This report presents a novel approach to increase the detection sensitivity of trace amounts of DNA in a sample by employing Förster Resonance Energy Transfer (FRET) between intercalating dyes. Two intercalators that present efficient FRET were used to enhance sensitivity and improve specificity in detecting minute amounts of DNA. Comparison of steady-state acceptor emission spectra with and without the donor allows for simple and specific detection of DNA (acceptor bound to DNA) down to 100 pg/ul. When utilizing as an acceptor a dye with a significantly longer lifetime (e.g., Ethidium Bromide bound to DNA), multi-pulse pumping and time-gated detection enable imaging/visualization of picograms of DNA present in a microliter of an unprocessed sample or DNA collected on a swab or other substrate materials.

We studied room temperature phosphorescence of tryptophan (TRP) embedded in poly (vinyl alcohol) [PVA] films. With UV (285 nm) excitation, the phosphorescence spectrum of TRP appears at about 460 nm. We also observed the TRP phosphorescence with blue light excitation at 410 nm, well outside of the S0→S1 absorption. This excitation reaches the triplet state of TRP directly without the involvement of the singlet excited state. The phosphorescence lifetime of TRP is in the sub-millisecond range. The long-wavelength direct excitation to the triplet state results in high phosphorescence anisotropy which can be useful in macromolecule dynamics study via time-resolved phosphorescence.

Graphene Quantum Dots (GQDs) are highly perspective bioimaging agents due to a plethora of advantageous properties making them superior to conventional fluorophores. Those properties include stability to photobleaching, large Stokes shifts circumventing biological autofluorescence, and a capability of functionalization for drug delivery. In this work, a variety of GQD structures are imaged via visible fluorescence microscopy in order to evaluate the optimal GQD structures for bioimaging and bioengineering in vitro.

Infections deriving from the highly pathogenic avian H5N1 influenza virus often result in severe respiratory diseases with a high mortality rate. Although rarely transmissible to humans, recent events such as the SARS-CoV-2 pandemic have shown that a proper understanding of the life cycles of deadly viruses like H5N1 and any variables that affect its terminality are vital. One such variable could be the method of entry, and its impact on the progression of H5N1 is the focus of the study. Utilizing previous data on cynomolgus macaques subject to samples of H5N1, we study how entry via a combined intrabronchial, oral, and nasal pathway affect disease progression. We fit the data using a viral kinetics model, which allows us to estimate parameters describing the H5N1 life cycle. This allows us to better understand the life cycle of H5N1 in vivo.

Everyone gets sick and illness negatively affects all aspects of life. One major cause of illness is viral infections. Some viral infections can last for weeks; others, like influenza (the flu), can resolve quickly. During infections, healthy cells can grow in order to replenish the cells that have died from the virus. Past viral models, especially those for short-lived infections like influenza, tend to ignore cellular regeneration – since many think that uncomplicated influenza resolves much faster than cells regenerate. This research accounts for cellular regeneration, using an agent-based framework, and varies the regeneration rate in order to understand how cell regeneration affects viral infections. The model used represents virus infections and spread in a two-dimensional layer of cells in order to generate graphs of virus over time for corresponding regeneration rates. We find that the effect of cell regeneration depends on the mode of transmission of the infection.

The first stars in the Universe, Pop III stars, formed out of the primordial hydrogen and helium sometime during the first billion years of cosmic time. Their formation ended the Cosmic Dark Ages. Despite their critical role in kick starting the formation of all “metals,” (ie. the carbon in our bodies and the oxygen we breathe), we do not know how massive these first stars were, and when and how the era of the first stars ended. While Pop III stars are too faint for a direct detection, their deaths are potentially visible by James Webb Space Telescope (JWST). A subset of Pop III stars end their lives as Pair Instability Supernova (PISN), explosions 100 times more powerful than a typical supernova. However, determining the astrophysics of the first stars will require combining the detection of PISN with theoretical work on the mass distribution of Pop III stars. In this theoretical work, we need to fully explore the range of mass distribution of Pop III stars to determine how dependent the PISN rate is on the masses of Pop III stars. In this work, we present results from a new model which explores the distribution of Population III masses with a set free parameters. We find an order magnitude difference in the PISN rates for various Pop III mass distribution. In addition, we find that PISN rates may provide one of the first independent probes of the maximum mass of Pop III stars.

It has been well established that ZnO is a versatile material with multiple existing and potential applications owing to its numerous and unique properties. ZnO in the nano- and microscale forms has been a focus of attention in recent years due to demonstrated utilities in pharmaceutics, bioengineering and medical diagnostics. Of particular interest is the utilization of ZnO as an antibacterial agent. With growth inhibition observed for both gram-positive and gram-negative bacteria as well as antibiotic strains, the antibacterial action of ZnO is well documented. Yet, there exists much debate over the fundamental mechanisms underlying the antibacterial action of ZnO. Commonly proposed mechanisms include the generation of various reactive oxygen species, release of Zn ions, surface-to-surface interactions, etc. In this work, we investigate the surface and near-surface optoelectronic properties of ZnO microcrystals as they relate to the antibacterial figures of merit. As microscale ZnO particles exhibit comparable antibacterial action to those at the nanoscale, while minimizing effects related to internalization, they are well-suited to serve as a platform to investigate the role of the crystalline free surfaces in this behavior. A bottom-up hydrothermal growth method was employed to synthesize ZnO microcrystals with tunable morphology and a well-controlled relative abundance of polar and non-polar surfaces. The quality of the crystalline lattice and free surfaces as well as the predominant morphology of these samples were confirmed by scanning electron microscopy, energy-dispersive X-ray spectroscopy, and surface photovoltage spectroscopy. The antibacterial efficacy of these particles was characterized via minimum inhibitory concentration assays, performed using Staphylococcus Aureus in a Mueller Hinton broth media. We performed a series of optoelectronic experiments including temperature dependent photoluminescence spectroscopy as well as spectroscopic and transient surface photovoltage as a means to observe changes occurring at the ZnO surface during these assays. We detected significant spectral changes due to interactions with bacteria and growth media. In particular, we showed that interactions with s.aureus resulted in considerable modifications of the excitonic luminescence.

Photothermal Therapy (PTT) provides a promising new method of radiative therapy cancer, using infrared wavelengths. In my project, the ability of these materials to heat up when shone with near infrared light, or the photothermal effect, of various nanomaterials—including reduced graphene oxide, reduced graphene quantum dots , and copper sulfide nanoparticles—is characterized by irradiation of the aqueous materials with near-infrared radiation.

CRISPR Cas9 is a programmable single guided RNA (sgRNA) ribonucleic protein (RNP) that has demonstrated their ease and practical use as a gene editing tool for in vitro and ex vivo applications. For in vivo applications of the Cas9 RNP, physiological barriers must be overcome and gene editing to occur transiently, demonstrating the need to develop biocompatible imaging agents to protect and locate Cas9 RNP in vivo. Graphene quantum dots (GQDs) are biocompatible carbon-based nanomaterials that have served as delivery and imaging agents for drug and gene medicine due to their ease in synthesis and repertoire of complexation capabilities arising from the choice of precursor materials. In this work, we have synthesized visible and near infrared emitting GQDs with glucosamine HCl and polyethylenimine (PEI) using a bottom-up approach to use them as non-viral delivery vehicles for the Cas9 RNP. PEI increases the net positive charge of GQDs allowing their electrostatic complexation with the net negatively charged RNP. We further demonstrate their complexation with gel retardation assay and TEM. The GQDs+PEI+RNP in vitro editing capability is shown by targeting the TP53 414delC frameshift mutation locus present in PC3 cancer cell line for prostate cancer. This form of editing serves as a guide for future cancer therapy using GQDs as non-viral delivery of Cas9 RNP to mutant TP53 genes overexpressed in about 50% of cancers.

With the onset of the SARS-CoV-2 pandemic in the U.S. in early 2020, much of the early response in the U.S. was made on a state level with varying levels of effectiveness. To characterize the effects of early preventative measures by state legislatures we can use a SEIR model and data gathered to analyze the effectiveness of lockdown measures from state to state. Using the data collected we can model the effect of lockdown measures on the infection rate to characterize the effect preventative measures had on case numbers. We chiefly used 4 models to simulate the change in infection rate: instantaneous, linear, exponential, and logarithmic. Then using these models, we fit each model to the case data and compared the relative accuracy of each model to the data to determine which model most accurately represented the change in infection rate within the first months of the pandemic. Following this, we used the fits obtained to create a possible distribution for each parameter, which helps accurately predict the actual number of cases and how it was affected by preventative measures.

Several different vaccines have been introduced to combat the spread of SARS-CoV-2 infections. As the virus is capable of mutating to escape the protection given by the vaccine, using multiple vaccines is believed to help prevent the virus from mutating to escape all vaccines, helping to combat spread of the virus. We simulate the effect of using multiple vaccines on the virus using a mathematical model. With the model, we can better understand the effect of multiple types of vaccines in helping to control pandemics.

One of the large unanswered questions in astronomy is: How does the Milky Way galaxy evolve, chemically and dynamically? Of all the objects that we could use to probe this question, groups of stars which were all born from the same gas cloud, known as open clusters, are the most reliable. This makes open clusters ideal for exploring the evolution of our Galaxy because we can determine not only the distance, position, velocity, and chemistry of the cluster, but we can also pin a reliable age to the cluster as well. Historically, assembling a statistically significant dataset of open clusters has proved to be challenging without inducing large systematic uncertainties by collecting data from multiple sources. The Open Cluster Chemical Abundance and Mapping (OCCAM) survey is a uniform dataset of star clusters that uses dynamical data from the Gaia space telescope and 16 different chemical abundances from the APOGEE survey, which is a part of the Sloan Digital Sky Survey. This new update to OCCAM includes uniformly measured data for 153 open clusters and a total of 2061 member stars, which we use to investigate the chemical evolution of the Milky Way.

Oxidative stress, an imbalance of reactive oxygen species, has been shown to participate in a multitude of diseases from Alzheimer to cancer. Thus, there is a search for radical scavenging agents capable of circumventing oxidative stress. Due to their remarkable properties, quantum dots are known to be utilized in a variety of applications including binding of reactive oxygen species (ROS). However, the translation of nanomaterials to clinic is often hampered by their off target toxicity. Thus, the aim of our work is to develop and test fully biocompatible graphene quantum dots (GQDs) with a variety of dopants that will the tune radical scavenging activity (RSA) of the GQD. We have synthesized and tested over ten types of doped GQDs and accessed their radical scavenging ability via DPPH, KMnO4, and RHB assays. Among those, thulium and aluminum doped GQDs show superior scavenging.

Respiratory syncytial virus (RSV) can cause a severe respiratory illnesses particularly in young children and the elderly. Defective viral genomes (DVGs) have recently been found during RSV infections and are thought to be linked to the severity of the illness. In this study, we use mathematical models to simulate the spread of RSV using data from environments in which DVGs are detected early and late in order to estimate infection rates and other infection parameters in each setting. We find that the presence of DVGs is reflected in changes in the infection rate and viral clearance rate of infections.

During the first billion years after the Big Bang the first, faint, galaxies formed. With luminosities less than one millionth that of our Milky Way galaxy, they are too faint to be observed by even our most advanced telescopes. A fraction of these first galaxies are preserved as ultra-faint dwarf galaxies in the local universe. These ultra-faint dwarfs are the fossils of the first galaxies. Therefore, we can study the faintest satellites of the Milky Way and learn about the formation and evolution of the first galaxies using galactic paleontology. We know that the stellar properties of the faintest Milky Way satellites match the stellar properties of galaxies formed in high resolution hydrodynamic simulations of the first billion years. We also know that the semi-analytic model Galacticus can reproduce the stellar properties of the faintest Milky Way dwarfs in the modern epoch. In this work, we determine whether Galacticus is also able to match the high resolution simulations of the first billion years.

The creation and evolution of elements throughout time across the Milky Way disk provides a key constraint for galaxy evolution models. To provide these constraints, we are conducting an investigation of the zirconium, neodymium, cerium, and barium abundances created in supernovae explosions, for a large sample of open clusters. The stars in our study were identified as cluster members by the Open Cluster Chemical Abundance & Mapping (OCCAM) survey that culls member candidates by Doppler velocity, metallicity, and proper motion. We have obtained new data for the elemental abundances in these clusters using the Subaru Observatory 8-m telescope in Hawaii with the High Dispersion Spectrograph (HDS). Analyzing these neutron-capture abundances in star clusters will lead us to new insight on star formation processes and the chemical evolution of the Milky Way galaxy.

Cancer is a leading cause of death worldwide with around one in every six caused by cancer, but many cancers can be cured if treated properly. Mathematically programmed cancer cell models can be used by researchers to study the use of oncolytic viruses to treat tumors. With these models, we are able to help predict the viral characteristics needed in order for a virus to effectively kill a tumor. Our approach uses both cancerous and non cancerous cells in relationship to the tumor to determine the speed at which the cells replicate, however there are several models used to describe cancer growth, including the Exponential, Mendelsohn, Logistic, Linear, Surface, Gompertz, and Bertalanffy. We study how the choice of a particular model affects the predicted outcome of treatment.

The first galaxies formed 12.5 billion years ago during the first billion years after the Big Bang. However, these first, faint, galaxies remain too faint for direct detection, even by our most powerful telescopes. Therefore we study them using their fossils relics, ultra-faint dwarf galaxies orbiting the Milky Way. In this work, we look at the histories of star formation in simulated analogs to the ultra-faint dwarfs. These star formation histories will allow us to study the details of how and when star formation occurred during the first billion years of cosmic time. We are particularly interested in how massive the first galaxies were when they formed the majority of their stars.

Coinfection affects up to 60% of patients hospitalized influenza-like illnesses, however, the role of the innate immune response in coinfections is not understood. Interferons, part of the innate immune response, are a type of chemical released by infected cells that can help establish an antiviral state in cells by increasing resistance to infection and reducing production of viruses. Although the increased resistance to infection can help suppress both viruses, the reduction in the production of one virus may aid in increasing the growth of another virus during coinfection due to less competition. We will use a mathematical model to examine the interaction via interferons between respiratory syncytial virus (RSV) and influenza A virus (IAV) during coinfections. This model will measure viral titer, duration of the viral infection, and interferon production allowing us to understand how interferon production of one virus helps or hinders the secondary virus.

Due to the enormity of different forms of cancer and the increase in cancer rates globally, it is essential to continually develop more advanced methods of early and localized detection of cancer cells, as well as methods of targeted drug delivery. As a result, a vast amount of research has gone into the use of nano-materials such as graphene quantum dots (GQDs) as the basis for a wide variety of biomedical sensing and treatment applications. While many diagnostic biomarkers have been detected using modified GQDs, one biomarker that has not yet been successfully detected or targeted using GQDs is Transgelin-2. Transgelin-2 is a unique actin-binding protein that has been projected to be a useful biomarker and target of treatment for many different forms of cancer, as well as asthma and immune diseases such as lupus. Herein I review the structure of the Transgelin-2 protein, novel methods of GQD modification to sense cell membrane surface proteins, and ultimately determine the viability of GQDs as a method for detecting and targeting Transgelin-2. Furthermore, I develop a possible methodology by which these biophysical applications may be tested.

Through the use of large-scale surveys, astronomers are able to investigate Milky Way galaxy evolution, both dynamically and chemically; however, determining reliable stellar ages has been elusive.  Star clusters are the most reliable way to measure ages of stars, and new surveys are measuring detailed chemistry for cluster stars that may be able to be correlated with age. For our study, we are using carbon and nitrogen abundances within red giant stars as age indicators. Using the Open Cluster Chemical Abundances and Mapping (OCCAM) survey, we utilized stellar parameters and abundances, and created a uniform empirical relationship between stellar ages and carbon-to-nitrogen abundances using star clusters. This new calibration will allow us to determine reliable ages for over 100,000 stars across the Milky Way galaxy, allowing us to measure the chemical evolution of the Galaxy.

Antimicrobial action of micro- and nanoscale ZnO particles has been documented, but the fundamental physical mechanisms driving these actions are still not identified. We hypothesize that one of the key mechanisms behind the antibacterial action of ZnO is rooted in interactions between ZnO surfaces and extracellular material. An investigation was done of the biological components of that interaction using diffusion theory and more specifically Brownian motion computational models to look at the interaction of Zn+2 and O-2 ions with staphylococcus aureus bacteria. The analysis allowed us to find a correlation between the thickness of the staphylococcus aureus bacteria and the amount of the zinc and oxygen ions present in the solution.

Nano- and microscale zinc oxide (ZnO) have demonstrated potential for applications in electronic, pharmacological and chemical industries among others. At these scales, surface properties dominate, rendering surface defects highly influential. Consequently, understanding of defect- related phenomena are crucial to achieving impactful figures of merit. Many optoelectronic properties of ZnO relevant for applications have been linked to defect-related visible luminescence. Its fundamental origins are still being debated, with attributions to oxygen vacancies, zinc vacancies, oxygen antisites, donor-acceptor pairs, etc. In our studies, we contribute to this discussion by probing the relationship between crystal morphology and this luminescence. We conducted optoelectronic studies to characterize the effects of remote oxygen plasma treatment on hydrothermally-grown microscale ZnO samples with controlled morphology as a means to help elucidate the nature of the visible emission. We report on the observed changes in the photoluminescence spectra indicative of the relationship between surface defects, morphology, and electronic structure of ZnO.

With the development of personalized cancer medicine and moving away from a conventional biopsy, there is a need in creating a multifunctional platform for cancer diagnosis and treatment monitoring. Sonography offers many advantages over standard methods of therapeutic imaging due to its non-invasiveness, deep penetration, high spatial and temporal resolution, low cost, and portability. The benefits of the ultrasound method make contrast agents an ideal platform for the efficient strategy of cancer diagnostic and therapy. In this work, we developed metal-doped graphene quantum dots that demonstrate high-contrast properties in ultrasound brightness mode. The successful imaging enhancement was observed in tissue phantom and chicken breasts tissue. The relatively small size of the metal-doped graphene quantum dots makes them easily be internalized into the cells, while functional groups on their surface allow binding a cancer-targeted marker and therefore be used as a cancer-targeted delivery. By a combination of imaging and targeting capabilities, ultrasound contrast agents based on metal-doped graphene quantum dots enable desired cancer-focused nanotherapeutic and imaging approaches.

For billions of years, our Milky Way galaxy has churned out countless stars. However, the best star-forming days of our galaxy are long gone and our galaxy is in a midlife crisis! It’s running out of gas to make new stars, and extraneous resources are scarce. Worse yet, high stellar winds might eject some gaseous material, such as the Smith Cloud. After it was ejected, the Milky Way’s gravity caused this cloud to reverse course and fall back toward our Galaxy. The Smith Cloud is now only 40,000 light-years away and carries with it the equivalent of over 1 million Suns worth of material. As it makes the journey back to our Galactic Plane, it must endure heavy winds that have temperatures in excess of 1 million degrees Celsius from the Milky Way galaxy’s coronal gas. I have already measured the amounts of various ions in adjacent cloud fragments positioned on the side of the Smith Cloud using Hubble Space Telescope observations. These ions include C+, Si+, Si2+, Si3+ , and S+. I will then determine the effects that these high winds have on the adjacent fragments and the trailing wake of the Smith Cloud to better understand the perils that gas clouds must undergo to reach massive galaxies.