Tuberculosis (TB) remains the world’s deadliest infectious disease, claiming over 1.25 million lives annually—surpassing malaria and HIV in mortality. TB’s causative pathogen, Mycobacterium tuberculosis (MTB), continues to spread rapidly due to inadequate access to accurate molecular diagnostic tests. The most commonly used tests include sputum-based and tuberculin skin tests, which require follow-up visits and have suboptimal sensitivity, particularly within certain patient populations. Moreover, these assays cannot identify emerging drug-resistant strains (DR-TB) that have reduced susceptibility to first-line antibiotics. Our aim is to design a diagnostic tool to detect cell-free DNA (cfDNA) in urine and identify the infecting strain to ensure patients receive appropriate antibiotics. To achieve this, we are developing a probe-ligation assay with single-nucleotide specificity. Current implementations are limited by the low specificity of ligase, leading to false positives and an inability to differentiate between mutated MTB strains. We hypothesized that Flap Endonuclease-1 (FEN1) could confer a specificity advantage by integrating a second enzymatic “check” into the process. The protocol involves a ligation reaction with MTB genome-derived targets and two probes, each containing a DNA flap with additional nucleotides. To detect the ligated product, FEN1 must cleave these flaps before the ligase catalyzes the repair of the nick between probes. To experimentally observe this, we carried out several ligation reactions containing FEN1 and ligase with wild-type and mutant targets, followed by PCR or gel electrophoresis to measure ligated product formation. We evaluated the efficiency and precision by analyzing the amplification profiles of WT targets and mutants containing SNPs neighboring the ligation site. Our data about whether FEN1 confers a significant specificity advantage remains inconclusive, but the double enzyme reaction is functional and could be further exploited in future experiments with additional optimization or modifications to enzymes or DNA probes.

With the rising popularity of TikTok and its role in widespread information sharing, and concerns about political misinformation on the platform, studying political discourse through immersive ethnographic methods leading up to the 2024 US Presidential Election was imperative. This study, conducted over 12 weeks in the summer of 2024, aimed to uncover the rhetorical and ideological topics and trends salient to Black Republican and Democratic TikTok creators through content analysis. To capture the distinct feeds that a person interested in right-leaning or left-leaning content may see, two partisan personas were created on separate phones. The personas were developed from a seed list of known partisan creators and snowball sampling. A quantitative content analysis was conducted using LabelStudio software on a sample of 120 acquired videos from Black creators across the two research phones. The videos were coded for style, topic, and person of interest, alongside other inductive attributes that emerged during the coding process. Thematic analysis revealed key discursive themes around harm and blame, along with different tactics of evidence used by creators to further their points. We find a divide between left- and right-leaning creators with regard to the institutions and politicians they hold accountable for harms, and the ideologies they perceive being pushed by the oppositional party. This study shows how the affordances of the TikTok platform allowed for, and algorithmically rewarded, infighting within the Black community leading up to the election. Future studies may apply these methods of persona-enabled ethnographic data collection for conducting bipartisan investigation on other online communities, including but not limited to racial minority groups, in gaining a better understanding of prevalent issues within these communities, political or otherwise.

The increasing rise in allergy prevalence has led to a growing demand for portable allergen testing devices. Food allergens, which can lead to fatal immune reactions, are especially complicated to avoid due to cross contamination and food mislabeling, as seen with many types of seafood. Instances of seafood mislabeling and inauthenticity also impacts consumers financially when cheaper options are passed off as more rare and expensive fish. Atlantic salmon is one of the most commonly used fish for this type of fraud. Devices to detect allergens and/or authenticity must be easy-to-use, quick, and require little to no dangerous reagents for the regular consumer. While there are some commercial devices on the market for peanut and gluten detection, they are costly and do not appear to be very accurate or sensitive. Our prior work showed a proof of concept for a one-pot amplification-detection method with recombinase polymerase amplification that allowed for a reaction to occur at a fixed temperature and with no expensive laboratory equipment. Currently, I am developing fluorescence-based polymerase chain reaction and recombinase polymerase amplification assays that can differentiate Atlantic salmon from other types of salmon. To further develop this technology into a consumer-friendly allergen detection and seafood authentication device, I plan on adapting the assay into an electrochemical format, allowing for simplified readouts of the results. The results from this assay would be able to be displayed on easily accessible electronic devices, such as a smartphone or laptop. In its final form, this project will demonstrate a portable heating device with a classification assay that would be able to detect the presence of Atlantic salmon without laboratory equipment.