Washington University Medical Center
Washington University St. Louis: Open ScholarshipNot a member yet
26344 research outputs found
Sort by
„[M]it meim Blumenstaub nähr ich den Geist der Zukunft.“ Der Rückgriff auf das Jahr 1807 in Bettina von Arnims Dies Buch gehört dem König
No full textThe Master\u27s thesis argues that the protagonist of Bettina von Arnim\u27s novel Dies Buch gehört dem König (1843) draws on aesthetic, political, pedagogical and medical discourses that emerged around 1800 in order to design a political alternative model to her hierarchical and normalistic present. Two observations can be made from this perspective: Firstly, a tension between the novel and the socio-statistical appendix becomes visible. Secondly, it can be shown that the protagonist has a form of subjectivation in mind that has strong similarities to that of the post-Fordist present
The Arowana
No full textMy thesis represents approximately the first third of my novel-in-progress “The Arowana,” a coming-of-age story about wildlife trafficking, obsession, the feminine gaze in hyper-masculine spaces, globalization, the American Rust Belt, and fish
Associations between Prenatal Inflammation and Dimensions of Depressive Symptoms across the Perinatal Period
No full textRisk for depression increases during the perinatal period due to several biological and physiological changes, including fluctuations in inflammation. However, the timing and cytokine-specific effects on depressive symptoms during and after pregnancy are unclear. In this study, we examined relations between four cytokines (IL-6, IL-8, IL-10, and TNF-α) and depression at multiple time points throughout the perinatal period and investigated the role of dimensions of depressive symptoms in these relationships. We used longitudinal data of 314 mothers in the Early Life Adversity and Biological Embedding Study from the first trimester of pregnancy to the end of the first year postpartum. Multiple linear regressions examined the relationships between cytokines and maternal depressive symptoms. Specifically, we investigated these relationships throughout pregnancy, using cytokine slopes and symptoms averaged across trimesters, in the third trimester, and by measuring changes from the second to third trimester. Then, we investigated whether cytokines levels predicted depressive symptoms at future time points, including postnatally. Analyses with the same model structure looking at different symptom dimensions were adjusted using multiple comparison procedures (FDR). Cytokine levels were not associated with total depression scores. IL-6 levels and anhedonia symptoms were positively associated in the third trimester (β = 0.10, p = 0.02, q = 0.04). More positive TNF-α slopes across pregnancy, indicating increasing levels of TNF-α over time, were associated with greater average prenatal anhedonia (β = 0.84, p = 0.02, q = 0.05). Increases in IL-6 from the second to third trimester predicted less postnatal anxiety (β = -0.16, p = 0.01, q = 0.02), whereas increases in TNF-α from the second to third trimester predicted greater third-trimester anxiety and depression (β = 0.08, p = 0.03, q = 0.05, β = 0.09, p = 0.01, q = 0.03). We did not find significant relationships between IL-8 and IL-10 and depressive symptoms at any time point (ps = 0.08-0.97). Findings provide additional evidence for the role of IL-6 and TNF-α in perinatal depression. Anhedonia symptoms and third-trimester inflammation may be particularly important. Future work focusing on dimensions of depressive symptoms and inflammatory processes across the perinatal period is key to elucidating specific temporal associations. Further investigation of how changes in inflammation across pregnancy relate to specific types of depressive symptoms could inform and improve perinatal care and intervention
Relational Linked Fate and the Racial Position of Asian Americans
No full textWhere do Asians fit in the racial order of the U.S., and how do they situate themselves relative to other racial groups? The racial position of Asian Americans remains an ongoing debate. Some scholars argue that Asians are becoming White due to socioeconomic attainment and intermarriage, while others emphasize ongoing racialization, exclusion, and solidarity with other people of color. Yet, these debates often overlook the heterogeneity of the Asian American population, and how it might further complicate how they perceive their racial position. The current study examines how Asian Americans situate themselves in relation to other racial groups by extending the concept of linked fate—the idea that individuals see their life chances as tied to those of given racial groups. Using data from the 2020 Collaborative Multiracial Post-Election Survey (CMPS), I introduce relational linked fate, which compares respondents’ sense of linked fate across racial groups to empirically assess their racial positioning. I ask: Do Asian Americans perceive themselves as aligned with Whites, other minorities, or exclusively with other Asians? How do they compare with other racial groups? How do factors such as ethnicity, immigrant generation, and socioeconomic status shape these perceptions? Findings reveal that Asian Americans do not fit neatly into a single racial position. While some lean toward Whiteness, others identify more strongly with other minorities, and a sizable portion remain disengaged from racial positioning altogether. South Asians are more likely to align with other minorities, while East Asians in general are more likely to lean White or emphasize pan-Asian identity. Immigrant generation also matters; second-generation and 1.5-generation Asians report stronger panethnic ties, while later-generation Asians are more likely to lean White. These findings challenge singular narratives about Asian American racial incorporation, highlighting the need for future research to account for intra-Asian diversity
Design of Hydrogen Powered High Altitude Conventional Tube-Wing Aircraft for Aerosol Injection in Stratosphere
No full textThis paper presents the conceptual design and performance analysis of a hydrogen-powered, high-altitude aircraft developed for long-endurance aerosol dispersion missions. Raymer’s methodology is used for initial sizing of the aircraft, followed by utilizing a hybrid weight estimation method comparing the Raymer, Torenbeek, NASA, and Roskam weight estimation methodologies to create a robust weight estimation. Analysis of aerodynamic, propulsion, weight, stability, and mission performance is conducted in RDSwin to demonstrate a sustained operation for a mission including a 65,000 ft altitude, 3.5-hour cruise segment for dispersing a 50,000 lb aerosol payload. Numerous iterations of the aircraft are performed to refine aircraft performance towards a more robust and efficient design. Simulation results showed that a conventional tube-wing aircraft using hydrogen propulsion is capable of efficient high-altitude flight with adequate thrust margin, structural feasibility, and subsystem compatibility per the mission requirements. Overall, the study verifies the hydrogen tube-wing concept as a viable platform for long-duration, high-altitude missions requiring substantial payload capacity and endurance
Transforming CO2 into Value-Added Products: Liquefied Petroleum Gas and Solid Carbon Materials
No full textThe escalating climate crisis, driven by anthropogenic carbon dioxide (CO2) emissions, necessitates the development of advanced Carbon Capture and Utilization (CCU) technologies. A critical distinction within CCU lies between transient carbon cycling, which converts CO2 into fuels, and permanent sequestration, which transforms it into durable, solid materials. This dissertation addresses fundamental catalytic challenges across both pathways to develop economically viable and technologically sound solutions for CO2 valorization. This work seeks to answer two primary research questions: (1) How can the catalyst temperature mismatch and stability limitations in the tandem conversion of CO2 to Liquefied Petroleum Gas (LPG) be overcome to create cost-effective, low-temperature processes? (2) How can the formidable thermodynamic barrier of direct CO2 splitting be circumvented to achieve permanent carbon sequestration in high-value solid materials? Utilizing advanced catalyst synthesis, comprehensive material characterizations, and in situ spectroscopic techniques, this dissertation elucidates critical structure-performance relationships and establishes new design principles for tandem catalysis. First, this study investigates the roles of palladium (Pd) incorporation and acid treatment in the catalytic performance of β-zeolite in low-temperature CO2-to-LPG synthesis. Our research challenges conventional reliance on Pd, demonstrating that Pd-free catalysts can achieve rapid stabilization and exhibit efficient catalytic activity. We demonstrate that judicious acid treatment of the zeolite component, not the incorporation of expensive noble metals like palladium, is the key factor enabling low-temperature activity. This is achieved by stabilizing surface methoxy species, the crucial intermediates for C-C bond formation. Palladium is shown to be not only unnecessary but detrimental, as it diverts these intermediates into parasitic side reactions. Furthermore, we systematically investigate this structure-performance relationship by engineering an inverse Zr0.2Cu catalyst with two distinct ZnO architectures for low-tempearture LPG synthesis: a homogeneously dispersed promoter via co-precipitation (6%ZnO) and a conformal surface overlayer via atomic layer deposition (ALD). We reveal that the spatial arrangement of the ZnO promoter governs long-term stability. A conformal surface promoter is shown to physically obstruct hydrogen transport pathways between catalytic components, leading to rapid deactivation by coking, whereas a bulk-dispersed promoter preserves these pathways and ensures robust performance. Second, this dissertation advances the conversion of CO2 to solid carbon for permanent sequestration. An efficient low-temperature CO2 methanation catalyst (Ni-MgO-SG) is first developed via a sol-gel method that synergistically optimizes metal dispersion, surface area, basicity, and oxygen vacancy concentration, resulting in markedly enhanced activity. Building on this, an innovative two-step tandem thermochemical strategy is designed and validated. This integrated process utilizes a highly active and stable sol-gel prepared Ni87Ce6.5Zr6.5-SG catalyst for the low-temperature CO2 methanation step, which is then coupled with a durable core-shell methane pyrolysis catalyst (Ni@Al2O3). This tandem system achieves nearly 99% overall CO2 conversion and a high carbon yield to carbon nanotubes (CNTs) in a single pass, providing a definitive proof-of-concept for a technologically viable pathway to transform a gaseous pollutant into a durable, high-value solid material. The findings of this research advance the fundamental science of catalyst design for tandem reactions and provide practical solutions for CO2 valorization. The noble-metal-free catalyst design paradigms and insights into promoter architecture offer pathways to more economical and sustainable fuel production. The successful demonstration of the integrated CO2-to-CNTs process establishes a compelling new technology for achieving negative emissions, contributing to the development of a circular carbon economy
Development and Evaluation of Processes Affecting Simulation of Diurnal Fine Particulate Matter Variation in Chemistry Transport Modeling
No full textFine particulate matter (PM2.5) has adverse effects on human health, affects climate forcing through complex interaction with radiative transfer and reduces ambient visibility. The diurnal variation of PM2.5 refers to the variation of PM2.5 mass concentration within a day, 24 hours. Understanding this diurnal variation is critical for building exposure assessment of PM2.5 at hourly resolution, predicting severe air pollution events and relating satellite-derived PM2.5 concentrations from overpassing times to 24h-averages. The diurnal PM2.5 variation has been widely observed around the world, showing a similar pattern across different continents and seasons. The PM2.5 mass concentration generally peaks in morning and late evening, with minima near daybreak and middle afternoon. The driving mechanisms of this variation were not fully understood. This dissertation uses the chemical transport model GEOS-Chem to interpret the diurnal variation of PM2.5, which includes three studies. The first study develops and evaluates the processes affecting the simulation of diurnal fine particulate matter variation in the GEOS-Chem model. The base GEOS-Chem model exhibits excessive PM2.5 accumulation overnight, overestimated diurnal amplitude and early timing of the morning peak and afternoon minimum comparing to in-situ observations. To reduce the above simulation biases, an emission inventory with hourly resolution is used, vertical representation difference between model and observations is resolved by correcting for aerodynamic resistances, boundary layer heights in the GEOS-FP meteorological inputs are constrained by aircraft observations and the dry deposition scheme is revised. The final revised study notably improves the capability of GEOS-Chem to reproduce diurnal PM2.5 variation over the US. Nevertheless, the nighttime nitrate remains after all developments applied, contributed mainly by excessive N2O5 hydrolysis according to the results from sensitivity simulations. The second study follows the model developments in the first study and extends the simulation of diurnal PM2.5 to a global scale using the GEOS-Chem model with the high-performance configuration (GCHP). Mass fluxes for surface PM2.5 caused by different model processes (chemistry, boundary layer mixing, convection, emission, dry deposition and wet deposition) are developed from the model diagnostics to quantify the driving forces of global diurnal PM2.5. Results indicate that the morning peak of observed PM2.5 is likely contributed by fumigation, the PM2.5 dip in afternoon is driven by both the growth of boundary layer and the partitioning into gas phase of semi-volatile aerosols, the PM2.5 accumulation throughout evening is contributed by chemical production and boundary layer collapse, and the PM2.5 dip near daybreak is likely contributed by decreased anthropogenic emissions. The third study focuses on simulating the diurnal variation of PM2.5 composition over Southeastern US using GEOS-Chem driven by the GEOS-FP offline meteorological datasets (GCHP) and the online WRF simulation (WRF-GC). The two GEOS-Chem model configurations exhibit different performance on reproducing observed diurnal variation of PM2.5 composition, likely caused by different representation of relative humidity, cloud water, dry deposition and boundary layer mixing. Driving forces of the diurnal variation of black carbon, organic matter, sulfate, nitrate and ammonium is revealed based on budget analysis. In addition, this study uses a Long-short Term Memory (LSTM) deep learning model to reduce the diurnal biases of nitrate simulation in GCHP
3D-Printed Bioelectronic Scaffolds: From Tissue-inspired Material Design to Devices for Dynamic Monitoring of Tissue Models
No full textTissue culture models are invaluable tools commonly utilized to study biological systems, develop novel therapies and predict patient response to treatments. It is now widely accepted that tissue models should more closely mimic the properties of the in vivo environment to enhance clinical translatability of studies. Additionally, there is a growing demand for incorporating functional capabilities such as electronic conductivity into these models to digitally control or monitor cell behavior. However traditional electronic devices differ significantly from tissues as they offer dry, stiff (GPa) and two-dimensional surfaces. These characteristics can lead to the monitoring of abnormal or artificial cellular behavior. Therefore, there is a need to develop tissue-inspired bioelectronics for improved integration with tissue models. Conducting polymer hydrogels, like those made from poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS), have emerged as promising candidates for bridging the gap between biology and technology, as these materials provide a more tissue-like conducting interface for cell interactions. However fabricating PEDOT:PSS hydrogels that have soft tissue-matching stiffness (1 – 100 kPa) while maintaining good electrical conductivity (\u3e100 S/m) remains a challenge. Moreover, majority of studies have used PEDOT:PSS hydrogels as implantable, encapsulated 2D electrodes. Thus, the potential of these hydrogels to support 3D cell interactions in vitro is largely understudied. In this dissertation I employ a tissue-inspired approach to address these limitations. First I investigated whether manipulating the crosslinking of the PEDOT:PSS hydrogels influences their compatibility with cell culture processes. It was found that manipulating the concentration of the gelation agent influenced the aqueous stability, mechanical, and electrical properties of the hydrogels. With sufficient crosslinking, the hydrogels were stable for cell culture applications. Additionally, it was determined that further processing, such as serum incubation, was necessary for the hydrogels to support populations of primary cells on 2D PEDOT:PSS hydrogel substrates. Next, I created 3D printed bioelectronic scaffolds from PEDOT:PSS hydrogels to support the creation of 3D tissue models. In this study, I successfully developed scaffolds with tailorable stiffness in the tissue range (\u3c100 kPa), high water content (\u3e89%) and high conductivity (\u3e200 S/m). These scaffolds supported 3D cell culture of fibroblasts and promoted inherent cell characteristics like extracellular matrix production. Finally, I created devices from these bioelectronic hydrogel scaffolds and investigated their ability to electronically detect changes in cancer cell behavior. I demonstrated that these devices could detect the presence or absence of cells and monitor temporal information on cell behavior including cell proliferation and chemotherapy drug-induced cell death. In the future, these devices could serve as on-chip technology that simultaneously supports tissue growth and provides an efficient method for screening cancer drugs and predicting patient response for precision medicine applications