Autoimmune Neuromuscular Disorders

Autoimmune neuromuscular disorders affecting peripheral nerves, neuromuscular junction or muscle have a wide clinical spectrum with diverse pathogenetic mechanisms. Peripheral nervous system may be targeted in the context of complex immune reactions involving different cytokines, antigen-presenting cells, B cells and different types of T cells. Various immunomodulating and cytotoxic treatments block proliferation or activation of immune cells by different mechanisms attempting to control the response of the immune system and limit target organ injury. Most treatment protocols for autoimmune neuromuscular disorders are based on the use of corticosteroids, intravenous immunoglobulins and plasmapheresis, with cytotoxic agents mostly used as steroid-sparing medications. More recently, development of specific monoclonal antibodies targeting individual cell types allowed a different approach targeting specific immune pathways, but these new treatments are also associated with various adverse effects and their long-term efficacy is still unknown

Crop pests and predators exhibit inconsistent responses to surrounding landscape composition

The idea that noncrop habitat enhances pest control and represents a win–win opportunity to conserve biodiversity and bolster yields has emerged as an agroecological paradigm. However, while noncrop habitat in landscapes surrounding farms sometimes benefits pest predators, natural enemy responses remain heterogeneous across studies and effects on pests are inconclusive. The observed heterogeneity in species responses to noncrop habitat may be biological in origin or could result from variation in how habitat and biocontrol are measured. Here, we use a pest-control database encompassing 132 studies and 6,759 sites worldwide to model natural enemy and pest abundances, predation rates, and crop damage as a function of landscape composition. Our results showed that although landscape composition explained significant variation within studies, pest and enemy abundances, predation rates, crop damage, and yields each exhibited different responses across studies, sometimes increasing and sometimes decreasing in landscapes with more noncrop habitat but overall showing no consistent trend. Thus, models that used landscape-composition variables to predict pest-control dynamics demonstrated little potential to explain variation across studies, though prediction did improve when comparing studies with similar crop and landscape features. Overall, our work shows that surrounding noncrop habitat does not consistently improve pest management, meaning habitat conservation may bolster production in some systems and depress yields in others. Future efforts to develop tools that inform farmers when habitat conservation truly represents a win–win would benefit from increased understanding of how landscape effects are modulated by local farm management and the biology of pests and their enemies

Modeling with Time Gaps : Application to UW-Eau Claire Housing Incidents

Color poster with text and graphs.The purpose of this project is to develop a framework for time series analysis on data sets which have long known periods of missing information. Such a situation presents itself when trying to predict judicial code violations in the UW-Eau Claire residence halls during the fall and spring semesters. This project presents a way to predict the number of students involved in these violations based on past observations and future known conditions. The effects of a full moon, homecoming, finals week, weekends, and semester breaks on the prevalence of students involved are considered and quantified. Time lags accounting for weekly and daily auto-correlation as well as a yearly moving average are incorporated. Because data is unavailable for summer and winter sessions, special consideration is made in the model for the beginnings of semesters. Better understanding the patterns of on-campus incidents over time will contribute meaningful insights for hall directors, resident assistants, and entities who support and protect students. In addition, this study can inform disciplines like sports analytics as well as other areas in which large time gaps might also be encountered when implementing time series analyses.University of Wisconsin--Eau Claire Office of Research and Sponsored Program

Neuronal Intranuclear Inclusion Disease Causing Homonymous Hemianopia

Neuronal intranuclear inclusion disease (NIID) is a rare, progressive neurodegenerative leukoencephalopathy associated with eosinophilic neuronal hyaline intranuclear inclusions. NIID is a difficult diagnosis to make, as the disease presents at varying ages, with varying inheritance patterns, and with various forms of central/peripheral/autonomic neurologic dysfunction. Previously reported ophthalmologic findings of NIID include miosis, nyctalopia, nystagmus, electroretinogram abnormalities, and retinal degeneration. Though the genetic basis for most NIID cases remains unknown, skin biopsy is sensitive for diagnosis. We report a patient who presented with visual hallucinations and a homonymous hemianopia from adult-onset NIID, which is a unique presentation

Baseball Analytics : Further Modeling

Color poster with text, images, charts, and graphs.Baseball has long served as a frontrunner for the integration of analytics with application, connected in part to the consistency of historical statistics as well as the widespread interest in the national professional and more local semi-professional sport leagues. This project builds on prior data-exploration and data-gathering for the local Northwoods League, with recognition of a reduced set of available technical information (as compared to MLB). The intention is to create a WAR calculation for the league using the available data. The original WAR statistic in the MLB uses data that is unattainable for the NWL. Therefore, this project attempts to modify the WAR statistic with reasonable substitutes to make it accessible for the NWL. The two primary focuses of the current project are modeling and coding generalization. Coding generalization summarizes the structure of the available data organization as well as discusses functions written to compute necessary inputs for the metrics, including different portions of the WAR analogy. With the adjustments and additional back-computations of metrics for individual players, we now have sufficient available information for modeling these player utilities. We summarize the modeling results found by connecting information about: player-by-game appearance, season-break information, refined player utility estimates, and use of reconfigured statistics.University of Wisconsin--Eau Claire Office of Research and Sponsored Program

Tracking COVID Locally and Adaptively

Color poster with text, charts, and graphs.In summer 2020, the project started with the faculty mentor created a dashboard to visualize and summarize information about local COVID data. Skills developed include learning a new programing package dplyr in R and hosting code on GitHub, which were then applied in preparatory work such as building new data frames and calculations. Thus, we will discuss a predictive time series model with lagged counts for future outcomes (such as hospitalizations), built on age-grouped case-counts to account for the disparities in outcomes observed for different ages in the COVID pandemic.University of Wisconsin--Eau Claire Office of Research and Sponsored Program