Learning Outcome: Provide education about the knowledge, behaviors and attitudes individuals have towards dietary fatty acids.

Background: Research has shown a strong relationship between dietary fatty acids (FAs) and their impact on blood cholesterol. Few studies have examined knowledge, behaviors and attitudes (KBA) towards dietary FAs impact on blood lipid levels.
Objective: To determine: 1) KBA of FAs using the modified General Nutrition Knowledge Questionnaire (GNKQ); and 2) correlations between anthropometric data, GNKQ responses and blood lipid levels.
Design: This study utilized a cross-sectional research design.
Methods: Upon IRB approval, 104 women ages 18-40yr consented and completed the modified GNKQ via Qualtrics®. The GNKQ consisted of 42 questions and took approximately 15min to complete. Additionally, a subset of nine women also were instructed to fast for 12-15hrs prior to testing at the Obesity Prevention Laboratory at TCU. Height (cm), weight (kg), BMI (kg/m2), waist-to-hip ratio were recorded. Next, a fasting blood sample (5mL) was obtained. The blood samples were sent to AnyLabTestNow® (Fort Worth, Texas) for a lipid panel. Results were analyzed via IBM SPSS® (Statistics Version 25.0. Armonk, NY). Significance was set at p<0.05.
Results: More than 80% of participants were aware of saturated, monounsaturated, and polyunsaturated FAs, but only 33.3% were able to identify their proper food sources. Of the survey responses, approximately 1.9% demonstrated poor knowledge (answered 0-11 questions correctly), 54.3% moderate knowledge (12-23 questions correctly), and 43.8% strong knowledge (24-34 questions correctly). 100% of lipid panel participants had normal total cholesterol and HDL levels. Risk ratio (LDL/HDL) and weight showed a strong positive correlation (p=0.004, r=0.846**).
Conclusion: Despite self-reported awareness, participants lack knowledge of dietary FAs. The subset results showed strong correlation between risk ratio and weight representing the relationship between weight and lipid levels. Overall, more research should ensue with a larger sample.

Background: Over 42 million Americans face food insecurity (FI). Simultaneously, approximately 40% of food produced in the U.S. is wasted. Where FI and food waste (FW) coexist, it is necessary to develop and implement programs to decrease the negative consequences caused by these issues.
Objective: The objective of this study was to create a standardized model for implementing a student-led food recovery program (FRP) for other universities to access and utilize. The secondary objective was to measure the effectiveness of the FRP at TCU.
Researchers hypothesized that by incorporating the FRP into the dietetics program, the FRP would achieve program sustainability and enhance dietetic students’ knowledge of FI and FW.
Design: This study utilized a mixed methods study design.
Methods: Over three academic semesters, researchers observed the overall operations of the FRP at TCU. Researchers collected quantitative data on food types (i.e. vegetables, grains, proteins, mixed), quantities (pounds), and raw food costs ($). Researchers conducted semi-structured interviews with nutrition and dietetics students, foodservice personnel, and faculty and analyzed interview transcriptions for prevalent theme codes. A codebook was created based on frequently identified phrases, and themes were extracted. Participants provided written consent. This project received IRB approval.
Results: Over 12,700 pounds of food were recovered during the study period. By weight, protein-containing foods were the most recovered type of food (~5700 lbs.), followed by grains (~2900 lbs.), vegetables (~2100 lbs.), and mixed foods (~2000 lbs.). Five major themes were extracted from interviews; all respondents identified the FRP as a meaningful and practical program.
Conclusions: FRP offers a sustainable solution for benefitting the environment, combating FI, and providing dietetics students with experience working with FI and FW. Efforts should be made to incorporate a FRP at the university level, and a dietetics program may offer an effective means to achieve this integration.

Background: Athletes increasingly skip meals because they lack time or knowledge to prepare their own meals; mobile applications have been proposed as a potential solution to this problem. Adherence to mobile app tracking may vary, but self-motivation and nutrition knowledge has been shown to increase chances of behavior change while using an app.
Objective: Determine if female college athletes’ nutrition/fueling behaviors changed over four weeks by utilizing a mobile application for tracking fueling practices.
Design: Pilot study with cohort of 17 female TCU NCAA Beach Volleyball athletes.
Methods: Pre and post-study questionnaires examined attitudes toward mobile applications, dietary behaviors, and frequency of fueling habits. Athletes also attended a pre-study training session about utilizing the Eat2Win app. Data analyses included recorded frequency of application usage and logged meals per/day plus impact on dietary behaviors/fueling habits. Study procedures were approved by TCU IRB. Participant informed consent was obtained. Data were analyzed to meet study objectives (SPSS, p<0.05).
Results: Most athletes (82%) disliked using the Eat2Win app, where app usage decreased from 88% in week one to 18% app usage at the completion of the study. Reasons for the pronounced decrease in usage included frequent app crashes, too time consuming, and limited phone storage space. Additionally, results did not show improvement in athletes’ eating habits with app usage. Although pre-study results showed 42% of athletes did not consistently eat breakfast and/or eat/drink something every 3-4 hours, those athletes who reported greater frequency of eating breakfast and/or every 3-4 hours or refueling one hour after practice, maintained consistent positive eating behaviors throughout the study. These same athletes also reported greater energy levels overall (r=.671; p=0.01).
Conclusions: Study results emphasize the importance of implementing user-friendly mobile apps for athletes that are time-use efficient and offers calorie-counting and picture logging functions to promote change in dietary and refueling practices.

Background: More than 66% of American adults are overweight or obese. Sugar sweetened beverages (SSB) are a primary source of added calories and may promote weight gain.
Methods: This study was approved by the Institutional Review Board. A random sample of college students provided informed consent before completing an electronic survey that included questions to determine participants’ demographics, self-reported height, weight, physical activity level, total beverage intake, health perceptions, and factors affecting beverage choices. Beverage kcals and intake were determined using the validated BEVQ15 Beverage Questionnaire.
Results: Participants (N=103) were 19.6+/-1.9 years of age with a healthy mean BMI of 23.3+/-3.7. Almost 70% (n=48) had a healthy BMI, ~25% (n=17) were overweight, 6% (n=4) were obese, ~81% (n=83) reported that they were lightly to very active, and 5% (n=5) reported that they were sedentary. Average beverage kcals/day (BKD) was 180.8+/-156.2 and ranged from 0-795 BKD. Among participants (n=75) that completed the BevQ15, 33% (n=26) consumed <100 BKD, 47% (n=35) consumed 100-<300 BKD, and 19% (n=14) consumed > 300 BKD. Normal BMI participants consumed 191 BKD, overweight participants consumed 204 BKD and obese participants consumed 69 beverage BKD. There was no significant correlation between BMI and BKD. Three primary factors which contributed to beverage choices were taste, quenching thirst, and health reported by 54% (n=55), 46% (n=47) and 44% (n=45), respectively. The factors health and calorie content were correlated (r=.23, p<0.05).
Conclusion: Participants had an average healthy BMI and were active. No significant correlations were detected between BMI and BKD. Obese participants consumed fewer BKD than healthy and overweight participants. This lower BKD contribution may be a method used to lose weight. Although calorie content was less frequently cited as a primary factor of beverage choices, participants that identified health as a determining factor were more likely to consider calorie content.

Background: Americans’ choice in caffeinated beverages, consumption amounts, and frequency of consumption varies depending on factors like age, demographics, education level, and social status. Caffeine has shown to increase energy, alertness, attentiveness, and sociability. Research shows that the amount of caffeine consumed by adolescents has increased 70% in the past 30 years.
Objective: The objective of this study was to determine the relationship between the onset of coffee consumption, amount of current coffee consumption, and personal well-being. It was hypothesized that an earlier onset of coffee consumption would have a positive correlation to increased coffee consumption and a negative effect on personal well-being later in life.
Methods/Design: An online survey was administered to college students, age 18-24. Participants were recruited via social media. The survey assessed participants’ history of coffee consumption, current coffee consumption, and perception of impact on appetite, mental status, mood, sleep patterns, and overall health. Data was entered into SPSS after survey responses were collected.
Results: Upon surveying participants (N=95), there were strong positive correlations (p<0.01) between the onset of coffee consumption, amount consumed at onset, and current consumption level. Notably, onset of coffee consumption was likely to occur during significant academic years, such as the first year of college (15.8%, n=15) and first year of high school (13.7%, n=13). Approximately 67% (n=64) reported consuming 1-2 cups/day at onset of consumption. Additionally, 52.6% (n=50) report that coffee consumption benefits their overall mood, while 41.1% (n=39) claim it has no effect on overall health and well-being.
Conclusions: The onset of coffee consumption is commonly seen in times of change, such as significant academic years. Consequently, participants also agreed that caffeine consumption benefits their mood above other qualities surveyed. Further research relating to other types of caffeinated beverages and foods would provide more conclusive results about onset and wellbeing.

Background: Diabetes Mellitus is a chronic condition that affects the body’s ability to use energy in food. Diabetes impacts more than 170 million people worldwide. Previous research suggests that people with diabetes report feeling stigmatized and that there is a lack of understanding by the public.
Objective: The objective of this study was to determine the level of diabetes knowledge among college students and their perception of people with diabetes. It was hypothesized that there is a lack of diabetes education among this group and that they would have an overall negative perception of people with diabetes.
Methods: An online survey was developed which assessed participants’ knowledge of Type 1 and Type 2 Diabetes and stigmas associated with the condition. Participants were recruited via email and social media. Data was analyzed using SPSS.
Results: Upon surveying participants (N=126), the majority reported knowing someone with Type 1 (63%; n=78) and/or Type 2 Diabetes (53%; n=67). Knowledge of someone with diabetes was strongly correlated with overall diabetes knowledge (p≤0.01). Approximately 63% (n=78) of respondents believe there is a stigma associated with diabetes. Reasons for the stigma include lack of diabetes education (63%; n=78) and negative portrayal of diabetes in the media (52%; n=65). There was a strong correlation (p≤0.01) between diabetes knowledge and whether or not respondents had a negative perception of people with diabetes.
Conclusions: Though the respondents reported that a stigma exists, a low percentage of respondents reported having negative perceptions of people with diabetes. This finding may be attributed to the large number of participants who knew people with diabetes, number of participants in health related majors, or those who had taken a college-level nutrition course. Future research could mitigate these variables by excluding participants in health-related majors or those who have had extensive education on the subject.

Background: Much of the research associated with eating patterns of adolescents or young adults has been related to genetics, weight gain associated with parental influence of food selection, and children’s food choices relative to their parent’s desires. There is little research conducted on children’s perceptions of their parent’s food choices and how those beliefs correlate to their own dietary choices later in life.
Objective: The objective of this study was to determine whether parents’ perceptions of food had an effect on their children’s eating behaviors later in life. The hypothesis was that the food-related behaviors and beliefs of the parents strongly influence the child’s future dietary choices and lifelong relationship with food.
Methods: An online survey was developed that consisted of questions regarding student’s perceptions of their parents’ dietary choices and their own current dietary choices and beliefs. Researchers recruited participants via email and social media. Data was analyzed using SPSS.
Results: Among survey participants (N=158) there was a significant correlation (p<0.01) between the parent’s past eating behaviors and child’s current eating behaviors for several dietary patterns, including vegan, low carbohydrate, calorie counting and gluten free. Approximately 42% (n=66) of respondents reported that they were made aware of their weight at a young age. There was a strong correlation (p<0.01) between parents discussing weight and discouraging attempts to try new foods.
Conclusions: There was a significant correlation between the way that children view diet and nutrition and how their parents view diet and nutrition, as perceived by the children. Parents’ specific eating behaviors and discussions about weight also correlate with their children’s current eating behaviors and awareness of weight, although they may not currently live together. For more conclusive results, future research on the subject should also include data regarding parents’ perspective of their own food choices and beliefs.

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.

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.

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.

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.

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.

With the advent of graphene, there has been an interest in utilizing this material and its derivative, graphene oxide (GO) for novel applications in nanodevices such as bio and gas sensors, solid state supercapacitors and solar cells. Although GO exhibits lower conductivity and structural stability, it possesses an energy band gap that enables fluorescence emission in the visible/near infrared leading to a plethora of optoelectronic applications. In order to allow fine-tuning of its optical properties in the device geometry, new physical techniques are required that unlike existing chemical approaches yield substantial alteration of GO structure. Such desired new technique is one that is electronically-controlled and lead to reversible changes in GO optoelectronic properties. In this work, we for the first time investigate the methods to controllably alter the optical response of GO with the electric field and provide theoretical modelling of the electric field-induced changes. Field-dependent GO emission is studied in bulk GO/PVP films with up to 6% reversible decrease under 1.6 V/µm electric fields. On an individual flake level, a more substantial over 50% quenching is achieved for select GO flakes in polymeric matrix between interdigitated microelectrodes subject to two orders of magnitude higher fields. This effect is modelled on a single exciton level by utilizing WKB approximation for electron escape form the exciton potential well. In an aqueous suspension at low fields GO flakes exhibit electrophoretic migration indicating a degree of charge separation and a possibility of manipulating GO materials on a single-flake level to assemble electric field-controlled microelectronics. As a result of this work, we suggest the potential of varying the optical and electronic properties of GO via the electric field for the advancement and control over its optoelectronic device applications.

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.

Non-invasive temperature sensing is necessary for the analysis of biological processes occurring in the human body including cellular enzyme activity, protein expression, and ion regulation. Considering that a variety of such biological processes occur at the microscopic scale, a novel mechanism allowing for the detection of the temperature changes in microscopic environments is desired. One-dimensional graphene quantum dots can serve as agents for such detection: they are promising non-invasive probes that because of their 2-5 nm size and optical sensitivity to temperature change enable sub-cellular resolution imaging. Both biocompatible bottom-up synthesized nitrogen-doped graphene quantum dots and quantum dots produced from reduced graphene oxide via top-down approach exhibit temperature-induced fluorescence variations. This response observed for the first time is utilized for deterministic temperature sensing in bulk suspension as well as inside mammalian cells. Distinctive quenching of quantum dot fluorescence by up to 19.8 % is observed, in a temperature range from 25℃ to 49℃, in aqueous solution, while the intensity is restored to the original values as the temperature decreases back to 25℃. A similar trend is observed in vitro in HeLa cells as the cellular temperature is increased from 25℃ to 41℃. Our findings suggest that the temperature-dependent fluorescence quenching of bottom-up and top-down-synthesized graphene quantum dots can serve as non-invasive reversible deterministic mechanism for temperature sensing in microscopic sub-cellular biological environments.

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.

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.

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.

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.