The Fermilab Muon g-2 experiment seeks to measure the anomalous magnetic moment of the muon to 140 ppb. A highly purified beam of muons is delivered to a magnetic storage ring in bursts of ~15,000 muons called fills. The rate of change of the angle between a muon’s momentum and spin while orbiting in the storage ring is the anomalous precession frequency, which is directly proportional to the anomalous magnetic moment. During each fill, muons orbit in the storage ring until they decay into positrons which spiral into electromagnetic calorimeters stationed around the ring. Positrons which impact the calorimeter deposit their energy in the calorimeters as Cherenkov radiation. The time dependance of the positron energy spectrum is used to extract the anomalous precession frequency of muons in the storage ring. “Early to late effects” are a class of systematic uncertainty in the experiment which result from coherent changes of experimental conditions within each fill. These effects can directly bias the measured anomalous precession frequency. One such effect arose from malfunctioning resistors in the ring’s electrostatic quadrupoles, resulting in non-ideal vertical focusing of the muon beam. This led to coherent downward motion of the beam during each fill. This directly couples into one of the largest systematic effects, as the calorimeter acceptance depends in part on the beam's vertical position. Using data from the calorimeters, I quantified early to late change in the beam’s vertical position and vertical distribution. These results were used to cross-check results from simulation programs. If the Fermilab Muon g-2 experiment retains the same central value as the previous generation measurement but with 140 ppb precision it will be in greater than 5-sigma tension with standard model calculations. Results from Run 1 of the experiment are expected to be published in early 2021.

With the rise of social media and video sharing platforms, many people are turning to sources like Youtube as their main source of information. However, these platforms have become easy targets for misinformation campaigns. Credibility is hard to ascertain on a video sharing platform like Youtube come from the wide base of content creators. On a typical Google search for a topic, the leading sources are usually mainstream-media companies. However, on Youtube, it is significantly easier for an individual person, or channel, to overtake mainstream media and become popular. There is also no standard way for creators to display credibility factors or cite their sources on video-sharing platforms. This leads to creators using a workaround to cite sources or simply foregoing citations all together. The implications of this for viewers is that they are unable to quickly identify the credibility of the source without cross-referencing other places on the web, or lateral reading. Currently, the only standardized information displayed about a channel is its display name, profile picture, subscriber count, and occasionally a verification indicator. The verification indicator, in particular, can be misleading as it only indicates whether a channel is who they claim to be. This project is researching and developing citations for Youtube videos. Video citations will allow creators to display credibility within individual videos and allow viewers to conduct lateral reading with ease. Citations specific to this format could also take on advantages of social media platforms, specifically user ratings and collaborative creation of citations. There are many possibilities in how citations can be introduced that we will explore through this project, each with pros and cons. For instance, sharing and creating credible videos could contribute to the pre-existing communities currently on Youtube through crowd-sourcing citations.

Copy number variants (CNVs) are typically a result of chromosomal duplications and deletions, making them a well-known form of genetic diversity and associated with several human disorders. Little is known about CNVs within humans and insight into CNV mechanisms would help scientists better understand, and potentially treat, many genome-based diseases. A particular form of CNV within humans is the inverted triplication of a gene without any chromosomal deletions. A similar phenomenon is observed at the SUL1 gene in Saccharomyces cerevisiae yeast cells, providing a model for studying such CNVs. The Brewer lab proposed a replication error mechanism responsible for this specific amplification described as Origin Dependent Inverted Replication Amplification (ODIRA). What impacts the initiation of this mechanism is unknown, but the proximity of SUL1 to the telomere raises the possibility that properties of the telomere may stimulate replication errors responsible for the triplication. I conducted a literature review analyzing 11 articles discussing various CNV mechanisms and telomeric influence on replication to establish their relationship. Through my review, I found a likely method to test whether the telomere does affect ODIRA. I propose utilizing a CRISPR-Cas9 based method to first circularize and eliminate the telomeres of the chromosome. Subsequently, the chromosome would be linearized at a location distant from the original telomere sites, effectively moving the entire SUL1 site away from potential telomeric influence. This research design allows for a comparison of SUL1 amplification events within the original and the restructured chromosomes and would reveal whether the telomeric region influences inverted SUL1 amplification formation. An observed reduction in rates of SUL1 amplification events with the reconstructed chromosomes would indicate telomeric influence on the amplification mechanism prompting further examinations within that genomic region. Attaining a greater understanding of this CNV mechanism yields information for future implications in genetic disease research.

Network goodness of fit (GOF), which deals with determining if an observed network could have been drawn from a particular graph model, is a common method to identify network structures and a prerequisite of further network analysis. In this talk, we will present a method that constructs a test statistics using advances in Random Matrix Theory, which traces the limiting behavior of the leading eigenvalue of the observed graph's adjacency matrix to perform network GOF. We show that under many network models - such as the Degree Corrected Stochastic Block model (DCSBM), the Beta model, and the Aggregated Relational Data (ARD) - our method performs well in identifying the correct model with high precision and low computation time. We further extend our method to the popular Latent Space model, and develop an algorithm that fast-and-accurately predicts the underlying dimension of the true model. With precision grows with network sizes, our algorithm enables better estimations for large-scale networks with minimal computational cost.

A mesoporous silica (MPS) membrane is an ultrathin permeable material characterized by numerous and uniform embedded pores whose sizes are on the order of 2-3 nanometers. MPS membranes are widely used in a number of research and industrial applications such as biomedicine for the isolation and characterization of macromolecules including DNAs and proteins. Such membranes can be synthesized in a variety of ways including electrodeposition. In our research, we have been developing an electrochemistry-based method for the preparation of ultrathin MPS membranes ranging from 50 to 150 nm in thickness. These membranes are synthesized on an electrode by a novel pulse deposition process and can be transferred onto other solid supports. A highly sensitive single-molecule analysis platform is being developed based on the use of such MPS membranes. We anticipate that our MPS membranes will find extensive use in future applications ranging from single-molecule analysis to high efficiency purification of macromolecules and other small biomolecules of interest.

Glioblastoma (GBM) is a cancer originating in glial cells in the brain that accounts for more than 60% of all brain tumors in adults. The low survival rate can be attributed to high resistance to radiotherapy due to the hypoxic tumor environment which induces signaling networks in cancer cells that lead to the epithelial to mesenchymal transition (EMT). EMT gives rise to mesenchymal cancer stem cells (MSC) with a highly invasive phenotype which resists traditional means of therapy. Phospholipid glutathione peroxidase (GPX4), a selenocysteine-containing enzyme that dissipates lipid peroxides, has been shown to regulate pathways that prevent ferroptosis, a unique iron dependent form of cell death initiated by an increase in reactive oxygen species. Disrupting the GPX4 pathway by siRNA-induced gene knockdown induces ferroptosis. Therefore, NPs as a vector for gene therapy may be able to eliminate mesenchymal state stem cells for a more effective treatment. Using hypoxia to induce EMT to develop a cell model for this work, preliminary results from quantitative real time PCR showed a correlation between GPX4 and EMT markers of human glioblastoma cells in hypoxia. GPX4 siRNA were evaluated using commercially available transfection agents on hypoxic and normoxic cells as proof of concept in vitro over a period of ten days. NP mediated delivery of validated siRNA were optimized using different ratios of NP and siRNA. Incubation time was also optimized. Finally, dual therapy of siRNA knockdown and radiotherapy were performed to evaluate sensitization of cells. The capabilities of NPs, along with concurrent radiation therapy, may provide a means to overcome radioresistance in GBM therapy.

CD8+ T-cell exhaustion during chronic human immunodeficiency virus (HIV) infection is characterized by increasing expression of inhibitory markers on the cell surface that lead to decreased effector function and dampened immune responses that are essential to achieving therapeutic vaccine efficacy. Inhibitory marker PD-1 is upregulated on exhausted CD8+ T-cells, and blockade with a monoclonal antibody (aPD-1) can help reverse exhaustion. We hypothesized that dosing with aPD-1 would boost the immune system and decrease expression of other exhaustion markers throughout infection to improve therapeutic vaccine responses. To investigate this hypothesis, we studied how exhaustion progresses over time in simian-human immunodeficiency virus (SHIV)-infected Rhesus macaques treated with a novel combinatorial therapeutic regimen consisting of a conserved-elements vaccine to circumvent viral mutants, GS986 to reverse latency, CCR5 gene editing to prevent viral entry, and aPD-1 to reverse CD8+ T-cell exhaustion. We characterized exhaustion in peripheral blood mononuclear cells and mesenteric lymph nodes with surface staining and flow cytometry, with a focus on exhaustion markers PD-1, TIGIT, CTLA-4, LAG-3, and TIM-3 at various timepoints throughout infection and vaccination. Although we observed no differences in viral burden between treatment groups, we observed higher CD8+ T-cell vaccine responses in animals receiving aPD-1 compared to vaccinated animals that did not receive aPD-1, suggesting aPD-1 improved vaccine responses. Although we did not find a correlation between PD-1 signaling and any exhaustion markers, we observed a significant negative correlation between CD8+ T-cell vaccine responses and pre-vaccination TIGIT levels (Spearman r= -0.75, p=0.007). We also found that PD-1 and TIGIT are largely independently expressed on CD8+ T-cells. Taken together, these data suggest a role for dual blockade of PD-1 and TIGIT to improve vaccine efficacy in future studies. Defining the impacts of CD8+ T-cell exhaustion on therapeutic vaccine immunogenicity is crucial to improving combinatorial immunotherapy towards a cure for HIV.

Nucleic acid vaccines introduce DNA or mRNA into cells in vivo, instructing them to express antigens from a pathogen resulting in the induction of immune responses that can provide long term protection from that pathogen. They provide many advantages over traditional vaccines including lower cost, improved safety, and the possibility to rapidly update the vaccine since only the genetic sequence of a new variant is required. One drawback of DNA vaccines has been their relatively poor immunogenicity compared to traditional vaccines which has been overcome, to some extent, by using improved delivery methods and co-formulation with plasmids expressing cytokines as adjuvants. Previous studies have established IL-12, as the “gold standard” genetic adjuvant due to its ability to support differentiation of antigen specific CD4+ T cells to produce Th1 cytokines as well as expansion of antigen specific CD8+ T cells to be more cytolytic in vivo. There is growing interest in identifying other adjuvants that not only increase immunogenicity of DNA vaccines but also modulate the types of responses they induce. In this study, we sought to determine if co-administration of an adjuvant cocktail including IL-18, a pro-inflammatory cytokine, and IRF7, a transcriptional activator of type I interferons, along with IL-12 would enhance antibody responses to DNA vaccines expressing SIV and Influenza antigens in a preclinical nonhuman primate model. Plasma samples were collected at different times post vaccination and the effect of the adjuvants on immunogenicity was measured via IgG ELISA and analyzed. After 2 vaccinations, we observed a significant increase (P=0.0272) in antibody responses against SIV gp130 in the adjuvant cocktail group compared to the IL-12 group. These results indicate that combining adjuvants could provide further improvement in DNA vaccine immunogenicity. Additional studies to determine the impact of this adjuvant cocktail on T cell responses are in progress.

 The methionine salvage pathway (MSP) is a set of metabolic reactions that is highly conserved among species. The SPE3 gene of the budding yeast Saccharomyces cerevisiae, characterized as essential for growth, encodes spermidine synthase, which catalyzes the 3rd enzymatic step of the MSP and is involved in biosynthesis of spermidine. We investigated the effects of mutations in SPE3 and other genes of the MSP by comparing strains containing mutations in genes encoding for different MSP enzymes. Diploid heterozygotes were created via mating, and double mutants were created via knockout PCR, transformation, and recombination. Cell growth rate, viability, vacuolar morphology, and genetic relationships were analyzed via growth curves, viability tests, microscopy, and spot test assays. We found that SPE3 knockout haploid (spe3Δ) mutants are viable with a generation time unaffected by growth in minimal media. We also show that SPE3 mutations result in a hindered ability to respond to stressors. Characterization of these mutant strains and their responses to stressors will lead to better understanding of spermidine biosynthesis and the functions of the Spe3p enzyme and other MSP enzymes in S. cerevisiae.

Misinformation, media containing misleading or inaccurate information, is an increasingly prevalent and complex issue in society. There has been lots of previous work to classify misinformation, but none have contextualized it in terms of its harms to people, groups, and society. Misinformation can also have disparate harms and impacts on different groups: political disinformation campaigns often target underprivileged groups to attempt to disenfranchise them, while recent coronavirus misinformation has significantly affected marginalized groups. Misinformation may vary in the scope of their societal harm: some harassment may target specific individuals with misinformation, while others can cause a broader societal effect, such as through the loss of trust in public institutions. We propose to develop a taxonomy that classifies types of misinformation according to their potential for harm to aid efforts to address the effects of misinformation effectively. We also start with specific examples from two domains: elections and public health. We aim to interview fact-checkers early about what factors they consider when deciding to fact-check specific content, as they often must triage and select incoming media, and harness their intuitions in terms of potential negative impacts of misinformation. After this, we will develop a survey and survey a broad demographic of people to obtain initial results. From the survey data, we will develop a taxonomy of harms related to misinformation and iterate on the taxonomy with more people to get feedback. Our harm taxonomy can help fact-checkers triage incoming misinformation and prioritize which needs to be checked first. It also offers an explicit characterization of different types of intended harms, which may be useful when considering what kind of response is warranted. Finally, it lays a groundwork for improvement of machine learning systems that could better aid human review.

Speech and language delays are often underdiagnosed in infants, although it is well established that children who receive intervention at an earlier age achieve better communication outcomes. Utilizing parent surveys of infant speech and language abilities may be a strategy that could enable the earlier identification of infants at risk. However, at what age early signs of delay emerge is not well understood. This study investigates whether measures of language ability obtained by both parent report and direct testing at 3 months are associated with language abilities at 11 months of age. We assessed receptive and expressive language skills longitudinally in 20 infants at 3 and 11 months of age. To obtain direct measures of language skills, the Mullen Scales of Early Learning (MSEL) was administered. To obtain parent report measures, the Vineland Adaptive Behavior Scales – Third Edition (Vineland) and the MacArthur-Bates Communicative Development Inventories (CDI) were administered. To interpret our results in the context of socioeconomic status, the Hollingshead Four Factor Index of Socioeconomic Status (Hollingshead) was also administered. Infants’ 3-month receptive and expressive language scores from the MSEL and Vineland subscales were compared to the 11-month CDI and Hollingshead scores using linear regression. We found that receptive language scores at 3 months, obtained via both Vineland and MSEL, predicted 11-month receptive language CDI scores. Hollingshead scores were also associated with 3-month Vineland receptive language scores, with lower receptive language skills seen with higher social status scores. Findings from this research advance our understanding of whether parent report surveys of language abilities can serve as an early screening tool to identify infants at risk for speech and language delays and disorders. These results may have implications in particular for healthcare providers and families in rural settings who rely on telehealth to access services.