Galaxies are giant playgrounds in which stars, planets, and potentially sentient carbon-based lifeforms live out their lives. We live in the Milky Way galaxy, however, like all larger galaxies the Milky Way has a slight cannibalism problem. Larger, more massive galaxies are assembled from smaller galaxies where the surviving small galaxies are dwarf galaxies. The latest victims of our Milky Way’s cannibalism are the Large Magellanic Cloud (LMC) and the Small Magellanic Cloud (SMC), and we have no idea what happened to their dwarf galaxies. To further complicate things, we don’t know how many dwarf galaxies fell into the Milky Way with the LMC, or where they ended up. In addition, the dwarf satellites of the LMC should be extremely faint and difficult to detect. We use computer simulations in order to take a bite out of these questions. We send a perfectly innocent LMC and its satellites into the gravitational potential of a Milky Way galaxy, and see where the dwarf satellites are flung.

Astronomers determine chemical abundances of stars through spectroscopy, which provides clues as to where the stars were formed. We use the chemical composition of stars to infer their relative ages due to past enrichment. However, the surface abundance of stars is not always constant during its life and will change as the star evolves due to its internal processes. As a result, if we assume the chemical makeup of stars is constant within a star cluster, it can cause systematic errors when inferring stellar parameters. For example, in previous investigations, the star cluster M67 has been observed to have signatures of atomic diffusion: the combined effect of gravity pulling elements deeper into the star and radiation preventing elements from floating to the surface locks elements below the observable surface of a star which cannot be unlocked until the star evolves further, changing the measured abundance. When the star evolves, convection reaches into the interior of the star and carries these elements back to the surface where they can now be observed once again. This process can explain the elemental abundance variation found in main-sequence stars, like our Sun, and also evolving stars, which can also affect what apparent age we determine. Stars within a cluster tend to form from the same gas cloud at the same time, giving them the same age and initial chemical composition. Therefore, star clusters are ideal test-beds for investigating elemental abundance and the resulting apparent age variations. Data from the Apache Point Galactic Evolution Experiment survey provides the opportunity to investigate how abundance variation/diffusion is affected by age.

With novel materials getting smaller and their size falling to the nanometer scale, it becomes harder to fully characterize them by only using the experimental apparatus at hand. Therefore, taking advantage of computational methods proves to be trustworthy in filling those gaps and in aiding our experimental data to get a better understanding of the nanomaterials’ structural and electronic properties. Graphene quantum dots (GQDs) have recently become one of the flagships of carbon nanotechnology due to their remarkable physical properties and, when functionalized, their ability to become water soluble, biocompatible, and capable of fluorescence in the visible and near-infrared. This makes them perspective carriers for therapeutic delivery and image-tracking. In order to assess the advantages of their utilization for a variety of bioapplications, we have investigated the optical properties of doped GQDs and their interactions with biomolecules using a variety of molecular simulation approaches. The true atomic ground state of the N-GQD is achieved by performing first-principle calculations based on density functional theory (DFT). DFT calculations also unrevealed the contributions of each functional group within the structure to HOMO–LUMO band edges. The adsorption of biomolecules and genes on the GQD surface has been further investigated with regard to the GQD structure, complementing experimental results that verify gene and drug complexation.

While silencing RNA (siRNA) technology has become a powerful tool that can enable cancer-specific gene therapy, its translation to the clinic is still hampered by several critical factors. These include the inability of cell transfection by the genes alone, poor siRNA stability in blood, and the lack of delivery tracking capabilities. Recently, graphene quantum dots (GQDs) have emerged as a novel platform allowing targeted drug delivery and fluorescence image-tracking in the visible and near-infrared. These capabilities can aid in overcoming primary obstacles to siRNA therapeutics. Here, for the first time, we utilize biocompatible nitrogen and neodymium-doped graphene quantum dots (NGQDs and Nd-NGQDs) for the delivery of Kirsten rat sarcoma virus (KRAS) and epidermal growth factor receptor (EGFR) siRNA effective against a variety of cancer types. The non-covalent loading of siRNA onto GQDs is evaluated and optimized by the electrophoretic mobility shift assay and zeta potential measurements. GQDs as a delivery platform facilitate successful gene transfection into HeLa cells confirmed by confocal fluorescence microscopy at biocompatible GQD concentrations of 375 µg/mL. While the NGQD platform provides visible fluorescence tracking, Nd doping enables deeper tissue near-infrared fluorescence imaging suitable for both in vitro and in vivo applications. The therapeutic efficacy of the GQDs/siRNA complex is verified by successful protein knockdown in HeLa cells at nanomolar siEGFR and siKRAS concentrations. A range of GQDs/siRNA loading ratios and payloads is tested to ultimately provide substantial inhibition of protein expression down to 31-45% comparable with conventional Lipofectamine-mediated delivery. This demonstrates the promising potential of GQDs for the non-toxic delivery of siRNA and genes in general, complemented by multiwavelength image-tracking.

In order for galaxies to sustain current star-formation rates, including our Milky Way, they need to replenish their reservoirs of gas. High-velocity clouds (HVCs) entering our galaxy, like the Smith Cloud, present a possible source of gas for future star formation. Although the chemistry of the Smith Cloud has been previously studied, it is unclear whether there is variation in the chemistry of the Smith Cloud. With the Hubble Space Telescope, we measure the absorption of various elements along the tail and an adjacent fragment of the Smith Cloud. For the tail, we used existing observations, and for the fragments, we observed two new sightlines with Hubble. We additionally use radio emission-line observations from the Green Bank Telescope and from the Galactic All-Sky Survey (GASS) to understand the neutral hydrogen gas. Using observations in conjunction with the Cloudy simulations, we provide constraints on the chemistry of all five sightlines. Our new sulfur abundances for the adjacent fragment of the Cloud are higher than those downstream in the trailing wake. By quantifying the properties of gas clouds traveling through the Galactic halo, we can assess how they are impacted by their environments and better understand how the star-formation gas reservoirs of large galaxies are replenished.

There is currently a mismatch between the chemical properties of a typical star and those within star clusters across the Milky Way galaxy. Star clusters are groups of stars bound by gravity, many of which are found in the disk of the Milky Way. Studying these star clusters reveals essential information about the rich history of our Galaxy, as we can measure their age and their chemical composition independently. While some clusters interact with their environment, causing them to dissolve, other clusters remain bound for billions of years. In order to investigate these disruption events, we will study the evolution of star clusters throughout cosmic time via simulations. With the use of cosmological simulations, such as the Feedback In Realistic Environment (FIRE) simulation, we are able to learn why clusters move from their original place of formation and how far they go. Additionally, FIRE allows us to trace star clusters through their different stages of their evolution, and study how they survive as they interact with other components of the galaxy. In this study, we will investigate the Galactic chemical gradient mismatch for the Milky Way, as we compare the FIRE simulations to the observed star cluster distribution and properties measured from Gaia satellite and the Sloan Digital Sky Survey.

Approximately 72% of Americans are overweight or obese, and healthcare for obesity-induced chronic diseases accounts for almost half of the total costs for disease treatment in the U.S. Further, obesity is a key risk factor for Alzheimer’s disease (AD), a fatal disease that is the 6th leading causes of death in the U.S. As obesity and AD are comorbid, dietary intervention could be a key strategy to reduce excessive weight gain and AD risk.

High obesity prevalence in the U.S. is most likely due to the typical American diet, known as the Western Diet (WD), which is comprised of simple carbohydrates, refined sugars and vegetable oils, processed meat, and high-fat dairy products. Conversely, the Mediterranean Diet (MD), a plant-based diet, is typically comprised of complex carbohydrates, fruits, vegetables, olive oil, seafood, and low-fat dairy products. The MD has been shown to reduce the risk of developing chronic diseases, and thus, has the potential to protect against AD.

The current study examined the effects of the MD and WD, modeled after typical human diets, in a hippocampus dependent learning task in wildtype mice. As the hippocampus is a crucial brain region for learning and memory, and hardest hit by AD pathologies, we aimed to explore how diet affects learning and memory processes that are dependent on this brain region. The results revealed that life-long consumption of the MD enhanced spatial learning and memory, in comparison to the WD, in male mice. These results suggest that long-term consumption of the MD could be used to enhance cognition in older adults.

Healthy sleep is imperative for many biological and psychological functions, including immune function and neural plasticity. Alarmingly, over one-third of US adults report getting less than the minimum recommended 7 hours of sleep each night. Unfortunately, sleep loss is linked with impairments in immune and cognitive function. Our lab previously demonstrated that chronic sleep restriction (CSR) is associated with cognitive impairment in wild-type mice. The present research investigated the impact of CSR on markers of inflammation and neural plasticity in response to an immune insult in adult C57BL/6 mice. Male and female mice underwent six weeks of CSR, followed by one intraperitoneal injection of lipopolysaccharide (LPS) or saline. Four hours post-injection, serum and hippocampal tissue were collected for brain-derived neurotrophic factor (BDNF) and cytokine analysis. Results revealed patterns that differed between males and females. Male mice that underwent CSR and received LPS had increased serum pro- and anti-inflammatory cytokines, while cytokine mRNA in the hippocampus was decreased compared to control mice that received LPS. Conversely, female mice that underwent CSR and received LPS had decreased pro-inflammatory cytokines in both the serum and hippocampus compared to control mice that received LPS. Moreover, males that underwent CSR exhibited decreased hippocampal BDNF mRNA compared to controls, while this difference was not observed in females. These patterns of findings suggest a complicated interaction between chronic sleep loss, immune function, and sex, underscoring the necessity to understand how lifestyle factors such as sleep loss can influence immune and cognitive dysfunction in both men and women.

Previous research finds that people are perceived as naïve and socially submissive when expressing fear. The outward expression of this emotion is thought to function to elicit prosocial responses from others. However, no work has examined whether fearful expressions are also perceived as an opportunity for exploitation in environments which favor opportunistic responding such as harsh, low resource environments. The current research was designed to examine 1) the perceived opportunities posed by fearful individuals, and 2) whether the presence of someone from a harsh environment leads individuals to suppress, rather than express, their fear. In two studies, participants were randomly assigned to evaluate the opportunities for exploitation posed by a person expressing either fear or no emotion. In a third study, participants were randomly assigned to view a fear inducing video from a horror movie or a neutral video from a nature documentary. Participants then disclosed to a bogus study partner (from a harsh or benign environment) the degree of fear they felt while watching the video. Results revealed that fearful individuals are perceived as posing more of an opportunity for exploitation than individuals expressing no emotion. Additionally, being in the presence of an individual from a harsh environment was associated with reduced fear expression after watching a scary video. These results suggest that the expression of fear may be risky under certain contexts.

Aim. This study aims to explore the feasibility, acceptability, appropriateness, and reliability of a new observational assessment tool - the Child and Adolescent Wellbeing Scale (CAWS), designed to evaluate socio-emotional health and attachment patterns in children and adolescents.
Background. There is significant interest in child trauma and interventions, and therefore a need for an assessment tool to assess child-level outcomes of trauma-informed interventions, care, and services. The CAWS was created to address this gap, providing a measure rooted in child-caregiver attachment and relational trauma. The CAWS is a 25-item scale with three subscales: Connection, Regulation, and Felt-Safety, which align with Bath’s Three Pillars of Trauma-Informed Care.
Method. Twenty mental health clinicians were trained to use the CAWS during two virtual sessions. Following training, each participant independently observed and rated 15 pre-recorded video interactions between children and their caregivers (totaling 300 independent ratings). Clinicians provided feedback on the CAWS instrument content and format after rating the videotaped interactions; validated measures were used to evaluate the feasibility, acceptability, and appropriateness of the instrument. Reliability estimates were calculated using the generalizability theory.
Results. Ninety-four percent of participants (95% white, 85% female, median age 40.5 years, 100% Master’s degree) reported that administering the CAWS was feasible (i.e., implementable, doable), 100% indicated it was acceptable (i.e., appealing, meets approval), and 100% indicated it was appropriate (i.e., suitable, applicable). Additionally, 100% of participants reported that they would likely use the CAWS in their practice. The CAWS demonstrated excellent inter-rater reliability overall (R1F = .82), was a reliable measurement of systematic change in children (Rc = .94), and reliability emphasized the stable individual difference between children (RKF = .98).
Conclusion. The current study demonstrates the CAWS as a promising evaluation tool with excellent reliability, feasibility, acceptability, and appropriateness. Additional studies should investigate the CAWS instrument's validity further, focusing on its applicability in field settings and its utility in measuring change over time.