissertation studies the democratic potential of public deliberation; in particular, whether such practices live up to normative standards and benefits, and how to situate them in broader social and political contexts. The first part of the dissertation examines the psychological processes of attitudinal and behavioral changes through democratic deliberation. In a California-wide Deliberative Poll and a participatory budgeting project in a Chinese neighborhood, I find that democratic dialogues on the basis of balanced information, respect, and mutual justification nurture sophisticated public opinion and better citizenries, and such democratic merits hold true across political contexts. The second part of the dissertation studies the intriguing marriage of deliberative democracy and authoritarianism with a focus on the "socialist deliberative democracy" in China. Combining evidence from field study and national-scale data, I have shown that China has adopted consultative institutions in order to maintain social stability. Democratic deliberation is compatible with authoritarianism, though the forms and functions integrate with the native political culture and institution. Local political elites perceive and practice deliberative democracy according to their inherent democratic orientations, which may open up a promising ground for public participation, or turn it into window dressing.

Keywords: Communication.
Advisor: Fishkin James S. primary advisor. Thesis advisor
He Baogang
Krosnick Jon A. advisor. Thesis advisor
Pan Jennifer
Quantifying temporally-varying induced seismicity hazard and regional risk [electronic resource] : statistical approaches, and application in Oklahoma

We describe a Bayesian change-point model to estimate time-varying seismicity rates, develop a mixture of mixtures model to associate wastewater injection volumes with seismicity, propose a regional ground-motion prediction equation and describe a framework to quantify temporally-varying seismic hazard and regional risk, with application to induced seismicity in Oklahoma. We describe a Bayesian change-point model that detects if the seismicity rate has changed using a time series of observed earthquake occurrences. We show that for steep changes in seismicity rates, such as those that have been observed for induced seismicity in Oklahoma, change can be detected within 3 months of its occurrence. The Bayesian model yields posterior probability distributions for the date of change, and the rates before and after the change. We compile a database of ground motions from the central and eastern United States for magnitude ≥ 3 earthquakes from 2001 through 2016. We observe that ground motions from tectonic earthquakes attenuate faster within the first 20 km. This results in slightly higher ground shaking from induced earthquakes. We propose a ground-motion prediction equation (GMPE) for induced earthquakes in the central US, by scaling an existing GMPE. We use a logistic regression model to show that high wastewater injection volumes are correlated with regions of seismicity change. We propose a statistical model to establish functional relationships between injection volumes and seismicity. We use a mixture of mixtures model to find these functional relationships. We also describe a generalized mixture of mixtures model that can be used to find temporal or spatial trends in the mixing proportions and parameters of mixture distributions. We extend the Probabilistic Seismic Hazard Assessment (PSHA) framework to account for temporally-changing seismicity rates due to induced seismicity. Seismicity rates can be obtained from multiple methods, like the change-point model or the mixture of mixtures model. For the latter model, injection volumes can be used directly for hazard estimation without first obtaining the seismicity rates. We implement a stochastic Monte-Carlo approach using OpenQuake to estimate temporally-varying induced seismicity hazard in Oklahoma City and estimate the regional risk for the complete portfolio of buildings in Oklahoma obtained using HAZUS. Our goal with this dissertation is to provide stakeholders, regulators and community members with the necessary tools to quantify impacts from induced seismicity. We believe that the tools developed in this dissertation will result in developing effective risk mitigation strategies for regions of induced seismicity.

Advisor: Baker Jack W. primary advisor. Thesis advisor
Deierlein Gregory G. (Gregory Gerard)
Zoback Mark D. advisor. Thesis advisor
A quantitative analysis of gaze in feature films [electronic resource]

This thesis explores human gaze behavior in response to dynamic visual stimulus. In particular, we are interested in examining the role of high-level image features in attracting visual attention. One promising body of knowledge comes from cinema: film directors are masters at controlling what we look at when we watch a film. Over the last century, the visual and temporal structure of films has matured into a rich compendium of conventions addressing image composition, temporal discontinuities (edits), lighting, and so on. Simultaneously, viewers' understanding of the common film grammar has co-evolved. However, there has been very little quantitative analysis of how gaze responds to this type of highly structured content. We examine the relationship between cinematic features and gaze response, with implications not only for the future of media, but for display technology, immersive reality, and human cognition.

Advisor: Hanrahan P. M. (Patrick Matthew) primary advisor. Thesis advisor
Agrawala Maneesh advisor. Thesis advisor
Card Stuart K.
Quantitative functional oncogenomics [electronic resource] : translational methods to study tumor initiation, progression, and metastasis in vivo

Cancer genome sequencing has been instrumental in identifying the genomic alterations that occur in human tumors. The functional importance of the vast majority of these alterations, both alone and in combination, remains unknown and largely uninvestigated due to lack of tools enabling high-throughput interrogation of coincident genetic alterations in vivo. This thesis describes a method that integrates tumor barcoding with CRISPR/Cas9-mediated genome editing and ultra-deep barcode sequencing (Tuba-seq) to interrogate multiple tumor genotypes simultaneously in autochthonous mouse models of human cancer. I demonstrate the quantification of the effects of eleven of the most frequently inactivated genes in human lung adenocarcinoma and uncover the methyltransferase Setd2 and the splicing factor Rbm10 as novel suppressors of lung cancer growth. By quantifying the in vivo fitness advantage conferred by inactivation of each of these eleven genes in combination with inactivation of p53 or Lkb1, we identify unexpected context-dependent tumor suppression. I further demonstrate the ability of tumor barcoding to investigate clonal relationships between tumors and metastases, as well as uncover potential drugs to inhibit metastatic progression. These approaches will redefine our ability to understand how tumor suppressor inactivation impacts tumor initiation, growth, malignant transformation, and ultimately lead to the identification of therapy responses. Specifically, we can begin to investigate genotype specific drug responses and hope to inform a more precise and personalized era of patient care.

Keywords: Genetics.
Advisor: Winslow Monte primary advisor. Thesis advisor
Petrov Dmitri Alex
Sage Julien advisor. Thesis advisor
Sherlock Gavin advisor. Thesis advisor
Quantum chemistry for solvated molecules and electronic excited states on graphical processing units [electronic resource]

This dissertation utilizes general-purpose graphical processing units (GPGPUs) to accelerate quantum chemistry computations for solvated molecules and molecules in electronic excited states. Most chemical and biological processes happen in the solution phase. However, the application of solvent models in quantum chemistry calculation of large biomolecular system is limited by the CPU computation bottleneck. In this work, we will first show our techniques to accelerate the Conductlike Polariable Continuum Models (C-PCM) at the Hartree-Fock and DFT level of theory. Then the machinery is extended to solvated molecules at electronic excited state described with time dependent density functional theory (TDDFT), with both the state-specific and linear-response approaches. Simulation of photochemistry usually involves multiple electronic states and propagation of the nuclear wavefunction on potential energy surfaces, especially near conical intersections. This requires the electronic structure methods used to be (1) able to describe multiple states in a balanced way; (2) efficient enough for the thousands of energy and gradient computations required in molecular dynamics (MD) simulation. We derived and efficiently implemented the analytical gradient of State-Interaction State-Averaged Restricted Ensemble Averaged Kohn Sham (SI-SA-REKS) method, which is an alternative to high-level multireference wavefunction based methods, thus enabling excited state MD study of larger molecules. Finally we will demonstrate an efficient computational workflow for accurately reproducing and predicting redox potential of quinones, using our GPU accelerated PCM method.

Keywords: Chemistry.
Advisor: Martinez Todd J. (Todd Joseph)
Devereaux Thomas Peter
Fayer Michael D. advisor. Thesis advisor
Quantum tunneling and spontaneous baryogenesis in the relaxion model

The Cosmological Relaxation mechanism is proposed as an alternative solution to the Electroweak Hierarchy Problem, where the mass of the Higgs boson is dynamically relaxed to its current value of 125 GeV through its interaction with the relaxion -- a hypothetical scalar particle which lies beyond the Standard Model -- in the early universe. So far, many of the theoretical implications of this model remain to be investigated. In this work we present the analytic calculations of quantum tunneling rate of the relaxion in a corrugated potential with growing sinusoidal barriers. We find that the tunneling rate is parametrically suppressed so that quantum tunneling effectively stops shortly after the electroweak phase transition. We also derive the baryon-to-entropy ratio generated by spontaneous baryogenesis from the slow-roll of the relaxion along its potential after reheating. We find that the minimal QCD relaxion model generates slightly insufficient baryon asymmetry and discuss several approaches to improve its agreement with the experimental values.

Keywords:  Department of Physics
quantum tunneling
relaxion
baryogenesis
cosmological relaxation
electroweak hierarchy
Thesis
Advisor: Graham Peter
Dimopoulos Savas
Rapid RNA-protein interaction detection in living cells [electronic resource]

RNA-protein interactions play numerous roles in cellular function and disease. Here we describe RNAprotein interaction detection (RaPID), which uses proximity-dependent protein labeling, based on the BirA* biotin ligase, to rapidly identify the proteins that bind RNA sequences of interest in living cells. RaPID displays utility in multiple applications, including in evaluating protein binding to mutant RNA motifs in human genetic disorders, in uncovering potential post-transcriptional networks in breast cancer, and in discovering essential host proteins that interact with Zika virus RNA. To improve the BirA* labeling component of RaPID, moreover, a new mutant BirA* was engineered from B. subtilis that enables > 1000-fold faster kinetics and > 30-fold increased signal-to-noise ratio over the prior standard E. coli BirA*, thereby enabling direct study of RNA-protein interactions in living cells on a timescale as short as one minute.

Advisor: Khavari Paul A. primary advisor. Thesis advisor
Oro Anthony
Sarnow P. (Peter) advisor. Thesis advisor