A Walk Through the ExEL Co-Curricular Internship Process

This presentation will focus on the Experiential Education Internship process that the Office of Career Development has created for students. We will dive into a step-by-step journey of a student and what they go through to show the beginning, middle, and end stages of an experiential internship. We will share best practices on how to incorporate intention and reflection into the process to ensure that the experience aligns with a student’s academic and career goals

Tritons United: Against Gender-Based Violence Campus Programming

Tritons United Against Gender-based Violence is a programming grant funded by the Department of Justice office on Violence Against Women. This presentation will introduce the UMSL community to grant activities and the work I have supported throughout this semester as an undergraduate research assistant on the project. The project is led by a Coordinated Community Response Team (CCRT) that includes key members both within and outside the UMSL campus and in the surrounding community from professionals in areas of victim services, prevention & education, law enforcement/safety, and student conduct. The overall goal of Tritons United is to reduce gender-based violence and promote victim safety by increasing trainings & education on college campus, and to complete campus campaign events promoting victim services, effective responses, and safety protocols following a gender-based event on UMSL campus. This presentation will discuss current and upcoming activities to support gender-based violence prevention and education at UMSL. Opportunities for collaboration and engagement with the CCRT will be provided

Developmental course of autistic social impairment in males

BACKGROUND: Recent research has suggested that autistic social impairment (ASI) is continuously distributed in nature, and that subtle autistic-like social impairments aggregate in the family members of children with pervasive developmental disorders (PDDs). This study examined the longitudinal course of quantitatively-characterized ASI in 3 to 18 year old boys with and without PDD. METHODS: We obtained assessments of 95 epidemiologically ascertained male-male twin pairs and a clinical sample of 95 affected children using the Social Responsiveness Scale (SRS), at two time points, spaced 1–5 years apart. Longitudinal course was examined as a function of age, familial loading for PDD, and autistic severity at baseline. RESULTS: Inter-individual variation in SRS scores was highly preserved over time, with test-retest correlation of 0.90 for the entire sample. SRS scores exhibited modest general improvement over the study period; individual trajectories varied as a function of severity at baseline and were highly familial. CONCLUSION: Quantitative measurements of ASI reflect heritable trait-like characteristics. Such measurements can serve as reliable indices of phenotypic severity for genetic and neurobiologic studies, and have potential utility for ascertaining incremental response to intervention

Machine Learning for the New York City Power Grid

Power companies can benefit from the use of knowledge discovery methods and statistical machine learning for preventive maintenance. We introduce a general process for transforming historical electrical grid data into models that aim to predict the risk of failures for components and systems. These models can be used directly by power companies to assist with prioritization of maintenance and repair work. Specialized versions of this process are used to produce (1) feeder failure rankings, (2) cable, joint, terminator, and transformer rankings, (3) feeder Mean Time Between Failure (MTBF) estimates, and (4) manhole events vulnerability rankings. The process in its most general form can handle diverse, noisy, sources that are historical (static), semi-real-time, or real-time, incorporates state-of-the-art machine learning algorithms for prioritization (supervised ranking or MTBF), and includes an evaluation of results via cross-validation and blind test. Above and beyond the ranked lists and MTBF estimates are business management interfaces that allow the prediction capability to be integrated directly into corporate planning and decision support; such interfaces rely on several important properties of our general modeling approach: that machine learning features are meaningful to domain experts, that the processing of data is transparent, and that prediction results are accurate enough to support sound decision making. We discuss the challenges in working with historical electrical grid data that were not designed for predictive purposes. The “rawness” of these data contrasts with the accuracy of the statistical models that can be obtained from the process; these models are sufficiently accurate to assist in maintaining New York City's electrical grid

“A General Separation of Colored and White”: the WWII riots, military segregation, and racism(s) beyond the White/Nonwhite binary

This article uses archival research to explore important differences in the discursive and institutional positioning of Mexican American and African American men during World War II. Through the focal point of the riots which erupted in Los Angeles and other major cities in the summer of 1943, I examine the ways in which black and Mexican ‘rioters’ were imagined in official and popular discourses. Though both groups of youth were often constructed as deviant and subversive, there were also divergences in the ways in which their supposed racial difference was discursively configured. I also consider the experiences of each group in the WWII military, a subject that has received little attention in previous work on the riots. Though both groups were subject to discrimination and brutality on the home front, only African Americans were segregated in the military - a fact that profoundly influenced the 1943 riots. Examining the very different conditions under which these men served, as well as the distinct ways in which their presence within the military and on the home front was interpreted and given meaning by press, law enforcement and military officials helps to illuminate the uneven and complex workings of racism in America, disrupting the common conceptualization of a definitive white/nonwhite color line

Mitochondrial Dysfunction and Apoptosis in Cumulus Cells of Type I Diabetic Mice

Impaired oocyte quality has been demonstrated in diabetic mice; however, the potential pathways by which maternal diabetes exerts its effects on the oocyte are poorly understood. Cumulus cells are in direct contact with the oocyte via gap junctions and provide essential nutrients to support oocyte development. In this study, we investigated the effects of maternal diabetes on the mitochondrial status in cumulus cells. We found an increased frequency of fragmented mitochondria, a decreased transmembrane potential and an aggregated distribution of mitochondria in cumulus cells from diabetic mice. Furthermore, while mitochondrial biogenesis in cumulus cells was induced by maternal diabetes, their metabolic function was disrupted as evidenced by lower ATP and citrate levels. Moreover, we present evidence suggesting that the mitochondrial impairments induced by maternal diabetes, at least in part, lead to cumulus cell apoptosis through the release of cytochrome c. Together the deleterious effects on cumulus cells may disrupt trophic and signaling interactions with the oocyte, contributing to oocyte incompetence and thus poor pregnancy outcomes in diabetic females

Call for emergency action to restore dietary diversity and protect global food systems in times of COVID-19 and beyond: Results from a cross-sectional study in 38 countries

Background: The COVID-19 pandemic has revealed the fragility of the global food system, sending shockwaves across countries\u27 societies and economy. This has presented formidable challenges to sustaining a healthy and resilient lifestyle. The objective of this study is to examine the food consumption patterns and assess diet diversity indicators, primarily focusing on the food consumption score (FCS), among households in 38 countries both before and during the first wave of the COVID-19 pandemic. Methods: A cross-sectional study with 37 207 participants (mean age: 36.70 ± 14.79, with 77 % women) was conducted in 38 countries through an online survey administered between April and June 2020. The study utilized a pre-tested food frequency questionnaire to explore food consumption patterns both before and during the COVID-19 periods. Additionally, the study computed Food Consumption Score (FCS) as a proxy indicator for assessing the dietary diversity of households. Findings: This quantification of global, regional and national dietary diversity across 38 countries showed an increment in the consumption of all food groups but a drop in the intake of vegetables and in the dietary diversity. The household\u27s food consumption scores indicating dietary diversity varied across regions. It decreased in the Middle East and North Africa (MENA) countries, including Lebanon (p \u3c 0.001) and increased in the Gulf Cooperation Council countries including Bahrain (p = 0.003), Egypt (p \u3c 0.001) and United Arab Emirates (p = 0.013). A decline in the household\u27s dietary diversity was observed in Australia (p \u3c 0.001), in South Africa including Uganda (p \u3c 0.001), in Europe including Belgium (p \u3c 0.001), Denmark (p = 0.002), Finland (p \u3c 0.001) and Netherland (p = 0.027) and in South America including Ecuador (p \u3c 0.001), Brazil (p \u3c 0.001), Mexico (p \u3c 0.0001) and Peru (p \u3c 0.001). Middle and older ages [OR = 1.2; 95 % CI = [1.125–1.426] [OR = 2.5; 95 % CI = [1.951–3.064], being a woman [OR = 1.2; 95 % CI = [1.117–1.367], having a high education (p \u3c 0.001), and showing amelioration in food-related behaviors [OR = 1.4; 95 % CI = [1.292–1.709] were all linked to having a higher dietary diversity. Conclusion: The minor to moderate changes in food consumption patterns observed across the 38 countries within relatively short time frames could become lasting, leading to a significant and prolonged reduction in dietary diversity, as demonstrated by our findings

Determinants of penetrance and variable expressivity in monogenic metabolic conditions across 77,184 exomes

Penetrance of variants in monogenic disease and clinical utility of common polygenic variation has not been well explored on a large-scale. Here, the authors use exome sequencing data from 77,184 individuals to generate penetrance estimates and assess the utility of polygenic variation in risk prediction of monogenic variants

Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care