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ACUTE REGULATION OF MITOCHONDRIAL ELECTRON TRANSPORT CHAIN PROTEINS: REVEALING THE RELATIONSHIP BETWEEN DYNAMIC PROTEIN ORGANIZATION, PERMEABILITY TRANSITION AND CHRONIC ISCHEMIA-REPERFUSION INJURY
No full textSkeletal muscle and heart have the essential task of contracting to allow for movement and blood pumping for organ perfusion. Mitochondria provide the ATP necessary for cardiac and skeletal muscle contraction by combining ADP and Pi at ATP synthase, or Complex V (CV), using the energy of the electrochemical H+ gradient generated during the movement of electrons down the electron transport chain (ETC). Several studies have shown that ETC protein complexes can interact forming structures called supercomplexes, which have been considered strong candidates in promoting metabolic advantage through the optimization of ATP production. Genetically modified murine models and long-term interventions, such as exercise and restrictive diets, have been connected to the modulation of supercomplex formation. However, the ability of mitochondrial proteins to acutely respond to intracellular signals, dynamically altering ETC protein organization, remains poorly understood. Increases in intracellular Ca2+ result in its mitochondrial uptake, with physiological levels activating mitochondrial ATP production and supraphysiological levels leading to a precipitous loss of function due to the opening of the mitochondrial permeability transition pore (MPTP). Although the deleterious effects of MPTP opening have been well described and implicated in the mechanisms of ischemia-reperfusion injury, the exact molecular identity and structural-temporal mechanism of pore formation remain elusive. We found that acute Ca2+ overload rapidly, in seconds, increased CV dimer (CV2) formation, in concert with mitochondrial swelling, loss of membrane potential, and reduced oxygen consumption rates in isolated mitochondria from murine heart and skeletal muscle. These findings suggest that CV2 plays a critical role in MPTP formation. In addition, inhibition of Cyclophilin D (which modulates MPTP opening) with cyclosporin A prevented CV2 formation and mitochondrial swelling. However, blocking CV2 formation with the Fo ATP synthase inhibitor oligomycin did not prevent mitochondrial swelling, suggesting that other proteins, such as ANT (Adenine Nucleotide Translocator), are also involved in MPTP opening. Inhibiting ANT in its matrix-facing conformation with bongkrekic acid reduced CV2 formation and swelling, while locking ANT in its cytosolic-facing conformation with carboxyatractyloside enhanced CV2 formation and mitochondrial rupture. These findings indicate that both CV2 and ANT are essential for MPTP formation, and their combined activity appears critical for permeability transition. Moreover, we were able to uncover that mitochondria can rapidly change their protein organization in response to acute intracellular signals, with these modifications occurring within seconds. This rapid adaptation highlights the dynamic nature of mitochondrial protein assembly in response to intracellular signals, enables investigations to determine if altered responsiveness of protein reorganization to these signals impairs function, and may have significant implications for therapeutic strategies to improve mitochondrial function and prevent MPTP-related ischemia-reperfusion injury. Innate mitochondrial protein organization and mitochondrial function were investigated in Sickle Cell Disease (SCD), a condition associated with chronic ischemia-reperfusion injury. Our results showed that, while SCD mice had similar skeletal muscle mitochondrial oxygen consumption rates, reactive oxygen species (ROS) production rates, and citrate synthase activity as controls, Complex IV (CIV) expression and supercomplex formation tended lower in SCD. SCD mitochondria were also more sensitive to calcium and prone to swelling, an effect that was alleviated by cyclosporin A, an MPTP inhibitor. These findings suggest that alterations in electron transport chain proteins may precede overt mitochondrial dysfunction in SCD skeletal muscle, with MPTP potentially playing a role in SCD pathology. Overall, my PhD research underscores the importance of fine-tuning acute mitochondrial protein organization in cellular homeostasis, bringing to light previously unrecognized mechanisms of pathology. Moreover, these investigations highlight new opportunities for drug development and non-invasive biomarkers that could improve the management of SCD
Hacia un judaísmo heterodoxo: Re/escrituras de Esther Seligson y Myriam Moscona
No full textIn Orthodox Judaism, the production of Biblical commentary is traditionally reserved for rabbis who usually provide varying textual readings. It is rare, however, to encounter literary works whose themes and references derive from rabbinic interpretative practice while, at the same time, exploring other motifs. In Hacia un judaísmo heterodoxo: Re/escrituras de Esther Seligson y Myriam Moscona I explore the ways in which Esther Seligson (1941-2010) and Myriam Moscona (1955), two Jewish Mexican writers, challenge the limits imposed by tradition as well as the conventions of rabbinic scriptural interpretation. Through close readings of their midrashim (reinterpretations of Biblical myths and legends), autobiographical writings, and their heterodox perspectives on mainstream religious thought, I propose a novel approach to understanding sacred scripture and Jewish tradition. To that effect, my research combines readings of canonical works of Jewish religious literature, such as the Babylonian Talmud and Kabbalistic texts, with contemporary Latin American and Jewish scholarship. Thus, by highlighting these references in their works, this study demonstrates how their writings constitute original Biblical commentaries by challenging and questioning established approaches to text and tradition. I show how Esther Seligson and Myriam Moscona inscribe themselves into the very tradition they challenge. Through this analysis, my study contributes to ongoing debates concerning literary traditions as well as the approaches to the hyphened identity of Jewish Latin American writers
Creating a Directory to Build Maryland’s Outdoor Recreational Businesses
No full textFinal report for HBUS 205: Capstone in Interdisciplinary Business (Spring 2025). University of Maryland, College ParkThis report outlines a strategic initiative by students in the Interdisciplinary Business Honors Capstone Program to support the Maryland Department of Natural Resources’ Office of Outdoor Recreation (OOR) in creating a statewide directory of outdoor recreation businesses. The directory aims to expand visibility, accessibility, and economic development for Maryland’s diverse outdoor recreation sector. Through literature review, benchmarking of existing directories in other states, and data analysis, the team developed a framework to organize business information, improve user experience, and ensure long-term accuracy. Key recommendations include implementing a dynamic, Excel-integrated online platform supported by community input and maintenance tools. This directory will help OOR identify underserved areas, allocate funding more effectively, and promote equitable access to outdoor recreation across Maryland.Marylan
SIMULATED REAL-LIFE TASKS AS A TOOL TO INVESTIGATE THE EXTRAPOLATION INFERENCE OF LANGUAGE ASSESSMENTS FOR PROFESSIONAL PURPOSES
No full textIn language test validity, the extrapolation inference refers to test scores being representative of the target linguistic performance in the target context of language use. This inference is investigated through criterion-related studies that compare test scores/performance with other external evaluation criteria such as actual samples from the target domain. However, obtaining these samples can be difficult in certain professional fields like the medical one. In these cases, simulated real-life tasks could be a suitable alternative. Following the argument-based approach to test validity (Chapelle et al., 2008), this study used a simulated real-life task specifically designed for this project to examine the extrapolation inference of the medical Spanish speaking section of the CanopyCredential exam—a language assessment for the medical domain. The simulated task represents a doctor-patient interaction, and was developed employing the theoretical frameworks of task-based language teaching (Long, 2015), task-based language assessment (Norris, 2016), and the language proficiency interview (Ross, 2017). The medical Spanish speaking section of the CanopyCredential exam measures examinees’ medical Spanish speaking ability to communicate with Spanish speaking patients in the U.S. medical workplace.
Upon self-assessing their medical Spanish listening and speaking ability, participants (N = 82) completed the exam and the simulated task in a counterbalanced order, within two weeks from each other. Their performance on each instrument was rated using linguistic-criteria rubrics. The many-facet Rasch model, ordinal regression analyses, and Spearman’s correlation were used to examine the appropriateness of the simulated task as external evaluation criterion, and the extrapolation inference of the medical Spanish speaking section of the exam.
The results indicated that the simulated task was a suitable external evaluation criterion. Furthermore, significant associations were found between participants’ scores in the exam and (1) their scores in the simulated task, (2) the linguistic characteristics of their production in the simulated task, and (3) their self-assessment of medical Spanish listening and speaking ability. This suggests that simulated tasks can be an appropriate instrument to examine the extrapolation inference of language assessments for professional purposes, and provide support for the extrapolation inference of the medical Spanish speaking section of the CanopyCredential exam
THE NUCLEAR OPTION: POLITICS OF THE PAST, WEST GERMAN ENERGY POLICY, AND THE QUEST FOR ENERGY INDEPENDENCE, 1973-1982
No full textThis dissertation explores the role of energy vulnerability in shaping the political landscape of the Federal Republic of Germany (FRG) from the 1973 OPEC oil crisis to the collapse of the Social-Liberal Coalition under Chancellor Helmut Schmidt in 1982. It focuses on the intense national debate over energy policy in the aftermath of the oil crisis, particularly the controversial decision by Schmidt and key ministers, such as Hans Matthöfer, to pursue nuclear energy as a solution to Germany’s dependence on foreign energy. While proponents saw nuclear power as a strategic and modern response to energy insecurity, critics feared its dangers and questioned the democratic implications of such a technocratic policy. The conflict between these two camps became a defining issue in West German politics, sparking protests, public debate, and a broader reckoning with the country’s energy future.The dissertation argues that Schmidt’s commitment to nuclear energy was rooted in a long-standing national concern with energy autonomy, intensified by the 1973 oil shock. Schmidt’s administration believed nuclear energy could secure the FRG’s energy future, stimulate industrial innovation, and provide economic benefits amid fears of recession. Despite fierce opposition from activists and members of his own party, Schmidt pressed forward, ultimately winning short-term policy victories but failing to generate lasting public support. This failure allowed nuclear skepticism to gain ground within the political left, shaping the future platforms of the SPD and the emerging Green Party. By reexamining Schmidt’s pro-nuclear arguments and the resistance they faced, this dissertation sheds new light on the limits of technocratic governance in democratic societies and the enduring challenge of balancing energy policy with public trust. Lastly, my dissertation highlights the important role of the Nazi past in German history and how the politics of remembering this past and democratic institutional concerns echoed throughout the nuclear energy debate
THE EFFECTS OF EROSION ON ARCHAEOLOGICAL SITES ALONG THE SUSQUEHANNA RIVER AT A STUDY AREA IN MUNCY, PENNSYLVANIA
No full textThe effects of erosion along river banks are leading to the loss of Pre-Contact Native American archaeological sites. Studies along the Mississippi River document this process and loss, but after a review of the identified literature, there is no systematic study looking at erosion and archaeological sites along the Susquehanna River near Muncy, Pennsylvania. This thesis asks: How is erosion likely to affect archaeological sites along the Susquehanna River? The thesis focuses on a study area adjacent to the Susquehanna River near Muncy, Pennsylvania. The study area has many documented pre-contact sites and has been predicted to have high and moderate potential for more sites based on the Pennsylvania pre-contact probability model. One of these sites, the Muncy Survey area, is used to show what a site around this area could look like and the type of information that is at risk of being lost. This thesis combines data sets to overlay known archeological sites recorded during a cultural resource inventory of the project area on a predictive soil erosion model to show areas of erosion and understand what sites are at risk. This study is important as it addresses a larger issue of the loss of archaeological sites and demonstrates a workable model for predicting vulnerability to future erosion from flooding of the Susquehanna River. These areas that are subject to erosion are also those with the highest probability of containing archaeological sites based on distance to water, elevation, and soil type, which are common variables for predicting archaeological site location. Without these sites, we lose the ability to understand and appreciate our history and culture
Expanding the Causal Logic Foundations of Human Reliability Analysis
No full textHuman reliability analysis (HRA) seeks to identify opportunities for operator error in complex engineering systems and quantify the probabilities of these errors occurring. Achieving accuracy and realism in HRA is a challenging process due to the lack of validated models and data available to analysts. First, it is necessary to design HRA methods capable of addressing the complexity of human cognition and the wide variety of operational scenarios where human errors are critical. HRA models should capture the multitudes of causal pathways to failure and their probabilistic nature. Second, error probabilities quantified through data-driven methods result in more accurate, traceable estimates; it is important that HRA methods completely and transparently incorporate human reliability data into the error quantification process.
This project develops robust causal logic models with a strong basis in cognitive psychological research that are quantified using human reliability data and engineering literature. This research has produced three literature-substantiated Bayesian network models that characterize human-machine error pathways and the mechanisms through which they occur. The network structures are parameterized with a variety of data to render them capable of quantifying human failure event (HFE) probabilities. Several data resources were synthesized, including nuclear power plant training simulator data, expert knowledge, HRA dependency idioms, and psychological literature. The contextual information in these quantitative resources allowed derivation of conditional probabilities for performance influencing factors (PIFs), human failure mechanisms, and crew failure modes (CFMs). The applicability of these models is demonstrated through a multi-stage validation. The model structures are validated through expert discussions and against pre-analyzed nuclear event narratives from the ATHEANA HRA method, while the quantitative outputs are validated against German nuclear power plant operational experience. Then, the models are holistically evaluated against nuclear power plant simulator data and other established method outputs from the U.S. HRA Empirical Study. Lastly, the models are applied to an external flooding hazard scenario as an extension of the cognitively focused Phoenix HRA method. This work presents a novel application of new and existing HRA data sources to create validated causal models via Bayesian network structures. The resulting models provide a robust technical basis suitable for scenarios beyond those covered in conventional HRA, and are intended for integration into the Phoenix HRA method
Assessing And Understanding Spatiotemporal Variation In Stable Hydrogen And Oxygen Isotope Values Of Maryland’s Rivers And Streams
No full textThis study explores the spatiotemporal variability of stable hydrogen (δ²H) and oxygen (δ¹⁸O) isotope values in Maryland’s rivers and streams during a two-year period (2022-2024), emphasizing the influence of precipitation sources, physiographic features, and hydrological processes. Rivers in western Maryland exhibited lower δ²H and δ¹⁸O values, likely due to long-distance moisture transport and altitude effects. In contrast, eastern rivers and streams displayed higher isotopic compositions, likely influenced by local moisture recycling, higher temperatures, and greater warm-season precipitation inputs. A Local Meteoric Water Line (LMWL) was derived for Maryland as δ²H = 7.84·δ¹⁸O + 12.86 (R² = 0.99), deviating slightly from the Global Meteoric Water Line (GMWL) because of regional climatic influences such as atmospheric vapor recycling, and sub cloud evaporation. Elevation demonstrated a clear isotopic control on river-water isotope values, with a 0.6‰ decrease per 100 m of increase in elevation for δ²H and 0.1‰ per 100 m for δ¹⁸O. Seasonal patterns were also evident, with lower isotopic values during winter due to cold-temperature isotopic fractionation and remote moisture sources and more positive values in summer as a result of convective storms and evaporation. During the drier year (2024) with a reduced moisture surplus, river systems relied more on stored winter precipitation, emphasizing the buffering role of groundwater. Deuterium excess (d-excess) values further showed regional differences in moisture sources. Higher d-excess in western Maryland pointed to potential lake-effect precipitation derived from the Laurentian Great Lakes and long-distance transport, whereas lower values in the east reflected enhanced local evaporation. These findings establish a regional baseline that enhances our understanding of hydrological and climatic controls of river-water isotope values across Maryland. They also imply that a reduction in winter precipitation could diminish groundwater recharge and baseflow, affecting dry-season water availability. Meanwhile, more intense summer rainfall may increase surface runoff and nutrient loading, heightening flood risks and degrading water quality
Soundscapes of Change: Challenging Social Norms in Traditionally Quiet Space
No full textUnlike many European countries, America's approach to childcare often places additional stress on parenting and hinders child development. The United States is the only developed country that does not have a federally mandated paid parental leave policy. Without guaranteed parental leave, parents are forced to find childcare, which is often unaffordable and inaccessible. Not only is society and policy making childhood and parenthood difficult, the built environment is as well. The built environment is designed as though children do not exist. America’s hostility towards children has enforced a mindset that children should be seen, not heard. This research reorients the design process and puts acoustics at the center to rethink the built environment in a way that supports both children and parents. Children are our future, and they deserve to be a visible and welcome part of the present. This thesis aims to explore how acoustic strategies can be implemented into traditionally quiet spaces to address, engage, and celebrate children and families in civic life. By designing spaces that are flexible and will fit the needs of the user, acoustic design will create environments where people of all ages can relax, enjoy, and learn.
This thesis challenges the social norms in traditionally quiet spaces. By designing spaces with acoustics at the center of the process, spaces will be more comfortable and welcoming to children and families. This thesis aims to reimagine the design process and put acoustics at the center to integrate children and families into civic life
IDENTIFYING AND MITIGATING BIAS IN MACHINE LEARNING FOR HEALTHCARE
No full textThe use of machine learning in healthcare settings has become increasingly common, from prediction of individual patient outcomes to supporting policy decision-making for public health officials. However, these machine learning models often replicate or exacerbate human biases and discrimination. In this dissertation, we seek to address this problem both through identification of bias in existing healthcare modeling settings and through the development of approaches to mitigate bias, focusing on several complementary problems.
We audit predictive models of county-level COVID-19 cases, identifying whether models perform equally well across counties with different demographic compositions when a) human mobility data is included as a model feature and b) when various approaches are used to correct case underreporting. We also investigate approaches to improve model performance specifically for small subgroups. We develop a regression model for joint estimation of multiple groups that uses sample weighting and separate sparsity penalties to boost model performance for smaller groups. Then we outline an easy-to-implement LLM-based synthetic data generation method to augment smaller, underrepresented groups in health datasets, conducting a comprehensive evaluation of two prompt templates and three LLMs across two health datasets. Lastly, we present a novel use of causal machine learning methods to investigate sociodemographic subgroups with heterogeneous racial health disparities.
Given structural inequities in allocation of health resources to marginalized communities and current disparities in a wide range of health outcomes, it is important that we both prevent machine learning systems from causing further harm through perpetuation of allocation inequities and leverage machine learning approaches to actively correct these harms