Affecting millions of Americans, depression is one of the leading causes of the Global Burden of Disease (GBD), followed by anxiety (Gibson-Smith et al., 2018). Communication that occurs between the human brain and the gut microbiome has been found to be a major contributor towards mental health. The human gut microbiome is comprised of many microbes that can communicate with the brain through the gut-brain axis. However, factors such as stress and diets can interfere with this process, especially after increasing the permeability of the intestine (Khoshbin et al., 2020). Perturbation of the gut-brain axis has been implicated across a wide scale of neurodegenerative disorders, with respect to psychopathology (Bonaz et al., 2018). The environment of the gut, along with which species reside there, can help determine the link between gut function and disease. Therefore, it may be possible to prevent the degradation of an individual’s immune function and well-being through alteration of the gut microbiome. (abstract)
This thesis looks at how Latinx communities in Wyoming, despite recognizing the impossibility of overcoming the traditional conservative autocracy, still utilize their identity as a political response to unify Latinx communities throughout the state. The project draws from oral histories conducted with Latinx/Chicanx community members in Wyoming, including professors, legislators, and everyday citizens.
The field of biomedical research relies on the knowledge of binding interactions between various proteins of interest to create novel molecular targets for therapeutic purposes. While many of these interactions remain a mystery, knowledge of these properties and interactions could have significant medical applications in terms of understanding cell signaling and immunological defenses. Furthermore, there is evidence that machine learning and peptide microarrays can be used to make reliable predictions of where proteins could interact with each other without the definitive knowledge of the interactions. In this case, a neural network was used to predict the unknown binding interactions of TNFR2 onto LT-ɑ and TRAF2, and PD-L1 onto CD80, based off of the binding data from a sampling of protein-peptide interactions on a microarray. The accuracy and reliability of these predictions would rely on future research to confirm the interactions of these proteins, but the knowledge from these methods and predictions could have a future impact with regards to rational and structure-based drug design.
Uniforms and logos are an essential part of sports teams and are created with the intention of representing the city and state of their respective teams. More than a uniform: How culture influences the creation of Arizona sports logos and jerseys presents a look at the conversations and processes undergone before teams are able to unveil their new threads. Four local professional teams are involved with this project: Phoenix Suns, Arizona Diamondbacks, Arizona Coyotes and Arizona Cardinals. Members from each of the organizations were interviewed, in addition to Greg Fisher of Fisher Design. Information was gathered from each of those interviews in addition to research done on the history of each of the team’s uniforms. The information was then created into a documentary that consists of visual and verbal components. The film highlights how each team attempts to represent Arizona and its culture when it comes to what they are wearing on the field, court or ice. The interviews capture the mindset of creative teams as they explore growing new ideas and looks, in addition to a historical delve into two of the team’s debuts in the 1990s. Many of Arizona’s sports teams have much more behind their logos and jerseys than meets the eye. The project taught me how adapt broadcast skills into documentary style storytelling and how important visuals are for longer features. The interviews showed that so many things are taken into consideration when designing a sports logo or uniform and the process can take either months or years to finally reach fruition.
The COVID-19 pandemic began in March of 2020 and drastically affected the global human population. Millions of people died due to a SARS-CoV-2 infection while many who survived developed devastating sequelae of the disease. In addition, the closure of schools and businesses led to international economic struggle in the year 2020 as global economies declined. Since the beginning of the pandemic, over 200,000 scientific articles have been published and compiled into a database that grows daily— a rare occurrence within the scientific community. This thesis uses natural language processing tools via Python and VOSviewer software to perform a bibliometric analysis on 205,712 papers published between January of 2020 and February of 2021 pertaining to COVID-19. We first investigate how to analyze these publications most effectively in terms of title versus abstract keyword searches, we further obtain the focus of the current scientific literature via co-occurrence analysis and clustering, and we at last discuss the time evolution of these topics over the course of 14 months.