American Foulbrood (AFB), a disease of honeybee larvae caused by the bacterium Paenibacillus larvae, has global economic significance. AFB spreads through colonies killing the next generation of bees. AFB has traditionally been treated with antibiotics or by burning infected hives and exposed materials. The former method is complicated by antibiotic resistance and bacterial sporulation, while the latter method carries severe financial liability for beekeepers. One alternative treatment is the use of bacteriophages, viruses that infect and destroy bacteria. Bacteriophages are host-specific and co-evolve with their host, unlike antibiotics, thus making resistance and collateral damage a non-issue. Characterizing these phages will be key to future treatments of infected hives. The P. larvae phage Willow, isolated in our lab, is both lysogenic (allow the infected bacterium to survive) and lytic (kill the infected bacterium). Currently, we have confirmed Willow lysogeny in P. larvae strain 3650. This relationship presents a model system for investigation. A comprehensive understanding of the host-pathogen interactions between Willow and P. larvae will aid in the effective targeting of P. larvae in the field. Our laboratory also seeks to determine the relatedness of four P. larvae phages to Willow to further characterize the genes responsible for lysogenic/lytic decision making. In sensitivity assays, lysogens (bacteria with integrated phage) are plated to form a lawn and dilutions of a different phage are spotted onto the plate. An identical wild-type plate is made, and comparison yields plating efficiencies. Plating efficiency determines what degree of protection is offered by the integrated phage. I hypothesize that genetic sequencing will show measurable genetic differences in the putative C1/Cro region of the phages under investigation, and that all genome sequence similarity will correlate directly with established plating efficiencies. Furthermore, I used sequence alignment, product alignment, and dot-plots to illustrate the degree of sequence similarity between phages.

Jephthah’s Daughter (Op. 53), a concert aria for soprano and orchestra written by Amy Beach (1867-1944) in 1903, has long suffered neglect due to the fate of its manuscript and the fate of Beach’s work in general. This investigation seeks to probe how Beach engaged the Biblical subject matter and mid-1800s French text in her setting. I discuss this engagement through stylistic comparison with the musical traits of her other work, translation comparison between the literal meanings of the original poem and Beach’s English rendition, and contextualization of Beach’s setting within the history of how this story has been interpreted. The aria fits within Beach’s dramatic Romantic style and deliberate molding of text, and tells a story with notable connections to her life and work. Because of the extent to which Beach’s life story aligns with that of Jephthah’s daughter, Beach’s own statements on music as autobiography, and her choice to engage this story in such depth, I argue that this aria may express lament for Beach’s own suppression as a female composer in Victorian society. This reading provides further support to a narrative of Beach’s life which examines the negative impact of her patriarchal context.

Augmented reality is a promising field of study which aims to enhance our daily experiences by overlaying digital information into our view of the world, thus “augmenting” our perception of reality in useful ways. A key component of AR is computer vision which enables a computer to map and interpret the physical world. My proposed experiment will examine the effectiveness of several computer vision algorithms in balancing a pendulum attached to a movable cart. A camera, suspended by the pendulum, will collect observational data and relay this information to a microcontroller. Then I will utilize Hough Transform and Canny Edge Detection algorithms to recognize stable lines/edges in the environment, so a reference frame can be constructed in which to balance the pendulum. As the pendulum tips and the camera begins to fall, the system will compare the input frame to the reference frame and adjust the cart accordingly via servo motors. My research will compare several methods of video tracking and object recognition as well as SLAM (Simultaneous Localization and Mapping) as viable options to balance and orient systems with the real world. By designing a system that dynamically responds to its environment using visual cues, I aim to contribute to a critical component in the realization of emerging technologies such as autonomous vehicles, domestic robots and augmented reality systems.

Patients and providers are beginning to use patient generated-health data (PGHD) to collaborate to understand patient routines, identify health problems, and tailor treatment strategies. However, current technology designs fail to support key aspects of collaboration, including planning, data collection, review, and analysis. Among all the health data people track, food data is essential for preventing and managing many health concerns. Although numerous tools exist to help people track and understand their diet and its consequences, these tools are often high burden, can lead people to focus on what is easily tracked rather than what is most relevant for their health, and fail to support effective collaboration between providers. In this study, we designed, developed, and deployed novel food tracking diaries to support healthy eating and the management of irritable bowel syndrome (IBS). Eighteen people with healthy eating goals used the food diaries for at least two weeks, and then worked with their health providers to plan changes to their diet. Sixteen IBS patients used the IBS version of the diary for at least nine days and then worked with providers to identify food triggers and plan changes. We interviewed patients and providers and observed their collaborations. The photo-based food diaries we designed supported patient-provider communication for both healthy eating and IBS. Compared to traditional food diaries, the photo-based food diaries make data collection, review, and analysis easier for patients and providers. However, patients and providers described scenarios when specific nutritional information -- beyond what they can see in photos -- helped the diagnostic or management process, such as when identifying IBS triggering nutrients. Our research will lead to better use of PGHD to give patients more tailored, accurate, efficient and informed treatment plans. Our results also inform the design of  food diaries that will better support people with different various health goals.

G Protein-Coupled Receptors (GPCRs) are seven-transmembrane proteins present throughout the body that can be activated upon binding of drugs, hormones, or neurotransmitters. Acting like an inbox for messages, these multi-protein complexes play a significant role in the body by regulating cell expression and signaling, making them attractive targets for drug development. One class of GPCRs, known as the adrenergic receptors (ARs) are critical in modulating the function of numerous targets, including cardiac muscle, vascular smooth muscle, and bronchial smooth muscle. There are nine AR subtypes: three α1s, three α2s, and three βs. In my research, I focus on deciphering the interactions of proteins with the α1D-AR due to a recent publication of the Hague Lab, which discovered that α1D-AR forms a multi-PDZ protein complex. To determine the participants of this complex and identify the presence of associated proteins, I first purified the proteins that potentially bind to α1D-AR. In my purification process, I first conducted Polymerase Chain Reactions (PCRs), transformed my bacteria, grew my bacteria, and finally purified my proteins of interest. With this information, my lab and I intend to identify the complexes using mass spectrometry and Octet. Determining how α1D-ARs are organized can create a deeper understanding of how drugs work in the body and assist in new drug development.

Every year there are at least one million new cases of sport-related concussion in children younger than 18 in the United States. Current diagnostic screening tools, such as CT and MRI, are insensitive to the subtle microstructural changes that occur following concussion, and in pediatric concussion, there is additional complexity of the still-developing brain and how concussion affects its long-term development. While these patients’ radiographic images often appear normal, they report an array of post-injury symptoms, which questions the true extent of brain injury after concussion. The aim of this research project is to utilize advanced neuroimaging and analysis tools, diffusion tensor imaging (DTI) and graph theory, to explore short-term and longitudinal changes in the brain following pediatric sports concussion and to obtain a more reliable and sensitive method to diagnose pediatric concussion. Children aged 10 – 14 with unresolved symptoms from a sports-related concussion and age-matched controls were included in this study. Each participant underwent MRI scans and clinical assessments 4-6 weeks post-injury and 6 months after the initial visit . We used DTI, which has been shown to be sensitive to microstructural changes related to concussion in adults. In addition, we analyzed the DTI data using graph theory, which is a mathematical tool that models information as a network. We investigated differences in network properties between concussed and non-concussed children and used random generated networks as a control. We confirmed that the network properties of children were distinct from random networks. We also observed a 9% reduction in global clustering and 16% increase in local connectivity in the concussed patients, suggesting overall network disconnect and stronger, but more segmented, local network groups. These preliminary results encourage further exploration of the methods employed and display clinical relevance in distinguishing between concussed and non-concussed youth. 

Imidacloprid (IMI), a neonicotinoid, is being sought as an alternative to the carbamate pesticide, carbaryl to control burrowing shrimp (ghost shrimp, Neotropea californiensis) in Willapa Bay and Grays Harbor, Washington. The shrimp destabilize sediments resulting in poor survival and low yields of the commercially harvested Pacific oyster (Crassostrea gigas). Previous laboratory tests indicate juvenile and adult ghost shrimp are overtly affected (immobilized) when exposed to IMI in artificial seawater (SW) at concentrations expected during control operations, but not killed and subsequently recover. Our objective was to determine if emamectin benzoate (EB) is an alternative to IMI. EB, the active ingredient (a.i.) in Slice®, is currently registered for use in marine waters for the control of sea lice on farmed salmon. We targeted juvenile shrimp because they are likely more sensitive than adults and reside within the upper 10-15 cm of the sediment facilitating control. In an initial test to determine the effective range, we exposed juvenile ghost shrimp (mean carapace length = 2.3 mm) to static concentrations of EB (as the insecticide Proclaim®) ranging from 0.01 to 100 ppb a.i. within artificial SW for 96 h. All shrimp within the 100 ppb treatment died within 48 h and 27% exposed to 10 ppb succumbed by 96 h. In a subsequent 96-h test (static 48-h renewal), we exposed juveniles (mean carapace length = 2.1 mm) to concentrations of EB ranging from 10 to 100 ppb to determine the median lethal concentration (LC50). All shrimp exposed to 100 ppb died within 24 h. The 96-h LC50 was 18.8 ppb compared to >12,000 ppb for IMI. EB may provide more effective control than IMI because it targets the primary neurophysiology of the shrimp. Further tests are required to determine effective concentrations within sediment, assess potential non-target effects, and evaluate environmental fate.

There is low economic incentive to pursue treatment and cure research and development for rare diseases; this leaves millions of patients living with rare diseases understudied and undertreated. With the inception of groups such as the Undiagnosed Diseases Network (UDN) there is now a wealth of rare disease patient data. One way to increase the number of diagnoses, and hopefully treatments, would be to use the data already available to identify disease causing genes and potentially treatments as well. It has been shown that the integration of network-interaction and genetic data can further our understanding of disease pathways and genes. We investigate how to unify rare disease patient data from sources like UDN and Protein-Protein Interaction (PPI) data to identify potential novel gene candidates on the individual patient level. We developed a pipeline integrating patient genetic data and PPI that shows promise in identifying novel disease genes. For one of our patients, our pipeline predicted a very compelling disease gene and their clinician was notified of our finding. In other cases, no disease genes were identified. These findings suggest that our pipeline shows promise but further optimization and validation are necessary. As more data becomes available and sequencing technologies become more inexpensive, we hope that our pipeline will be more accessible and find use to undiagnosed patients and their clinicians around the world.

The alpha-1D adrenergic receptor (A1DAR) is a G-protein coupled receptor (GPCR) and is known for its function as a regulator for cardiovascular, urinary, and central nervous system function. This unique GPCR has a PDZ ligand at the C-terminus of this receptor. A PDZ ligand is a region on a protein that can bind to a PDZ domain on another protein and is named based on the three proteins that it was observed in. Previously, it has been discovered that this ligand interacts with the syntrophin family of PDZ domain proteins. The hDLG1 protein is a human homologue of the Drosophila disc large (DLG1) tumor suppressor protein and contains three PDZ domains that have been implicated in interacting with A1DARs. By determining how/if the PDZ domains on the hDLG1 protein bind to the A1DAR, a more accurate depiction of this macromolecular complex can eventually be determined. Several methods were used in order to determine this. First, I cloned hDLG1 PDZ domains separately as well as varying combinations of the three domains. Next, I purified the protein constructs so I could determine the binding efficiency of the hDLG1 proteins to the A1DAR via Bio-Layer Interferometry (Octet). SNAP gel assays can also be used to determine the interaction with the A1DAR. Upon reviewing the results of these techniques, the nature of the interaction between the PDZ domains of the hDLG1 protein to the A1DAR can be determined. Understanding the architecture of this structure has many implications in pharmaceuticals as this protein can be specifically targeted by medications to treat a multitude of diseases. Side effects can be minimized by targeting specific parts of this large protein complex with medications than produce more specific responses thus limiting unwanted side effects. Medications that target the proteins involved in this complex can affect the function of the cardiovascular, urinary, and central nervous system.

This research focuses on the mathematics of gerrymandering. Gerrymandering refers to how political parties draw district boundaries to give them better odds at receiving a majority during congressional elections. Every 10 years district boundaries in the United States are redrawn for congressional elections by the current majority party. With such change in political cartography, redrawing district boundaries not only affects who wins but also the people who live within them. Given the loosely defined criteria for redistricting, we seek to quantify the process of redrawing district lines to determine when this partisan process becomes an act of manipulation and exclusion. We will be use The Metropolis Hastings (M.H.) Algorithm to produce a random walk that has a stationary distribution that will be the probability distribution of all possible districting plans for a given U.S state. By collecting congressional maps and election results, we implemented the M.H. algorithm in python to produce sample spaces for Washington State and Iowa. We will simulate local and federal redistricting requirements using self-defined parameters which measure: compactness of districts, population division, division of counties, and minority voter populations. We simulated election results with respect to our sample districts and compared the simulated outcomes with actual district maps and their election results. This study helps to determine if current redrawn maps legitimately reflect the people they purport to represent or if they are manipulations and subversions of our democratic process.

Organic electronics have generated wide interest and excitement because they are relatively inexpensive to produce and are created from abundant resources, unlike their inorganic counterparts. Many organic materials also possess the unique potential of being stretchable in electronic applications including solar cells, OLEDs, and transistors. These materials can be made into wearable electronic devices and have the potential to power other advanced technology. Organic electronics are often made using semiconducting polymers. However, these polymers are semi-crystalline and brittle in solid state. To enhance their stretchability, our approach is to incorporate stretchable rubber into the semiconducting material by chemically linking the two polymers to combine their properties. This research investigates the crosslinking the well-known semiconducting polymer P3HT, poly(3-hexylthiophene), with polybutadiene (PB), a common rubber, to create a stretchable semiconducting material. To make crosslinking possible, we synthesize P3HT that includes a functional bromine to produce P3HBrT, poly(3-(6-bromohexyl)thiophene). Once the P3HBrT is synthesized, it can then be crosslinked with PB at different ratios to optimize for conductivity and stretchability. The crosslinked P3HBrT/PB can then be made into a thin film transistor and characterized for the desired properties. Ultimately, future research in this area will lead to a new generation of electronic devices with improved material properties.

Ultrasonic transducers are key components in the probes of ultrasound devices used for medical imaging. The probe consists of 4 different materials; a piezoelectric element, backing material, an acoustic matching layer and an acoustic lens. The properties of these materials will directly impact the performance of the transducer and the quality of the images produced, making them a high priority for future development. Currently, researchers at Siemens Healthineers are looking to develop new materials for our ultrasound probes to help increase device performance and make better ultrasound devices. This senior capstone project looks to develop the Acoustical Properties Measurement System (APMS), a characterization testing system, to aid in the production of the new transducer materials. Development of new MATLAB and LabView code has been carried out to provide a smoother operating experience and enhanced design simulation. Data storage has been revised to provide a single location for users to access all collected data and a new naming system has been implemented for easier sample tracking. A standard operating procedure has also been established to help aid new users in operation of the system and a new method for measuring high attenuation materials has been developed. These improvements to the APMS system will further benefit the research and development of Siemens Healthineers ultrasound devices, providing customers and their patients with provide accurate diagnoses and help them to make the best decisions for their care.

Organic materials show promise as alternative materials for many modern-day electronics applications, such as transistors, LEDs, and photovoltaics. They hold many advantages over their inorganic counterparts, such as being lighter weight, lower cost, and flexible. Self-healing polymers are a specific form of organic polymer that are particularly promising because of their potential use in flexible devices. Self-healing materials have the capacity to spontaneously reform damaged bonds, thereby returning the material to its original state and recovering its initial properties. Imine bonds are a type of self-healing bond. Imines have a highly dynamic nature, allowing for the reshuffling of bonds required to recover material properties. Much research has been done on the use of imine bonds in self-healing polymers; however, no work has been done utilizing imine bonds for self-healing in semiconducting polymers. To incorporate self-healing behavior into a semiconducting polymer, we have investigated the synthesis of a poly(azomethine), a semiconducting polymer with an imine bond along the backbone. Initially, as a proof-of-concept for the dynamic exchange of bonds in our specific system, we reacted aniline with 2-thiophenealdehyde to form an imine. Then, to determine if bond exchange occurred, the imine produced was reacted with another amine. The reaction showed that a significant amount of imine exchanged, so we moved on to a polymer system. We synthesized 4,4'-dinitrotriphenylamine, which we then reduced to produce a diamine species. This diamine was then polymerized with a dialdehyde species, resulting in a fully conjugated polymer with multiple imine bonds along the backbone. The polymer will be made into thin films for testing. Mechanical properties will be investigated to determine initial film properties. Additionally, transistors will be produced to see if electrical properties can be recovered after the film has been damaged.

Solar energy has unmatched potential as the energy source of the future and semiconducting polymers offer a unique set of properties that can address many of the current barriers that hold solar technology back. Little work has been done investigating bulk film microstructure formation, but the ability to control and engineer defects opens the door to new applications that employ tunable energy levels and adjustable open circuit voltage and short circuit density. Semiconducting polymers are exciting because they have untapped potential for improvements in efficiency, they offer a cheap, energy efficient alternative to silicon, and can be easily mass produced via roll-to-roll printing. Solution processing via roll-to-roll printing is transformative as it allows for low energy, high throughput manufacturing of flexible devices. This research focuses on generalizing structure-property relationships for semiconducting polymers and investigating the locations and causes of crystalline defects. The goal is to extrapolate measurements made at a nanometer scale on self-assembled poly(3-hexylthiophene) (P3HT) nanowires to larger production of bulk films. Current understanding of polymer crystallization is built on two competing models, both of which were developed for non-conjugated, therefore non-semiconducting polymers. The Luscombe group has previously demonstrated that the crystalline defects, such as unfavorable monomer arrangement (regioregularity), bulky end groups, the range of polymer lengths (dispersity) and the specific polymer length (degree of polymerization (DP)) do not affect nanowire width, meaning defects are not excluded to the perimeter of the nanowires. This research isolates the variable of polymer length and controls other defects. Using X-ray diffraction and differential scanning calorimetry, nanowires synthesized from polymer lengths ranging 50 to 150 DP have been tested for melting temperature, level of crystallinity and dimensions to determine where the defects reside. Once this is understood, we can confirm which model for conjugated polymer defects is correct.

Organic photovoltaic (OPV) cells are an emerging technology with the potential to become a major source of energy in our future. In addition to a lower environmental impact than common silicon-based solar cells, OPV cells are flexible, lightweight, and comparably inexpensive to fabricate. They are also quite customizable via molecular engineering providing the opportunity for much novel architecture. Our research team focuses on innovating a modular processing system for OPV cells in the form of multi-component fibers by continuously coating device layers onto wires. Using a small, user-friendly system allows us to focus on the most important factors that affect the morphology of the resulting OPV fiber. After characterizing the fibers we are able to consider what changes need to be made to the modular system, allowing us to better advise on the design of a larger-scale manufacturing process for organic photovoltaic fibers.

Roughly 20% of young adults in the United States experience some sort of mental health disorder. The majority of this research has focused on young adults in general or 4-year college students, however less is known about the mental health and coping strategies of young adults not currently attending school. The purpose of this study was to compare mental health, the use of alcohol and/or other substances as a coping mechanism for stress, and alcohol and marijuana use among young adults who attend 4-year colleges and those not attending school. A subsample (N=552; 56% female, 59.5% White, M age=20.58, SD=1.7) of young adults using baseline data from a larger longitudinal study on health behaviors was used for the current analyses. The subsample included 355 students currently attending 4-year college and 197 young adults not attending school (highest education status of these individuals included less than a high school diploma (1.5%), high school diploma (19.3%), some college (15.2%), 2-year degree (10.1%), 4-year college degree (52.8%), and graduate degree (1%). Findings indicated that young adults not in school reported significantly higher rates of depression, anxiety, and perceived stress in the past month than students in 4-year colleges. Similarly, findings indicated that non-students reported being high from marijuana for more hours, higher rates of alcohol use and coping with stress through alcohol and/or substance use in the past month than 4-year college students. Further research is needed, which focuses on young adults who are not currently attending 4-year colleges as they may face different life stressors and cope differently than 4-year college students.

This research attempt proposes a novel approach to processing and utilizing aerial imagery and data for mapping. With the advancement of unmanned aerial systems (UAS), airborne data has gained considerable momentum in recent decades, revolutionizing methodologies of geographic research, law enforcement, agriculture, and mapping. Specifically, advances in consumer electronics significantly eased access to UAS and development in parallel computing has enabled machine learning on large data sets. This paper proposes an alternative method to the current practice of processing airborne data sets. Instead of obtaining aerial imagery of an object and merely presenting those objects as pixels on a map, the proposed method uses machine learning techniques to recognize the object, assign parameters to the object and render the object in a fashion that is most efficient and understandable to the end user. The object is no longer merely a set of pixels but a list of classified objects with associated parameters, an abstraction analogous to cognitive processes. This approach allows a single data set to be used in multiple fashions. For example, the data can be used to simulate changes in the environment or render the environment in different scenarios. This paper explores the methodology for collecting airborne data sets for this process and presents several cases of this using flight test data.

On top of being iconic symbols of climate change, glaciers integrate year-to-year precipitation and temperature variability, which can mask their response to a climatic trend. For this reason, it is vital to identify the variability in their records to better detect regional climate change. With time-varying sea-level pressure (SLP) and sea-surface temperature (SST) fields, we examine the influence of natural climate variability on 14 glaciers in the North Atlantic region by using a statistical method called dynamical adjustment. The SLP and SST fields each explain 50-60% of variance in the winter mass-balances and 30-40% in the summer mass-balances of the maritime glaciers. The continental glaciers are less closely linked to oceanic variability, with SST explaining roughly 30% of variance in winter and summer mass-balances. The glaciers located further south fluctuate with the North Atlantic Oscillation (NAO) in the winter, while glaciers near the Arctic show influence from the Atlantic Multidecadal Oscillation (AMO) in the winter. To investigate how this variability affects glacier trends, adjusted mass-balances are compared to observational mass-balances with no signs of variability forcing trends. The observed and adjusted summer mass-balance trends of the southern glaciers are significantly negative, while the observed and adjusted winter mass-balances of the northern glaciers are significantly negative. This indicates that winter trends are more likely to emerge in glaciers near the Arctic, while summer trends are more likely to emerge in glaciers further south which is consistent with surface temperature time of emergence for global warming.

Hydrogen sulfide (H₂S) is a gas most commonly known for its pungent scent and toxicity. However, administered in low doses, H₂S can be tolerated, and it can even facilitate the acclimation to higher doses in the nematode Caenorhabditis elegans, a model organism with relatively short generation times and extensive tools for genetic manipulation. Furthermore, H₂S could have important medical uses due to its function as a vasodilator and chemical signal in cellular signaling, such as conserving donor organs, extending the time prior to an ischemic response, and decreasing nociception in severe injuries (Miller, and Roth). Data from our lab suggest that a low dose exposure to H₂S during early stages of development forms a “bookmark” which permits the survival of the animal at high doses of H₂S during adulthood. Through a genetic screen, epigenetic factors including spr-5, set-2, swsn-4, and swsn-1 were discovered to be involved in the bookmark. The ease of bookmark formation and the short time between formation and manifestation of phenotype present a unique opportunity to dissect a complete epigenetic pathway in addition to understanding cellular responses to H₂S. Our project aims to develop tools that will help understand temporal and spatial requirements for the protein products of these bookmarking genes. To achieve this, we intend to use CRISPR to attach a tag to the endogenous loci of target genes that allows for auxin-induced degradation (AID) (Zhang, L. et al.). Our targets will include both bookmarking genes and previously identified H₂S response elements such as hif-1. Thus far, we have tested the efficiency of the tag on Green Fluorescent Protein (GFP). Presently, we are working to create the transgenic lines of nematodes that carry the AID tag alongside proteins involved in the formation or maintenance of the H₂S bookmark.

In some locations (e.g., refugee camps or rural areas in countries like Haiti), fecal waste systems are not water-based, but resemble a pit latrine, for which current sampling and processing methods were not designed. The fecal waste is collected and held, often under poor infrastructure. The fecal sludge management process is important to consider for environmental surveillance, as this may be the only source for screening. This surveillance is important for the continued eradication of poliovirus (PV). The goal of my research was to develop a method for PV extraction from sludge in pit latrines for use in locations with concentrated fecal waste. Towards this goal, I modified two existing protocols for extraction of various viruses from different solid media and applied them to evaluate virus recovery from primary sludge. The first (M1) was originally designed to recover hepatitis A from oysters, while the second (M2) was originally developed to extract somatic coliphages from sewage sludge. The modified methods were evaluated using primary sludge collected from a wastewater treatment plant in Seattle and spiked with the vaccine strain of poliovirus type 1 (PV1). Virus recovery was assessed by a plaque assay. M1 involved acid adsorption followed by glycine elution, threonine elution, skimmed milk flocculation, vertrel and threonine extractions. For M2, liquid and solid fractions were initially separated by centrifugation. Processing of the solid fraction involved beef extract elution, sonication, skimmed milk flocculation, and vertrel extraction, while the liquid fraction was concentrated using membrane filtration and beef extract elution. The preliminary data indicate that M1 may have a higher recovery, and therefore be the preferred method for use during environmental surveillance of poliovirus. Future work should include additional replicates and optimization of the preferred method. 

Osteoarthritis, a disease in which the cartilage that cushions joints is lost, affects 27 million people each year. Ankle arthroplasties, or total ankle replacements —i.e., replacement of joint surfaces with artificial materials— have become the procedure of choice for many end-stage ankle arthritis (ESAA) patients. The purpose of this study is to compare foot joint kinematic differences in end-stage ankle arthritis patients pre- and postoperative to receiving a total ankle replacement. Hypotheses over the recovery period include (1) increased range of motion in joint and planar angles, (2) negative correlation between patient pain and ankle function, and (3) ankle function converging towards that of normal gait patterns. Twenty adults with ESAA scheduled for ankle arthroplasty surgery were evaluated preoperatively and at 12 and 24 months postoperatively. A validated five-segment foot model was applied to the affected limb using retro-reflective markers. The model allowed for five three-dimensional joint angles and eight planar angles to be calculated. Subjects completed follow-up surveys self-assessing function and pain preoperatively and at 3, 6, 12, and 24 months postoperatively. Results are limited as the longitudinal study is still ongoing. Thus far, mean joint rotations show increased range of motion at the ankle joint, decreased range of motion between the midfoot and forefoot, and decreased toe splay during the stance phase of gait 24 months postoperative. Correlation between patient pain and ankle function show a trend in decreasing ankle range of motion with increased patient pain, both preoperatively and 24 months postoperatively. Patient pain also significantly decreased between every survey administration time point. These findings will likely aid ESAA patients when considering ankle arthroplasty surgery, informing them about expected recovery and comparing trade-offs between pain and function. Future work includes the ongoing collection of control data for comparison.