VictorJuiz/thesis huggingface dataset:
Molecular Mechanisms of the Membrane Sculpting ESCRT Pathway

The Endosomal Sorting Complex Required for Transport (ESCRT) is an ancient, complex machinery that remodels and scissions cellular membranes. Uniquely, the ESCRTs remodel and scission membranes in a reverse topology – away from the cytosol. Since their discovery the ESCRTs have been identified in a large number of cellular processes, but detailed mechanistic understanding has proven difficult. As a system of over 20 components that rapidly and dynamically rearrange themselves to constrict and scission membranes, the ESCRTs prove a difficult machinery that will require high-quality reconstitutions to study./nIn Chapter 1 I provide an introduction to the ESCRTs and describe recent advances toward achieving a consensus on the mechanism of ESCRT-mediated membrane remodeling and scission. In Chapter 2 I discuss the first reconstitution of ESCRT-mediated membrane scission, combining microscopy, microfluidics, and optical trapping to achieve this goal. In Chapter 3 I describe a novel function of the ESCRTs, finding that CHMP1B, IST1, and Spastin are capable of normal-topology membrane scission. Finally, in Chapter 4 I provide an outlook on the remaining challenges in the field, and the approaches that will be crucial for tackling them.

Advisor: Hurley, James H
Uncovering the Genetic and Functional Diversity of Midbrain Dopamine Neurons

Midbrain dopamine (DA) neurons in the substantia nigra pars compacta (SNc) and ventral tegmental area (VTA) project throughout the brain to modulate a diverse set of behaviors and brain states. Although their effects are widespread, they represent a very small fraction of neurons. Dopamine neurons rely on their diverse inputs, outputs, physiology, and gene expression in order to maintain their broad behavioral influence. To better understand the different roles dopaminergic projections play in the brain, the circuits need to be studied in isolation as adjacent neurons and circuits often mediate distinct behaviors. Because of their close anatomical proximity, novel tools and methods must be devised in order to precisely dissect dopaminergic sub-circuits. New tool development will depend on identifying the underlying genetic signature of dopaminergic subpopulations to allow consistent, reproducible labeling of distinct populations. Gene expression analysis will also reveal unique genes expressed in DA neurons that could lend functional importance to already established dopaminergic circuits./nHere we used single-cell RNA-sequencing to determine the unique gene expression signature of DA neurons and identify genes that define distinct dopaminergic subpopulations. We used retrograde tracing, electrophysiology, and disease models to show that genetically defined populations are functionally distinct with defined projections, unique physiological characteristics, and selective sparing in a Parkinson’s disease model. Through this work, we defined two circuits that arise from populations in the ventromedial VTA marked by their expression of Neurod6 and Grp and determined that single genes are not sufficient to label dopaminergic subtypes. Because of this, we developed a Flp-recombinase dopaminergic reporter mouse (DAT-Flp). Using this mouse, we were able to use intersectional genetic tools to selectively label Neurod6-DA neurons to enable future investigations into the role that these neurons play in dopaminergic functions.

Advisor: Bateup, Helen S
Self-Talk and Self-Esteem: Do Non-First Person Parts of Speech Influence Affective Components of the Self-Concept?

Self-distancing has been linked to reductions in negative emotional experience (i.e., lower anger and sadness) as well as changes in appraisal processes (i.e., more reconstrual/less recounting; more challenge/less threat). We examined whether self-distancing also influences the self-concept, specifically its affective component (i.e., self-esteem). In a series of four experiments (total N = 2301), we investigated how distanced self-talk affects self-esteem relative to immersed self-talk, which involves using non-first versus first-person pronouns, respectively, in reference to the self during introspection. Study 1 employed implicit and explicit measures to test condition differences in self-esteem. Compared with immersed participants, those who distanced demonstrated higher implicit self-esteem but did not differ in explicit measures. Study 2 aimed to replicate the effects on implicit self-esteem and discern whether positive associations with the self were increased or maintained during Study 1. This study did not replicate Study 1, as implicit self-views did not differ by self-talk condition. Studies 3 and 4 addressed limitations in Study 1 that may have contributed to null explicit self-esteem findings, but did not provide evidence that distanced self-talk influences explicit self-views. Finally, a meta-analysis (Study 5) indicated that across all our studies, relative to immersed self-talk, those who distanced did not experience significant changes in self-esteem. Together, these findings indicate that although distanced self-talk may be an effective method for engaging more adaptive evaluations of emotional experiences, this emotion regulation strategy does not influence how one affectively evaluates the self.

Advisor: Ayduk, Ozlem
Hydrodynamics of Integrable and Near-Integrable Quantum Systems

``Integrable systems'' are physical systems that possess an extensive number of suitably local conservation laws. Such systems include experimentally realizable quantum models, like the Lieb-Liniger gas of quasi-one-dimensional bosons and the spin-$1/2$ Heisenberg chain, and paradigmatic classical models, such as the anharmonic Toda lattice. On the one hand, the presence of an extensively large set of local conservation laws endows these systems with unusual transport and thermalization properties. On the other hand, the dynamical constraints implied by these conservation laws yield a remarkable degree of analytical tractability./nIn this first part of this thesis, we establish hydrodynamics as a powerful tool for probing nonequilibrium dynamics in integrable and near-integrable many-body systems, both quantum and classical. We first show that hydrodynamics can be used to predict finite-time, local equilibrium dynamics in integrable systems to a striking degree of accuracy. We then extend these results to integrable systems in confining traps, which break integrability, albeit relatively mildly. Our findings are directly applicable to contemporary experiments on ultracold Bose gases, such as the ``quantum Newton's cradle''. Finally, we elucidate some mathematical properties of the hydrodynamic equations themselves, focusing on their underlying semi-Hamiltonian structure and its connections with classical integrability./nIn the second part of this thesis, we show how classical hydrodynamics can shed light on ``anomalous transport", i.e. that which is neither ballistic nor diffusive, in one-dimensional quantum systems. We first present a simple model of anomalous diffusion, supported by numerical simulations, for the emergence of superdiffusive spreading of heat in one-dimensional metals at low temperature. This effect should be observable in time-resolved experiments on quantum wires. We next propose a physical mechanism for the emergence of Kardar-Parisi-Zhang universality in quantum and classical spin chains with isotropic symmetry. We argue that this phenomenon originates in ``soft gauge modes'' -- long-wavelength, dynamical fluctuations of the Bethe pseudovacuum -- that arise from spontaneous breaking of the internal symmetry.

Advisor: Moore, Joel E
An Examination of Two Facets of Empathic Accuracy in Neurodegenerative Disease: Diagnostic Differences and Neural Correlates

The ability to infer another person’s emotions accurately (i.e., empathic accuracy) is an important aspect of normative socioemotional functioning that may go awry in neurodegenerative diseases. Because most studies of empathic accuracy in neurodegenerative disease focus on the ability to make single judgments of emotional stimuli (e.g., identifying the emotion experienced by a character in a film), little is known about how neurodegenerative diseases affect more dynamic forms of empathic accuracy (e.g., tracking another person’s changing emotions over time). The present study tests the hypothesis that these two forms of empathic accuracy are differentially affected across neurodegenerative syndromes and have distinct neuroanatomical correlates. I compared performance on an emotion labeling task (where participants label the emotion of a character in a series of film clips) with performance on a dynamic tracking task (where participants track the changing valence of emotion portrayed by a character in a film) between seven diagnostic groups (N = 178) including: Alzheimer’s disease (AD; n = 21), behavioral variant frontotemporal dementia (bvFTD; n = 33), semantic variant primary progressive aphasia (svPPA; n = 30), nonfluent variant primary progressive aphasia (nfvPPA; n = 23), progressive supranuclear palsy (PSP; n = 25), corticobasal syndrome (CBS; n = 22), and healthy controls (n = 24). In addition, I examined the neural correlates of performance for each task using whole-brain voxel-based morphometry in a subset of the sample (n = 147). Results indicated that, compared to controls, only patients with bvFTD were significantly impaired on both tasks. Patients with svPPA were significantly impaired on the emotion labeling task, whereas patients with nfvPPA, PSP, and AD were significantly impaired on the dynamic tracking task. Neuroimaging results revealed that smaller volumes in bilateral frontal, caudate, thalamus, and left insular regions were associated with worse labeling, whereas smaller volumes in bilateral, predominantly right medial frontal, temporal, insular regions were associated with worse tracking. Results suggest that these two different forms of empathic accuracy have relatively unique neuroanatomies and are therefore differentially affected by syndrome-specific patterns of neurodegeneration. Findings significantly advance our understanding of the aspects of empathic functioning that go awry across multiple neurodegenerative diseases and the neural circuits that subserve these aspects. They also help explain why real-world empathic accuracy deficits are observed to be more severe in bvFTD relative to other diseases.

Advisor: Levenson, Robert W.
Development of Single-Walled Carbon Nanotube Protein Optical Nanosensors

Many diseases, such as neurodegenerative disorders, cancer, and autoimmune diseases are caused by or exhibit symptoms of abnormal regulation of signaling proteins. In order to obtain a molecular understanding of diseases, we require tools capable of probing the intricate signaling pathways that govern biological function. Understanding the role these proteins play as they circulate between cells will allow us to examine disease progression from an intercellular point of view. Currently, it is difficult to study these proteins in their natural environment, in vivo, because they are created and function on very broad time and length scales. Existing protein detection methods have several limitations as they are optimized for intracellular imaging, performed in vitro, require lengthy sample handling, function over short time scales, or have molecular recognition elements that are unstable in biological media./nThis dissertation presents a modular platform to create optical nanosensors that are able to address current limitations in signaling protein detection. Nanosensor elements require optimization of both signal transduction and molecular recognition elements. Single-walled carbon nanotubes (SWCNTs) are nanoparticles that are ideal signal transducers for biological imaging. SWCNTs have optical properties well-suited for biological sensing such as infinite fluorescence lifetime, no blinking, small size, and fluorescence in the near-infrared region of the electromagnetic spectrum that is least attenuated by biological systems. Several SWCNT nanosensors have already been developed for signaling small molecule targets and peptides, but, to date, none have been created for signaling proteins./nIn order to create a robust imaging platform based on SWCNTs for sensing signaling proteins, it is possible to couple molecular recognition elements to SWCNT signal transducers using dual noncovalent and covalent functionalization strategies. The development of noncovalent molecular recognition elements is explored using peptide mimetic polymers called peptoids. The discovery of a synthetic peptoid binding loop for wheat germ agglutinin protein as a proof-of-principle case study shows the ability to utilize diverse chemical materials to create a fully synthetic binding element for desired protein targets. Additionally, the development of covalently functionalized SWCNTs is explored for the creation of multifunctional optical SWCNT nanosensors. Here covalently functional groups provide functional handles that work synergistically with noncovalent passivation to enable the development of a diverse nanosensor toolbox./nThe findings presented in this dissertation lay the foundation of valuable techniques and materials to optimize the binding to and study of signaling proteins. Future work to streamline the development of novel nanosensors is discussed, and the framework for the creation of other biological nanomaterial tools through these noncovalent and covalent techniques is also explored.

Advisor: Landry, Markita P
Quantum Monte Carlo Excited State Orbitals for Optical Gaps of Molecules and Materials

Although amazing progress has been made since the genesis of quantum mechanics in modeling the ground state wave functions and energies of electronic states, modeling the excited electronic states with similar accuracy is still a difficult challenge. In this dissertation orbital optimization of Multi-Slater Jastrow wave functions and its coupling to various Quantum Monte Carlo (QMC) features are used to determine the optical gaps of various systems. The new features being coupled to orbital optimization include: an excited state targeting function, configuration selection for QMC wave functions, a variance matching scheme for optical gaps, and a modified guiding function for sampling within QMC. After a study of the utility of these features, the success of optical gap prediction on both gas phase molecules (aperiodic systems), and condense phase materials (periodic systems) is explored./nFor aperiodic systems we found that our QMC optical gap workflow produces predictions on par in terms of accuracy with other standard techniques (e.g. MRCI+Q, CASSCF, CASPT2, EOM-CCSD) for small molecules (e.g. Formaldimine, Thioformaldehyde). In addition, for cases like [C3N2O2H4Cl] in which state-averaged orbitals (between the ground and first excited state) heavily compromises the accuracy of these states, and multiple reasonable active-space choices lead to very different state energies, our workflow can be advantageous to use./nFor periodic systems we found that our QMC optical gap workflow produces predictions on par in terms of accuracy with other standard techniques (e.g. DFT, G0W0) for simple bulk materials (e.g. MgO, Trans-Polyaceylene). For more challenging systems, such as bulk transition metal oxides (FeO and MnO) we found that QMC orbital optimization provides the advantage of allowing one to bypass difficult parameterization (e.g. +U value, choice of functional).

Advisor: Neuscamman, Eric
The Role of Visual Context in Emotion Recognition

Emotion recognition is an essential human ability critical for social functioning. It is widely assumed that identifying facial expression is the key to this, and models of emotion recognition have mainly focused on facial and bodily features in unnatural, static, or decontextualized conditions. However, an individual’s face and body are usually perceived within a meaningful context, not in isolation. The visual context, therefore, may provide useful or even necessary information when interpreting emotion. Here, we investigated the role of visual context in dynamic emotion recognition. First, we developed a novel method, "inferential affective tracking (IAT)", to reveal and quantify the contribution of visual context to affect (valence and arousal) perception. We show that when characters’ faces and bodies were masked in silent videos, viewers inferred the affect of the invisible characters successfully and in high agreement, based solely on visual context. We further show that the context is not only sufficient but also necessary to accurately perceive human affect over time, as it provides a substantial and unique contribution beyond the information available from face and body. Next, we tested the efficiency of IAT by measuring the speed of recognizing emotion from contextual information alone. Using cross-correlation analyses, we found that inferring affect based on visual context alone is just as fast as tracking affect with all available information including face and body. We further demonstrated with empirical evidence that this approach has high precision in detecting a sub-second temporal lag. Finally, we extended and adapted the IAT method to test categorical emotion perception rather than affect. This method is very similar to the IAT technique and so we call it “inferential emotion tracking (IET)”. Using IET, we show that the presence of visual context can override interpreted emotion categories from face and body information. Strikingly, we find that visual context determines perceived emotion nearly as much and as often as face and body information does. Taken together, these experiments reveal that emotion recognition is, at its heart, an issue of context as much as it is about faces. Seemingly complex context-based emotion perception is far more efficient than previously assumed.

Advisor: Whitney, David
Readdressing Network Layers

It has long been common practice to split the functionality of computer networks into distinct layers. In the context of the most common networks today, there are five such layers, bracketed by hardware at the lowest layer and application software at the highest. While this modularization has generally been a huge success story for the field, networks have now been subject to decades of changes in terms of both technologies and use cases. Moreover, we have accumulated significant hindsight./nThis dissertation examines the three infrastructural layers that fall between hardware and applications, and in each case suggests an improvement. A new approach to resiliency is explored at the link and network layers. In the former case, the result eliminates the need for the typical spanning tree based approach. In the latter, it can radically improve performance during times of routing protocol convergence, eliminating the need for things like precomputed backup paths. At the transport layer, an approach to server load balancing is discussed, which avoids the fate-sharing problem of stateful load balancers as well as the consistency problems of stateless ones. Finally, this dissertation argues that there is a layer "missing" from our common layered model, the inclusion of which is a vital enabler for the continued evolution of the Internet.

Advisor: Shenker, Scott
An Examination of Cognitive and Emotional Empathy in Caregivers of Persons with Neurodegenerative Disease: Relationships with Mental Health

Caring for a loved one with a neurodegenerative disease can be highly rewarding, but it can also have devastating effects on caregivers’ mental health. Research on vulnerability and resilience to the negative effects of caregiving has emerged over the past few decades, largely focusing on disease factors and caregiver demographics, resources, personality, and coping strategies. The extent to which caregivers’ own emotional functioning, specifically their empathy, relates to their mental health is poorly understood. Because caregiving encompasses a multitude of interpersonal experiences with the person in their care, and emotions play an important role in these interactions, caregiver empathy may be particularly important for their mental health. Thus far, no known studies have utilized laboratory measures of caregiver empathy in examination with caregiver mental health. The present study addressed these gaps by using laboratory measures of two kinds of empathy: cognitive empathy (understanding others’ emotions) and emotional empathy (sharing others’ emotions). In 78 caregivers, we examined cognitive empathy (i.e., accuracy in emotion recognition from films and continuous ratings of a person’s emotions) and emotional empathy (i.e., physiological, behavioral, and self-reported emotional experience to a film depicting suffering) in relation to caregiver mental health (validated questionnaires of depression and anxiety). Results revealed that greater emotional empathy in caregivers (i.e., greater report of negative and caring emotions in response to the film depicting suffering) was associated with worse caregiver mental health. This relationship remained stable when accounting for caregiver physiological and behavioral responses to the film, measures of caregiver cognitive empathy, measures of caregiver emotional reactivity, or a measure of cognitive empathy in the person with neurodegenerative disease. Measures of caregiver cognitive empathy were not related to caregiver mental health. The relationship between caregiver emotional empathy and caregiver mental health was not moderated by disease or caregiver factors known to make caregivers more vulnerable to negative mental health outcomes (i.e., frontotemporal dementia diagnosis, caregiver female gender). These findings identify emotional empathy as a potentially important vulnerability in caregivers of persons with neurodegenerative diseases. One implication of these findings is that, when facing a chronic stressor such as a caregiving, caregivers who are higher in emotional empathy may benefit from strategies that create emotional distance in response to their loved ones’ suffering.

Advisor: Levenson, Robert W