VictorJuiz/thesis huggingface dataset:
Hydroamination and C–C Activation Methods for the Expedient Synthesis of Lycopodium Alkaloids and Phomactin Natural Products

This dissertation describes our efforts toward the total synthesis of complex natural products in the Lycopodium alkaloid and phomactin terpenoid families. The first chapter focuses on our strategy to construct fawcettimine-type Lycopodium alkaloids (such as palhinine A) that contain unique bridging ring systems. The synthesis of a model substrate to examine an atom- transfer radical cyclization is described, as well as the synthesis of a 6-5-9 tricycle that could serve as a common intermediate to access many fawcettimine-type natural products./nAfter observing an unprecedented hydroamination while working toward the synthesis of Lycopodium alkaloids, we explored the possibility that trimethylsilyl iodide (TMSI) could be a novel effector of this transformation. The second chapter describes our optimization studies of this hydroamination reaction on simple sulfonamides. We show that catalytic amounts of TMSI and water are unique in their ability to effect hydroamination and hydroetherification of unactivated olefins at room temperature. We found that the iodide anion is crucial to obtain high reactivity at low temperatures./nThe third chapter of this dissertation provides background and initial strategies toward the synthesis of phomactin natural products. Biological activity and previous syntheses are described. Our general strategy for accessing the phomactin terpenoids by utilizing strategic C–C activation of a cyclobutanol-derived substrate is illustrated as well as initial strategies and model studies. These include investigating C(sp3)–H functionalization reactions with a ketone-derived directing group and assessing the ability to accomplish a hydrazine/aldehyde “traceless” bond construction./nThe fourth chapter describes the development of our synthetic route to access several phomactin-like compounds. This has been accomplished through exploiting the unique properties of cyclobutanol-containing compounds. Both π-allyl cross-coupling and aldehyde addition reactions are efficient means of appending the linear fragment to the [3.1.1]bicycle. Templated macrocyclization was achieved in excellent yield, aided by the scaffolding ability of the rigid [3.1.1]bicycle. The cyclobutanol was selectively cleaved open through the action of rhodium catalysis. We’ve shown mechanistically that the products of this process are dependent on subtle changes to the substrate as well as the solvent. Final functionalizations include a reductive sulfone removal in the presence of an enone moiety via the intermediacy of an in situ generated cyclopropanol “protecting group”.

Advisor: Sarpong, Richmond
Fast and accurate quantification and differential analysis of transcriptomes

As access to DNA sequencing has become ubiquitous to scientists, the use of sequencers has expanded from determining the genomes of individuals to performing molecular probing assays. These assays have turned DNA sequencers into molecule counting machines and can be used to measure biological activities such as gene expression (RNA-Seq), DNA accessibility (ATAC-Seq) and many others./nEach new assay poses new analytical challenges, and the main focus presented here is in analyzing RNA-Seq data./nOne of the main challenges in RNA-Seq is that sequenced fragments are often ambiguous, meaning they are compatible with multiple splice forms or genomic locations./nIn order to estimate gene abundances effectively, these ambiguous fragments should be used in a comprehensive model in order to not bias results./nAnalysis has come a long way from ignoring ambiguous mappings, to maximum likelihood models, and even streaming models./nAdvancements in these models have greatly improved the accuracy of estimating gene and transcript abundances./nIn parallel, methods for determining true expression differences between experimental conditions, termed differential expression, have been developed./nHistorically, these methods have mostly ignored advancements in gene expression estimation but have made much progress in between-sample variance estimation when sample sizes are small -- a common practice in this field./nHerein, we present advancements to both abundance estimation and differential expression analysis./nWe show dramatic improvements to the speed of abundance estimation while maintaining accuracy./nFurthermore, we bridge these two fields by developing a differential expression model incorporating the uncertainty introduced by abundance estimation./nWe show that this model outperforms existing techniques at both the transcript and gene level./nAdditionally, we show that these methods can be used to address other biological questions such as the discovery of novel retained introns and estimation of their abundances./nAn extension to the differential expression model is proposed to identify differences in retained intron levels while incorporating abundance estimation uncertainty.

Advisor: Pachter, Lior
Personal Politicians: Biography and its Role in the Minds of Voters

Despite the central role of politicians in representative democracies, political science has largely ignored how who candidates for elected office are shape campaigns and elections. By communicating biographical details about their family, occupation, education, religion, and other background, political candidates attempt to build trust and alter how they will be evaluated by voters. Using systematized biographies of all US congressional candidates from 2008-2014, television advertising data from 2008-2012, and six survey experiments, including four panel experiments, I demonstrate that biographical presentation by candidates is ubiquitous, systematic, and effectual in shaping the opinion of voters./nTo assess biography’s role in campaigns and candidate evaluation, I address and provide solutions to a number of theoretical and measurement problems in existing literature using a diverse set of methodological strategies. Grounded in literatures in both political science and psychology, I focus on the nexus between the strategic behavior of electoral candidates and voters’ cognition. Because of the complexity of candidates’ biographies, many scholars have often overlooked them in favor of more parsimonious measurement strategies, often overlooking critical variation in candidate backgrounds. Indeed, many of the interesting hypotheses and findings about the role of biography lie not in broad main effects – but in its interaction with other characteristics of candidates, elections, districts, or voters./nI find that a diverse set of biographical attributes are associated with candidates’ partisan affiliation and particular types of campaigns, and are also independently related to electoral success. Candidates strategically present themselves to voters through television advertising, highlighting advantageous characteristics while glossing over others. In realistic over-time conjoint-style experiments, I find that biographical factors independently affect evaluations of candidates alongside party and policy information. I also find that the role biography plays in voters’ cognition is affected by its importance to voters, its memorability, its timing and order of presentation, and its conformance to party stereotypes.

Advisor: Lenz, Gabriel
Benchmarks for Cloud Robotics

Several areas of computer science, including computer vision and natural/nlanguage processing, have witnessed rapid advances in performance, due in part/nto shared datasets and benchmarks. In a robotics setting, benchmarking is/nchallenging due to the amount of variation in common applications: researchers can use/ndifferent robots, different objects, different algorithms, different tasks, and/ndifferent environments./nCloud robotics, in which a robot accesses computation and data over a network,/nmay help address the challenge of benchmarking in robotics. By standardizing/nthe interfaces in which robotic systems access and store data, we can define a/ncommon set of tasks and compare the performance of various systems./nIn this dissertation, we examine two problem settings that are well served by/ncloud robotics. We also discuss two datasets that facilitate benchmarking of/nseveral problems in robotics. Finally, we discuss a framework for defining and/nusing cloud-based robotic services./nThe first problem setting is object instance recognition. We present an/ninstance recognition system which uses a library of high-fidelity object models/nof textured household objects. The system can handle occlusions, illumination/nchanges, multiple objects, and multiple instances of the same object./nThe next problem setting is clothing recognition and manipulation. We propose a/nmethod that enables a general purpose robot to bring clothing articles into a/ndesired configuration from an unknown initial configuration. Our method uses a/nlibrary of simple clothing models and requires limited perceptual capabilities./nNext, we present BigBIRD (Big Berkeley Instance Recognition Dataset), which has/nbeen used in several areas relevant to cloud robotics, including instance/nrecognition, grasping and manipulation, and 3D model reconstruction. BigBIRD/nprovides 600 3D point clouds and 600 high-resolution (12 MP) images covering/nall views of each object, along with generated meshes for ease of use. We also/nexplain the details of our calibration procedure and data collection system,/nwhich collects all required data for a single object in under five minutes with/nminimal human effort./nWe then discuss the Yale-CMU-Berkeley (YCB) Object and Model Set, which is/nspecifically designed for benchmarking in manipulation research. For a set of/neveryday objects, the dataset provides the same data as BigBIRD, an additional/nset of high-quality models, and formats for use with common robotics software/npackages. Researchers can also obtain a physical set of the objects, enabling/nboth simulation-based and robotic experiments./nLastly, we discuss Brass, a preliminary framework for providing robotics and/nautomation algorithms as easy-to-use cloud services. Brass can yield several/nbenefits to algorithm developers and end-users, including automatic/nresource provisioning and load balancing, benchmarking, and collective robot/nlearning.

Advisor: Abbeel, Pieter
Sparse optimization models with robust sketching and applications

Sparse machine learning has recently emerged as powerful tool to obtain models of high-dimensional data with high degree of interpretability, at low computational cost. The approach has been successfully used in many areas, such as signal and image processing. In sparse learning classification, for example, the prediction accuracy or some other classical measure of performance is not the sole concern: we also wish to be able to better understand which few features are relevant as markers for classification. Furthermore, many of sparse learning tasks in practice, including cross-validation, parameter search, or leave-one-out analysis, involve multiple instances of similar problems, each instance sharing a large part of learning data with the others. In this thesis, we introduce a robust framework for solving these multiple sparse regressions in the form of square-root LASSO problems, based on a sketch of the learning data that uses low-rank approximations. Our approach allows a dramatic reduction in computational effort, while not sacrificing—sometimes even improving—the statistical performance./nWe present our technique by first studying sparse optimization with applications in different domain of interests, from text analytics to system design, and then developing theories for robust solutions for sparse regression in multi-instance setting. We also provide comparisons with other heuristics to obtain sparse models in various applications. In more detail, our central contributions from this thesis include:/n- Identifying key tasks in domains of interests under real-world setting,/n- Suggesting models that are suitable for these tasks along the axes of computational complexity and model understandability,/n- Exploiting problem structures when working with multiple instances to robustly improve computation while maintaining high learning performance, and/n- Proposing applications of our robust solutions in high-dimensional setting.

Advisor: El Ghaoui, Laurent
Bioluminescence imaging of hepatic nutrient fluxes

Bioluminescence imaging (BLI) is a powerful technology for studying molecular and cellular features in living animals. Impressive advances in luciferase engineering and ease of targeting by genetic encoding permit the broad use of bioluminescence for in vivo imaging for diverse purposes. First, we generated transgenic mice with liver-specific expression of luciferase and used BLI with a FFA probe to enable non-invasive real-time imaging of FFA flux in the liver. Our approach enabled us to observe the changes in FFA hepatic uptake under different physiological conditions in live animals. We found that our novel imaging system is a useful and reliable tool to study the dynamic changes in hepatic FFA flux in preclinical model systems./nWe also utilize this imaging approach to study the role of fatty acid transport proteins in hepatic carcinogenesis. We generated a genetically engineered liver cancer mouse model via hydrodynamic transfection and determined the changes of fatty acid uptake during tumor formation. Our results demonstrated that the rate of FFA uptake is significantly decreased during the development of hepatocellular carcinoma (HCC), but not that of intrahepatic cholangiocarcinoma (ICC). We additionally showed that FATP5 knockdown suppresses ICC tumor formation and that the down regulation of FATP5 expression delays tumor growth even after the onset of ICC. These findings uncovered the critical role of FATP5 in ICC development and demonstrated the potential utility of these proteins as therapeutic targets for the prevention and treatment of ICC./nWe expanded our bioluminescent imaging approaches to other nutrients and copper in particular. We demonstrated Copper-Caged Luciferin-1 (CCL-1), a bioluminescent copper-responsive probe can detect physiological changes in labile Cu+ levels in live cells and mice under situations of copper deficiency or overload. Application of CCL-1 to mice with liver-specific luciferase expression in a diet-induced model of non-alcoholic fatty liver disease (NAFLD) reveals onset of hepatic copper deficiency and altered expression levels of central copper trafficking proteins that accompany symptoms of glucose intolerance and weight gain./nLastly, we also utilized bioluminescent approaches to detect liver damage and apoptosis. We shown that D-cysteine and 2-cyanobenzothiazoles can selectively react with each other in vivo to generate a luciferin substrate for firefly luciferase. We applied this "split luciferin" ligation reaction to the imaging of apoptosis associated with caspase 3/7. Importantly, this strategy was found to be superior to the commercially available DEVD-aminoluciferin substrate for imaging of caspase 3/7 activity. Moreover, the split luciferin approach enables the modular construction of bioluminogenic sensors, where either or both reaction partners could be caged to report on multiple biological events. These imaging approaches for nutrient fluxes should open up our understandings of complex metabolic networks in various metabolic processes and diseases states.

Advisor: Stahl, Andreas
Site-Specific Modification of Proteins with 2-Pyridinecarboxaldehyde Derivatives

The ability to chemically modify proteins is an essential tool for many scientific fields. The attachment of synthetic compounds on the surface of proteins has led to a better understanding of cellular function, the identification of protein structure, the development of biotherapeutics, and the generation of protein-based materials. As these applications have become more advanced, there has become an increasing need for modification strategies that target a single site to produce well-defined protein conjugates. However, strategies that only modify a single location are limited in number and often require protein engineering. This work describes the development of a site-specific N-terminal modification strategy using 2-pyridinecarboxaldehyde (2PCA) derivatives. The 2PCA reaction has been shown to effectively modify a wide range of peptide and protein substrates with excellent site-specificity. Furthermore, the usefulness of this reaction has been highlighted by the development of new protein-based materials. This strategy was used to incorporate high-affinity binding proteins into polymer matrices for the detection and removal of endocrine disrupting chemicals. To further demonstrate the versatility of this reaction, it was applied to the synthesis of a well-defined targeted imaging agent by incorporating 2PCA moieties into site-selective heterobifunctional crosslinkers. Additionally, libraries of aldehydes and rationally designed 2PCA reagents have been investigated. These preliminary studies have increased our understanding of the reaction and have provided useful information for improving product yields. Overall, the simplistic setup of this protein modification reaction and its broad protein scope make this reaction a useful strategy for the development of complex protein-based materials.

Advisor: Francis, Matthew B
Medical Imaging Technology Innovations to Minimize the Safety Risks of Angiography for Chronic Kidney Disease Patients

Cardiovascular Disease (CVD) is the leading cause of death in the United States. CVD is/ncaused by a buildup of plaque in the blood vessels of the heart and brain. CVD is comorbid/nwith Peripheral Vascular Disease (PVD), which is a buildup of plaque in the extremities/nand organs below the stomach. Medical imaging is a clinically indispensable tool for diagnosing CVD and PVD, as well as guiding real-time interventional procedures. Currently,/nthe two main procedures for diagnosing CVD and PVD are X-Ray and CT angiography,/nboth of which rely on injection of iodinated contrast agents. However, about 25% of patient/nundergoing these procedures suer from Chronic Kidney Disease (CKD). For this patient/nsubpopulation, iodinated contrast agents are risky and can lead to complete kidney failure./nPhysicians risk damaging patients' kidneys in order to alleviate the more imminent threat of/ndeath from a heart attack. Hence, an open challenge remains to develop a safer diagnostic/nangiography method that could match current methods in resolution, contrast, and speed./nHere we introduce and develop two new imaging methods for imaging patients with CKD./nThe rst method is MR Saline Angiography, an alternative Magnetic Resonance (MR) based/nangiographic method for coronary imaging. In combination with the inherent resolution and/nspeed of traditional MR methods, MR Saline Angiography has the advantage of utilizing/nsaline as a safe contrast agent. This approach is an improvement upon the commonly used/nGadolinium-based contrast agent that is also toxic to patients with CKD. Using a novel/nelectromagnetically shielded catheter and a tailored pulse sequence, we have demonstrated/nthat MR Saline Angiography is a feasible alternative for imaging coronary arteries. The second method is Magnetic Particle Imaging (MPI), a tracer imaging modality, which images/nSuperparamagnetic Iron Oxide nanoparticles. MPI is an emerging imaging technique with/npossible applications in angiography as well as targeted and non-targeted tumor imaging,/nhyperthermia, perufsion, cell tracking and targeted drug delivery. Here we study the feasibility/nof MPI as an angiographic imaging method by looking at short-term biodistribution/nand long-term iron clearance for two most common MPI tracers.

Advisor: Conolly, Steven M
Desire, Event, Vision: Forms of Intersubjectivity in the Nineteenth-Century Russian Novel

This dissertation contends that the philosophical problem of the existence of other people constitutes a central preoccupation of the nineteenth-century Russian novel, a problem that its authors worked through not only in the content of their novels but on the level of form, as well. At the heart of this study, which examines the emergence of the Russian realist novel in the years between 1850 and 1880, is the following question: How is the Russian understanding of the modern self (subjectivity) related to the formal aesthetic features of the Russian novel?/nI focus on three novels – Ivan Turgenev’s Rudin (1856), Fyodor Dostoevsky’s Demons (1872), and Lev Tolstoy’s Anna Karenina (1873-77) – in order to account for relations between subjectivity and form in the nineteenth-century Russian novel as well as these authors’ various conceptualizations of the human subject. In each of the novels I identify a mediating concept that unites that novel’s most conspicuous formal features to its (implicit) understanding and representation of intersubjectivity. In Rudin, Demons, and Anna Karenina, these concepts are desire, event, and vision, respectively. My chapters describe how these concepts exert a decentering force on the subject, interrupting the subject’s ability to take efficacious action, to engage in self-conscious rational reflection, and ultimately to make meaning of his or her life. At the same time, these forces of desire, the event, and vision also bind subjects together, constituting the intersubjective structures that my close readings seek to describe./nMethodologically, my dissertation stages a dialogue between twentieth-century theories of the novel and the nineteenth-century Russian novel, in order to articulate the relationship between the categories of subjectivity and form. Recent years have witnessed a renewed interest in questions of form within novel studies, particularly with respect to the novel’s role in the formation and representation of the human subject. My dissertation contributes to this current turn towards form, marking out a place for the nineteenth-century Russian novel. Approaches to the novel in the field of Slavic studies, for historical as well as ideological reasons, have not fully benefitted from the challenges as well as insights offered by contemporary novel theory; post-structuralist theories represent a particularly conspicuous gap this dissertation seeks to fill.

Advisor: Golburt, Luba
The Practice of Shi‘i Jurisprudence in Contemporary Lebanon

Drawing on ethnographic and archival research conducted in Lebanon and France between 2012 and 2014, this dissertation discusses Shi‘i methods of legal reasoning (ijtihad), and considers their incorporation into state juridical apparatuses. Since its colonial inception in 1926, the Lebanese state has harnessed the shari‘a tradition to regulate the family life of its Shi‘i citizenry. In order to properly grasp the ethical and epistemological transformations underlying the state’s appropriation of Shi‘i legal discourse, I suggest we first examine the training judges, clerics, and jurists receive in traditional hawza seminaries. This dissertation’s first three chapters show that learning to perform authoritative shari‘a reasoning requires not only developing a mastery of the sacred texts, but also submitting oneself to the discipline of the Shi‘i moral tradition./nThe remaining chapters examine what Islamic legal reasoning becomes when it gets entangled with the judicial functions of a modern nation-state. To this end, I shift the ethnographic focus toward Beirut’s Shi‘i family courthouse, where hawza-trained judges are appointed by the Lebanese state to adjudicate familial disputes. I show that under the institutional and conceptual conditions of state legality, the Islamic legal tradition is divested of many of its interpretative possibilities and oriented toward the purpose of governing marital relationships uniformly. What accounts for this reorientation, I argue, is not so much the volition of individual judges, but the grammar of procedural norms and legal mechanisms through which these judges perform their work. While making this argument, I discuss the social and gender consequences of the Lebanese state’s appropriation of Shi‘i legal thinking.

Advisor: Mahmood, Saba