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AJUR Volume 14 Issue 4 (March 2018)
https://doi.org/10.33697/ajur.2018.001
Links to individual manuscripts, abstracts, and keywords are provided below.
p.5. Thermodynamics of Concanavalin A Self-Association in the Presence of Osmolytes
https://doi.org/10.33697/ajur.2018.002
Tyler Pfister*, Shamus Cooper, & Jeffrey K. Myers
Department of Chemistry, Davidson College, NC
Students: Typfister17@alumni.davidson.edu*, Shcooper16@alumni.davidson.edu
Mentor: Jemyers@davidson.edu
ABSTRACT: Protein-protein interactions are critical for biological function and depend significantly on environmental factors. A wide variety of small organic molecules that comprise the cellular environment are capable of interacting with proteins to affect folding, binding, and association. The plant lectin concanavalin A (ConA) undergoes a reversible, pH dependent dimer-to-tetramer equilibrium and has been used in our laboratory as a model system to study the effect of osmolytes on protein self-association. Previous research determined that trimethylamine N-oxide (TMAO) stabilizes the tetrameric conformation, while urea favors the dimer. Studying the equilibrium over a range of temperatures allowed quantification of the enthalpy change (∆H) and entropy change (∆S) of tetramer formation. Urea increased both the ∆H and ∆S of tetramer formation, while TMAO decreased both. These effects are consistent with preferential hydration of the dimer-dimer interface in TMAO solution and preferential binding of urea to the interface.
KEYWORDS: Concanavalin A; Osmolytes; Trimethylamine N-oxide; Urea; Protein-Protein Interaction; Equilibrium; Enthalpy; Preferential Hydration
https://doi.org/10.33697/ajur.2018.003
KatrinaA.Williams*a, Nathaniel S. Thomas b,c, Amy E. Adkins b,c, & Danielle M. Dick b,c,d
a Department of Kinesiology and Health Sciences, Virginia Commonwealth University, Richmond, VA, United States
b College Behavioral and Emotional Health Institute, Virginia Commonwealth University, Richmond, VA, United States
c Department of Psychology, Virginia Commonwealth University, Richmond, VA, United States
d Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, United States
Student: williamska5@vcu.edu*
Mentor: thomasns@vcu.edu
ABSTRACT: Alcohol consumption is common in college attending populations and can have a negative impact on an individual’s academic, physical, and mental health. Previous research suggests that living at home could act as a protective measure. The current research looks at potential mediators of the association between living with parents while attending college and amount of alcohol consumed. In particular, this study examined access to alcohol, parental involvement, and perception of peer drinking as mediators of the association. This study examined freshman data collected from a survey conducted at a large public university in the mid-Atlantic United States. A pathway model was fit to test the relationships between residence status, access to alcohol, parental involvement, and perception of peer drinking on alcohol consumption. We observed statistically significant indirect effects of residence status on alcohol consumption through the perception of peer drinking and access to alcohol. Parental involvement was significantly related to lower alcohol consumption and there was a direct effect of residence status on alcohol consumption. There were significant indirect effects of residence status on alcohol consumption through both peer drinking and access to alcohol. Parental involvement was associated with decreased alcohol consumption, with no indirect effect in association with residence status. These effects were persistent in the presence of a range of covariates, including age, gender, ethnicity, and parental education.
KEYWORDS: Emerging Adult; Alcohol; Residence Status; Peer Drinking; Access to Alcohol; Parental involvement; Path Analysis
p.23. Speedup Potential for Reconstruction Techniques for Prompt Gamma Imaging During Proton Radiotherapy
https://doi.org/10.33697/ajur.2018.004
James Della-Giustina*a, Johnlemuel Casilagb, Elizabeth Gregorioc, & Aniebiet Jacobsb
aDepartment of Information Technology & Computer Science, Community College of Baltimore County, Baltimore, MD
bDepartment of Computer Science & Electrical Engineering, University of Maryland, Baltimore County, Baltimore, MD
cDepartment of Physics, Hamline University, St. Paul, MN
dDepartment of Mathematics and Statistics, University of Maryland, Baltimore County, Baltimore, MD
eDepartment of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD
fDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
Students: jdella@umbc.edu*, cas6@umbc.edu, anie1@umbc.edu, egregorio01@gmail.com
Research Assistant: Carlos Barajasd, barajasc@umbc.edu
Faculty Mentor: Matthias K. Gobbertd, gobbert@umbc.edu
Clients: Dennis Mackinf, dsmackin@mdanderson.org, Jerimy Polfe, jpolf@umm.edu
ABSTRACT: Proton beam radiation treatment was first proposed by Robert Wilson in 1946. The advantage of proton beam radiation is that the lethal dose of radiation is delivered by a sharp increase toward the end of the beam range. This sharp increase, known as the Bragg peak, allows for the possibility of reducing the exposure of healthy tissue to radiation when comparing to x-ray radiation treatment. As the proton beam interacts with the molecules in the body, gamma rays are emitted. The origin of the gamma rays gives the location of the proton beam in the body, therefore, gamma ray imaging allows physicians to better take advantage of the benefits of proton beam radiation. These gamma rays are detected using a Compton Camera (CC) while the SOE algorithm is used to reconstruct images of these gamma rays as they are emitted from the patient. This imaging occurs while the radiation dose is delivered, which would allow the physician to make adjustments in real time in the treatment room, provided the image reconstruction is computed fast enough. This project focuses on speeding up the image reconstruction software with the use of of parallel computing techniques involving MPI. Additionally, we demonstrate the use of the VTune performance analyzer to identify bottlenecks in a parallel code.
KEYWORDS: Proton Beam Therapy; Image Reconstruction; SOE Algorithm; Parallel Computing; High Performance Computing; Medical Imaging; Prompt Gamma Imaging; Radiotherapy
p.39. Knowledge and Behaviors Associated with a Campus Tobacco-Free Policy
https://doi.org/10.33697/ajur.2018.005
Sarah Powell*a, Cassie Odahowskib,c, Elizabeth Crouchd, Erica Sercyb,c, Jackie Knighte, & Jan M. Eberthb,c
a Department of Epidemiology and Biostatistics, College of Public Health, University of South Florida, Tampa, FL
b Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC
c Statewide Cancer Prevention and Control Program, Arnold School of Public Health, University of South Carolina, Columbia, SC
d Department of Health Services Policy and Management, Arnold School of Public Health, University of South Carolina, Columbia, SC
e Healthy Carolina Coalition, University of South Carolina, Columbia, SC
Student: sepowell1@health.usf.edu *
Mentor: jmeberth@mailbox.sc.edu
ABSTRACT: Objective: Nearly half of U.S. colleges/universities have implemented tobacco-free campus policies. This study analyzed knowledge, attitudes, and practices associated with the tobacco-free policy at a large public university. It is important to study public university tobacco policies to determine the most efficient and cost-effective way to reduce tobacco related disease due to tobacco use and exposure. Methods: This study used a cross-sectional, campus-wide electronic survey distributed in November 2016. The primary outcomes of interest included 1) correct knowledge of the tobacco-free policy, 2) community member willingness to approach observed violation of the policy, and 3) a positive opinion of the policy’s effectiveness. Descriptive statistics and logistic regression were used to examine the impact of demographic factors on the outcomes. Results: After analysis, the team found that 23% of university faculty, staff, and students had incorrect knowledge about the campus tobacco-free policy. Almost 70% of the university community reported not having approached a smoking violator. Males were significantly less likely to understand the tobacco-free policy in full, approach a violator, or have a positive opinion about its effectiveness. Staff had better knowledge of the policy, a higher likelihood of approaching a violator, and a better opinion about the policy’s effectiveness compared to graduate and undergraduate students. Conclusions: Interventions are needed to increase awareness and confidence regarding implementation and enforcement of the tobacco-free policy on campus, particularly among faculty and students. This paper expands on the currently increasing knowledge of tobacco-free policy enforcement and benefits.
KEYWORDS: Campus; Tobacco Regulation; Tobacco; Secondhand Smoke; Cross-Sectional Survey
p.49. Conduction Mechanism in Electrically Conducting Polymers
https://doi.org/10.33697/ajur.2018.006
Daniel L.Gochnauer & T. H. Gilani*
Department of Physics, Millersville University, P. O. Box 1002, Millersville PA-17551
Student: dlg15@uw.edu
Mentor: tariq.gilani@millersville.edu
ABSTRACT: The conduction mechanism in conducting polymers is reviewed and experimental results of temperature dependence of electrical conductivity of PF6 doped polypyrrole in temperature range of 77 to 300 K are discussed. The room-temperature conductivitywas experimentally determined to be 73 ± 3.4 S/m and temperature dependence follows the Mott’s variable range hopping model. The average hopping distance at 298 K was (6.75 ± 0.97) ×10-8 cm. The coefficient of decay of the localized states, the density states at the Fermi level, and the hopping activation energy were calculated to be (3.5±0.51) ×107 cm-1, (1.92 ± 0.83) ×1022 cm-3 eV-1, and 0.040 ± 0.001 eV respectively.
KEYWORDS: Electrically Conducting Polymers; Doped Polypyrrole; Temperature Dependence of Conductivity; Hopping Activation Energy; Density of State at Fermi level