"Unplug your devices" BU Libraries Sustainable Practices Posters

These posters were created to encourage the BU community to develop sustainable practices

Party hats "congrats grads 2020" posters

These posters were created to celebrate the achievements and graduation of Boston University's class of 2020

"Red and white confetti" Happy New Years poster

These posters were created to wish students at BU a happy new year

"Orange Snapchat Ghost" Librarians Won't Ghost You Posters

These posters were created to encourage BU students to ask a librarian for help with research, an essay, or another assignment

"Fall colors" Thanksgiving Food Drive posters

These posters were created to encourage the BU community to participate in a food drive to help families in the Boston area around Thanksgiving

Integration of Mao-B Inhibitor Rasagiline into Computational Model of Levodopa for the Treatment of Parkinson\u27s Disease

Parkinson’s Disease (PD) is the second most common neurodegenerative disorder in the world after Alzheimer’s. The hallmark symptoms of PD are tremor and rigidity, which are caused by the death of dopaminergic neurons, specifically within the substantia nigra of the basal ganglia. These symptoms are often treated by Levodopa (L-DOPA), MAO-B inhibitors, and other pharmaceuticals with the goal of increasing the dopamine concentration in the brain. To better understand how L-DOPA impacts the brain’s dopamine dynamics, various computational models have been developed. One model, by Véronneau-Veilleux et al. (Chaos 30, 093146, 2020), integrates L-DOPA pharmacokinetics, dopamine dynamics, and a neurocomputational model of the basal ganglia to predict the impact of L-DOPA regimens on a patient\u27s motor function. In this study, we extended the model to investigate an adjunct therapy of L-DOPA with the MAO-B inhibitor Rasagiline utilizing an enzyme inhibition model, which showed a 1.67% increase of dopamine concentration in the brain when compared to L-DOPA therapy alone. Our model provides a foundation for optimizing treatment strategies using both L-DOPA and an adjunct

Taking the Second Step: Section 924(C) Sentencing Disparities as an Extraordinary and Compelling Reason for Compassionate Release

This Note argues that courts are empowered to, and should, grant compassionate release based solely on the sentencing disparities created by the First Step Act -- specifically, the significant changes to § 924(c)\u27s sentencing scheme. [...] Part I of this Note provides background on the two relevant sections of the First Step Act: changes to the compassionate release process and changes to the § 924(c) sentencing scheme. Part II examines recent district court opinions addressing § 924(c) sentencing disparities as extraordinary and compelling reasons for reduced sentences. Part III argues that courts are empowered to grant compassionate release to inmates convicted of multiple § 924(c) charges under the old sentencing scheme because of the sentencing disparities the First Step Act created. Finally, the Note concludes by urging courts to take the second step Congress was unwilling to take itself. This abstract has been adapted from the author\u27s introduction

Modeling purple sea urchin and California sheephead populations in southern California kelp forests

In this project I am modelling the predator-prey relationship between California sheephead and purple sea urchin populations, respectively, in kelp forests off the coast of southern California. The Lotka-Volterra equations explain predator-prey relationships in their most basic form. These equations incorporate a set of biological assumptions that can be unrepresentative of many ecological systems. I will consider alternate models that incorporate variations of the Lotka-Volterra model which may better represent the biology of the purple sea urchins and California sheephead. Using biological characteristics of both species in kelp forests, I will set possible and likely parameters and solve for unknown parameters. After constructing the models, I will fit each model to the population data. Once I have fit each model to the data, I will compute various error estimations using four possible objective functions and determine the model of best fit

Sustenance Abuse: Anorexia, Bulimia, and & Black Women

Food had become my drug.” Thus writes Stephanie Covington Armstrong, a bulimia survivor—and black woman. Contrary to popular belief, eating disorders are not limited to wealthy white women trying desperately to achieve a bone-thin summer body. In fact the National Eating Disorder Association (NEDA) reports that black women are actually 50% more likely than white women to show signs of bulimia (“Statistics & Research on Eating Disorders”). But black eating disorder patients are often undiagnosed and under researched. Many black women have attested that their symptoms were not taken seriously by medical professionals, and even official research papers and medical reports claim a low prevalence of disordered eating among black women. However, black women are indeed suffering from disordered eating. The question is why? Despite common perceived correlations between eating disorders and body image, eating disorders among black women have more to do with self-harm and unhealthy coping mechanisms

Screening Ocean Samples from Georgia for the Presence of MSX and Dermo Using PCR and qPCR Methods

This Senior Thesis project aimed to be able to screen samples that came in from a PhD student in Georgia for the presence of two oyster diseases, MSX and Dermo. This study was done using PCR followed by visualizing on E-gels for initial presence of disease. These were then followed by qPCR and visualization on Criterion gels. These Criterion gels were able to be analyzed in order to calculate the pg/uL of MSX and Dermo in the original ocean samples. Since the samples were sent in over the course of February-August ‘21 the presence over time was also able to be tracked. It was shown that the diseases are either present in less high volumes or absent entirely in the earlier winter months, with an increase in rates in the spring and summer. They showed that the diseases are mostly prevalent in the spring months