Food insecurity is a major issue within the United States. Millions of households experience limited food availability, especially in regions deemed food deserts. Food deserts are geographical regions across the United States that possess limited access to grocery stores or supermarkets, and thus limited access to healthy food options. Individuals living in food deserts are at an increased risk of developing a mental illness, including depression, bipolar disorder, Alzheimer’s Disease, and Attentional Deficit Hyperactivity Disorder (ADHD). Mental health is often associated with one’s environment or genetic susceptibility, and treatments are often focused on psychotherapeutic methods and prescription medication. In investigating food deserts and diets characteristic of food deserts, one can begin to make connections between food and mental health. Dietary patterns that exhibit greater concentrations of fats and sugars are associated with many of the symptoms of common mood disorders and are significant in producing biological indicators, like inflammation, which is identified in various neurodegenerative disorders. Brain foods like vitamins and omega-3 fatty acids among others, provide a unique lens into the ways the food and the brain interact, specifically through a concept termed the gut-brain axis. Research surrounding these connections, especially in a newer field called nutritional psychiatry, inform the ways in which researchers, scholars, and medical professionals understand mental health and food insecurity. These connections may also prompt future research in the field focused on food-based treatments and the use of food as a preventative form of medicine.

We attempted to apply a novel approach to stock market predictions. The Logistic Regression machine learning algorithm (Joseph Berkson) was applied to analyze news article headlines as represented by a bag-of-words (tri-gram and single-gram) representation in an attempt to predict the trends of stock prices based on the Dow Jones Industrial Average. The results showed that a tri-gram bag led to a 49% trend accuracy, a 1% increase when compared to the single-gram representation’s accuracy of 48%.

Maternal morbidity and mortality rates in the United States continues to rise, with a wide range of contributing factors such as mental illness, cardiovascular disease and systemic inequality. This metastudy provides a holistic view of the research that has been published on the issue of U.S. maternal healthcare from 2000-2022. The patterns of publications on specific topics over time can tell us what is perceived as a current major cause by physicians, public leaders, researchers, and the public. A deeper dive into systemic inequality as a cause of maternal morbidity and mortality highlights it as a major contributor to these high rates, but that progress is slowly being made through the implementation of detection and prevention tactics, as well as accessible prenatal programs and care.

The field of veterinary medicine can be rewarding, but also very demanding. Research has shown that many practicing veterinarians struggle with mental illness, and the profession has one of the highest suicide rates in the United States. Research has also shown that many veterinary students struggle with mental illness. It is important to further research the mental health of veterinary students and how that can correlate with one's mental health as a practicing veterinarian. The purpose of this project is to summarize findings of the literature concerning the mental health of veterinary students and to present a new resource, the Wisdom Vet app, that can potentially support the well-being of veterinary students.