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Leveraging Natural Variation in Yeast to Understand Susceptibility Differences in Parkinson’s Disease
Full text linkParkinson’s Disease (PD) is a neurodegenerative disorder that causes countless suffering around the world. Both forms, familial and sporadic, have been associated with the misfolding and cytotoxicity of α-synuclein, an otherwise non-pathogenic protein suspected to have various roles in the normal maintenance of the central nervous system. Model organisms have emerged as great vessels to uncover the cellular and molecular mechanisms that shape α-syn biology, and great strides have been made to understand it. Yet, it is still unclear why some individuals are affected by α-syn toxicity, while others not so much. Since it’s extremely complicated to study and probe natural variation in human populations, we turn to the friendly yeast Saccharomyces cerevisiae to understand this phenomenon. We identify wild populations of yeast with increased resistance or susceptibility to α-syn cytotoxicity, and we leverage this natural variation to further understand α-syn resistance. By employing transcriptomic and genetic mapping via whole genome sequencing approaches, we are able to narrow down candidate genes for resistance. Moreover, some of these candidate genes have also been functionally validated as mediators of α-syn resistance in yeast and opened new avenues of research in other model organisms. Finally, we employ genetic engineering and genome modification techniques to create a new panel of strains that can be used in the future for further dissecting α-syn resistance or other similar phenotypes for these strains. Our results highlight the importance of using natural variation to dissect complex traits, as we are able to pinpoint genes that are only causal for a specific genetic background, underlining the real complexity behind any resistance phenotype. Beyond our findings relevant to the PD-research field, we showcase how similar methods could be used to leverage natural variation in model organisms for other human diseases or complex traits
Effects of Cholesterol Concentration on Liposome and Proteoliposome Behavior
Full text linkCholesterol is crucial in modulating the behavior and characteristics of biological membranes, liposomes, and proteoliposomes, for instance in drug delivery applications. Cholesterol regulates membrane stability by influencing lipid density, phase separation, and protein-membrane interactions. In planar bilayers, cholesterol enhances membrane thickness, reduces permeability, and promotes lipid ordering, adding rigidity and fluidity. Cholesterol also modulates membrane curvature in curved bilayers and vesicles, stabilizing low-curvature regions. In this work, all-atom molecular dynamics (MD) simulations were employed to examine how varying cholesterol concentrations influence the structure and dynamics of membranes, focusing on planar and curved geometries. Bilayers with cholesterol molar ratios of 0%, 10%, 20%, 30%, 40%, and 50% were simulated, analyzing parameters such as area per lipid (APL), membrane thickness, leaflet interdigitation, and segmental order parameters (SCD). Increasing cholesterol concentration in planar bilayers decreased APL, while increasing membrane thickness and lipid ordering, consistent with cholesterol condensing effect. In curved bilayers, cholesterol induced an expansion effect, particularly in the inner leaflet, with APL increasing as cholesterol concentration rose. SCD profiles indicated that cholesterol enhanced tail ordering up to 40%, after which the effect plateaued, suggesting structural saturation or packing frustration. These findings emphasize the need to consider curvature in liposomal drug delivery design. Additionally, the impact of cholesteryl hemisuccinate (CHS) on the conformational dynamics of mGluR2 involved in neurotransmitter signaling, was studied. CHS concentrations modulated mGluR2 structural stability and conformational behavior, particularly in transmembrane helices, affecting receptor dynamics in both active and inactive states. Optimal CHS concentrations stabilized mGluR2, balancing rigidity and flexibility, with implications for receptor-targeted drug design. This study provides molecular insights into cholesterol role in regulating membrane behavior, lipid-protein interactions, and GPCR function, facilitating the rational design of liposomal systems for therapeutic applications
Atomic Level Characterization for the Transport Cycle Conformational Pathways of Multidrug Resistance Protein 1 (MRP1)
Full text linkThe multidrug resistance-associated protein 1 (MRP1/ABCC1) is an ATP-binding cassette (ABC) transporter that mediates the cellular efflux of endogenous and xenobiotic substrates, including therapeutic drugs. Its overexpression is a major contributor to multidrug resistance in cancer, which tends to result in negative clinical results. Even with considerable progress made in structural biology, the intricate details of how membrane lipid composition affects the conformational changes and functional switches of MRP1 still lack explanation.
This thesis employs long-timescale, all-atom molecular dynamics (MD) simulations to study the influence of various lipids on MRP1 lipid bilayer environments. Both inward-facing and outward-facing conformations of MRP1 were simulated using physiologically relevant POPC and POPE bilayers containing cholesterol. Attention was directed to key structural features, including domain movements, RMSD stability, salt bridge persistence, and hydrogen bonds.
The results demonstrate that bilayer composition strongly impacts the structural flexibility of MRP1. POPE-rich and cholesterol-containing bilayers have been demonstrated to strengthen stabilizing, electrostatic, and nucleotide-binding domain (NBD) compaction, such as ASP1453–LYS1332 and GLU1064–LYS1343, particularly in the inward-facing state. Conversely, POPC-rich membranes exhibit greater freedom of movement and weaker electrostatic interactions. In the post-hydrolysis outward-facing state, cholesterol destabilizes NBD by salt bridge severing and increasing inter-NBD distance, which aligns with reset-ready conformation. A salt bridge ASP749 and ARG1327 was found to undergo dissociation post ATP hydrolysis in all systems, acting as a structural switch onto the NBD opening.
These changes highlight the dynamic nature of the lateral pressure profile that the lipid environment exerts as an allosteric switch on MRP1 function. The results elucidate how specific lipids and membrane components dictate the function of the transporter, thus allowing for targeted approaches to modulate ABC transporter activity through membrane lipid manipulation. Such approaches may aid in formulating new therapeutic strategies to combat drug resistance in cancer and other diseases associated with proliferative ABC transporters
Automation of Vulnerability and Patch Management: Information Extraction, Association, and Optimization
Full text linkVulnerability and patch management is an integral part of a robust cybersecurity program, yet it grows increasingly complex due to the sheer amount of data that must be analyzed. Particularly in Operational Technology (OT) environments, analysis must be done manually because of the lack of automated solutions. Additionally, there are many steps in this process, from the initial discovery of the vulnerability to the implementation of its remediation, and each step in the process requires different data in order to be performed effectively. In this work, we provide approaches and strategies to assist operators in industrial or OT environments throughout the vulnerability management cycle. Security advisories provide key information about mitigation strategies, or actions that can be taken when a patch is unavailable or cannot be installed. Details of these strategies are not shared in public vulnerability databases and must be found manually. We approach this problem by designing a solution to automatically identify that information within vendor security advisories and retrieve it for operator use. We start with an approach that requires domain-specific knowledge of certain frequently-seen reference websites. Next, an approach that can work on an arbitrary website but relies on certain keywords. Finally, an approach that uses Natural Language Processing (NLP) methods and does not require specific knowledge or keywords. Each of these approaches is more general than its predecessor; we demonstrate high accuracy for all approaches. Advisories also often contain details of affected products in non-standard or natural language formats. While this information can be easily understood when read by an operator, the non-standard format acts as a barrier to effective automation. We provide an approach for the first step in this process: identifying vendors in security advisories and mapping them to a standard framework for representing digital assets and software products. We evaluate five established string similarity algorithms, plus one of our own design that combines string similarity and information theory, on the task of mapping vendors to their corresponding entries in the Common Platform Enumeration (CPE) repository. Our results show that our proposed metric outperforms all others. Due to the constraints on time, finances, and personnel for organizations, Large Language Models (LLMs) may seem like attractive opportunities for security operators to speed up information gathering; however, it is still not clear whether LLMs can handle vulnerability management tasks well. To answer this question, we perform an empirical study of LLMs’ ability to provide consistent, accurate information about vulnerabilities in order to guide organizations in their adoption of LLMs. We observe poor performance for all models tested, suggesting that these models are not well-suited to the consistent retrieval of accurate vulnerability information. Finally, once vulnerabilities have been identified and any additional information has been obtained, operators must decide which remediation actions to implement based on their available resources. This already-complex problem becomes even more so when we consider that a vulnerability may have multiple avenues for remediation. We formulate this scenario as two knapsack problems and provide solutions, which we then compare against several existing strategies for vulnerability prioritization seen in real operational environments
Rotation Errors Due to Field Quantization for Simultaneously Driven Atoms
Full text linkIf we want to physically implement qubits by using two level atoms within a cavity, then certain single-qubit gates (such as the X-gate) can be performed by bathing the atoms in an electromagnetic field from a laser. If the average photon count n̄ of the field greatly exceeds the number of N qubits, then the slight fluctuations of the field\u27s phase and amplitude are mostly negligible. However, such a strong field might require more energy than what is desirable for the setup. If a weaker field is used in which phase and amplitude fluctuations might be noticeable, then the gate implementation may be imperfect. This error means that the actual qubit state is different from what we would expect from a state created by a perfectly classical field. In this paper, we compare three different techniques to show how this error scales as 1/n̄ for any preferred system of X-gates or Rx(θ)-gates on N atoms. We use a semiclassical treatment of a fluctuating field in addition to the Tavis-Cummings model and second order perturbation. The second order perturbation gives excellent results for when the initial atomic state is in a Cat State or an average of all states. From this, we find equations for maximum and average gate errors, respectively. We show how this error can be reduced by squeezing the coherent source as well as adjusting the interaction time between the field and atoms to be different from what is classically expected
Investigating Evolution Through the Lens of AI-driven Protein Exploration and Phylogenetic Modeling
No full textRecent advances in computational biology, artificial intelligence, and sequencing technologies have enabled new perspectives for addressing longstanding questions in evolutionary biology. Increased computational power has made large-scale simulations feasible for investigating diverse aspects of evolutionary and phylogenetic modeling. Similarly, deep learning algorithms now allow for the prediction of reasonably accurate tertiary protein structures, unlocking the potential for investigating diversity and evolution of protein structure across a broad range of organisms. This thesis presents two studies that target different aspects of evolutionary inference from unique perspectives. Yet, the share an overarching goal of presenting new perspectives on the evolutionary basis of biodiversity from comparative analyses of protein and trait evolution.
Viewing molecular evolution through the lens of protein structural diversity, the second chapter leverages deep learning models to examine olfactory receptor (OR) evolution in long-horn beetles. That is, we sought to investigate the diversity and structure of proteins encoded within recently-sequenced insect genomes using machine learning. Using two recently developed deep learning models, RoseTTAFold and AlphaFold, we predicted the tertiary structure of OR proteins in two Cerambycid species. We then investigated diversity among these OR proteins and analyzed the relationship between structural and sequence-level evolutionary distances. These findings highlight the promise of deep learning models for gaining meaningful biological insights, particularly in systems where experimental resources are limited.
The third chapter addresses evolutionary biology at a broader comparative scale, evaluating how phylogenetic assumptions influence evolutionary conclusions using statistical regression approaches. Here, we focused on a core question of comparative biology: understanding how phylogenetic modeling choices influence statistical conclusions about trait evolution. Through large-scale simulation studies and analysis of an empirical dataset containing traits associated with longevity, we assessed the sensitivity of phylogenetic regression to tree choice. Across these analyses, tree selection emerged as an important factor influencing the behavior of phylogenetic regression. The results show that an incorrect tree choice, that does not accurately represent the evolutionary history of a trait, can lead to significantly elevated false positive rates. This holds particularly true as the amount of data (species and traits) included in the analysis increases. These findings underscore the importance of thoughtful tree selection across studies in comparative biology. Together, these chapters highlight the diversity of questions and scales encompassed by evolutionary biology and contribute to a broader understanding of the field
Experiences of Black Senior Housing Officers at Predominantly White Institutions in the South
Full text linkThis study examines the lived experiences of Black Senior Housing Officers (SHOs) at predominantly white institutions (PWIs) in the Southern United States. This narrative inquiry study interviewed nine Black SHOs who worked at Southern PWIs. The findings of this study are that participants emphasized that racism remains a significant and present concern at their institutions as informed by Critical Race Theory (CRT). One participant stressed the importance of Black professionals fully understanding the historical context of the South when working in higher education, noting that this knowledge was critical for survival and success. Many participants also described how effective mentorship helped them navigate institutional challenges, resist burnout, and maintain their sense of purpose as Black housing professionals in predominantly white environments. Additionally, participants expressed their passion for fostering community and enhancing the residential experience in campus environments, which propelled them through various professional levels, including hall director, assistant director, and associate director, ultimately culminating in roles as executive directors of housing. Participants felt a sense of accomplishment, and their work matters as a key reason many of them remain in the field. This study also reveals that Black SHOs likewise turn to professional associations to find solidarity at the senior level to combat the feeling of onlyness. The results from this study magnify the importance of SEAHO and other regional housing institutions offering affinity groups and belonging initiatives to continue providing spaces for Black SHOs to be their true, authentic selves. SEAHO operates outside of state politics, which positions it to fill the gap where state institutions cannot do so due to anti-DEI legislation. A forthcoming research study emerging from this study will investigate the experiences of Black SHOs at Historically Black Colleges and Universities (HBCUs)
#Girls Gone Viral: Girlification Trends and the Digital Postfeminist Sensibility
Full text linkThis thesis provides a critical analysis of viral girlification trends on TikTok to bolster understanding of the rhetoric of popular feminism in the emerging digital landscape. Grounded in feminist cultural theory, this thesis posits that women’s digital engagement influences their notions of self-actualization, their avenues for resisting sexist ideals, and ultimately, their political mobilization. Extending scholarship on postfeminism, I offer two unique but co-constructive features of the postfeminist sensibility: post-irony and the confession paradigm. The first chapter analyzes the “girl dinner” trend as a site of post-ironic discourse. Characterized by ambiguity and ambivalence, post-ironic discourse muddles the line between sincerity and irony to the extent that no distinctive feminist sentiment can be reliably discerned. The second chapter examines on the “girl math” trend with a focus on confession, discipline, and humiliation. I argue that the postfeminist sensibility has developed a confession paradigm that promises women empowerment through self-disclosure but ultimately results in feminine humiliation and further discipline. In an effort to cultivate digital visibility in an economy of popular feminism, these trends have adopted both post-irony and confession as central discursive tools. In doing so, the culture of the postfeminist sensibility has persistently evolved and with it, the ways in which women conceptualize feminist engagement
Arkansas Corn and Grain Sorghum Research Studies 2024
Full text linkThe 2024 edition of the Arkansas Corn and Grain Sorghum Research Studies Series includes research results on topics pertaining to corn and grain sorghum production, including weed, disease, nematode, and insect management; economics; irrigation; agronomics; soil fertility; drone use; and research verification program results.
Our objective is to capture and broadly distribute the results of research projects funded by the Arkansas Corn and Grain Sorghum Board. The intended audience includes producers and their advisors, current investigators, and future researchers. The Series serves as a citable archive of research results.
The reports inform and guide our long-term recommendations, but should not be taken solely as our recommended practices. Some reports may appear in other University of Arkansas System Division of Agriculture’s Arkansas Agricultural Experiment Station publications. This duplication results from the overlap between disciplines and our effort to broadly inform Arkansas corn and grain sorghum producers of the research conducted with funds from the Corn and Grain Sorghum Check-off Program. This publication may also incorporate research partially funded by industry, federal, and state agencies.
The use of products and trade names in any of the research reports does not constitute a guarantee or warranty of the products named and does not signify that these products are endorsed or approved to the exclusion of comparable products. All authors are either current or former faculty, staff, or students of the University of Arkansas System Division of Agriculture or scientists with the United States Department of Agriculture, Agricultural Research Service.
We extend thanks to the staff at the state and county extension offices and the research centers and stations, producers and cooperators, and industry personnel who assisted with the planning and execution of the programs
Licensure as Pathway, Not Barrier
Full text linkThe legal profession knows it has an access to justice crisis. One side lacks a lawyer in approximately three-quarters of the twenty million civil cases filed across state courts every year. Against that concerning backdrop is how we license attorneys. The most common method is the written bar exam. But that exam bears little resemblance to the practice of law, produces racially disparate results, and is shockingly expensive for law graduates to prepare for and take. Its opaque scoring practices alongside its rare administration—offered just twice per year—strengthens the idea that the modern bar exam operates more as a barrier than a measure of competence to practice law. But no one has suggested connecting a public service pathway to a state’s pre-existing “civil-Gideon.” Civil Gideon “refers to the idea that people who are unable to afford lawyers in legal matters involving basic human needs - such as shelter, sustenance, safety, health, and child custody - should have access to a lawyer at no charge.” This Article argues that Connecticut should pair its right to counsel eviction defense statute with a supervised practice pathway to attorney licensure. The Article proceeds in three parts. First, it briefly explains the bar exam and its history. Second, it considers the state of the legal profession with a particular focus on Connecticut and its efforts to address and improve access to justice. Finally, the piece argues for pairing CT-RTC with a supervised practice pathway to attorney licensure