Throughout every liberation movement in America’s history, poetry has been an undeniably powerful act of resistance. Even today, protest poetry is instrumental to countless resistance movements because it captures attention, evokes emotion, and demands social progress. My project is divided into two parts. The first part is made up of five journals. These journals are informal written responses that conversate with different texts and analyze specific images within specific passages. My exploration of protest poetry focuses on five prominent poets of the last century: Langston Hughes, Maya Angelou, Gloria Anzaldúa, Camille T. Dungy, and Claudia Rankine. The second part of this project is my contribution to protest poetry. For my collection, I crafted ten poems in which I resist a range of issues that have to do with class, gender, and ethnicity. My protest poetry is also an examination of what it means to be human, particularly in modern day America.

Pathogenic drug resistance is a major global health concern. Thus, there is great interest in modeling the behavior of resistant mutations–how quickly they will rise in frequency within a population, and whether they come with fitness tradeoffs that can form the basis of treatment strategies. These models often depend on precise measurements of the relative fitness advantage (s) for each mutation and the strength of the fitness tradeoff that each mutation suffers in other contexts. Precisely quantifying s helps us create better, more accurate models of how mutants act in different treatment strategies. For example, P. falciparum acquires antimalarial drug resistance through a series of mutations to a single gene. Prior work in yeast expressing this P. falciparum gene demonstrated that mutations come with tradeoffs. Computational work has demonstrated the possibility of a treatment strategy which enriches for a particular resistant mutation that then makes the population grow poorly once the drug is removed. This treatment strategy requires knowledge of s and how it changes when multiple mutants are competing across various drug concentrations. Here, we precisely quantified s in varying drug concentrations for five resistant mutants, each of which provide varying degrees of drug resistance to antimalarial drugs. DNA barcodes were used to label each strain, allowing the mutants to be pooled together for direct competition in different concentrations of drug. This will provide data that can make the models more accurate, potentially facilitating more effective drug treatments in the future.