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MEMS 4110: DBF Banner
No full textThe DBFBanner is a project made for the WashU Design / Build / Fly club. After interviewing DBF club president Sarah Donner, we interpreted the club’s needs as: (1) a banner that could achieve vertical stability in flight; (2) the banner could deploy and release remotely; (3) the banner and associated components were as light as possible. We went through several design iterations, including mathematical and CAD models, mockups, prototypes, and testing apparatus. Many designs were considered, including designs based on linear motion and collapsible trusses. We arrived at a design that used a servo motor to rotate a 3D-printed part through specified degrees, with each rotation setting allowing a di!erent washer to release. In order to test our design, we designed a testing apparatus that could be mounted on the side of a car, allowing the banner deployment / release and banner stability to be tested in similar conditions to a remote control plane. Our final design met all performance goals mentioned above- it could achieve vertical stability in flight, deploy / release remotely, and had minimal weight. Future improvements include deployment / release reliability, improving flight stability even further, adding housing for electronic components, and a combined servo control arm and rotator
MEMS 4110: ASME Garbage Collection Challenge
No full textThe AY25-26 ASME Student Design Competition (SDC) is inspired by the global issue of recycling and waste collection management. Garbage and recycling are, in many instances, collected at the curb or roadside, where residents and/or business establishments place their garbage and recyclables in designated containers for pickup by local waste management companies or municipalities. In some areas around the world, waste collection is a challenge to establish due to variations in terrains and storage locale/capacity. In some instances, waste management companies might utilize a single vehicle that separates materials during the collection process to minimize the number of required vehicles in operation at the same time. Waste collection vehicles are often dispatched early in the morning to avoid traffic delays common during typical work hours. Time is paramount to the safe management, transportation, and disposal of waste. An efficient route, speed capability, and a large containment reservoir helps limit the time it takes for a waste collection vehicle to complete the job. However, the larger the vehicle, the more difficult it can be to navigate the roads, especially in high-population and/or business districts. Additionally, a waste collection vehicle must be able to pass under bridges, signage, and other overhangs that limit the vehicle’s vertical height. Damage to property is to be avoided. The AY25-26 SDC challenge is to design, fabricate, and test a versatile waste collection device that can rapidly and accurately navigate a model city with various terrains, collect and sort garbage and recycling, and transport and dump the waste materials into the correct facility (recycling center or landfill). This device must operate in a safe and efficient manner that obeys traffic and safety laws and avoids property damage or waste spillage. Points will be awarded based on the proper sorting and handling of the waste materials, as well as the size and required power source of the device
MEMS 4110: Air Hockey Table Physics Education Exhibit
No full textThis project centers on creating an educational air-hockey exhibit designed for use in a science museum. The goal of the device is to transform a familiar game into a hands-on demonstration of basic physics and engineering concepts such as motion, momentum, energy transfer, and impact forces. Through discussions with our customer, Professor Potter, we established that the exhibit must balance two priorities: it must be fun and intuitive for visitors of all ages, and it must provide meaningful real-time feedback that helps users understand the science behind the experience
Biomolecular Engineering of Intrinsically Disordered Proteins
No full textIntrinsically disordered proteins (IDPs) lack a fixed structure and play important roles in organizing cellular biochemistry. Many membraneless organelles, such as nucleoli and RNA granules, arise via liquid-liquid phase separation (LLPS) of IDPs or intrinsically disordered regions (IDRs) within the proteins. These dynamic condensates can selectively concentrate specific biomolecules, enabling spatial control of processes like gene expression, signaling, and stress responses. Based on this distinct biochemical behavior, recent research has begun to engineer IDP-based systems that mimic and extend existing compartmentalization strategies to regulate the intracellular environments. Apart from this, synthetic biologists also explored the molecular grammar of IDPs and created synthetic IDPs (synIDPs) to precisely program the cellular functions. However, limited understanding of how molecular grammar and sequence-dependent interaction cooperativity relate to the functional impacts of synIDPs and synthetic condensates on endogenous cellular processes constrain the design space of this powerful capability. In this thesis, I first developed a platform that evolves synIDPs with desired properties, such as concentration- or temperature-dependent phase transition behaviors. Next, I applied the evolved synIDPs from the first part to demonstrate their applicability in synthetic biology. Specifically, these evolved IDPs were used as modular genetic parts to enhance protein solubility and reversibly control the ampicillin resistance of E. coli. Finally, based on the same evolutionary platform, I engineered binders derived from native sequences of natural condensate-forming proteins, such as FUS and TDP-43. These formation of these intracellular condensates was effectively inhibited by fusing the evolved binders with soluble IDPs. Altogether, these tools expand our understanding of IDP molecular grammar and enable precise engineering of cellular behaviors using evolved IDPs
Effects of ANGPTL3 Deficiency on the Regulation of Hepatic Lipoprotein Production and Lipid Metabolism
Get PDFCardiovascular disease is the leading cause of death worldwide. A major treatment goal is to lower plasma lipids, especially low-density lipoprotein cholesterol (LDL), the cardinal risk factor for coronary artery disease (CAD). Patients with familial hypercholesterolemia (FH) experience early-onset CAD due to extremely high LDL. Underdiagnosis and undertreatment of FH are exacerbated by limited therapeutic options. However, one strategy has successfully lowered LDL in FH patients: Inhibition of the hepatically secreted protein Angiopoietin-like protein 3 (ANGPTL3). Despite promising clinical data, the mechanism by which ANGPTL3 inhibition lowers LDL has not been fully described. Although ANGPTL3 has been shown to modulate the metabolism of circulating lipoproteins, its role in hepatic lipoprotein assembly and secretion remained incompletely characterized. In a hepatocyte cell culture model of ANGPTL3 deficiency, we demonstrate increased LDL receptor (LDLR)-dependent turnover of Apolipoprotein B100 (ApoB100)-containing triglyceride-rich lipoproteins (TRLs) and concomitant impairment of their secretion. Additionally, we show that ANGPTL3-deficient hepatocytes exhibit enhanced lipid catabolism. Our findings suggest an unanticipated intrahepatic role for ANGPTL3, whereby ANGPTL3 deficiency leads to the production of fewer lipoprotein particles and adaptive changes in hepatocyte lipid metabolism
Understanding Strain-level Dynamics in Gut Commensal-Pathogen-Host Interactions
Get PDFThe human gut microbiome is a consortium of trillions of bacteria, archaea, fungi, and viruses that colonizes the gastrointestinal tract and promotes health under homeostatic conditions. This microbial community trains the immune system, modulates inflammation and anticancer immunity, promotes cardiometabolic health, enables nutrient extraction, and prevents pathogen overgrowth. The latter function manifests through colonization resistance, in which microbes occupy spatial and nutritional niches thereby excluding pathogens from the community entirely, and through limiting pathogen population growth if colonization occurs. These roles are facilitated by complex host-microbe and microbe-microbe interactions that underlie differences in susceptibility to microbiome-mediated infectious diseases. The strain-level diversity of commensal and potentially pathogenic organisms, which determines their functional potential, is an important aspect of these microbe-microbe relationships and their impact on pathogen colonization outcomes. This thesis work delves into the gut commensal-pathogen-host dynamics that affect bacterial infections across different patient populations with the goal of advancing therapies and prevention efforts for microbiome-mediated infections. In Chapter 2, I present results from a study investigating whether the gut microbiome is a reservoir of serious extraintestinal bacterial infections (EBIs) in infants, who are at heightened risk. The most common EBI pathogens in infancy are aerobic and facultatively anaerobic bacteria that commonly inhabit the early life microbiome, but a direct link between these sites has not been established using strain-level genomics. We selected participants with and without EBI from a multi-center cohort of febrile term infants presenting to the emergency department. Based on genome assemblies from cultured isolates and gut metagenomic sequencing, we established that a strain isogenic to the extraintestinal pathogen was present in the intestine of 25/40 cases at the time of infection. The pathogen species was often more abundant and prevalent in the gut of infants with EBI, and for 18/25 cases colonized by the EBI-causing strain, its DNA was at sufficient abundance to be detected via metagenomic reads alone. For infants with E. coli EBI, E. coli strains from phylogroup B2 were significantly more abundant in the gut of cases whose EBI-causing E. coli strain was detected in the gut rather than E. coli-colonized controls, as were several virulence factor genes associated with adhesion, nutrient acquisition, and exotoxin production. These results point to the intestine as a potential source of EBI in young infants, and they raise the potential for microbiome screening as a diagnostic and clinical risk assessment tool for this population. Chapter 3 focuses on understanding why many people colonized by the enteric pathogen Clostridioides difficile do not get sick, while in others it causes severe infection (CDI). C. difficile remains a global public health burden despite advances in infection prevention practices and antimicrobial stewardship programs. We analyzed stool samples and pathogen genomes from two cohorts of hospitalized patients colonized by C. difficile. Using a random forest classifier, we found that microbiome-related features were more discriminatory between patients with CDI and asymptomatic carriers than pathogen strain and demographic features. By engrafting stool communities from carriers into germ-free mice, we observed that both the colonizing C. difficile strain and commensal taxa, including those from Lachnospiraceae, influenced disease severity in vivo. We next designed two defined communities of bacteria that recapitulated microbiome structures of C. difficile-colonized patients and performed C. difficile challenge experiments in mice engrafted with either community. Clinically prevalent C. difficile strains showed a range of virulence in vivo that was suppressed in the background of the more diverse community, possibly through enhanced nutrient availability. These results provide support for commensal-pathogen interactions being a key driver of C. difficile carriage that may be leveraged to develop antibiotic-sparing strategies to prevent CDI in colonized patients
Essays on Macroeconomic Frictions and Policy
Get PDFInformation, Production Networks and Optimal Taxation: This paper studies optimal taxation in an economy with information frictions and a production network across industries. I show that when all industries share the same information structure, production efficiency holds and optimal policy features no taxes on intermediate goods. Deviating from this benchmark, I characterize the optimal policy when information structure is heterogeneous across industries: The government optimally imposes higher revenue taxes on industries during economic downturns if: (i) these industries exhibit greater information rigidity, (ii) their downstream industries display less information rigidity, and (iii) their input goods are also utilized by less informed industries. I quantify information heterogeneity across industries with a standard text analysis method. Industries display varying levels of attention to economic outcomes, which are correlated with their exposure to business cycle shocks. The calibrated model indicates that, in response to the COVID-19 shock, the optimal taxation leads to a welfare increase of 0.7% for the U.S. and 1.23% for China in terms of consumption, compared to the tax policy that ignores the heterogeneity in information structure. Liquidity trap revisited: when wages are sticky: This paper revisits the New Keynesian model in a liquidity trap when the government lacks commitment, showing that incorporating stickywages restores continuity of the equilibrium path with price flexibility λp = ∞ and λp → ∞ and resolves counterintuitive implications such as the explosive effects of forward guidance and fiscal policy. In the standard New Keynesian model, greater price flexibility deepens recessions and intensifies deflation during a liquidity trap. As prices become more flexible, the effects of forward guidance and fiscal policy increase explosively, ultimately diverging to infinity. With sticky wages, these limit puzzles disappear. The economy follows a stable path, and policy interventions have moderate and realistic effects during a liquidity trap. Price flexibility is beneficial, while wage flexibility can be beneficial or harmful depending on whether the zero lower bound (ZLB) constraint is binding. Industry Dynamics and Economic Growth with Labor Market Frictions: We develop a multi-industry growth model with labor market frictions to explore the interaction between such frictions and industrial upgrading and economic growth. Experienced workers in an old industry lose their industry-specific expertise when they are relocated to a more capital-intensive industry and suffer a mismatch. These workers gradually become experienced through on-the-job learning, till the sunrise industry itself becomes a sunset one and workers have to move to an even more capital-intensive industry. We analytically characterize the properties of dynamic labor market performance, the life-cycle dynamics of each of the underlying infinite industries, and the aggregate growth rates. We show that, without any exogenous aggregate shocks, the aggregate unemployment rate exhibits recurrent cycles along with the perpetual structural change driven by capital accumulation
Characterizing PIEZO1 Mechanotransduction in Articular Chondrocytes
Get PDFOsteoarthritis (OA) is the most common degenerative joint disease, affecting more than 350 million people worldwide. Along with inflammation and pain, a hallmark of OA is the degradation of articular cartilage (AC), an avascular and aneural tissue that coats and facilitates the bending of diarthrodial joints. AC withstands millions of cyclic mechanical loads annually, and chondrocytes, the only resident cells in the tissue, sense these loads through mechanically gated ion channels, including Transient Receptor Potential Vanilloid 4 (TRPV4), PIEZO1 and PIEZO2. PIEZO1 is a highly expressed calcium ion channel in chondrocytes that can be activated through mechanical loading or chemically with Yoda1, a PIEZO1-specific agonist. Our lab recently demonstrated that PIEZO1 expression is elevated in osteoarthritic cartilage and that interleukin-1α (IL-1α), a pro-inflammatory cytokine abundant in OA, led to the upregulation of PIEZO1 expression in porcine chondrocytes. The increased expression of PIEZO1 in IL-1α-challenged chondrocytes led to a sustained increased intracellular calcium concentration and the rarefication of the actin cytoskeleton. However, while PIEZO1contributes to the development of osteophytes, bony formations on the edges of bones, during OA, PIEZO1 plays a key role in endochondral ossification, a key anabolic process during long bone formation. Therefore, understanding how PIEZO1 mechanotransduction differs in healthy or pathological conditions is key in developing novel therapeutics for treating OA. Herein, the overall goal of my thesis was to characterize PIEZO1 mechanotransduction in healthy articular chondrocytes. First, I employ Atomic Force Microscopy (AFM) to monitor changes in the nuclear elastic modulus in situ in response to PIEZO1 activation with Yoda1. Then, I use confocal live imaging and develop an image analysis pipeline to characterize calcium and actin dynamics following PIEZO1 activation. Finally, I combine qPCR and immunofluorescence to monitor both transcriptomic and epigenetic changes following PIEZO1 activation with Yoda1. My research integrates biophysics, live-cell imaging, and omics approaches to characterize PIEZO1-mediated mechanotransduction in articular chondrocytes. Overall, this work establishes a foundational, mechanistic understanding of PIEZO1 mechanotransduction and provides a molecular basis for developing PIEZO1-modulating drugs to treat OA or other mechanically driven diseases
Models and Mechanisms of Chemotherapy-Induced Side Effects
Get PDFCancer is among the leading causes of death worldwide. Chemotherapy remains a cornerstone in the treatment of various cancers; however, it often leads to a range of debilitating side effects that compromise its efficacy and profoundly impact patients\u27 quality of life and psychosocial well-being. These side effects can be broadly categorized into short-term effects, such as nausea, vomiting, fatigue, hair loss, and neutropenia, and long-term effects which can persist months or even years after treatment, including peripheral neuropathies, cognitive impairment, cardiotoxicity, nephrotoxicity and ototoxicity. Among the most common and dose-limiting side effects are chemotherapy-induced peripheral neuropathy (CIPN) and cardiotoxicity (CTX). Another life-threatening condition typically associated with cancer and chemotherapy is cachexia, a wasting syndrome causing significant loss of body mass, affecting up to two-thirds of patients with advanced cancer. Despite their prevalence and severity, the underlying mechanisms are not fully understood, limiting the development of early diagnostic markers and effective therapeutic interventions. This thesis focuses on developing models and elucidating mechanisms of CIPN, CTX, and chemotherapy-induced cachexia-like syndrome. Specifically, the research is centered around oxaliplatin, a third-generation platinum-based chemotherapeutic drug commonly used in the treatment of various cancers primarily colorectal cancers as well as gastric, pancreatic, and ovarian cancers in combination of other agents. The study aims to enhance the understanding of these adverse effects and to improve patient outcomes and tolerability of chemotherapy by establishing pre-clinical models that closely mimic the clinical symptoms observed in patients, developing behavioral and imaging measurements to quantify the progression of these conditions, and identifying potential biomarkers and targets for early diagnosis, prevention, and treatment. The first aim investigates mechanisms underlying oxaliplatin-induced peripheral neuropathy with emphasize on the chronic phase of pain. We established in vivo and ex vivo models of the chronic CIPN and explored the role of oxidative stress in CIPN. Though RNA-sequencing (RNA-seq), we further identified Thioredoxin-interacting protein (Txnip), which plays a central role regulating reactive oxygen species (ROS), as a potential therapeutic target. Pharmaceutical inhibition of Txnip demonstrated improvement in CIPN symptoms in both in vivo and in vitro models. Second, cardiotoxicity of oxaliplatin is studied with a rodent model of cardiotoxicity (CTX), where a decrease in heart rate and abnormal ECG reads were observed in mice following oxaliplatin administration. RNA-seq revealed an energy metabolism shift from fatty acid oxidation to glycolysis in heart, accompanied by lactate accumulation, indicating an impaired energy supply necessary for normal heart function. Additionally, significant up-regulation of Nmrk2 gene and depletion of NAD+ were detected. Based on those results, supplementation of nicotinamide riboside (NR), a precursor of NAD+, may serve as potential treatment to restore NAD+ levels and improve cardiac function. The final aim explores the mechanisms of chemotherapy-induced cachexia, where a systematic metabolic disorder was observed in mice treated with oxaliplatin, characterized by severe body mass loss, skeletal muscle wasting and adipose tissue loss, reduced daily activity, and altered energy metabolism. RNA-seq data indicated inflammation as a key driver of muscle wasting, while decreased lipogenesis and adipogenesis contributed to white adipose tissue (WAT) loss. Moreover, we observed a dysregulation of adipokines – neuropeptides axes in WAT and hypothalamus which may serve as therapeutic targets to improve appetite and increase body mass. These findings suggested oxaliplatin alone can induce cachexic syndrome, highlighting the critical need for therapeutic interventions that target cachexia arising from both cancer progression and chemotherapy
Aerosol Technology for Carbon Capture and Utilization
No full textThe CO2 concentration in the atmosphere has continued to increase over the past century and now poses an increasing potentially catastrophic effect to human life and the environment via global warming and the concomitant effect of climate change. Anthropogenic carbon dioxide emissions due to fossil fuel combustion for increasing energy demand is the main driver for the increased carbon dioxide in the atmosphere. A multifaceted approach including carbon dioxide capture and utilization is required to mitigate anthropogenic carbon dioxide emissions. Aerosol science and technology, an enabler for clean combustion technologies and nanomaterial synthesis, can contribute significantly to the advancement of carbon dioxide capture and utilization technologies. To deploy clean combustion technologies, such as pressurized oxy-combustion, for carbon dioxide capture, it is important to understand particle formation and growth mechanisms in relevant combustion conditions. Similarly, to seize the advantages of nanomaterial synthesis via aerosol route for carbon dioxide utilization, it is important to establish fundamental relationships between the aerosol synthesis method and the synthesized nanoparticle functionality and to develop accurate computationally efficient models to enable scalability. To advance carbon capture and utilization using aerosol technology, this dissertation therefore focuses on developing a pressurized drop tube furnace experiment system to understand particle formation and growth in pressurized oxy-combustion systems and the synthesis of nanocatalysts using the spray flame aerosol reactor. This dissertation is divided into four sections. The first section focuses on the development of the pressurized combustion experiment system to enable studies to elucidate the particle formation mechanism in pressurized combustion systems. The design of the pressurized drop tube furnace is presented. Likewise, the design of all accessories of the pressurized drop tube furnace experiment system (sampling unit, particle feed unit, exhaust gas treatment unit, gas supply unit) are presented. Finally, experiments to elucidate the impacts of pressure, combustion atmosphere and temperature on the particulate matter size distribution are proposed. The second section focuses on quantifying carbon dioxide conversion potential for reforming processes. Thermodynamic analysis based on equilibrium conditions is used to quantify the CO2 utilization potential for the reforming of oxy-combustion exhaust gas using methane and the reforming of CO2 with hydrocarbons at practical operating regimes for reforming. The reforming process at equilibrium was modeled using Aspen Plus. In this study, the boundaries of the practical operating window for reforming are identified and discussed. The zero-coke equilibrium line is introduced and its relevance to reforming as boundary for the feasible operating window is discussed. Finally, the carbon dioxide conversion potential for reforming is determined for oxy-combustion exhaust gas and then extended to reforming using any hydrocarbon. The third section focuses on the synthesis of catalysts using the spray flame aerosol reactor. Firstly, alumina, a widely used catalyst and catalyst support, was synthesized. The spray flame aerosol reactor was characterized to determine the effect of its control parameters (precursor flow rate, dispersion O2 flow rate and sheath O2 flow rate) on synthesized nanoparticle properties (size distribution, surface area, crystal phase composition). Consequently, more complex supported reforming catalysts Rh/Al2O3 and methanol synthesis catalysts CuO/ZnO/ZrO2 and CuO/ZnO/MgO were designed and synthesized using the spray flame aerosol reactor. The methanol synthesis catalysts were admixed with an acid function catalyst to produce a hybrid catalyst for direct DME synthesis from CO2 rich synthesis gas. The hybrid catalyst showed superior performance in terms of activity and selectivity when compared to similar catalyst whose methanol synthesis component was synthesized by co-precipitation. The fourth section focuses on the development of hybrid physics-based machine learning model for aerosol coagulation. The model which consists of a data driven ANN model used to determine the proxy coagulation coefficients and a reduced order coagulation model enabling an analytical solution was proposed and validated. Comparison of proposed hybrid ANN model results depicting the evolution of particle size distribution in the furnace aerosol reactor with high fidelity sectional model and the computationally efficient moment model indicates the proposed hybrid ANN model is both accurate and computationally efficient. In summary, this dissertation, advances aerosol technology as an enabler for carbon dioxide capture and utilization