VictorJuiz/thesis huggingface dataset:
Retinal ganglion cell responses to extracellular stimulation for high-fidelity vision restoration
Keywords: Medicine.

Future high-fidelity, large-scale electrical brain-machine interfaces will have the ability to restore population-level neural function to treat debilitating sensorimotor conditions. Achieving this will require fine, simultaneous, targeted closed-loop extracellular control of many individual neurons, carefully taking into account their natural physiological properties. Reconstitution of naturalistic neuronal activity in vivo necessitates advances in the engineering of bio-interfacing electrodes, understanding of population-level functional physiology, and mapping of biophysical responses to artificial external current. However, until recently, the electrophysiological exploration of neuronal responses to pulses of extracellular electrical current has been limited to either mostly non-primate cells, aggregated signals from hundreds or thousands of neurons, or peripheral nerve-fiber bundles. Additionally, most detailed explorations of single neuron biophysics have been conducted on cultured neurons with unnatural morphologies and extracellular environments. Using intact pieces of excised retinal tissue as a model system for ease of access, correlatability to therapeutic interventions for patients, and similarity to the cortex, our lab has previously independently characterized the recording and extracellular stimulus response properties of four macaque retinal ganglion cell (RGC) types: ON and OFF parasol and midget cells at a large scale using a densely spaced 512-electrode MEA. My graduate work builds on these initial studies by 1) systematically relating the recorded features of spontaneous activity of four RGC types at different eccentricities to their electrical response properties across dozens of different retinal preparations and thousands of individual cells, exploring the mechanism of this relationship using simulated neural models, and investigating the practical utility of such a characterization for future retinal implant engineering, and 2) generalizing the insights derived from the extracellular probing of macaque RGCs to human RGCs, which demonstrate very similar recording and electrical response properties. This work reveals that RGCs across different macaque and human eyes have near a uniform relationship between activity recording and electrical response properties that depend on broad cellular characteristics such as membrane morphology and ion channel density. It also demonstrates that these properties can be leveraged to aid in retinal implant design--specifically calibration of electrical stimuli--for use in treating acquired blindness. Finally, it implies that similar analyses are possible in various CNS circuits, making high-resolution artificial electrode access to these systems possible
Rewiring oncogenic signaling to therapeutic viral activation for treatment of metastatic cancer
Keywords: Engineering.
Bioengineering.

Despite recent advances in cancer treatments, improvements to long-term survival in metastatic solid tumors, such as pancreatic or ovarian cancer, remain limited. Current medical therapies suppress growth-promoting biochemical signals or activate immune responses to tumor-associated antigens (TAAs). However, these approaches are limited by toxicity to normal cells that utilize the same signaling pathways or express the same antigens. Previously we developed a method for Rewiring Aberrant Signaling to Effector Release (RASER) to selectively redirect hyperactive ErbB signaling, found in many solid tumors but not normal tissues, to programmable responses. Here in my thesis, I report the engineering of viral vectors that express and are regulated by RASER, resulting in the selective ablation of cancer cells exhibiting hyperactive ErbB signaling. In mice, RASER-restricted vesicular stomatitis virus (VSV) exhibited 10000-fold less toxicity per dose than parental VSV, and 10-fold less than the attenuated VSV-∆M51 variant. RASER-restricted VSV conferred a larger survival benefit in non-immune mouse models of peritoneally disseminated ErbB-hyperactive pancreatic and ovarian cancers. Thus, RASER-restricted viral activation may represent a new approach for treating ErbB-hyperactive metastatic cancers that is independent of adaptive immunity. I also successfully extended the RASER concept to additional signals caused by oncogene mutations including hyperactive c-Met and KRAS and successfully developed Ad and VSV controlled by c-Met and KRAS RASER. With its generalizability and application in vivo, RASER controlled viruses will thus build a completely new type of cancer therapy, in which synthetic proteins are engineered to specifically identify and destroy cancer cells.
Ring-opening metathesis polymerization of 2,3-dihydrofuran
Keywords: Humanities and Sciences.
Chemistry.

Plastics are critical to every modern industry, but the chemical stability of common polymers causes them persist for decades. As a result, plastics are accumulating in the environment at an alarming rate. To address the growing plastic pollution crisis, new end-of-life strategies must be developed. One important approach is the development of new polymers that can be broken down on demand. These degradable polymers may be converted back into monomers or into building blocks for second-generation materials. This thesis introduces the surprising ring-opening metathesis polymerization (ROMP) of 2,3-dihydrofuran (DHF), a commercial cyclic enol ether. Enol ethers have historically been used as quenching agents in ROMP, reacting rapidly with Grubbs catalysts to form thermodynamically stable electron-rich Fischer carbenes. However, these Fischer carbenes remain competent metathesis catalysts. Using Grubbs catalysts, DHF can be both homopolymerized and copolymerized with common norbornene ROMP monomers. Furthermore, rapid acid-catalyzed hydrolysis enables degradation of enol ether-containing materials. Chapter 1 introduces the challenge of polymer recycling for both thermoplastics and thermosets. Special attention is paid to modern approaches and recently commercialized recycling technologies. The foundation for the discovery of DHF ROMP is also described. Chapter 2 summarizes the synthesis of degradable and depolymerizable polyDHF. Chapter 3 explores copolymerization of DHF with common norbornene monomers. Finally, Chapter 4 describes the use of DHF in ROMP of dicyclopentadiene. In addition to enabling hydrolysis of polydicyclopentadiene thermosets, the unique reactivity of Ru Fischer carbenes suppresses crosslinking in these materials
RNA structures in non-coding RNA : from the SARS-CoV-2 genome to S. cerevisiae introns
Keywords: Humanities and Sciences.

Structured RNAs play critical roles across the domains of life, whether facilitating viral packaging and replication or regulating complex eukaryotic RNA processing pathways like pre-mRNA splicing. Understanding RNA in the context of its folding can give us a better picture for the mechanism and regulation of these processes, and moreover, this understanding could inform attempts to intervene in these pathways. In the first section of this dissertation, I will discuss the capabilities of computational RNA structure prediction and RNA structure determination. I will highlight our efforts towards evaluating de novo computational prediction methods for RNA tertiary structures, along with our work on building RNA structures in cryo-EM density maps for large RNA or RNA-protein complexes. Then I will focus on our application of de novo RNA structure modeling in making predictions for secondary and tertiary structures in the SARS-CoV-2 RNA genome, providing candidate target regions for diagnostics and anti-viral therapeutic development. In the second section of the dissertation, I will focus on our characterization of the RNA structure landscape in S. cerevisiae pre-mRNA through biochemical experiments and computational prediction. We identify intron secondary structures through transcriptome-wide dimethyl sulfate (DMS) probing experiments, enriching for low-abundance pre-mRNA through splicing inhibition. These data reveal structures bridging splice sites present across yeast introns, along with previously uncharacterized long stems that distinguish pre-mRNA from spliced mRNA. With high-throughput structure-function experiments, we measure the effects of modulating a set of candidate intron structures, finding that some structured elements can increase spliced mRNA levels despite being distal from canonical splice sites, while other structures can increase intron retention. To more deeply interrogate these functional intron structures, we explore the potential protein-binding partners and tertiary structure for a candidate functional structured domain. Our transcriptome-wide inference of intron RNA structures suggests new ideas and model systems for understanding how pre-mRNA folding promotes splicing efficiency and regulation of gene expression. This approach provides a blueprint for computational, structural, and functional experiments that can help dissect the role that RNA structure plays in various biological processes
Robotic mobility using extendable booms : design, control, and experimentation
Keywords: Engineering.
Aeronautics and Astronautics.

Space exploration drives us to push the boundaries of engineering, especially in the fields of robotics and autonomous systems. Innovations such as satellite communication, GPS technology, and advancements in materials science, originally developed for space missions, have significantly enhanced everyday life on Earth. As we aim to tackle increasingly ambitious space missions -- from the Lunar Gateway to Martian colonization to asteroid mining -- the mobility and manipulation requirements of our robotic platforms exceeds current capabilities. Many of these missions involve environments characterized by adverse gravity conditions and sparse footholds that impede traditional means of locomotion. The solution offered by this thesis, ReachBot, provides unique access to previously inaccessible terrain, broadening our capability to make new scientific discoveries and expanding humanity's reach into space. ReachBot realizes mobility in challenging terrain by combining the portability and maneuverability of small mobile robots with the long reach and high force capability of large robots. It does this by merging two technologies with little previous overlap: mobile manipulation robots and lightweight extendable booms. This thesis begins with a discussion of ReachBot's design, optimized via a trade study method to tailor an extendable-boom architecture to mission-specific parameters and objectives. We demonstrate this method by applying it to a Martian lava tube mission, resulting in a final configuration of booms, joints, and sensors that will provide a continuing example throughout the thesis. Subsequent chapters develop models to describe ReachBot's kinematics and dynamics, including a contact model that addresses uncertainties inherent to grasping in rocky terrain. We then incorporate these models into a robust motion planning algorithm to move ReachBot through its environment while maintaining grasp contact. In particular, we leverage optimal control techniques to generate trajectories that maximize the probability of successful execution. Finally, we validate ReachBot's system capabilities, in addition to our modeling and simulation approaches, with a series of hardware experiments ranging from low-fidelity prototypes using tape measures as deployable booms to a mission-realistic field test in the Mojave Desert. Collectively, this thesis lays the foundation for extensive future work on robotic systems using extendable booms; in particular, the tools used for design, modeling, and control will enable the development of extendable-boom robots built to explore complex adverse gravity environments previously inaccessible to robotic or human exploration.
Robotic path planning with sparse environment representations
Keywords: Engineering.
Mechanical Engineering.

This thesis explores different aspects of robot resiliency in path planning problems. Our goal is to endow autonomous robots with the ability to be robust to uncertainty and adaptable so that they can be entrusted in challenging real-world applications. To do so, we focus on four application areas, and in each we carefully co-design the robot's environment representation and path planning algorithms so that they jointly capture the key properties of each problem. We first focus on unknown environment exploration, which is a problem where model uncertainty is so high that the planners proposed in the literature are myopic and greedy. We propose an environment representation and coverage planning algorithms that strategically balance greedy information gain and long-horizon planning so that the robot is able make strategic planning decisions over its full time budget. By doing so, we outperform methods that either ignore model uncertainty, or compensate with a myopic planning strategy, while remaining robust to perceptual challenges. We used the method in practice to explore a variety of urban, tunnel, and mine-like environments with autonomous Spot and Husky robotic platforms, and we integrated the solution in Team COSTAR's global planning framework for participating in the DARPA SubTerranean Challenge in 2021. The second application area in this thesis is the problem of searching for radio signal sources in an unknown environment. We find a similar gap in the literature where to overcome the high model uncertainty, solutions proposed unfortunately limit the robot's action space to the extent of its explored regions. We propose a formulation where the robot looks ahead into the unknown space to search for radio emitters that may be located far away from its visited locations. In the third application area, we focus on the robot's ability to adapt to human indications, which is a key aspect of making a robot resilient and trustworthy in the real world. We propose an encoding of a human's intention that enables the robot to infer a human's path preference from indications and adapt to these preferences online. Finally, we explore the Multi-Agent Path Finding problem, and propose a stochastic travel time model for robots to compute solutions optimizing their expected performance, making them robust to unexpected delays in travel time.
The role of Caspr2 in autism spectrum disorder-related gastrointestinal function
Keywords: Medicine.

Gastrointestinal (GI) symptoms are highly prevalent among individuals with autism spectrum disorder (ASD), but the molecular link between ASD and GI dysfunction remains poorly understood. The enteric nervous system (ENS) is critical for normal GI motility and has been shown to be altered in mouse models of ASD and other neurological disorders. Contactin-associated protein-like 2 (Caspr2) is an ASD-related synaptic cell-adhesion molecule necessary for regulating sensory function in the central and peripheral nervous system. In this study, we examine the role of Caspr2 in GI motility by characterizing Caspr2's expression in the ENS and assessing ENS organization and GI function in Caspr2 mutant mice. We find that Caspr2 is predominantly expressed in enteric sensory neurons in both the small intestine and colon. We further assess colonic motility in Caspr2 mutants using an ex-vivo motility monitor and show altered colonic contractions and faster expulsion of artificial pellets. The organization of neurons within the myenteric plexus remains unchanged. Our results suggest a role for enteric sensory neurons in ASD-related GI dysmotility, a finding relevant to consider in the treatment of ASD-related GI symptoms
Role of co-receptors LRP6 and Tspan12 in Norrin/ß-catenin signaling
Keywords: Medicine.
Molecular and Cellular Physiology.

The Wnt/β-catenin signaling pathway co-evolved with multicellularity and dictates embryogenesis and tissue renewal across metazoans. In this pathway, the secreted growth factor Wnt binds and heterodimerizes the receptors Frizzled (Fzd1-10) and Low-density lipoprotein receptor-related protein 5 or 6 (LRP5/6) in the plasma membrane; this ultimately leads to the stabilization of transcriptional co-activator β-catenin, which directs the transcription of target genes. This pathway is also activated by the atypical ligand Norrin. In response to Wnt or Norrin binding to Fzd and LRP5/6, Dishevelled (Dvl1-3) is recruited from the cytoplasm to the plasma membrane. Dvl is essential to Wnt/β-catenin signal transduction because it bridges the receptors with downstream signaling partners, yet how Dvl is recruited to the membrane in response to ligand binding is unclear. Wnt ligands generate Fzd-LRP5/6 heterodimers and may also homodimerize Fzd, but it is not known whether or how these receptor complexes work together to transduce the ligand-binding signal to Dvl. Further, although Fzd and LRP5/6 are sufficient for Wnt-stimulated signaling, and Norrin simultaneously binds these two receptors, Norrin-stimulated signaling additionally requires the membrane protein Tetraspanin-12 (Tspan12) through an unknown mechanism. Tspan12 coimmunoprecipitates with Fzd4 and Norrin, suggesting that it acts as a co-receptor. In this dissertation, I develop biochemical tools to investigate whether the Fzd-Dvl interaction is directly strengthened either by ligand binding to Fzd or by Fzd homo- or heterodimerization with LRP5/6 or Tspan12. Using purified protein, I find that Fzd-Dvl affinity is agnostic to ligand binding or Fzd homo- or heterodimerization. Instead, we show that Fzd-Dvl binding is highly dependent on the lipid phosphatidylinositol 4,5-bisphosphate. I also find that Tspan12 directly binds Norrin with nanomolar affinity, and provide data consistent with a model in which Tspan12 captures Norrin on the cell surface, then hands it off to Fzd4 for association with LRP5/6 and subsequent signaling. This work builds on our understanding of the direct physical interactions that underlie signal initiation in Wnt- and Norrin/β-catenin signaling.
The role of monounsaturated fatty acids in ferroptosis
Keywords: Humanities and Sciences.
Biology.

Ferroptosis is an iron-dependent, oxidative form of cell death that is a result of toxic accumulation of polyunsaturated fatty acid phospholipid hydroperoxides (PUFA-PL-OOH). This death can occur upon inhibition of the phospholipid glutathione peroxidase, GPX4. I find here that cancer cell lines are not uniformly reliant on GPX4 for cell survival. A compendium of factors drives GPX4 essentiality including PUFA content within cells but also reliance on de novo MUFA biogenesis. This work reveals novel MUFAs that can inhibit ferroptosis. Protective MUFAs lead to decreased abundance of toxic PUFA-PLs which reduces ferroptotic stress in cancer cells. I also find that ASCL3, which is required for oleic acid to protect from ferroptosis, is required for some but not all MUFAs to protect from ferroptosis. I identify a novel player in MUFA metabolism, MBOAT2, which prevents cells from using MUFAs to prevent ferroptosis. Finally, I discover that oleic acid can become less protective against ferroptosis when FSP1 is inhibited, depending on the cell line context. Overall, these findings suggest there is a complex machinery within cells that metabolizes MUFAs and complicates our view of how ferroptosis pathways interact
Room : drawing presence and absence
Keywords: Humanities and Sciences.
Music.

Room is a shared aural experience. In Room, the performer sits in a four-foot cubed wooden box, drawing circles on its walls. This sound is captured by a system of contact microphones relayed into a Max/MSP patch that directs, filters, and spatializes these signals onto a dome of speakers surrounding the audience. Encircling the listener in the center of creation, the hidden performer explodes the interiority of the box outside, and brings the presence of performance inside, like a hypercube. Room explores the continuous sound and gesture of the circle, innate and timeless
Safe machine learning-based perception via closed-loop analysis
Keywords: Engineering.
Aeronautics and Astronautics.

While machine learning enables new capabilities for the automation of safety-critical systems such as aircraft and cars, its introduction to these systems will require a significant validation effort. Machine learning presents new challenges in safe design and validation due to its complex nature. For this reason, the initial use of machine learning in these systems is likely to be limited to tasks that cannot be performed solely by traditional automation techniques. This thesis focuses on perceptual tasks that require processing high-dimensional image data from cameras to replace visual tasks typically performed by human operators. Specifically, we outline methods that rely on closed-loop analysis to encourage safety in machine learning-based perception systems. Our first two contributions relate to the safe design of neural network-based perception systems. Once designed, these systems should be put through a thorough verification process. The final two contributions of this thesis develop methods for the formal verification of these systems
Sample-efficient uncertainty calibration for reliable autonomous systems
Keywords: Engineering.
Electrical Engineering.

As the capabilities of autonomous systems continue to improve, they are increasingly deployed in unstructured environments for safety-critical tasks where the cost of failure is high. These systems take as input observations from the external environment, rely on intermediate learning-based components, and output actions that govern system behavior. To operate safely and reliably in high-stakes environments, these systems must have a meaningful and well-calibrated notion of uncertainty over the inputs, over the outputs, and for the internal components. In the first part of this thesis, we address the problem of designing a meaningful and calibrated notion of uncertainty over the system inputs. Knowing when the underlying data distribution has changed and the system may be operating outside its domain of competency is a critical form of uncertainty, as such distribution shifts may lead to catastrophic failures for learning-based systems. To address this problem, we present a warning system that issues alerts when the data distribution shifts, and show that these alerts are calibrated in the sense that there are rarely false alarms (backed with statistical guarantees). This alert system issues alerts an order of magnitude faster than prior work. In the second part of this thesis, we address the problem of calibrating the uncertainty representations used by intermediate components, enabling improved real-time decision-making. In the third part of this thesis, we address the problem of designing a meaningful and calibrated notion of uncertainty over the system outputs. Recognizing when the outputs of the system may lead to a dangerous mistake is a critical form of uncertainty; thus, we present a warning system that issues alerts when a dangerous situation is imminent, and show that these alerts are calibrated by providing a statistical guarantee on their false negative rate. This calibration is achieved with limited data using techniques from conformal prediction.
Sarah Diane Olmstead's NSC ePortfolio
Keywords: Communication in science
Human biology
Cancer
Pediatrics
Genetics
Mixed materials
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This document is an archive of an electronic portfolio (ePortfolio) produced as a capstone requirement for the Notation in Science Communication. In their ePortfolios, NSC students demonstrate how they have met the NSC learning outcomes. These learning portfolios detail students’ growth and development as scientists and science communicators rather than showcasing only their best work. ePortfolios are reviewed and approved by faculty, earning students a special designation on their official Stanford transcript that reflects their science communication acumen.