VictorJuiz/thesis huggingface dataset:
Mapping the structural dynamics of the DNA gyrase N-gate

DNA gyrase is an essential bacterial molecular motor that uses ATP hydrolysis to drive the directional introduction of DNA supercoils. The enzyme employs a duplex strand passage mechanism that requires coordinating the opening and closing of three protein "gates": the N-gate, DNA-gate, and Exit-gate. The N-gate is formed by the dimerization of ATPase domains and acts as a nucleotide-dependent clamp that captures DNA for subsequent strand passage. Dynamic measurements of N-gate conformational changes are necessary to understand how gyrase harnesses chemical energy to direct changes in DNA topology. Here, we report real-time single molecule measurements of E. coli gyrase N-gate conformational dynamics under varying DNA and nucleotide conditions. We identify a landscape of distinct conformational intermediates whose populations can be shifted upon DNA and nucleotide binding. The N-gate is primarily open in the absence of DNA and nucleotide, but transiently samples closed conformations. The non-hydrolyzable ATP analog AMPPNP, but not ADP, induces stable N-gate dimerization, where FRET values are consistent with a closed conformation seen in crystal structures based on in silico modeling of dye positions. In the presence of DNA, the enzyme samples a distinct high FRET conformation of the N-gate that is consistent with an intermediate conformation previously described in studies of B. subtilis gyrase. Our measurements support a loose-coupling model in which N-gate conformations are highly dynamic and depend on both DNA and nucleotide binding. Substrate-induced N-gate conformational changes appear to be conserved across divergent bacterial species and could extend to other enzymes in the Gyrase-Hsp90-MutL (GHL) ATPase family. This work sets the stage for detailed structural modeling and for multimodal measurements that directly correlate protein and DNA dynamics in this complex molecular machine.

Advisor: Bryant Zev David 
Pande Vijay 
Huang Possu
Marital states : kinship, ethnicity, and gendered citizenship in Jordan

Modern states increasingly rely on families to manage political and economic problems, such as migration and statelessness. This dissertation ethnographically examines how Jordan polices its borders by regulating the marital and reproductive choices of Jordanian women, showing that our understandings of the state cannot stand separate from analyses of gender and kinship. In Jordan, men can pass their citizenship to their children, but women can't. Dependent nationality results in the daily reproduction of statelessness in Jordan and beyond. Of the 15 million stateless people around the world, most become stateless not by moving but by getting married or being born into mixed-nationality families. This ethnography departs from existing analyses that probe statelessness solely through the prism of mobility. Jordan has become exemplary of a new paradigm. Waves of Syrian, Iraqi, and Palestinian refugees have made mixed-nationality marriages routine. The dissertation reveals that the categories of "refugee, " "stateless persons, " and even "citizen" are not self-evident. Faced with an inability to take care of all its citizens, the state intervenes in women's bodies to delineate an ever-narrowing definition of "citizen, " denationalizing swaths of the populace for which it has divested responsibility. This project contributes to anthropological, historical, and philosophical scholarship by analytically linking marriage and political sovereignty.

Keywords: Anthropology.
Advisor: Yanagisako Sylvia Junko
Hansen Thomas
Tambar Kabir 
Thiranagama Sharika
Massive parallelism and sampling strategies for robust and real-time robotic motion planning

Motion planning is a fundamental problem in robotics, whereby one seeks to compute a low-cost trajectory from an initial state to a goal region that avoids any obstacles. Sampling-based motion planning algorithms have emerged as an effective paradigm for planning with complex, high-dimensional robotic systems. These algorithms maintain only an implicit representation of the state space, constructed by sampling the free state space and locally connecting samples (under the supervision of a collision checking module). This thesis presents approaches towards enabling real-time and robust sampling-based motion planning with improved sampling strategies and massive parallelism. In the first part of this thesis, we discuss algorithms to leverage massively parallel hardware (GPUs) to accelerate planning and to consider robustness during the planning process. We present an algorithm capable of planning at rates amenable to application within control loops, ∼10 ms. This algorithm uses approximate dynamic programming to explore the state space in a massively-parallel, near-optimal manner. We further present two algorithms capable of real-time, uncertainty-aware and perception-aware motion planning that exhaustively explore the state space via a multiobjective search. This search identifies a Pareto set of promising paths (in terms of cost and robustness) and certifies their robustness via Monte Carlo methods. We demonstrate the effectiveness of these algorithm in numerical simulations and a physical experiment on a quadrotor. In the second part of this thesis, we examine sampling-strategies for probing the state space; traditionally this has been uniform, independent, and identically distributed (i.i.d.) random points. We present a methodology for biasing the sample distribution towards regions of the state space in which the solution trajectory is likely to lie. This distribution is learned via a conditional variational autoencoder, allowing a general methodology, which can be used in combination with any sampling- based planner and can effectively exploit the underlying structure of a planning problem while maintaining the theoretical guarantees of sampling-based approaches. We also analyze the use of deterministic, low-dispersion samples instead of i.i.d. random points. We show that this allows deterministic asymptotic optimality (as opposed to probabilistic), a convergence rate bound in terms of the sample dispersion, reduced computational complexity, and improved practical performance. The technical approaches in this work are applicable to general robotic systems and lay the foundations of robustness and algorithmic speed required for robotic systems operating in the world.

Keywords: Aeronautics and Astronautics.
Advisor: Pavone Marco
Olukotun Oyekunle Ayinde 
Rock Stephen M.
Massively parallel RNA device engineering

Synthetic RNA devices sense drugs and metabolites to precisely and dynamically control gene expression inside cells, with the potential to transform medicine and biomanufacturing. The unique advantage of RNA devices lies in RNA's capacity to generate novel sensors that nature has yet to evolve. This is enabled by SELEX (Systematic evolution of ligands by exponential enrichment), in which large nucleic acid libraries are iteratively enriched for high-affinity aptamers de novo to bind proteins or small molecules. However, the number of small molecule-binding aptamers is still severely limited, as only a handful have been reported to be successfully integrated into RNA devices for intracellular use. Currently available quantitative assays in mammalian cell systems are limited in throughput and standardization, which hinders rapid iteration and predictable reuse of engineered devices for biomedical applications. We aimed to develop new platform technologies that 1) significantly accelerate the design-build-test cycle of engineering RNA devices in mammalian cells by integrating existing aptamer sensors, and 2) streamline the de novo generation of RNA devices with novel sensing capabilities. Leveraging massively parallel RNA-seq and FACS-seq assays, we developed techniques for quantitative and high-throughput measurements of the regulatory function of ribozyme-based RNA devices at both the mRNA and protein expression levels directly inside mammalian cells. With the newly developed methods, we identified highly performing RNA devices that respond to theophylline, xanthine, cyclic-di-GMP and folinic acid from tens of thousands of device library sequences. Furthermore, we found sequence and structural motifs that underlie the function of this class of RNA devices, which may in turn inform future rational design. To facilitate the discovery of new small molecule RNA biosensors, we developed De novo Rapid In Vitro Evolution of RNA biosensors (DRIVER), an automated, in vitro evolution platform coupled with a NGS cleavage assay that directly generates small molecule-sensing RNA devices. By alternately selecting for cleaving and non-cleaving sequences in the absence and presence of complex small molecule pools, DRIVER efficiently enriches a library of 10^12-13 sequences for novel ribozyme-based RNA devices. Thus far, we have discovered novel RNA biosensors to a variety of plant natural products and therapeutics. Furthermore, we demonstrated that several in vitro evolved RNA biosensors can be directly applied to function inside yeast and mammalian cells. Finally, the data-rich nature of DRIVER will shed light on the sequence requirements of high-sensitivity RNA biosensors, which will benefit rational design of libraries towards more efficient evolution efforts.

Keywords: Bioengineering.
Advisor: Smolke Christina D. 
Altman Russ 
Covert Markus
Materials and methods for in vitro electrophysiological measurement

The pace of progress in measuring electrical phenomena in cells and tissues has largely been dictated by the available measurement tools. These tools can be grouped into two general classes: those that measure the intracellular potential of cells and those that measure changes of the membrane potential extracellularly. In this thesis, I cover the development of three in vitro tools across the two classes of measurement. For intracellular measurement of electrophysiology, I discuss the fabrication and optimization of nanopillar electrodes. These nanopillars, when coupled with electroporation, temporarily yield low impedance access to the intracellular potential. In fabrication, I show a method which uses two lithography steps and no dry etches to generate high aspect ratio electrodes. In optimization, I explore parameters of electroporation which yield the highest amplitude and longest duration intracellular recordings from stem cell-derived cardiomyocytes. For extracellular measurement, I introduce a new motif in recording two-dimensional areas with a single amplification path and with neither dead space nor electrical cross-talk. This motif is enabled by the optoelectronic properties of graphene. In our configuration, a change in the electrostatic gating of graphene yields a change in its absorptivity which we exploit to transduce the electrical spikes of cells into optical signals. I first detail the voltaic and temporal resolution of the system. I then demonstrate the application of this technique to the recording of field potentials from an embryonic chicken heart. In the final tool, I demonstrate the use of soft three-dimensional electrodes to minimally invasively record field potentials from cardiac cells.

Keywords: Chemistry.
Advisor: Cui Bianxiao 
Boxer Steven G. (Steven George)
Cui Yi
Mathematical investigations into fundamental population-genetic statistics and models

This dissertation explores three projects that take a theoretical approach to studying the underlying models and statistics that are used in population genetics research. Each focuses on a fundamental model or statistic in population genetics, building on the long history of theoretical research in the field while relating the quantity of interest to current research in population genetics. The first two projects relate to the fundamental population genetic model, the coalescent, and the third project explores Wright's FST. The first project consists of modeling a biological process to understand the signature it leaves in data. "A Markov Model of the Coalescent with Recombination and Population Substructure", develops an extension of the coalescent model that incorporates recombination and population substructure. This project serves to offer a framework to simulate random neutral processes that could produce similar genomic signatures to another biological phenomenon, horizontal gene transfer. The second project uses probability theory to study the random genealogies invoked in the coalescent process: coalescent trees. A better understanding of the coalescent model itself can inform the development and use of the statistics derived from the coalescent. "On the Joint Distribution of Height and Length of Trees Under the Coalescent" explores the joint distribution of coalescent tree height, Hn, and length, Ln. Understanding the relationship of height and length is important to the development and analysis of statistics that estimate the length from observed data as a proxy for the height. The third project relates to understanding the properties of a biological statistic, FST. "FST and the Triangle Inequality for Biallelic Markers" explores the use of FST as a measure of distance. FST is not a true distance metric because it does not satisfy the triangle inequality and we show that biallelic FST fails the triangle inequality everywhere. We also show that biallelic FST always fails to be a tree-like distance for distinct allele frequencies. We explore the consequences for analyses that take in a distance matrix, such as spatial analyses, like multidimensional scaling, and tree-building algorithms, like neighbor-joining.

Keywords: Biology.
Advisor: Rosenberg Noah
Feldman Marcus W. 
Palacios Roman Julia Adela
Mathematical modeling of genetic and cultural traits

Understanding the history of populations of organisms is one of the core purposes of biological research. This research is undertaken through two interacting methods: the collection and analysis of large amounts of data and the development and analysis of mathematical theory. In this dissertation I explore several different avenues in the intersection between biological systems and mathematics. Chapters 1 and 2 study the mathematical models underlying the shapes of genealogies of genes, with the intent of determining the probabilities of a particular type of feature---a monophyletic group---occurring in these gene genealogies. This work can help us better understand the histories of populations from existing genetic data. Chapters 3 and 4 shift from a temporal to a spatial perspective, studying the mathematical properties of FST, a statistic that is used frequently to describe population differentiation. In these chapters I find upper and lower bounds on FST given population homozygosities, and I study how the value of FST changes as the length of the haplotypes upon which it is computed increase. This work can help us use and interpret FST more rigorously, with a careful consideration of the mathematical context of such measurements. Finally, Chapter 5 moves from genetics to epidemiology with an investigation of the interaction between a transmissible anti-vaccine sentiment and the dynamics of a vaccine-preventable disease. This work reveals that the presence of anti-vaccine sentiment as a "cultural pathogen" can effectively determine the outlook of the disease, as well as cause the disease frequencies to fluctuate in ways that cannot be observed when sentiment is ignored.

Keywords: Biology.
Advisor: Rosenberg Noah
Feldman Marcus W.
Pritchard Jonathan (Jonathan K.)
Measurement and modeling of head impact kinematics

Mild traumatic brain injury was once considered a silent epidemic due to difficulties in detecting and diagnosing its subtle neurological symptoms. However, increased public awareness of mild traumatic brain injuries coupled with recent advances in wearable sensing, sideline assessments, and basic understanding of underlying mechanisms has placed a large spotlight on the dangers of brain injuries to short-term and long-term neurological health. Today, researchers are approaching a consensus that head angular rotations are particularly dangerous as it results in shearing of the brain tissue. Studies on animals, cadavers, and surrogates were instrumental in developing hypotheses linking head angular rotations with injury, while studies on human subject populations at high risk of brain injury were instrumental in confirming these hypotheses. Yet, despite all that has been discovered regarding mild traumatic brain injuries, they are still difficult to predict and prevent. This is because we lack an understanding of how impact forces cause dangerous head rotations, and we lack methods to accurately measure the head rotations that result in brain injuries. In this thesis, I will discuss my work in the development of head and neck models to understand how the head is set in motion by impact forces, and the development of wearable sensors to measure head impact rotations in the field. In the future, my head and neck models can serve to determine susceptibilities of the head to impact forces and inform improvement for preventative equipment. Furthermore, the wearable sensor technologies and algorithms I developed in my thesis can be used as accurate, real-time diagnostic tools to detect severe head impacts likely to result in brain injuries. Together, these can be both be used to reduce brain injury incidence and identify injured individuals for proper treatment and rest.

Keywords: Mechanical Engineering.
Advisor: Camarillo David 
Delp Scott 
Kuhl Ellen
Mechanical regulation of E-cadherin adhesion and signaling in epithelia

Mechanical force has been shown to regulate the shape and size of tissues in multicellular organisms. Cells within the tissue can respond to mechanical stimuli and elicit a downstream signaling response called mechanotransduction. One of the many protein complexes that sense and respond to mechanical force in epithelial cells are E-cadherin cell-cell junctions. E-cadherin links neighboring cells, and through its interaction with catenin proteins, is a signaling hub for many pathways involved in cell proliferation, differentiation, and migration, and tissue morphogenesis. The focus of my thesis was to study how E-cadherin responds to changes in mechanical force and the role of tension in regulating downstream cellular processes. We showed that changes in mechanical force is balanced between both cell-cell junctions and cell-extracellular matrix (ECM) junctions in cell pairs. We also developed a cell stretching system as a technology for studying the role of mechanical force in epithelial tissue biology. We observed that mechanical stretch can regulate cell cycle progression through the phosphorylation and nuclear localization of β-catenin. Also uniaxial mechanical stretch can orient the mitotic spindle in the direction of stretch through the mechanosensitive E-cadherin/LGN complex. Altogether, my thesis provides more understanding of how cell-cell junctions respond to mechanical force and the role of mechanical force in E-cadherin-regulated cell cycle and cell division.

Keywords: Biology.
Advisor: Nelson W. J. (W. James)
Feldman Jessica L.
O'Brien Lucy
Weis William I.
Mechanics at the cadherin-keratin interface

Mechanical forces are ubiquitous in living tissues. From embryonic development to adult tissue repair, cells coordinate forces and mechanical properties to control tissue shape. In addition to a remarkable ability to remodel and grow, tissues must also be mechanically resilient to strains associated with motion and external force. In this thesis two classes of tools are employed to better understand shape and tension homeostasis in living cells. The first project describes the development and use of an artificial extracellular matrix for evaluating the response of pluripotent cell colonies to mechanical cues. This system reveals an interplay between colony morphology and substrate mechanics in pluripotent cells, a potentially relevant finding for models of the epiblast from which the cells are derived. The second project describes the development and use of a tension reporter for desmoplakin, a linker protein that connects the intermediate filament cytoskeleton to the cell-cell junction. Measurements of this sensor in epithelial monolayers revealed that the this linkage responds to acute deformations, but does not bear significant loads during homeostasis in culture. These measurements provide an essential step toward understanding the molecular origins of the mechanics of living tissues.

Keywords: Biophysics.
Advisor: Dunn Alexander Robert 
Pruitt Beth 
Weis William I.
Mechanisms of High Grade Glioma Invasion of the Lateral Ventricle Subventricular Zone

The lateral ventricle subventricular zone (SVZ) is a common area of spread for both pediatric and adult gliomas, but the mechanism mediating this spread has been poorly understood. Diffuse Intrinsic Pontine Glioma (DIPG), a childhood glioma, begins in the pons and spreads to the SVZ, making DIPG an ideal model for studying the invasion mechanism of gliomas. Preliminary research elucidated that four proteins—pleiotrophin, secreted protein acidic and rich in cysteine (SPARC), SPARC-like protein 1, and heat shock protein 90B—are secreted from SVZ neural precursor cells and promote glioma invasion. One of these proteins, pleiotrophin, is a neurite outgrowth-promoting factor and has been previously implicated in adult glioblastoma cell migration. By understanding the role of pleiotrophin along with the other three proteins, we could elucidate the mechanism of glioma invasion. To further explore the role of these factors, we knocked down the four proteins using both in vitro and in vivo methods. Subsequently, we explored the effect of knocking down a known pleiotrophin receptor, protein tyrosine phosphatase receptor type ζ, on DIPG invasion. The results of these experiments show that pleiotrophin, in complex with its binding partners, has a chemoattractant effect leading to DIPG invasion of the SVZ. These findings demonstrate the role of these four secreted factors in glioma interactions and may lead to future therapeutic targets to limit glioma invasion.

Keywords:  Department of Biology
high grade glioma
cancer
Subventricular Zone
PTN
SPARCL1
SPARC
HSP90B
PTPRZ
diffuse intrinsic pontine glioma
neural precursor cell
Thesis
Advisor: Monje Michelle
McConnell Susan
Mechanisms of the intergenerational transmission of math anxiety from mothers to their children

Math anxiety is prevalent among children as early as first grade, and recent research suggests that the development of math anxiety among elementary school children may be influenced by their interactions with math-anxious teachers and parents. This study examined maternal behaviors that might, in part, explain how math anxiety is transferred from mothers to children during math homework-helping situations, namely mothers' use of autonomy-support versus controlling behaviors, their use of person- versus process-based praise, and their affect. Forty mothers and their second- or third-grade children completed two math worksheet tasks together, which were videotaped and coded for maternal behaviors. Mothers' and children's math anxiety and perceptions of their math competence were also assessed. Findings revealed that mothers' math anxiety is significantly and positively associated with boys', but not girls', math anxiety. Additionally, mothers' with high math anxiety were more likely to adopt controlling behaviors when helping their children with a math task and were more likely to make negative affective comments, especially when the math problem was difficult for the child. Children's math anxiety was predicted by mothers' use of controlling behaviors and their use of negative affective comments.

Keywords: Education.
Advisor: Stipek Deborah J.
Langer-Osuna Jennifer 
Levine Susan