VictorJuiz/thesis huggingface dataset:
Electron microscopy methods to overcome the challenges of structural heterogeneity and preferred orientations in small (sub-500 kDa) macromolecular complexes

While cryo-EM imaging technology and software suites have led to a “resolution revolution”, the poor reproducibility and inefficiency offered by current specimen preparation techniques remain challenges largely unexamined and under-prized. Regardless of camera or software proficiency, a poor-quality specimen will always produce an equivalently substandard 3D reconstruction. To further advance the high-resolution EM pipeline and establish quality control for grid specimens, we tested three techniques to assess optimum conditions for vitrification of small (<500kDa), multi-subunit biological macromolecular complexes./nWe performed specimen optimization for a 300kDa, five-component, macromolecular complex, PRC2. PRC2 is a key regulator of gene silencing in eukaryotes and mutations in its catalytic subunit, Ezh2, are linked to a number of human cancers and degenerative diseases. To date, no high-resolution structure of the complete complex has been solved. PRC2 presents a number of unique challenges for the structural biologist, including its small size, highly flexible regions, and conformation heterogeneity. A high-resolution structure of PRC2 would provide unparalleled insight into the biochemical mechanisms that mediate gene silencing by methylation of histone tails. For these reasons, PRC2 is an ideal candidate for optimizing cryo-EM grid preparation techniques translatable to similar complexes and for future research./nPrevious EM studies of PRC2 revealed a distinct preferred orientation when bound to carbon substrates, necessitating the collection of tens of thousands of images to generate a complete structure containing high-resolution features. To overcome this impediment, we experimented with two other grid specimen preparation techniques. First, we vitrified solution-suspended PRC2 in open holes on carbon mesh support. Despite modifications of chemical and physical buffer and substrate parameters to stabilize the complex, denaturation upon surface binding at the air-water interface and dissociation of the complex during vitrification proved insurmountable. We next tested a method of affinity binding to a streptavidin monolayer substrate covering the holes of a carbon mesh support. We found that chemically biotinylated PRC2 was intact, monodisperse, and bound the grid in random orientations, all factors critical to high-resolution cryo-EM structure determination. Negative stain EM analysis revealed a more even distribution of views for 3D reconstruction. From these results, we conclude that streptavidin monolayer substrates are an option for overcoming the obstacle of preferred orientations for small complexes and provide an easily reproducible protocol for grid preparation.

Advisor: Nogales, Eva
Mechanisms of Cohesin Function Revealed by Analysis of Smc3

A central problem in biology is how genetic material is organized and inherited during cell divisions without loss of information. The conserved protein complex cohesin functions to ensure chromosomes are partitioned equally when cells divide. Cohesin mediates sister chromatid cohesion, chromosome condensation, efficient repair of DNA damage and regulation of transcription. The activity by which cohesin performs these functions is through DNA tethering. Tethering can occur between two sister chromatids or within a single chromatid to bring together two separate positions along its length. Within this dissertation, I will describe novel insights into the mechanism by which cohesin performs these critical activities on chromosomes. I chose to study this problem in the budding yeast Saccharomyces cerevisiae because of the unparalleled genetic tools available in this model eukaryote./nCohesin consists of four core subunits referred to in yeast as Mcd1p, Scc3p, Smc1p, and Smc3p, whereas spatiotemporal control of cohesin activity depends on auxiliary factors. To better understand cohesin architecture and regulation, I performed a genetic screen to identify novel mutants of the Smc3p subunit. Characterization of these mutants has revealed functions for previously undescribed regions of Smc3p and new activities for previously described domains that further our understanding of this complex molecular machine. First, I describe a series of mutations at the interface between Smc3p and Mcd1p termed the DNA “exit gate”. This investigation revealed an unexpected role for this interface in loading cohesin on chromosomes. Second, I reveal a novel role for the Smc3p hinge domain in cohesion maintenance that is independent of its ability to stably bind chromosomes. This discovery lends additional weight against a simple “embrace” model for DNA tethering by cohesin still supported by many in this field. Moreover, this observation suggests that communication between the Smc3p hinge, Mcd1p, and regulator Pds5p is required for cohesion maintenance. Finally, I show that a specific region in the middle of the cohesin ring is critical for a step in the process of cohesin loading onto chromosomes. This result is surprising since it suggests that a contortion of the cohesin ring is critical for it to productively bind chromosomes. In sum, this dissertation advances our understanding of the mechanism by which cohesin functions and supports a variation of the “handcuff” model in which an activity after DNA binding is required for cohesin to achieve tethering.

Advisor: Koshland, Douglas E
Learning to Reconstruct 3D Objects

Ever since the dawn of computer vision, 3D reconstruction has been a core problem, inspiring early seminal works and leading to numerous real world applications. Much recent progress in the field however, has been driven by visual recognition systems powered by statistical learning techniques - more recently with deep convolutional neural networks (CNNs). In this thesis, we attempt to bridge the worlds of geometric 3D reconstruction and learning based recognition by learning to leverage various 3D perception cues from image collections for the task of reconstructing 3D objects./nIn Chapter 2, we present a system that is able to learn intra-category regularities in object shapes by building category-specific deformable 3D models from 2D recognition datasets enabling fully automatic single view 3D reconstruction for novel instances. In Chapter 3, we demonstrate how predicting the amodal extent of objects in images and reasoning about their co-occurrences can help us infer their real world heights. Finally, in Chapter 4, we present Learnt Stereo Machines (LSM), an end-to-end learnt framework using convolutional neural networks, which unifies a number of paradigms in 3D object reconstruction- single and multi-view reconstruction, coarse and dense outputs and geometric and semantic reasoning. We will conclude with several promising future directions for learning based 3D reconstruction.

Advisor: Malik, Jitendra
Clustering of mRNA-Seq Data for Detection of Alternative Splicing Patterns

Whereas prior methods of studying expression in a cell returned only estimates of gene expression, sequencing of mRNA can provide estimates of the amount of individual isoforms within the cell. As a result, many standard statistical methods commonly used for analyzing gene expression levels need to be modified in order to take advantage of this additional information. Many methods have been developed to study differential isoform expression between known groups but little research has been done utilizing methods of unsupervised learning, such as clustering. One novel question is whether we can find clusters of samples that are distinguishable not by their gene expression but by their isoform usage. That is, instead of using clustering to find groups with shared changes in gene expression, we want to utilize clustering to find groups with shared changes in isoform usage. Here, we propose a novel approach to clustering mRNA-Seq data that identifies such clusters. In order to utilize both gene and isoform information when clustering, we treat the sequencing data as a vector denoting the relative isoform usage of each isoform in a gene. In simulated data, we show that clustering using relative isoform usage values rather than isoform counts is more sensitive to finding clusters based on changes in isoform usage. In a real data set, we demonstrate its performance in finding a technical artifact that resulted in different batches having different isoform usage patterns. Additionally, we also illustrate its usage on several TCGA data sets. Specifically, we looked at whether groups determined from clustering on relative isoform usage were associated with tumor stage or splicing mutations.

Advisor: Purdom, Elizabeth
Particle-laden fluids for industrial and manufacturing processes

In several industrial and manufacturing processes, particle additives are placed into fluid flows to enhance overall properties or process parameters when the base fluid may not be sufficient. We refer to these fluids as particle-laden, and we find the use of them ubiquitous. As such, it is an important area of study. The work herein will propose a modeling methodology for such systems. In order to account for particles in the flow, a Discrete Element Method (DEM) framework is implemented. To resolve the fluid flow, a Lattice Boltzmann Method (LBM) model is employed. The LBM is able to account for porous media in a simple manner, thus proving useful for our work./nApplications studied within this work are non-invasive magnetic pipe healing, where particles are injected into a flow and guided to a damage site via external magnetic fields. Also, infiltration into permeable porous media for ceramic matrix composites (CMC's) is covered. Variance based approaches are used to ascertain the input parameters the models are most sensitive to. Finally, we introduce frameworks for other particle-fluid systems such as nozzle wear, biological channel growth, and electrically-aided pumping.

Advisor: Zohdi, Tarek I
The Long-Term Outcomes of Double White Dwarf Mergers

In double white dwarf (WD) systems with sufficiently short initial orbital periods, angular momentum losses from gravitational wave radiation shrink the orbit and can lead to the merger of the WDs. Simulations of the merger show that the less massive WD is tidally disrupted, forming a disk around the more massive WD. Beginning with output from WD merger simulations, I study the subsequent viscous evolution using multi-dimensional hydrodynamical simulations. I find that the remnants evolve towards a spherical end-state, where the rotationally-supported disk has been converted into a hot, thermally-supported envelope. I then map these results into a stellar evolution code and evolve them over thermal and nuclear timescales. This is a necessary procedure to self-consistently study the long-term outcomes of WD mergers. I apply this to the merger of two carbon-oxygen WDs with a total mass in excess of the Chandrasekhar mass. My work follows the evolution of the remnants for longer than previous calculations and finds alternating episodes of fusion and contraction can lead to the formation and subsequent collapse of an iron core. I also characterize the observable properties of the remnant during this evolution. Additionally, I develop a framework to compute weak reaction rates that are essential in the evolution of massive, accreting WDs. I apply these results to understand the evolution of oxygen-neon WDs towards accretion-induced collapse to a neutron star.

Advisor: Quataert, Eliot
Transdiagnostic Cognitive Control Training for Emotion-Relevant Impulsivity

The tendency to respond impulsively to strong emotions is a surprisingly common trait across many forms of psychopathology. Emotion-relevant impulsivity is closely tied to problems with cognitive control, raising the possibility that strengthening underlying cognitive mechanisms might also reduce aspects of impulsivity. Cognitive control training programs have been used to improve emotion regulation skills in several studies (cf. Siegle, Price, Jones, Ghinassi, Painter, & Thase, 2014), but despite conceptual similarities, it is unknown whether cognitive control training might also reduce emotion-relevant impulsivity. The goal of the present study was to test whether training cognitive control through working memory and response inhibition tasks (two dimensions specifically implicated in emotion-relevant impulsivity) is efficacious in reducing emotion-relevant impulsivity transdiagnostically./nParticipants (N = 52) were recruited based on self-reported tendencies to experience difficulties with impulsivity in the face of strong emotion, using the Feelings Trigger Action scale (Carver, Johnson, Joormann, Kim, & Nam, 2011). Participants were randomly assigned to either a two-week waitlist condition or to immediately begin six in-lab training sessions (including the adaptive PASAT: a working memory task, and the Go/No-Go task: a response inhibition task in each session) over the course of two weeks./nResults showed a significant reduction in emotion-relevant impulsivity from pre-training to post-training and during the two-week follow-up phase; these improvements were not observed in the waitlist control period. Participants also showed significant improvements on the working memory task, and non-significant improvements on transfer tasks of working memory and response inhibition. Results provide preliminary support for the efficacy of cognitive control training interventions that target emotion-driven impulsivity.

Advisor: Johnson, Sheri L
Surface and Solution Mediated Studies of Small Molecule Enediyne Reactivity

Enediyne chemistry is a field with growing potential especially in the industries of material synthesis, catalysis, and therapeutic drug design. Enediynes offer a flexible synthetic handle with which to design these materials. However reactivity of enediynes is complex and in need of extensive and unambiguous characterization (Chapter 1). Imaging techniques like non-contact atomic force microscopy (nc-AFM) and scanning tunneling microscopy (STM) can be utilized for unambiguous determination of reaction products. Using, nc-AFM and STM, supported with ab initio density functional theory (DFT), we provide a glimpse into the reactive capabilities of enediynes and precisely characterize the complex product mixture from a reaction of 1,2-bis((2-ethynylphenyl)ethynyl)benzene (Chapter 2). Tailoring reaction conditions, including enediyne structure, can also result in tailoring the product of enediyne cyclization reactions. We characterize the chemical and electronic structure of individual chains of oligo-(E)-1,1’-bi(indenylidene), a poly-acetylene derivative that we have obtained through cooperative C1–C5 thermal enediyne cyclizations on Au(111) surfaces followed by a step-growth polymerization of the (E)-1,1’-bi(indenylidene) diradical intermediates (Chapter 3). These chemical transformations offer contrast to those from our initial investigation prompting a comprehensive study of the molecular energetics and conformational dynamics underlying these transformations. We report the detailed investigation of a surface-catalyzed cross-coupling and sequential cyclization cascade of 1,2-bis(2-ethynyl phenyl)ethyne on Ag(100) supported by theoretical simulations. These simulations indicate that the kinetic stabilization of experimentally observable intermediates is observably influenced by selective energy dissipation to the substrate and entropic changes associated with key transformations along the reaction pathway (Chapter 4). Finally, we begin to build on a motif by which to synthesize one-dimensional materials using the reactivity lessons learned from surface studies of enediynes. Synthesis of new small molecule enediynes is discussed, the thermodynamics of Bergman cyclization is considered and evaluated, and polymers are synthesized using Bergman Cyclization Polymerization (BCP) (Chapter 5).

Advisor: Fischer, Felix R
Ion Transport and Structure in Polymer Electrolytes with Applications in Lithium Batteries

When mixed with lithium salts, polymers that contain more than one chemical group, such as block copolymers and endgroup-functionalized polymers, are promising electrolyte materials for next-generation lithium batteries. One chemical group can provide good ion solvation and transport properties, while the other chemical group can provide secondary properties that improve the performance characteristics of the battery. Secondary properties of interest include non-flammability for safer lithium ion batteries and high mechanical modulus for dendrite resistance in high energy density lithium metal batteries. Block copolymers and other materials with multiple chemical groups tend to exhibit nanoscale heterogeneity and can undergo microphase separation, which impacts the ion transport properties. In block copolymers that microphase separate, ordered self-assembled structures occur on longer length scales. Understanding the interplay between structure at different length scales, salt concentration, and ion transport is important for improving the performance of multifunctional polymer electrolytes./nIn this dissertation, two electrolyte materials are characterized: mixtures of endgroup-functionalized, short chain perfluoropolyethers (PFPEs) and lithium bis(trifluoromethanesulfonyl) imide (LiTFSI) salt, and mixtures of polystyrene-block-poly(ethylene oxide) (PS-b-PEO; SEO) and LiTFSI. The PFPE/LiTFSI electrolytes are liquids in which the PFPE backbone provides non-flammability, and the endgroups resemble small molecules that solvate ions. In these electrolytes, the ion transport properties and nanoscale heterogeneity (length scale ~1 nm) are characterized as a function of endgroup using electrochemical techniques, nuclear magnetic resonance spectroscopy, and wide angle X-ray scattering. Endgroups, especially those containing PEO segments, have a large impact on ionic conductivity, in part because the salt distribution is not homogenous; we find that salt partitions preferentially into the endgroup-rich regions. On the other hand, the SEO/LiTFSI electrolytes are fully microphase-separated, solid, lamellar materials in which the PS block provides mechanical rigidity and the PEO block solvates the ions. In these electrolytes longer length scale structure (~10 nm – 1 μm) influences ion transport. We study the relationships between the lamellar grain size, salt concentration, and ionic conductivity using ac impedance spectroscopy, small angle X-ray scattering, electron microscopy, and finite element simulations. In experiments, decreasing grain size is found to correlate with increasing salt concentration and increasing ionic conductivity. Studies on both of these polymer electrolytes illustrate that structure and ion transport are closely linked.

Advisor: Balsara, Nitash P
Minor, Andrew M
Essays on Service Operations Systems: Incentives, Information Asymmetries and Bounded Rationalities

This dissertation is concerned with service operations systems with considerations of incentives, information asymmetries and bounded rationalities. Chapter 1 provides an overview of the dissertation./nIn Chapter 2, motivated by the information service operations for the agricultural sectors in the developing economies, we propose a Cournot quantity competition model with price uncertainty, wherein the marketing boards of farmers' cooperatives have the options to obtain costly private information, and form information sharing coalitions. We study the social value of market information and the incentives for information sharing among farmers./nIn Chapter 3, we offer a behavioral (bounded rationality) theory to explain product/technology adoption puzzle: Why superior investment goods are not widely purchased by consumers? We show that present-bias encourages procrastination, but discourages strategic consumer behavior. Advance selling is beneficial not only to the consumers as a commitment device, but also to the seller as a price discrimination instrument./nIn Chapter 4, motivated by the fresh-product delivery industry, we propose a model of service operations systems in which customers are heterogeneous both in terms of their private delay sensitivity and taste preference. The service provider maximizes revenue through jointly optimal pricing strategies, steady-state scheduling rules, and probabilistic routing policies under information asymmetry. Our results guide service mechanism design using substitution strategies./nIn Chapter 5, motivated by the puzzle of excessively long queue for low quality service in tourism and healthcare industries, we study the customers’ learning behaviors in the service operations systems, when they hold incorrect beliefs about the population distribution. We highlight a simple behavioral explanation for the blind ``buying frenzy'' in service systems with low quality: The customers under-estimate others' patience and are trapped in a false optimism about the service quality./nChapter 6 concludes the dissertation with a summary of the main results and policy recommendations.

Advisor: Shen, Zuo-Jun