Stander Symposium Projects

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  Investigation of Bacterial Efflux Pump Inhibitors from Edible Plant Sources and Aptamers

  Sarah Patterson Baxter

  Multidrug resistant bacteria have become a great concern in the world of medicine. Antibiotics are not being discovered at a fast enough rate to fight this resistance, leaving many bacterial infections left unable to be treated with the current antibiotics. The efflux of drugs out of cells is one of the mechanisms contributing to this resistance. Transporter proteins called efflux pumps, located in the membranes of bacterial cells, are responsible for this antibiotic exporting activity. In drug resistant bacterial cells, efflux pumps can expel antibiotics out of the cell, making it difficult for the bacteria to receive the intended dose of the drugs. I have investigated the bacterial efflux pumps and their role in conferring multidrug resistance. I sought to identify new efflux pump inhibitors through the screening of extracts made from edible plants and through the development of synthetic nucleic acid aptamers that bind to the efflux pumps and block their activity.

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  Investigation of the Cycloaddition Reactions of Some New Azophosphonates and Azobis(phosphonates): A New Manifestation of the Staudinger Synthesis

  Joshua Killian

  Newly synthesized azo-compounds, with one or two pendant phosphonate groups, have recently been shown to react easily with conjugated dienes, such as 2,3-dimethylbutadiene or cyclopentadiene. In both cases, the ensuing [4+2] cycloaddition reactions have led to the preparation, isolation, and full characterization of a series of products. However, there is no clear evidence in chemical literature on [2+2] cycloaddition reactions with an azo-component. These [2+2] reactions are rare in principle, and have been typically conducted with an alkene and a ketene component. This study investigated the question as to whether azo-compounds can participate in such reactions, in place of the alkene component. Investigation focused on diphenylketene, which was reacted with several azobis(phosphonates) or azophosphonates, at ambient temperature. The 1H-, 13C- and 31P-NMR spectroscopic results confirmed that a ring structure was formed, but the data suggested that instead of a [2+2] cycloaddition, resulting in a four-membered ring, a six-membered ring formed, the product of a formal [2+2+2] cycloaddition. The Staudinger synthesis, used for the preparation of β-lactam rings, provides a possible explanation for the mechanism of formation of the six-membered ring.

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  Investigation of the role of OPA1 and Drp1 gene mutations in amyloid-beta 42 mediated neurodegeneration in Alzheimer’s Disease

  Elizabeth Ann Borchers, Neha Gogia

  Alzheimer’s Disease (AD), is a progressive neurodegenerative disorder with no known cure to-date. This disease is caused by extra-cellular accumulation of amyloid-beta 42 (Aβ42) plaques, which results in neuronal cell death. As the genetic machinery is conserved between fruit flies and humans, in this study, we have used Drosophila melanogaster (a.k.a fruit fly) as our model organism and Drosophila eye as our model organ. We have developed a transgenic Drosophila model of AD where using GAL4/UAS system, the human Aβ42 peptides are misexpressed specifically in the differentiating photoreceptor neurons of the fly eye, resulting in death of these neurons without affecting the reproductive ability and life span of the flies. One of the hallmarks of AD is the generation of reactive oxygen species (ROS) from mitochondria, which triggers neuronal cell death. We hypothesize that 1. OPA1 (Mitochondrial Dynamin Like GTPase), and 2. Drp1 (dynamin related protein-1), (conserved between flies and humans), regulate mitochondrial fusion and fission respectively, are involved in regulating Aβ42 mediated neurodegeneration. A fine balance between mitochondrial fission and fusion events is essential for normal mitochondrial and cellular function and it has been known that mutations of OPA1 (an early stop signal) produce small unstable mitochondrial proteins, which increase ROS levels in the neurons. There is a strong correlation between increased ROS levels and mitochondrial fragmentation with neuronal death. Thus, we investigate the role of both OPA1 and Drp1 in Aβ42 mediated neurodegeneration. Results from our preliminary data show that up-regulation of OPA1 in Aβ42 background, significantly rescued Aβ42 mediated neurodegeneration only in female flies, and down-regulating OPA1 rescued Aβ42 neurodegeneration only in male flies. In contrast, down-regulating Drp1, rescued Aβ42 mediated neurodegeneration only in female flies, while up-regulation of Drp1 did not produce any rescues. Further studies on how mitochondrial maternal inheritance takes place will help us better understand these results.

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  Isolating Antibiotic Producing Bacteria from Soil

  Megan Ashley Marasco

  There are many issues within healthcare, with one of the most concerning being antibiotic resistance. Healthcare providers’ over-prescribing of antibiotics artificially selects for antibiotic resistant populations. Over time, bacteria that are selected for have the ability to become resistant to one or many of the antibiotics that are currently used in healthcare. These types of pathogens that can survive antibiotics are called “super bugs” and those are the type that healthcare providers worry about. These “super bugs” are the type of pathogens that are causing the issues, since there has been no new antibiotic class discovered in the last decade or they are still in the FDA approval process. Thus, the goal of my project is to explore the soil for antibiotic producing bacteria. The soil is home to a diverse set of microbes that are constantly competing for nutrients. Most of today’s antibiotics were discovered in the soil. Some bacteria develop the ability to create antibiotics in order to kill their competition. This characteristic is not only beneficial to their survival, but also to us. After soil isolation, we ran several tests for identification, production of antibiotic compounds, and extraction of the compound. The compound was then tested for effectiveness against known pathogens and safety in eukaryotic cells. This process allows for quicker antibiotic discovery in a teaching lab. With the many people working to discover new antibiotic compounds a major issue in the healthcare field can be corrected before all antibiotics become obsolete when treating bacterial infections.

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  Kinematic Coordination Patterns Change with Task Speed during a Lateral Step Down Task

  Lindsey Renee Weisman

  This study applied vector coding to analyze a lateral step down task at three different speeds, 45 60, and 75 bpm. Vector coding utilizes points on an angle-angle diagram to create an angle between two sequential points. An angle-angle diagram is a plot that has joint angles plotted on the x- and y-axis. For this test, the two angles studied were the knee angle from the sagittal plane and the pelvis angle from the frontal plane. The angle calculated from vector coding is the coupling angle which can be classified into four coordination patterns. Analysis of the coordination patterns determines the overall performance. The study found that subjects tended to compensate with increased pelvis motion at slower speeds; therefore, performance deteriorated with decreased speed.

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  Land Cover Change and Biological Invasion: Chinese Tallow Tree in Eastern Texas

  Emily Elizabeth Jones

  Chinese tallow, Triadica sebifera (L.) Small (Euphorbiaceae), is one of the most pervasive invaders of in the southeastern United States. In various ecosystems, Chinese tallow forms dense monocultures, displacing native species at multiple trophic levels and potentially facilitating the invasion of other non-native species. To mitigate the spread of this species, researchers have attempted to identify areas especially prone to invasion, historically using environmental and climatic data. Recent studies suggest, however, that anthropogenic disturbance may be a powerful driver of this species invasive success. The goal of this study is to determine if Chinese tallow range expansion in eastern Texas is correlated with anthropogenic disturbance, using land cover change as a proxy. To achieve this, Chinese tallow abundance data from multiple Forest Inventory Analysis surveys (2001-2017) will be compared with historical national land cover data (2001, 2006, 2011) from 42 counties in Texas using correlation analysis. Based on existing research, we hypothesized that Chinese tallow abundance will be related to changes in land cover - correlating positively with increases in developed land, agricultural land, and forested land. The findings of this study will inform scientific understanding of the relationship between anthropogenic disturbance and species’ invasions and could assist land managers in identifying areas prone to invasion by this pervasive weed.

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  Late Eocene Onset And Progression Of Extension With Exhumation In Southeastern Humboldt Range Nevada

  Joseph William Jeruc

  The East Humboldt Range (EHR), located in northeastern Nevada, includes metamorphosed rocks surrounded by sedimentary rocks. Transportation of this metamorphic core complex to its present location includes a dimension of vertical uplift, along with regional extension. The metamorphosed rocks of the EHR include minerals capable of recording temperature histories associated with rising from mid-crustal depths. A recently discovered kyanite-bearing schist in the southeastern EHR requires peak pressures and temperatures above 7 kb and 625oC, implying tectonic burial to depths >22 km. This deep-seated metamorphic terrain lies < 500 m beneath a large scale fault system known as the Ruby-EHR detachment fault inferred to have caused its exhumation.To determine timing and progression of uplift beneath this fault, mineral samples collected along a 20 km WNW-trending transect mimic the direction of gradual exhumation from depth. Sampled minerals, including biotite, muscovite, and K-feldspar, are dated using 40Ar/39Ar thermochronometry. These data record cooling through a temperature unique to each mineral known as its closure temperature. In addition, the diffusive loss of argon from K-feldspar allows modeling of cooling histories over a range extending from 450oC to <150oC. The initial phase of cooling beneath the normal fault system and the onset of uplift on the detachment fault occurred from 42 Ma to 35 Ma. Following initial cooling and extension, K-feldspar modeling reveals a reheating event after 28 Ma, and return to cooling signifying renewed extension (See companion presentation by A. Carte). The second cooling event occurs across a range of dates from 26 Ma to 14 Ma from the southeast to northwest. Comparing cooling ages along the transect, records a westward propagating wave of rapid cooling consistent with rotation of the fault to its current angle. Thus it supports the tectonic process of rolling hinge style exhumation.

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  Laundry machines and the environment

  Christina Louise Diersing, Riana Renee Dozier, Justin Blake Smith

  Do you know what your laundry machines are doing to the world around you? We intend to provide information comparing multiple brands of laundry machines in terms of efficiency, electricity used, and water used. After comparing the machines we intend show what kind of environmental impact the machines have in terms of greenhouse gas emissions and carbon footprint.

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  Lights Out - An Exploration of Domination in Graph Theory

  Christian Steven Hemsath

  A graph is a mathematical object that consists of two sets: a set of vertices and a set of edges. An edge joins two vertices and depicts a relationship between those vertices. The following is a project for MTH 466 - Graph Theory and Combinatorics. Consider each vertex in a graph being associated with a light and with a button. Each push of the button will change the state of the light from on to off, or from off to on. Additionally, the state of each vertex joined by an edge to the vertex in question is changed. Given a graph with all vertex lights on, does there exist a set of light buttons which, when pressed, will turn off all vertex lights? An exploration of several examples of this question for different graphs is presented. It will also be proven that, for any connected graph, there exists a sequence of light buttons which when pressed will turn off all vertex lights.

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  Linkages In Mechanical Presses That Produce Substantial Dwell

  Matt Owen Deters, Zack James Jordan

  A mechanical press is a common manufacturing machine that is used to form and cut sheet metal. Presses can use mechanical, hydraulic, or pneumatic power to delivering a force over the stroke of the machine. The benefit of mechanical presses is the high stroking rate that can be achieved with low energy input while in use. Mechanical presses use a flywheel to store energy and a series of linkages to convert rotational motion into linear motion. Some forming operations like coining and squeezing benefit from a dwell at the bottom of the stroke, a position commonly referred to as bottom dead center (BDC). This research explores models for different mechanical systems that obtain this desired dwell. The designs presented include variations of a knuckle joint press mechanism and variations of a geared five bar with connecting rod and sliding output. Each of the mechanisms is being developed as a solid model and animation to assess the viability of the proposed designs.

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  Living with Loss: Resources Available to UD Students Grieving the Death of a Loved One

  Lexi Diane Brezovec, Henry A Kuechly, John R Moresea

  College students deal with a variety of stressors throughout their college experience. Several major stressors that arise on college campuses have been heavily researched and publicly addressed, while other stressors are ignored. One particularly prevalent overlooked stressor is the death of a family member or close friend of a student. Research has shown that anywhere from 22-30% of college students have experienced the loss of a close friend or family member within the past year. Additional research has shown that living with loss can negatively influence a students’ GPA and social life. Due to such a high percentage of impacted students, along with the impact on GPA and social life, we believe it is important to address this issue and what resources are available to University of Dayton (UD) students. Our research has primarily focused on the resources available at other universities as well as those resources available at UD. After conducting in person interviews and reviewing survey results, we have concluded that this topic is an issue that current UD students face. While many students are impacted by this issue, we discovered limited resources on UD’s campus to assist students in coping with this problem. Due to a lack of resources, our team will propose recommendations along with a brochure for students in order to aid in the grieving process.

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  Machine Learning for Cyberattack Detection

  Kayla D Chisholm

  Over the last two years, machine learning has become rapidly utilized in cybersecurity, rising from almost non-existent to currently over half of cybersecurity techniques utilized commercially. Machine learning is advancing at a rapid rate, and the application of new learning techniques to cybersecurity have yet to be investigated. The presented work discusses the use of novel machine learning algorithms for network intrusion detection. Typically, this type of network intrusion detection system operates based on a set of rules programmed to recognize known attacks and intrusion techniques. However, this detection method does little to prevent new, or ‘zero day’ attacks. On the other hand, a detection system that uses machine learning could analyze patterns in network data in real time to determine attack likelihood. To test the efficacy of machine learning and neural network algorithms for network security, we use publicly available data sets to ‘teach’ these neural systems what an attack may look like. After training, the system will be tested to determine how well it learned the features contained within the input data. Our results show accuracy and error rates of the algorithms that have been implemented.

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  Maternal Depression, Child Temperament, and Risk for Depression in Adolescence: A Test of the Differential Susceptibility Hypothesis

  Karina H Palermo

  This study examined the relationship between maternal depression, child temperament, and maternal parenting. Maternal depression has many effects on perceptions of and reactions to everyday interactions with the child (Belsky et al, 2007). Evidence has been found for depressed mothers reporting negative child behavior, while teachers report positive or neutral behavior in children of depressed mothers. Depression may skew a mother's understanding of her child's behavior. On the other hand, a child's difficult temperament may be especially challenging for a depressed mother. The depression, in combination with child difficult temperament, may cause changes in parenting styles that put the child at a greater risk for depression. The purpose of this study was to examine whether links between maternal depression and maternal parenting vary according to child difficult temperament. The identification of risk factors, such as difficult temperament or maternal depression, is important when trying to develop effective intervention strategies. It was predicted that maternal depression would be more strongly predictive of parenting deficits for mothers of children with a difficult temperament. This study used previously collected longitudinal data from a nationally representative sample of mothers and their offspring. Maternal depression before the birth of their child was measured using the CESD. Mothers reported on their children’s temperament between 1 and 23 months of age. Maternal parenting was assessed when children were between 3 and 5 years of age using a combination of an interview and observer ratings. Maternal depression showed a trend level association with decreased responsiveness (Beta = -.16, p = .076), and showed a significant association with increased harsh parenting (Beta = .15, p = .047) and decreased learning stimulation (Beta = -.14, p = .002). Fussy temperament did not moderate associations between maternal depression and parenting. These findings suggest that maternal depression is a risk factor for parenting characteristics that are associated with negative child outcomes, but that difficult temperament does not affect these associations.

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  Median Housing Prices in the Boston Area

  Danny Jeffrey Fleming

  This paper examines the relationship between housing prices and various demographic factors. In particular, the effect of several variables on the median price of houses in the greater Boston area was studied. The study uses independent variables such as crime rate, property tax rate, and house age. Stepwise regression analysis was used to determine which variables were most significant in predicting median house price. Variables such as crime rate, average number of rooms, and nitric oxide concentration were found to be statistically significant.

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  Medical Image Denoising with Deep Convolutional Neural Networks

  Zahangir Alom

  In the last few years, Deep Leaning (DL) approaches are applied in different modalities of Bio-Medical imaging application including classification, segmentation, and detection tasks. In addition, DL based generative methods are also used for image denoising and restoration tasks. In particular, the generative models have applied for enhancement and restoration of Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) images and achieved state-of-the-art performance for noise cancelation and restoration. In this work, we apply different generative model including Generative Adversarial Network (GAN), and denoising convolutional auto-encoder for bio-medical image enhancement problem. The experiments are conducted on different publicly available datasets for MRI and CT images. The experimental result shows promising outputs which can be applied for different applications in the modalities of MRI and CT.

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  Medical Image Segmentation using Deep Convolutional Neural Networks

  Zahangir Alom, Ranga Burada

  Deep learning (DL) has been evolved in many forms in recent years, with applications not only limited to the Computer Vision tasks, expanded towards Autonomous Driving, Medical Imaging, Bio-Medical Imaging including Digital Pathology Image Analysis (DPIA), and in many other forms. Deep Convolutional Neural Network (DCNN) methods such as LeNet, AlexNet, GoogleNet, VGGNet, ResidulaNet, DenseNet, and CapsuleNet within the DL has been very successful in object classification and detection problems on a very large scale publicly available data set. Due to the great success of these DCNN methods, researchers have explored these methods to other imaging areas such as medical imaging problems, where there is a greater need for automated computer algorithms to make the diagnosis quick and cost-efficient, specifically for image classification, segmentation, detection, registration, and medical image data processing. Several state of art methods that provided superior performance in medical image segmentation such as Fully Connect Networks (FCN), SegNet, DeepLabs, U-Net, V-Net, and R2U-Net have outperformed hand-crafted machine learning algorithms. These models have been tested on several medical imaging and DPIA data sets but have not been explored on multi-organ segmentation, so the primary goal of this proposal is to explore more on these state of art models and test on several publicly available multi-organ segmentation data sets. The quantitative and qualitative performance will be evaluated against existing models using different performance metrics including, Accuracy, Sensitivity, Specificity, F1-score, Receiver Operating Characteristics (ROC) curve, dice coefficient (DC), and Mean Squared Error (MSE).

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  Medical Imaging to Patient Specific Additively Manufactured Implant

  Monica M Yeager

  As of 2018, there are only standard sized, cast molded hips available to patients requiring hip implants. However, everyone has a unique body, so a cast molded hip implant will fit people differently. Personalized additively manufactured, or 3D-printed, implants created from a patient’s own computerized tomography (CT) or magnetic resonance imaging (MRI) images may provide numerous benefits. A main benefit would be that the implant would provide a personalized fit for the patient, as it would be made from scans of his or her own body. With a personalized fit, there would be reduced surgery and recovery time. For people with a physiological abnormality, a customized solution may be printed for reconstructive surgery. Another benefit would be for surgeons who could 3D print their patient’s bone for pre-surgical planning, such as planning screw placements. As the baby boomer population ages, the commercial market for 3D-printed joint replacements is expected to soar over the next decade. The goal of the research conducted here is to demonstrate a prototype process for patient specific, additively manufactured hip implants made from Digital Imaging and Communications (DICOM) images of human femur bone, leading to additional research on imaging of trabecular bone for biomimetic lattice development.

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  Mental-Health in School

  Reid Coleman Eschallier, Kaitlin B Lewis

  Anxiety has increased in students over the last few decades and has proven to affect their well-being and overall academic performance. One common factor that has increased stress-levels is the implementation of standardized testing. The pressure and weight that standardized tests put on students are detrimentally affecting their grades and overall health. In addition, certain demographics are being more negatively affected by standardized tests; therefore, putting specific groups at a disadvantage. As a result of increased anxiety, schools have started to address the need for programs that assess and assist students’ mental health. The first step many schools take is figuring out sources of anxiety for students. Educators and administrators have realized the importance of offering counseling for students as well as increasing awareness of mental health, as it has proven to lower anxiety levels. However, many obstacles still fall in the way of resources being available to all students, whether it be social pressures or outside factors that impact the school. As future educators, we are interested in researching why anxiety has increased in students in recent years, and how it can be addressed. We believe that teachers should help develop their students as people, not just focus on the student’s academic performance.

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  Microbial Resistance to Traditionally Medicinal Plant Extracts

  Emilee Kay Zoog

  Microbial resistance to pharmaceutical antibiotics is a growing problem in healthcare and animal husbandry that has led to hundreds of deaths from bacterial infections that could once be cured with antibiotics. Scientists are currently studying these resistance mechanisms and formulating novel treatments for bacterial infections, but exhaustive research of the antimicrobial properties of many common plants has yet to be established. In this study, I tested five traditionally medicinal plants common to the Dayton area including wild hydrangea, black haw, dandelion, mayapple (roots), and red clover for antimicrobial action against several strains of the human pathogens Listeria monocytogenes, Staphylococcus aureus, and Escherichia coli, using disk diffusion assays in aerobic and anaerobic environments. Each extract had antimicrobial activity against at least most of the pathogens tested, but each pathogen reacted variably to each extract, though antimicrobial activity in both oxygen environments were comparable. This suggests that there may be active compounds in plants with antimicrobial properties, in which case said compounds should be isolated and tested further in order to better understand bacterial defense mechanisms in plants, and what, if any, benefit these antimicrobial properties could have for humans with bacterial infections.

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  Micronutrients, hurricanes, and invasive species: insights into the micronutrient limitation and stress of an invasive ant along the coast of Texas

  Maddie Rose Kurlandski, Ryan William Reihart

  Human activities associated with climate change are rearranging the distribution of elements and species across the globe, but the consequences of these alterations remains unknown. Coastal ecosystems are likely at risk to an increase in the intensity and frequency of large tropical storms. These storms often deposit large amounts of micronutrients, which are less abundant in living tissue, and can affect the abundance and diversity of arthropods. Little is known, though, how additions of micronutrients can affect the success of consumers, especially invasive arthropods. To determine how changes in biogeochemistry affects litter arthropods, we utilized a factorial, fertilization experiment that manipulated macro- (N&P) and micronutrients (Ca, K, and Na; 16 treatments x 8 replicates = 128 plots), in 2016 and 2017, in large 30 m x 30 m plots in a coastal tallgrass prairie near Houston, TX. We collected litter arthropods using pitfall traps in 2017, and one year post-fertilization in 2018. Based on results from 2017, we conducted feeding trials, that manipulated the ratio of Ca:Na (by 10%, 25%, and 40%) in food, on an invasive ant, Nylanderia fulva in 2018. In 2017, N. fulva was the dominant litter arthropod across all treatments, and their abundance was limited by Ca, but tends to be suppressed by Na. In 2018, however, these effects disappeared as soil cations were likely leached from the soil, and abundance of N. fulva dropped 98%, likely due to Hurricane Harvey. Preliminary lab results show that manipulating the Ca:Na ratio in the food of N. fulva affects colony fitness, indicating that Na can reach toxic levels, suppressing colony size, while Ca ameliorates these toxic effects. These results indicate that changes in micronutrient availability may facilitate the success of an invasive species, and gives insight as to how human activities are altering coastal ecosystems.

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  Modeling Chaotic Population Dynamics with Feedbacks

  Christina Farwick

  While generating a model for a particular system typically relies on the ability to predict the behavior of the system at some arbitrary time, deterministic chaos measures the diversion from predictability: more chaotic implies more disorder, less chaotic implies more predictable. This work will employ Lotka-Volterra equations to describe the dynamics of biological systems. The bifurcation point is the point at which the system goes from stable to unstable. Thus, the objective of this project is to modify the existing Lotka-Volterra model and create bifurcation diagrams. Previous work shows that population dynamics depend heavily on feedback with the environment. Feedback will therefore be introduced as a new variable, and it is expected that the updated model will be able to describe chaotic-dynamics with feedback included.

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  Modeling of Nucleation-and-Growth in Macroscopic Systems Using Kolmogorov-Avrami-Johnson-Mehl (KAJM) Equation

  Ming Gong

  Many macroscopic (like lakes) and microscopic (like macromolecules) physical systems exhibit so-called nucleation phenomena, “collective growth” of patterns in the system. Nucleation could be illustrated as infinitesimal seeds of the stable phase from inside the unstable phase. The process of phase transitions, including continuous (second order) or discontinuous (first order), forms the nucleation. Moreover, the fact that the kinetics when the temperature is quenched from above to below the critical temperature is observed in continuous phase transitions. In reality, the formation of clouds, fog, rain, smoke from burning, ice crystals in the refrigerator, bubbles from soda and beer, etc. are all representatives of nucleation phenomena. Thus, nucleation is applicable everywhere from chemistry to climate science. The objectives of this work are to model nucleation and growth by applying Kolmogorov-Avrami-Johnson-Mehl (KAJM) equation based on the probability equation and to implement a computation algorithm to describe pattern growth.

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  Modified Ramsey Numbers

  Jack W Mccarthy

  This presentation is a project for the course MTH 466: Graph Theory and Combinatorics. A graph is a mathematical objects that consists of two sets: A set of vertices and a set of edges. An edge joins two vertices and depicts a relationship between those vertices. This project will explore a modified Ramsey number, the rainbow Ramsey number RR(F) of a graph F, which is defined as the smallest positive integer n such that if each edge of a complete graph--a graph containing all possible edges between its vertices--is colored from any number of colors, then either an F with edges of only one color (monochromatic) or an F with edges with no repeated colors (rainbow) is produced.

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  Modulation of Listeria monocytogenes Carbon Metabolism by Short Chain Fatty Acids

  Diksha Bedi

  Listeria monocytogenes, a bacterial pathogen, is associated with foodborne infections in humans. Listeria encounters short chain fatty acids (SCFAs) during its transit through the intestine but its metabolic responses to SCFAs are not fully understood. To determine how Listeria metabolism is affected by SCFAs, I performed basic microbiology assays, including monitoring optical density, determining acetoin production, and measuring culture pH levels. I also performed preliminary 13C-NMR assays to provide a more in-depth look into carbon metabolism in SCFA-treated Listeria. I found that propionate-supplemented Listeria produced significantly more acetoin compared to no supplemented controls. Because acetoin is a product of central carbon metabolism, my result suggests that Listeria is capable of changing its carbon metabolism in response to propionate. My preliminary 13C-NMR results have not revealed how carbon metabolism is altered by propionate and are under current investigation. Further investigation will provide more knowledge in the metabolic mechanism associated with Listeria responses to SCFAs during intestinal transit.

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  Money Supply Growth and Inflation Trends Post 2008 Recession: A Closer Look at the PCE Inflation Index

  Reed Thomas Aleck

  After the 2008 recession, the Federal Reserve initiated an aggressive policy of monetary easing. In this study, I examine the relationship between money supply growth and inflation using Personal Consumption Expenditures (PCE-All) as my measure of inflation. I develop univariate regression models with M1, M2, and MZM as the independent variables and PCE-All as the dependent variable. I test the hypothesis that the slope coefficients are positive and statistically significant (T-Stats > 2). I also forecast 2018 PCE-All inflation rates to determine the forecasting accuracy of the models. My forecasts also take into account the root mean square forecasting error (RMSE).