Rat Parvovirus is found in rat liver and can infect and cause changes in tumor cells. When tumor cells are infected, the cells can revert back to benign or uncancerous cells. We describe and analyze a mathematical model of infected and noninfected tumor cells when introduced to the parvovirus. Using nonlinear analysis, we find the conditions for cure of the tumor.
Author(s): Elizabeth Campbell Physics & Astronomy Giridhar Akkaraju Biology Roberto Gonzalez-Rodriguez Chemistry & Biochemistry Md. Tanvir Hasan Physics & Astronomy
Advisor(s): Anton Naumov Physics & Astronomy
Location: Session: 2; Basement; Table Number: 10
Graphene quantum dots (GQDs) are novel materials with a number of unique properties that can be applied in electronics, sensing and biotechnology. GQDs possess physical properties that are critical for biomedical applications, including small size (3-5 nm), high quantum yield, and pH-dependent fluorescence emission in the visible/near-infrared, providing a possibility of molecular imaging, and pH-sensing. They also show very low cytotoxicity suggesting high potential for multiple biomedical applications. GQDs can also be doped to form nitrogen doped graphene quantum dots (N-GQDs), sulfur doped graphene quantum dots (NS-GQDs) and boron nitrogen doped graphene quantum dots (BN-GQDs), which allow these optical properties to be adjusted. We utilize and modify these properties to yield a multifunctional delivery/imaging/sensing platform geared toward the analysis of cancer therapeutics delivery in vitro. In our work, we outline how GQDs can serve as potential drug transport agents and as molecular markers for imaging the delivery pathways. Optimal emission and excitation are selected for each quantum dot to minimize the autofluorescence of cells, allowing them to be imaged in vitro. Emission in healthy (HEK-293) and cancer (HeLa and MCF-7) cells is quantified for a variety of pH environments to identify the ideal conditions for cellular internalization and pH-sensing of acidic cancerous environments. In addition, in vitro fluorescence microscopy analysis provides quantitative assessment for accumulation in cells. The results of this work suggest GQDs as innovative and effective highly biocompatible multifunctional platforms for cancer therapeutics.
Author(s): Luca Ceresa Physics & Astronomy Jose Chavez Physics & Astronomy Ignacy Gryczynski Physics & Astronomy Joe Kimball Physics & Astronomy
Advisor(s): Zygmunt Gryczynski Physics & Astronomy
Location: Session: 1; 2nd Floor; Table Number: 2
Fluorescence is a very useful and popular technique which has been used in a wide variety of fields and, of late most importantly, at the intersection of biophysics, biochemistry and medicine. Despite being relatively simple from a theoretical point of view, it turns out that practical applications can have trivial problems that can cause significant spectroscopic problems. Specifically, an often overlooked yet fundamental obstacle in fluorescence spectroscopy is the nonlinearity of fluorescence intensity versus fluorophore absorption. This is referred to as the inner-filter effect. In literature, it is divided into a “primary inner-filter effect” and a “secondary inner-filter effect”. The former is caused by the absorption of the excitation light, which results in the lowering of the intensity of light reaching deeper regions of the solution. The latter is represented by the reabsorption of the emitted fluorescence by the fluorophores in the solution. Due to the fact that the primary inner filter effect is a direct consequence of the high concentration of the solution, to observe the secondary inner filter effect it is necessary to have a chromophore which absorbs part of the light that is emitted by the main fluorophore. Although working with low concentrations is generally recognized as a good practice to avoid artifacts related to inner filter effects, the primary inner filter effect can occur even at low absorbances (< 0.05). Furthermore, it is possible that using solutions with high absorbance is strictly necessary in studying the photophysical properties of fluorescent dyes and the interactions of biological macromolecules. Therefore, a reliable correction method for inner filter effects is fundamental for spectroscopic studies. Since it has been reported that the existing methods for correcting the fluorescence intensity are hard to implement in practice, we propose a strategy based on the previous calculation of the so called “sensitivity factor” of a spectrofluorometer. By mounting a cuvette on a movable holder in a square geometry setup, we can modify the position of the cuvette during a regular emission/excitation experiment. This allows us to determine the sensitivity factor. This result can be effectively used to correct the emission/excitation spectra to restore the linearity between absorbance and fluorescence intensity in samples characterized by high concentrations.
Author(s): Jose Chavez Physics & Astronomy Luca Ceresa Physics & Astronomy Ignacy Gryczynski Physics & Astronomy Joe Kimball Physics & Astronomy
Advisor(s): Zygmunt Gryczynski Physics & Astronomy
Location: Session: 2; 3rd Floor; Table Number: 2
Fluorescence has grown to be the most sensitive detection technique used in a variety of biophysical, biochemical and medical applications for several decades. However, there is an interesting luminescence similar to fluorescence which causes an “afterglow effect” (“glow in the dark”). This is called “phosphorescence”. Phosphorescence has an exceptionally longer lifetime (milli or microseconds) compared to fluorescence (nanoseconds). This can be up to a million times longer. Modern fluorescence lifetime measurements require sensitive detectors that cost several ten to hundreds of thousands of dollars, while a phosphorescence lifetime detector can be in the thousands range. This detector uses ocean optics spectrometry with a phosphoroscope to measure phosphorescence. With this application we want to use it for studying protein dynamics such as shape, spacing, binding, etc. The novelty for this approach is using tryptophan as a probe for direct excitation to the phosphorescence triplet state. This means the usual encounter of fluorescence there is a continuous light source. When exposed the sample will emit its fluorescence. Once removed from the light source, since fluorescence is so fast when decaying, will expire off. However, with phosphorescence, after the removal of the light source, the sample still emits. This procedure if successful will circumvent fluorescence and just achieve phosphorescence. To study this we will be using PVA (poly vinyl alcohol [plastic]) with 5,6 – Benzoquinoline, Indole, and Tryptophan where the first compound is confirmed to have phosphorescence able to be seen even with the naked eye at room temperature. These will be studied in a device that will measure phosphorescence called a fluorospectrometer (Varian Eclipse) and the phosphoroscope. With this information we can find out what color (wavelength) to excite the tryptophan and circumvent fluorescence to phosphorescence.
Massive amounts of gaseous material are being ejected from the nearby Large Magellanic Cloud (LMC) due to supernovae explosions occurring inside the galaxy. These explosions influence how gas cycles in and out of a galaxy and is crucial for our understanding of how galaxies evolve. Being the nearest gas-rich galaxy, the LMC provides us with an excellent opportunity to explore this gas cycle in detail. We have combined spectroscopically resolved observations to investigate the influence supernovae have on the LMC gas and the connection between supernovae explosions and the currently flowing galactic wind.
The problem of fitting isochrones, theoretical models of stellar populations, to the observed stellar populations (e.g. star clusters) has plagued observational astronomy for decades. A plethora of algorithms have been developed, but many fall short of their goals, and almost all are very computationally expensive. We present a new, computationally efficient technique made possible by first creating a fiducial representation of the data. This concise representation allows for a robust comparison to many theoretical models using a Markov-Chain Monte Carlo (MCMC) approach, quickly producing not only accurate fits but reasonable constraints on the final fitting parameters. The technique is applied to a number of star clusters, and the results are discussed in the context of Galactic chemical evolution.
A virus spreads through a body in two known ways: free cell transmission and cell to cell transmission. During free cell transmission, cells make viruses that diffuse throughout the body which may cause any cell that the virus touches to become infected. During cell to cell transmission, a virus spreads to a neighboring cell through an intercellular transfer. While previous research has investigated viruses based on free cell transmission, few models have incorporated cell to cell transmission leading to unclear results and bias to certain variables. This research accounts for both free cell and cell to cell transmission, using an agent-based framework. The model represents virus infection and spread in a two-dimensional layer of cells in order to generate total virus over time graphs for corresponding initial dose of virus.
Author(s): Md Tanvir Hasan Physics & Astronomy Roberto Gonzalez-Rodriguez Physics & Astronomy Conor Ryan Physics & Astronomy
Advisor(s): Anton Naumov Physics & Astronomy
Location: Session: 1; Basement; Table Number: 2
(Poster is private)
In this work, a simple/scalable microwave-facilitated hydrothermal route is used to produce nitrogen self-doped graphene quantum dots (NGQDs) from a sole glucosamine precursor. These NGQDs with average sizes of ~6nm show bright/stable fluorescence both in the visible and near-IR. The structural and optical properties of as-prepared NGQDs are further altered to provide control for optoelectronic applications by using ozone and thermal treatment. Thermal processing serves as controllable avenues to decrease GQD emission via anticipated reduction processes. Oxidative ozone treatment results in the decrease of GQD average size down to 5.23 nm and a more disordered structure due to the introduction of the new functional groups. Structural and optical characterization was performed utilizing TEM, AFM, SEM microscopy and FTIR, EDX, Raman, fluorescence, absorbance spectroscopy. FTIR, EDX and Raman data suggest that this processing introduces oxygen-containing functional groups, enhancing the atomic percentage of oxygen and increasing ID/IG ratio. Ozone treatment shows enhancement of visible emission which is observed from 0 to 16 min ozone processing with following over oxidation-induced defect-related quenching. On the other hand, a progressive increase in defect-related NIR emission is observed up to 45 min. Such alteration of optoelectronic properties enhances NGQD performance in photovoltaic devices.
Untreated NGQDs (Un-NGQDs) and ozone-treated NGQDs (Oz-NGQDs) are utilized as a photoactive layer to fabricate a variety of solar cells. Although devices with untreated NGQDs show performances similar to existing reports, Oz-NGQDs exhibit significant improvement (~six fold) with maximum PCE of 2.64%, an open circuit voltage of ~0.83V, a short circuit current density of 4.8 mA/cm^2, and an excellent fill factor of ~86.4%. This enhancement can be potentially attributed to the increased/broadened visible absorption feature in device state due to the efficient charge transfer between the hole-blocking layer of TiO2 and Oz-NGQD having enhanced concentration of functional groups. This work suggests ozone treatment as an easy and powerful technique to alter the optoelectronic properties of versatile and scalably produced NGQDs which can be successfully utilized as an eco-friendly photoactive layer to boost the photovoltaic performance of solar cells.
Quantum mechanical oscillations of a many-body system about a local potential minimum can in a first approximation be modeled by a set of harmonic oscillators about a local potential minimum. In more sophisticated models one also has to consider anharmonic effects.
Here we present the first steps towards a systematic solution of ground and excited state energies for a set of coupled quartic oscillators using coupled cluster techniques. We present the general approach of the equation of motion coupled cluster (EOM-CC) method. We give illustrative details of the diagrammatic approach to obtaining our operating equations as well as the resulting EOM-CC equations for a simple system of coupled harmonic oscillators perturbed by a quadratic perturbation. We point to the connection with Bogoliubov transformations and finally we illustrate the numerical behavior of the EOM-CC non-linear iterations and matrix diagonalization of our effective Hamiltonian obtained with our Python code.
Respiratory syncytial virus, or RSV, is a virus that commonly causes lower respiratory tract infections throughout childhood and infancy. Most people who contract the virus recover within a short period of time, but it can cause respiratory illness, hospitalization, and even death within infants and the elderly. Agents that can effectively combat RSV are still not available for widespread clinical use, but one of the targets being investigated is PC786, a novel inhaled L-protein polymerase inhibitor. Using data from previous publications, we created models of the relationship between volume of PC786 and viral load in patients with RSV to try to determine how to best model the action of this drug.
Author(s): Bong Han Lee Physics & Astronomy Elizabeth Campbell Physics & Astronomy Md Tanvir Hasan Physics & Astronomy
Advisor(s): Anton Naumov Physics & Astronomy Giri Akkaraju Biology
Location: Session: 1; Basement; Table Number: 5
(Poster is private)
Carbon nanomaterials have recently attracted the interest of the scientific community, in the field of electronics, photonics, material and environmental science, due to their unique physical, electronic, and optical properties. In the context of biotechnology, these nanomaterials have been utilized to deliver cancer therapeutics and gene medicines. For tumor-specific delivery those can be conjugated with biomolecules to target receptors of cancer cells. This allows nanomaterials to bind providing fluorescence-based cancer diagnosis and imaging as well as drug delivery by the nanomaterials. However, conjugation has been accomplished mainly via covalent bonding that may involve toxic reagents and is at times cost-ineffective. For some nanomaterials functionalization may also alter the physiochemical properties rendering them less emissive. In this work, we assessed whether non-covalent bonding to a targeting agent would be enough to focus the intake of graphene oxide (GO) and nitrogen-doped graphene quantum dots (NGQDs) into the cancer cells. The targeting of CD44 receptors via a hyaluronic acid (HA) non-covalently attached to these nanomaterials was evaluated in human breast cancer (MCF-7) cells, which overexpresses the CD44 protein versus healthy (HEK 293) cells that do not overexpress it. In vitro fluorescence microscopy indicated a significant increase in accumulation of HA-conjugated nanomaterials as assessed from their intracellular emission signal. Thus, in this work, we have demonstrated the feasibility of non-covalently bonding HA onto GO and NGQDs as biocompatible nanomaterials for a targeted delivery. Further investigation will compare these findings to accumulation of covalently-attached HA-nanoparticle conjugates and assess the advantages of non-covalent complexation.
We are modeling the effect of the Hill coefficient on the volume of a tumor. This is to test drugs that may bind to multiple receptors and compare them to each other. We are using Python and used 4 main parameters and one equation. We modeled the Volume and the Dose Response Curves as well as the Emax and Ic50. We used the different positive Hill Coefficients and studied the effect on dose and carrying capacity.
Fluorescing nanoparticles are utilized widely for applications in optoelectronics, sensing, biomedical imaging, and cancer detection. In these applications it is often overlooked that the temperature may affect the optical performance of nanomaterials in optoelectronic devices or even in the biological live systems. In this work we built an apparatus for controllable temperature adjustment of aqueous dispersions of nanomaterials inside the spectrometer as their fluorescence spectra are being monitored. This module is built based on the thermoelectric elements with a corresponding controller and affixed to a cuvette holder of the fluorescence spectrometer. Using this setup, we assess the fluorescence of 0D, 1D and 2D carbon nanomaterials: graphene quantum dots, carbon nanotubes, and graphene oxide subjected to temperatures ranging from room temperature to 100 ⁰C. These experiments will allow us to assess the performance of nanomaterials as they fluorophores at a variety of temperatures and will serve as basis for understanding the thermal effect on their optoelectronic and, potentially, structural properties.
Sagittarius (Sgr), a dwarf galaxy and satellite to the Milky Way, is currently being tidally torn apart. To study the chemistry of Sgr, we have taken thousands of stellar spectra across the galaxy. We have analyzed the stellar component of Sgr member stars by using The Cannon, a machine learning algorithm for determining stellar parameters (temperature, surface gravity, chemical abundances) from stellar spectra. A subset of our stars have previously been observed as part of SDSS/APOGEE survey, at higher quality, which allows us to use these spectra to train The Cannon so that we can obtain accurate abundances for the ~1,200 Sgr member stars. This will allow us to confidently study the formation history and stellar evolution of Sgr, and place it within the context of other dwarf galaxies.
In order to determine correct dosage of chemotherapy drugs, the effect of the drug must be properly quantified. There are two important values that characterize the effect of the drug: ε_max is the maximum possible effect from a drug, and IC_50 is the drug concentration where the effect diminishes by half. We use mathematical models to estimate how the values depend on measurement time and model choice. Improper choice of growth model is problematic and can lead to differences in predictions of treatment outcomes for patients. This work intends to understand how choice of model and measurement time affects the relative drug effect and causes the differences in predictions for the most effective dose of anticancer drug for a patient. This work determines the correct doses before trying those in patients to get the most effective therapeutic treatment.
Author(s): Christine Pho Physics & Astronomy Madison Frieler Biology Angel Guyton Biology
Advisor(s): Hana Dobrovolny Physics & Astronomy Giridhar Akkaraju Biology Anton Naumov Physics & Astronomy
Location: Session: 1; Basement; Table Number: 11
(Poster is private)
New anti-cancer drugs are constantly being developed and tested. Eﬀectiveness of these drugs is currently assessed by measuring the reduction in number of cancer cells cultured in experiments as a function of the applied drug dose. These measurements determine the drug dose needed to achieve half of the maximum reduction in cells (IC50) and the maximum eﬀect of the drug (εmax). However, the technique that measures values of IC50 and εmax depends on the time chosen to make the measurements. We have developed a method to analyze the growth of cancer cells in different concentrations of drugs that will provide estimates of both parameters that are independent of measurement time. Here, we computationally simulated the growth of cancer cells according to a logarithmic model, adding different levels of noise. And, we found the error in IC50 and εmax as a function of the level of noise. Development of this new technique will lead to more consistent measurement of the eﬃcacy of known and novel anti-cancer therapies.
Star clusters are key chemical and age tracers of Milky Way evolution. The use of star clusters to provide significant constraints on galaxy evolution, however, has been limited due to discrepancies between different studies. This work seeks to add additional open clusters into an existing large, uniform chemical abundance system. We analyze spectra of giant stars in 31 open clusters and, using a machine learning method called The Cannon, determine iron abundances. This uniform analysis is compared with previous results, and we present new chemical abundances of 12 star clusters.
Author(s): John Reeks Physics & Astronomy Tabitha Haun Physics & Astronomy Benite Ishimwe Environmental Sciences Bao Thach Engineering Jacob Tzoka Physics & Astronomy Kimon Vogt Engineering
Advisor(s): Yuri Strzhemechny Physics & Astronomy
Location: Session: 2; 3rd Floor; Table Number: 4
Antimicrobial action of micro- and nanoscale ZnO particles has been documented, but the fundamental physical mechanisms driving this action 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. Crystalline structure of ZnO results in two distinct types of crystallographic surfaces: polar (charged) and non-polar (neutral). The excess charge and electronic states at the polar surfaces of micro- and nano-scale ZnO particles may affect interfacial phenomena with surrounding media. Therefore, it is feasible that the relative abundance of such polar surfaces could significantly influence their antibacterial action. In this study we use a hydrothermal growth method established in our lab to synthesize ZnO crystals with different controllable surface morphologies. We study the effects of relative abundance of polar surfaces on antibacterial action. These experiments performed in conjunction with optoelectronic studies of ZnO crystals yield information regarding the fundamental nature of their antibacterial action.
Author(s): John Reeks Physics & Astronomy Tabitha Haun Physics & Astronomy Benite Ishimwe Environmental Sciences
Advisor(s): Yuri Strzhemechny Physics & Astronomy
Location: Session: 1; 3rd Floor; Table Number: 4
Polysulfone is a stable and strong semitransparent thermoplastic material that is applicable in many industries due to its resistance to low and high temperatures, as well as unique hydrophobic properties. Hydrophobic films are frequently used in waterproofing devices and to improve the efficiency of water vessels. It was recently discovered that polysulfone has a unique behavior as it changes from being hydrophobic to hydrophilic after exposure to a UV radiation. In order to elucidate the mechanisms behind this phenomenon we are performing surface photovoltage (SPV) studies on polysulfone thin films, which is done for the first time, to the best of our knowledge. Whereas SPV is sensitive to buried interfaces, SPV spectral features contain contributions not only from the polysulfone films, but from the silicon wafer and the silicon oxide layer beneath the polymer films. Thereby, to identify the signal germane to the polysulfone properly, we employ in our studies polysulfone films of varying and controllable thicknesses. To establish controllable methods for producing such films by spin coating, we use different concentrations of polysulfone in solutions with different spin rates. Film thickness is determined employing a thin film analyzer. From these thicknesses, trends are established relating film thickness to solution concentration and spin rate. SPV studies provide initial investigations into surface electronic transitions and mechanisms behind the hydrophobic ‘flipping’ of polysulfone.
High-power laser excitation systems are critical in observing and studying nanomaterials and their optoelectronic properties on a single specie level. These systems enable inducing fluorescence and observing emission microscopically from individual flakes and or molecules. As the fluorescence of nanomaterials is often excitation dependent, multiple laser with different frequencies are needed to probe their optical properties. In this work we construct such multi-laser setup to use for a microscopy system to enable imaging nanocarbons: flakes of functional derivatives of graphene, carbon nanotubes, and graphene quantum dots.
The system is composed of four lasers of varying wavelength: blue at 450 nm, green at 532 nm, red at 637 nm, and near-infrared (NIR) at 808 nm. An additional near-infrared laser at 980 nm is included for special applications with deep NIR imaging. These lasers were set up to be turned on and off remotely and traverse through a system of dichroic and regular mirrors and a periscope coupled to a fluorescence microscope. A neutral density filter wheel designed and set up in the light path enables altering the intensity of the lasers leading to optimized fluorescence and imaging. The resulting laser set up allowed effective imaging of graphene oxide flakes, graphene quantum dots, and carbon nanotubes both on a microscope slide and in biological cells and tissues.
(Poster is private)
The goal of this project was to engineer complexes of antibiotics and nanomaterials that address gram negative bacteria more efficiently than antibiotics alone. The gram-negative class of bacteria has two cell membranes, as opposed to the gram-positive class which has only one; this second membrane poses an additional challenge for antibiotic cell entry. Theoretically, the amphiphilic nanomaterials may aid the antibiotics by assisting them through both membranes and masking their entry. A number of nanomaterials were tested including graphene quantum dots, single-walled carbon nanotubes, and graphene oxide, and antibiotics including Penicillin, Methicillin, Amoxicillin, Norfloxacin and Linezolid were tested as well. Carbon nanotubes were supplemented with polyethylene-glycol coating agent, while water-soluble GQDs and graphene oxide were used as synthesized in our laboratory. The complex of the antibiotic Norfloxacin and Graphene Quantum Dots (GQDs) was selected as the most efficacious. It allowed killing of the gram-negative bacteria E. Coli at moderate concentrations significantly more efficiently than unaccompanied Norfloxacin. Its colocalization with bacteria was verified via high quantum yield (over 62%) intrinsic fluorescence of GQDs in the visible. This may lead to substantial improvement of antibacterial techniques against gram negative bacteria, increase in antibiotic efficacy, and potentially the recycling of antibiotics to which bacteria exhibit resistance.
The interaction between low-mass galaxies are of critical importance for the growth and evolution of galaxies. The star formation can be enhanced during interactions between massive galaxies, but very few studies focus on the interaction between low-mass galaxies. In this work, we explored the current star-formation surface density in both isolated and interacting galaxies and look for enhanced star formation during the interactions. A galaxy will be considered as a galaxy pair candidate if the physical separation between it and its closest low-mass galaxies is smaller than 5000 light years, otherwise it will be put into the isolate galaxy sample. This sample intentionally excludes galaxies with a massive galaxy neighbor nearby as massive neighbors can harass low-mass companion galaxies and can cause them to become quenched. This project is the first attempt to systematically study how the internal star-formation activities of low-mass galaxies are influenced by outer environment.
The details of how galaxies form and evolve remains uncertain. Observing galaxy evolution in real time is impossible; hence simulations are invaluable in analyzing their behavior. Dwarf galaxies are the most abundant type of galaxies in the universe, their sensitivity to local feedback and neighboring galaxies makes them excellent probes of their environments. We simulate dwarf galaxies in the environment around the Milky Way Galaxy using multi-body simulations of a Milky Way analog. Star formation and feedback are then added using GALACTICUS, a model that solves equations by breaking them into smaller components. Our work investigates the effect of star formation rate, stellar feedback, supernova winds among other effects on the dwarf satellites of the Milky Way. The models will then be compared to already available observational data and existing high resolution dynamical simulations to determine the best fitting parameters.
(Poster is private)
In this experiment we take the differential equation model from Heldt 2012 for the viral life cycle and apply a stochastic algorithm in order to simulate random events on a molecular level. We then introduce a known mechanism by which to mutate the produced virus particles and attempt to understand the relationship between surface proteins and these random mutations. This work will shed light on the efficacy of particular antiviral drugs that act on the binding of surface proteins to the cell membrane.
Nearby, the Large Magellanic Cloud galaxy (LMC), has ejected massive amounts of gaseous material, some of which is headed toward the Milky Way. The material consists of ionized hydrogen gas which is a consequence of significantly energetic events that have occurred in the LMC. Such events are not only the cause of the ionized material, but also the immense amount of material being thrown out. This ejected wind holds a substantial amount of information regarding both galaxies in general and the LMC’s physical processes. Studying this ionized outflow will reveal new details concerning the internal processes that produce such massive ejections, the potential for galactic outflows to replenish gas reservoirs for future star formation, and the environments surrounding galaxies. The latter will influence our view of a galaxy’s environment and how it may interact with nearby neighbors such as our Milky Way galaxy.