Housing Affordability and Instability

This snapshot looked at housing affordability and instability in the Houston area. Residents were asked how difficult it was in the past 12 months to afford housing costs, and if certain factors such as increasing rents or utility bills, contributed to the difficulty they experienced. Residents were also asked whether the challenges they faced had forced them to move in the past year

Valentina V. for harp, immersive electronics, and lighting

Valentina V. is an extended work for solo harp, immersive electroacoustic sound, and lighting, commissioned by Hope Cowan through a generous grant from the American Harp Society. The piece is inspired by my own musicological research into the medieval song “La harpe de melodie” and the provenance of the illuminated manuscript containing the song’s renowned pictographic musical score. Valentina V. is conceived as a tragic monodrama in which the solo harpist adopts the persona of 14th-century noblewoman and virtuoso harpist Valentina Visconti (1371–1408). Research suggests that the medieval song “La harpe de melodie” by Jacob de Senleches — famous for its illuminated pictographic score — was likely composed as a vehicle to showcase Valentina’s prodigious musical talents. Married to the brother of the King of France, Valentina was eventually forced into exile after others at the royal court accused her of witchcraft. My piece presents an imagined scene near the end of Valentina’s life in which she is confined to her chamber with only her precious harp to confide in. Cast in four movements played without pause, Valentina V. unfolds fantasia-like as its protagonist processes her grief through playing her beloved harp. Compositional materials are partly derived from “La harpe de melodie,” which is performed in full as the work’s penultimate movement. At other points in the piece, the song emerges in a fragmented, distorted, or embellished form, representing Valentina’s reminiscences as they are filtered through her fractured psyche

Characteristics and Profiles of Pre-K Classrooms and Teachers in the Houston Region

The Kinder Institute for Urban Research’s Houston Education Research Consortium (HERC) examined the characteristics of public pre-K teachers and classrooms in school districts in the Houston region in 2021-22 to better understand how well the programs align with research-based indicators that have been shown to produce positive student outcomes. This research examined characteristics of pre-K classrooms and teachers and analyzed them to identify and describe common profiles of classrooms and teachers

Delivery of Large Gene Circuits In vivo Using an Engineered Baculovirus Vector for Multifactorial Control of Gene Expression

Many of the viral vectors used for gene therapy are limited by the cargo size they can deliver into cells in tissue. As a result, most therapies being actively considered today tend to consist of monomodal expression of one or two genes. While this modality is undoubtedly effective for many applications, there remains advantages to being able to deliver more genetic cargo. A viral vector with an increased cargo capacity could allow room not only for more and larger therapeutic genes, but also regulatory elements that permit complex, multifactorial regulation of therapeutic gene expression. Here we use the insect-derived baculovirus capable of packaging and delivering >100 kb of transgene DNA as a vector for complex gene circuits that regulate and enhance in vivo gene therapy. Baculovirus has many advantages over other vectors: the ability to transduce a broad spectrum of mammalian cells, a large packaging capacity, no replication in mammalian cells, and a low toxicity in vivo. However, while baculovirus has been used as a gene therapy vector previously, its potential has been limited by its transient expression, as well as its susceptibility to inactivation by the complement system. We then implemented a hierarchical cloning scheme for the rapid generation and prototyping of baculovirus vectors containing up to 10 different expression units. We then address several shortcomings of the baculovirus by pseudo-typing the AcMNPV baculovirus with two proteins, the Vesticular stromatitis virus protein G and a fusion protein consisting of several complement regulatory domains. This engineered vector has increased transduction and persistence in mouse liver, muscle, and brain tissue. To our knowledge, this is the first time systemic delivery of baculovirus has been shown to be an effective delivery route. Using this engineered virus, we screened a library of 24 variations of a tamoxifen inducible circuit in order to select the architecture with the highest dynamic range, up to a 67-fold increase over uninduced. Finally, we demonstrate two orthogonal small molecule inducible systems (grazoprevir and tamoxifen) delivered by baculovirus in vivo, both as separate viruses and as one complete circuit. Our findings demonstrate the usefulness of complex regulation for the gene therapy field, as well as the utility of the baculovirus as a therapeutic vector

Treadmill-IO: a novel multi-modal VR tool for studying learning of complex rodent behaviors

Traditionally, spatial navigation in animal models in virtual reality (VR) settings has been studied primarily using visual cues. However, few studies have investigated VR navigation in environments promoting interactions between the auditory system and hippocampus. Here I present a novel multi-modal virtual reality system that can be defined by either visual, sound, or both stimuli that are modulated based on the animal’s real-time position. To examine how the hippocampus represents the visual and sound environment, I developed a hippocampus-depend task where animals are trained to lick for a reward on each lap in the reward zone. I report behavioral evidence that mice can learn to navigate in our sound VR task. Similarly, in the visual VR environment, I replaced the sound stimuli with different types of visual stimuli in the same location to preserve the spatial information for both types of VR environments and observed the same result. There has been an increasing volume of research that requires a large amount of resources used on high-throughput animal training in difficult tasks. Evidently, how to make informed decisions early in the training is important to any experimenter so that valuable resources and time are not wasted on animals that are not able to learn. Here I present possible parameters that could differentiate learners from non-learners, namely lick probability, lick selectivity, lick rate, percentage of valid laps, average speed, and lick latency. I observe that learners have a higher lick probability, and low lick latency while maintaining a high percentage of valid laps, on the other hand, non-learners exhibit low lick probability, and high lick latency with a low percentage of valid laps. During the transition of different maze-length environments, learners exhibit an increase in average speed while non-learners maintain or exhibit a decrease in speed. With combined information from these parameters, experimenters can now focus on using resources more efficiently thus contributing to a faster turnover for research

LLMs One-shot Learning from Human Demonstration on Inductive Reasoning Tasks

Large Language Models (LLMs) have shown impressive proficiency across a range of natural language tasks. However, recent research has highlighted their limitations in inductive reasoning, a key aspect of human cognitive ability. While chain-of-thought demonstration have improved LLM performance on various tasks, there has been limited exploration into their effectiveness for inductive reasoning tasks specifically. Since inductive reasoning rules can vary widely, providing a tailored demonstration for every question is impractical. This study aims to investigate how LLMs perform with minimal demonstration and whether they can generalize in different regimes. To support this research, we design a programmable dataset with inputs of varying lengths and complexities to test LLMs' generalizability. Our findings suggest that a single human demonstration can enable LLMs to achieve perfect in-distribution generalization performance in some tasks. LLMs sometimes exhibit comparable or even better out-of-distribution generalization performance relative to their in-distribution performance

Sequence-based and structure-based methods for studying the adaptive immune response

The adaptive immune system comprises various biological mechanisms that, in unison, protect an organism against various threats, such as pathogens, viral infections, and tumor cells. One of such mechanisms involves the binding of intracellular protein fragments called peptides to class-I Major Histocompability Complexes (MHCs). The formed peptide-MHC (pMHC) complex is presented to the surface of the cell, where it interacts with the T-cell receptor, an interaction that can elicit an immune response. Knowing which peptides bind to MHCs, which peptides are presented to the surface of the cell, and which peptides elicit an immune response is crucial for successful clinical applications and therapies. Due to the advent of mass spectrometry resulting in high-throughput generation of amino acid sequence-based pMHC binding data, amino acid sequence-based Machine Learning (ML) approaches have dominated the field, showing immense potential. At the same time however, it is known that the pMHC interaction is characterized by a strong structural component that is shown to be extremely important in fully explaining pMHC binding and peptide immunogenicity. This thesis presents methodologies that attend to both the amino acid sequence component and the structural component of the pMHC interaction. Focusing on the sequence component first, we present TLStab and TLImm, two ML-based tools that predict peptide kinetic stability and peptide immunogenicity respectively. Developed through adopting transfer learning methodologies, TLStab and TLImm outperform state-of-the-art approaches in their respective tasks. Next, focusing on the structural component, we present APE-Gen2.0, a new pMHC structural modeling tool. APE-Gen2.0 outperforms other approaches in the literature in regard to modeling accuracy. It also expands the pMHC structural modeling repertoire to peptides exhibiting post-translational modifications, as well as peptides that assume non-canonical geometries in the MHC binding cleft. Finally, we present RankMHC, a novel, Learning to Rank-based pMHC binding mode identification tool. RankMHC outperforms both classical protein-ligand scoring functions and pMHC-specific scoring functions in predicting the most representative peptide conformation among an ensemble of conformations. Overall, acknowledging the potential of both pMHC sequence and pMHC structure information, our work expands on both areas, through novel and effective computational contributions

How African Immigrants Interpret The Connection Between Their Religion and Health.

Religion can positively and negatively influence individuals’ health behaviors. While religion can deter risky behaviors like alcohol abuse, it can sometimes discourage seeking healthcare. Religion has primarily been presented as a barrier to seeking healthcare. Additionally, African immigrants in the United States of America have received less coverage in research about their religion and health despite being part of a demographic group (Blacks) that has developed a mistrust of the medical health system in the U.S. due to historical treatment. This thesis examines the health experiences of African immigrants in Houston, Texas, focusing on how they interpret the connection between their religion and physical health. It also explores the perceived role that religious congregations play in the health experiences of African immigrants. Drawing on in-depth interviews of 37 Christian African immigrants living in Houston, I find that religion acts as a pathway to healthy living and seeking healthcare among African immigrants. Thus, religion provides a framework for a positive perspective on medical healthcare. By focusing on African immigrants, this study serves as a case for understanding the health experience and behaviors of highly educated and religious populations

Neutron scattering studies of Sr(Co1−xNix)2As2, FeSn, CsV3Sb5, and YbMnBi2

In this thesis, we present several neutron scattering investigations on the complex magnetic and electronic properties of a series of quantum materials, including helical order in Sr(Co1-xNix)2As2, spin excitations in FeSn and CoSn, electron-phonon coupling in charge-density-wave state of CsV3Sb5, vortex lattice in Ta doped CsV3Sb5, and spin chirality in YbMnBi2. Firstly, we investigate magnetic ordering and spin fluctuations in Sr(Co1-xNix)2As2, a quasi-two-dimensional planar magnet. Neutron scattering studies reveal a c-axis incommensurate helical magnetic structure in Sr(Co1-xNix)2As2, with enhanced quasi-2D ferromagnetic spin fluctuations induced by Ni doping. Band structure calculations suggest that this helical order arises from Ruderman-Kittel-Kasuya-Yosida (RKKY) interactions mediated by itinerant electrons, offering insight into the quantum order-by-disorder mechanism near a quantum critical point. Next, we examine spin excitations in the metallic kagome lattice materials FeSn and CoSn. In these systems, destructive quantum interference of electronic hopping paths produces nearly localized electrons, resulting in flat electronic bands. Our neutron scattering measurements uncover well-defined spin waves in FeSn and paramagnetic scattering in CoSn, highlighting the delicate balance between geometric frustration and magnetic order in kagome systems. Furthermore, we observe anomalous non-dispersive excitations, attributed to the scattering from hydrocarbon contamination. We also investigate the electron-phonon coupling in CsV3Sb5, a kagome lattice material exhibiting intertwined CDW and superconductivity. Neutron scattering experiments demonstrate that the CDW in CsV3Sb5 is associated with a static lattice distortion and a sudden hardening of a longitudinal optical phonon mode. This finding underscores the critical role of wave vector-dependent electron-phonon interactions in the CDW order, contributing to our understanding of its coupling with superconductivity in kagome metals. The fourth study focuses on the superconductivity in Ta-doped CsV3Sb5, which exhibits enhanced superconductivity upon suppression of CDW order. Through Small-Angle Neutron Scattering (SANS), we probe the vortex lattice structure and its evolution in the superconducting state of Cs(V0.86Ta0.14)3Sb5. Our results show that the vortex lattice exhibits a strikingly conventional behavior, including a triangular symmetry, conventional 2e pairing, and a field dependent scattering intensity that follows a London model. Our results suggest that optimal bulk superconductivity in Cs(V0.86Ta0.14)3Sb5 arises from a conventional Bardeen-Cooper-Schrieffer electron-lattice coupling. Finally, we investigate the giant anomalous Nernst effect (ANE) and anomalous Hall effect (AHE) in the canted antiferromagnet YbMnBi2. The ab-plane spin canting in YbMnBi2 is believed to break time-reversal symmetry, generating a non-zero Berry curvature that gives rise to the giant ANE and AHE. However, direct evidence for this mechanism has remained elusive, as earlier unpolarized neutron measurements excluded significant moment canting. By leveraging the unique advantages of polarized neutron scattering, which can differentiate magnetic scattering from nuclear scattering, we have uncovered clear evidence of spin chirality persisting at temperatures well above room temperature. Additionally, further neutron scattering measurements have revealed inversion-symmetry breaking and anisotropic spin fluctuations, indicating the presence of Dzyaloshinsky-Moriya interactions that likely drive the observed spin chirality, which in turn underlies the ANE and AHE. Our findings provide a detailed mechanism that directly explains the origins of the giant ANE and AHE in YbMnBi2. Overall, the combination of these works advances the understanding of quantum materials by revealing new insights into the magnetic, electronic, and lattice dynamics of these complex systems. The results presented herein pave the way for future studies on quantum magnetism, unconventional superconductivity, and the development of new materials with novel electronic and magnetic properties

Copper-Mediated Approaches to Selective Modification of Peptides and Proteins

Peptides and proteins have long played crucial roles in diverse applications, including drug development, biomaterials, and diagnostic imaging. However, recent advances in biosynthetic engineering, synthetic methodology, combinatorial screening approaches, and analytical methods have allowed more routine access to diverse peptidic structures that diverge markedly from natural structures, incorporating unnatural amino acids or significantly altering the canonical polypeptide structure. Indeed, the very definition of “peptide” is less clear today, with blurred lines separating peptides from peptoids, peptidomimetics, stapled structures, foldamers, hybrid conjugates, and other structures. Peptides and proteins play increasing roles in drug development, and non-canonical modification is often employed as a tool to improve drug properties, including cellular uptake, in vivo stability, and selective localization. This thesis focuses on the development of selective modification of natural peptides and proteins by transition-metal catalysis. The first chapter provides a summary of important approaches to side chain modification methods developed in the past two decades, focusing on fundamentally enabling mechanistic, selectivity, or reactivity ideas. The second chapter reviews the synthesis and transformations of sulfines, a class of S-oxides of thiocarbonyl compounds which are widely studied in synthetic chemistry but rarely used in peptide stapling or protein bioconjugation. Development of selective peptide and protein modification methodologies is discussed in chapters 3-5. Chapter 3 describes a straightforward means of late-stage one-step oxidation of methionine residues within polypeptides to afford NH-sulfoximines. The use of an ex situ gaseous chlorosulfine reagent for peptide macrocyclization and protein bioconjugation is shown in chapter 4. Furthermore, chapter 5 highlights a copper-catalyzed cross-coupling selective for pyroglutamate post-translational modifications (PTMs) that is directed by peptide backbone amides, which serves as a complementary strategy for the histidine-directed pyroglutamate arylation chemistry reported previously. Based on the rhodium(II)-metallocarbene catalysis developed in the Ball group, the application of rhodium proximity labelling in cell lysates for identifying new drug-protein interactions was described in chapter 6. Taken together, these contributions expand the toolbox for peptide and protein modification, and could provide new opportunities in several areas of chemical biology, such as inhibitor design, cellular imaging, and PTM profiling, etc