Student Presentations
Oral Presentations
Using Surfactants to Solubilize Luminescors to Aid in the Detection of Explosives Through Fluorescence Quenching
Tristan Torres, Elon University
There are an estimated 22,800 backlogged cases dealing with fire debris and explosives awaiting forensic analysis across the United States. Investigators of crimes could benefit from a forensic analysis kit that could be deployed the scene of the crime rather than waiting on lab analysis. Many explosive chemicals exhibit luminescence quenching, which is a decrease in fluorescence intensity. Kits that are based on one form, known as electrochemiluminescence (ECL), have the potential to be less expensive and therefore more affordable to municipal law enforcement agencies. In order to distinguish among various explosives and be effective, multiple luminescors would need to be utilized, but many known substances that exhibit ECL require non-aqueous solvents, most of which are hazardous. This barrier can be overcome with the use of surfactants to solubilize luminescors. For rapid screening of luminescor/surfactant combinations, 96-well plates were used in a fluorescence plate reader, with the intention of expanding to study ECL once optimum parameters have been established. The luminescor used in experimentation was rubrene, and solutions of rubrene in toluene, a known solvent, were used to create a calibration curve to provide an estimate of maximum solubility of rubrene in the surfactant, TX-100. Varying concentrations of TX-100 above the critical micelle concentration (CMC) were used in determining the maximum solubility: 0.025%, 0.05%, 0.1% and 0.5%. Using those estimated values, rubrene/TX-100 solutions were studied using a fluorescence plate reader to provide a more accurate value for maximum solubility of rubrene; it was found that 0.5% TX100 provided the best results, with a rubrene solubility of 0.045mg/mL. To a set of rubrene/TX100 solutions of constant concentration, increasing amounts of TNT were added, followed by fluorescence analysis and calculation of the quenching factor (QF) for each solution. A plot of QF vs. TNT concentration yields the Stern Volmer constant (Ksv) as the slope. Theoretically, the Ksv should be unique to each luminescor/explosive pair. Similar studies have been conducted with luminol and TNT, and the results from those studies and other luminescor/explosive pairs will be reported.
Tristan Torres, Elon University
There are an estimated 22,800 backlogged cases dealing with fire debris and explosives awaiting forensic analysis across the United States. Investigators of crimes could benefit from a forensic analysis kit that could be deployed the scene of the crime rather than waiting on lab analysis. Many explosive chemicals exhibit luminescence quenching, which is a decrease in fluorescence intensity. Kits that are based on one form, known as electrochemiluminescence (ECL), have the potential to be less expensive and therefore more affordable to municipal law enforcement agencies. In order to distinguish among various explosives and be effective, multiple luminescors would need to be utilized, but many known substances that exhibit ECL require non-aqueous solvents, most of which are hazardous. This barrier can be overcome with the use of surfactants to solubilize luminescors. For rapid screening of luminescor/surfactant combinations, 96-well plates were used in a fluorescence plate reader, with the intention of expanding to study ECL once optimum parameters have been established. The luminescor used in experimentation was rubrene, and solutions of rubrene in toluene, a known solvent, were used to create a calibration curve to provide an estimate of maximum solubility of rubrene in the surfactant, TX-100. Varying concentrations of TX-100 above the critical micelle concentration (CMC) were used in determining the maximum solubility: 0.025%, 0.05%, 0.1% and 0.5%. Using those estimated values, rubrene/TX-100 solutions were studied using a fluorescence plate reader to provide a more accurate value for maximum solubility of rubrene; it was found that 0.5% TX100 provided the best results, with a rubrene solubility of 0.045mg/mL. To a set of rubrene/TX100 solutions of constant concentration, increasing amounts of TNT were added, followed by fluorescence analysis and calculation of the quenching factor (QF) for each solution. A plot of QF vs. TNT concentration yields the Stern Volmer constant (Ksv) as the slope. Theoretically, the Ksv should be unique to each luminescor/explosive pair. Similar studies have been conducted with luminol and TNT, and the results from those studies and other luminescor/explosive pairs will be reported.
Parking Traffic Analysis Using Machine Learning
Jake Haines, University of North Carolina - Asheville
Many residents attending and living at my university have a very difficult time finding parking near their dorms due to lack of available resident parking provided by the campus. Additionally, some of the resident parking was closed due to structural issues, further making finding parking a darwinistic situation. Having to make a hike back to the dorm in cold weather after a long night of working is not something anyone looks forward to, so rather than trying to manipulate circumstances out of my control, I decided to find any loopholes that could be manipulated-- which are hidden in some more general traffic patterns in resident parking and in downtown Asheville parking trends. Gathering such data on campus in a cost effective and non-intrusive manner required use of an object classification model deployed to a Raspberry Pi system, which could be run autonomously. Further analyses and visual representation of the data could then be done after the data collection. Using time-series analyses and data visualization, it will be possible to create time bins to arrive back to campus after a long day at work or grocery shopping, with the highest likelihood of finding a parking spot in resident parking.
Jake Haines, University of North Carolina - Asheville
Many residents attending and living at my university have a very difficult time finding parking near their dorms due to lack of available resident parking provided by the campus. Additionally, some of the resident parking was closed due to structural issues, further making finding parking a darwinistic situation. Having to make a hike back to the dorm in cold weather after a long night of working is not something anyone looks forward to, so rather than trying to manipulate circumstances out of my control, I decided to find any loopholes that could be manipulated-- which are hidden in some more general traffic patterns in resident parking and in downtown Asheville parking trends. Gathering such data on campus in a cost effective and non-intrusive manner required use of an object classification model deployed to a Raspberry Pi system, which could be run autonomously. Further analyses and visual representation of the data could then be done after the data collection. Using time-series analyses and data visualization, it will be possible to create time bins to arrive back to campus after a long day at work or grocery shopping, with the highest likelihood of finding a parking spot in resident parking.
A Statistical Analysis of COVID-19 Mental Health Data
Lucas Hansen, Wake Forest University
In late December 2019, the novel coronavirus (Sars-Cov-2) and the resulting disease COVID-19 were first identified in Wuhan China. The disease slipped through containment measures, with the first known case in the United States being identified on January 20th, 2020. In the present paper, we utilized survey data from the Inter-university Consortium for Political and Social Research and constructed several statistical models to analyze the impacts the COVID-19 pandemic has had on the mental heath of frontline workers in the UnitedStates. The results indicate that the top predictors of mental health were the Healthcare role a person is in (Nurse, Psychologist, Emergency Room Staff, etc.), the amount of alcohol consumed, and how many hours a person has slept.
Lucas Hansen, Wake Forest University
In late December 2019, the novel coronavirus (Sars-Cov-2) and the resulting disease COVID-19 were first identified in Wuhan China. The disease slipped through containment measures, with the first known case in the United States being identified on January 20th, 2020. In the present paper, we utilized survey data from the Inter-university Consortium for Political and Social Research and constructed several statistical models to analyze the impacts the COVID-19 pandemic has had on the mental heath of frontline workers in the UnitedStates. The results indicate that the top predictors of mental health were the Healthcare role a person is in (Nurse, Psychologist, Emergency Room Staff, etc.), the amount of alcohol consumed, and how many hours a person has slept.
Force Plate Data Machine Learning Analysis
Morgan A Glisson, University of North Carolina - Wilmington
Machine learning plays a crucial part in our society's efforts to combat injury to athletes. The purpose of this paper is to analyze and examine the studies conducted and to predict the condition/trial type (eyes open, closed, etc.) based on anterior-posterior sway (AP sway) and medial-lateral (ML) sway from the dataset provided by Rachel McCormick on the University of North Carolina Wilmington's diving team. In McCormick's experiment, a force plate is used to measure a series of trials conducted. It is surmised that the more dives performed, the worse the individual's balance became over time. This work uses regression, deep learning, and classification to predict AP sway, ML sway, trial type, and subject number. We were able to accurately predict all features with over 90\% accuracy. This means that not only are we able to accurately predict the amount a participant would sway in the anterior-posterior and medial-lateral direction, but also predict who the participant was, and the manner in which they were standing on the force plate.
Morgan A Glisson, University of North Carolina - Wilmington
Machine learning plays a crucial part in our society's efforts to combat injury to athletes. The purpose of this paper is to analyze and examine the studies conducted and to predict the condition/trial type (eyes open, closed, etc.) based on anterior-posterior sway (AP sway) and medial-lateral (ML) sway from the dataset provided by Rachel McCormick on the University of North Carolina Wilmington's diving team. In McCormick's experiment, a force plate is used to measure a series of trials conducted. It is surmised that the more dives performed, the worse the individual's balance became over time. This work uses regression, deep learning, and classification to predict AP sway, ML sway, trial type, and subject number. We were able to accurately predict all features with over 90\% accuracy. This means that not only are we able to accurately predict the amount a participant would sway in the anterior-posterior and medial-lateral direction, but also predict who the participant was, and the manner in which they were standing on the force plate.
Force Plate Data Machine Learning Analysis
Blythe Layne, University of North Carolina - Wilmington
Machine learning plays a crucial part in our society's efforts to combat injury to athletes. The purpose of this paper is to analyze and examine the studies conducted and to predict the condition/trial type (eyes open, closed, etc.) based on anterior-posterior sway (AP sway) and medial-lateral (ML) sway from the dataset provided by Rachel McCormick on the University of North Carolina Wilmington's diving team. In McCormick's experiment, a force plate is used to measure a series of trials conducted. It is surmised that the more dives performed, the worse the individual's balance became over time. This work uses regression, deep learning, and classification to predict AP sway, ML sway, trial type, and subject number. We were able to accurately predict all features with over 90\% accuracy. This means that not only are we able to accurately predict the amount a participant would sway in the anterior-posterior and medial-lateral direction, but also predict who the participant was, and the manner in which they were standing on the force plate.
Blythe Layne, University of North Carolina - Wilmington
Machine learning plays a crucial part in our society's efforts to combat injury to athletes. The purpose of this paper is to analyze and examine the studies conducted and to predict the condition/trial type (eyes open, closed, etc.) based on anterior-posterior sway (AP sway) and medial-lateral (ML) sway from the dataset provided by Rachel McCormick on the University of North Carolina Wilmington's diving team. In McCormick's experiment, a force plate is used to measure a series of trials conducted. It is surmised that the more dives performed, the worse the individual's balance became over time. This work uses regression, deep learning, and classification to predict AP sway, ML sway, trial type, and subject number. We were able to accurately predict all features with over 90\% accuracy. This means that not only are we able to accurately predict the amount a participant would sway in the anterior-posterior and medial-lateral direction, but also predict who the participant was, and the manner in which they were standing on the force plate.
Slot-die Coater and Organic Field-effect Transistors
Arina Yu, Wake Forest University
I’ll talk about the solution processing methods for organic semiconductors, working principles of slot-die coating, and functions related to the film control when processing transistors.
Arina Yu, Wake Forest University
I’ll talk about the solution processing methods for organic semiconductors, working principles of slot-die coating, and functions related to the film control when processing transistors.
Computing the Value of Data in Machine Learning Applications
Jasmine Xu, Wake Forest University
Today, data helps people make different types of decisions and predictions. Especially in some industries, such as health care and marketing, data is an important resource for the analysis and decision-making.General public is becoming increasingly aware of the data they generate and the value of these data. When some entities, such as business or researchers, collect data from the public, it becomes a challenge for them to quantify the value of data and to decide how to compensate those individuals who provide the data. The value of data used in machine learning, may be estimated computationally. Specifically, in order to compute the value of data, we need three ingredients: training data set, learning algorithm and the metric of model's performance. The presentation will talk about a method to data valuation, Data Shapley, and its applications.
Jasmine Xu, Wake Forest University
Today, data helps people make different types of decisions and predictions. Especially in some industries, such as health care and marketing, data is an important resource for the analysis and decision-making.General public is becoming increasingly aware of the data they generate and the value of these data. When some entities, such as business or researchers, collect data from the public, it becomes a challenge for them to quantify the value of data and to decide how to compensate those individuals who provide the data. The value of data used in machine learning, may be estimated computationally. Specifically, in order to compute the value of data, we need three ingredients: training data set, learning algorithm and the metric of model's performance. The presentation will talk about a method to data valuation, Data Shapley, and its applications.
Numerical Approach to Pricing Exotic Options
Scott Crowley, Wake Forest University
In this work we use stochastic calculus to price a variety of options. Options are assets whose value depends upon an underlying asset, akin to insurance. We study call options, knockout barrier options, Asian options and spread options. For each option, we derive a PDE which the value satisfies, and then use numerical techniques to solve the associated PDE.
Scott Crowley, Wake Forest University
In this work we use stochastic calculus to price a variety of options. Options are assets whose value depends upon an underlying asset, akin to insurance. We study call options, knockout barrier options, Asian options and spread options. For each option, we derive a PDE which the value satisfies, and then use numerical techniques to solve the associated PDE.
Cell-type Identification using Supervised and Unsupervised Machine Learning
Nathan Whitener, Wake Forest University
Experimental methods to collect the expression of cellular RNA data have improved in recent years. These improved methods allow for the analysis of gene expression at a single-cell level. Analysis of single-cell RNA sequencing (scRNA-seq) experiments may provide valuable insights into the composition of individual cells and the identification of their types. We evaluated the accuracy of cell-type identification using both unsupervised and supervised machine learning methods, cluster analysis and classification, respectively. Specifically, we tested the k-means and PhenoGraph clustering algorithm and the XGBoost classification algorithm and estimated two performance metrics using the ground truth labels of 13 benchmark datasets of varying size, organism, complexity, etc. Normalized mutual information (NMI) was used to evaluate clustering and accuracy was used to evaluate classification. We found that both clustering and classification can identify known cell types accurately, although their performance varied in different benchmarks. In unsupervised cell-type identification, k-means algorithm outperformed PhenoGraph by achieving an average NMI score of 0.54 compared to NMI of 0.45 for PhenoGraph. In classification, the average accuracy of XGBoost was 82.7%. Taken together, these results demonstrate that the supervised classifier, XGBoost, performs better in cell-type identification.
Nathan Whitener, Wake Forest University
Experimental methods to collect the expression of cellular RNA data have improved in recent years. These improved methods allow for the analysis of gene expression at a single-cell level. Analysis of single-cell RNA sequencing (scRNA-seq) experiments may provide valuable insights into the composition of individual cells and the identification of their types. We evaluated the accuracy of cell-type identification using both unsupervised and supervised machine learning methods, cluster analysis and classification, respectively. Specifically, we tested the k-means and PhenoGraph clustering algorithm and the XGBoost classification algorithm and estimated two performance metrics using the ground truth labels of 13 benchmark datasets of varying size, organism, complexity, etc. Normalized mutual information (NMI) was used to evaluate clustering and accuracy was used to evaluate classification. We found that both clustering and classification can identify known cell types accurately, although their performance varied in different benchmarks. In unsupervised cell-type identification, k-means algorithm outperformed PhenoGraph by achieving an average NMI score of 0.54 compared to NMI of 0.45 for PhenoGraph. In classification, the average accuracy of XGBoost was 82.7%. Taken together, these results demonstrate that the supervised classifier, XGBoost, performs better in cell-type identification.
Musical Influence on Skin Conductivity & Emotional Frequency in Type II Diabetes
Adunoluwa Akinola, Forsyth Technical Community College
Because type II diabetes (T2DM) is a complex disease that exhibits complications such as hyperglycemia, insulin resistance, and neuropathy, numerous therapies are underway to help to mitigate these problems. In African American populations, the risk for T2DM is high; consequently, many in this group deal with such symptoms and suffer from emotional imbalance. Music therapy is a growing field that not only elicits emotional responses, but also improves mental balance, builds the immune system, and reduces stress. Varying the musical genre can affect the body as well, by regulating both heart rate and blood pressure. When utilizing music therapy in conditions such as T2DM, relaxation of blood vessels also occurs. Thus, we hypothesize that music therapy will reduce neuropathy in T2DM by improving skin conductivity and emotional frequency. To test our hypothesis, participants between the ages of 10 to 55, listened to four genres of music (gospel, rock, afro beats, neo soul), having one song per genre; as well as a control (no music) and their favorite song. The galvanic skin response (GSR) to each musical genre was measured for two minutes pre-, during, and post-music, using a Qubit Q-S222 GSR sensor. Each participant’s current emotion was obtained, at similar time points as the GSR measurements. The emotions were compared to an Emotional Vibrational Frequency Scale to determine emotional frequency. Additional information from each participant was surveyed including: i) age; ii) ethnicity; iii) gender. According to the preliminary data we collected from a control group, listening to music had little effect on the participant’s skin conductance, and a positive effect on their emotional frequency (on average); these data indicate that listening to music of any genre raises the listeners’ emotional frequency.
Adunoluwa Akinola, Forsyth Technical Community College
Because type II diabetes (T2DM) is a complex disease that exhibits complications such as hyperglycemia, insulin resistance, and neuropathy, numerous therapies are underway to help to mitigate these problems. In African American populations, the risk for T2DM is high; consequently, many in this group deal with such symptoms and suffer from emotional imbalance. Music therapy is a growing field that not only elicits emotional responses, but also improves mental balance, builds the immune system, and reduces stress. Varying the musical genre can affect the body as well, by regulating both heart rate and blood pressure. When utilizing music therapy in conditions such as T2DM, relaxation of blood vessels also occurs. Thus, we hypothesize that music therapy will reduce neuropathy in T2DM by improving skin conductivity and emotional frequency. To test our hypothesis, participants between the ages of 10 to 55, listened to four genres of music (gospel, rock, afro beats, neo soul), having one song per genre; as well as a control (no music) and their favorite song. The galvanic skin response (GSR) to each musical genre was measured for two minutes pre-, during, and post-music, using a Qubit Q-S222 GSR sensor. Each participant’s current emotion was obtained, at similar time points as the GSR measurements. The emotions were compared to an Emotional Vibrational Frequency Scale to determine emotional frequency. Additional information from each participant was surveyed including: i) age; ii) ethnicity; iii) gender. According to the preliminary data we collected from a control group, listening to music had little effect on the participant’s skin conductance, and a positive effect on their emotional frequency (on average); these data indicate that listening to music of any genre raises the listeners’ emotional frequency.
Effects of Nitric Oxide and Far-red Light on Thrombosis
Fernando Rigal, Wake Forest University
Nitrite, which was previously thought to be inert, acts as a storage pool for nitric oxide that is activated in the presence of deoxygenated red blood cells (RBCs) and may have potential for treating thrombosis. Fibrin fibers form the backbone of blood clots that are highly responsible for thrombotic conditions, such as Deep Vein Thrombosis. As shown by turbidity measurements, clots treated with nitrite and far-red light synergistically alters the kinetics of fibrin fiber formation as measured by optical turbidity to aid in thrombotic conditions 1,2. These studies were originally done with platelet-poor plasma so as to follow the standardized turbidity assay, however, so as to make it more biophysically relevant, it was extended to platelet-rich plasma. We hypothesize that far-red light (FR) potentiates the effects of nitrite on clot kinetics including clot lag time (CLT) and clot fibrinolysis time (CFT). Turbidity measurements of clot formation and clot lysis were performed on both platelet poor and platelet-rich plasma samples with or without nitrite (10 µM) as well as FR light exposure (660 nm) using a microplate reader spectrophotometer. It was found that clots treated with nitrite had a longer CLT prior to clotting (p = 0.098) as well as a considerably shorter CFT (P = 0.025). Furthermore, clots that were treated with nitrite and FR light had a significantly longer CLT than just the nitrite treatment itself (p < 0.05) while the dual treatment also elicited a shorter CFT (P = 0.035). These results further indicate that the NO donor, nitrite, in hypoxic conditions, contains potential value for treating thrombotic conditions that could be enhanced with FR light.
Fernando Rigal, Wake Forest University
Nitrite, which was previously thought to be inert, acts as a storage pool for nitric oxide that is activated in the presence of deoxygenated red blood cells (RBCs) and may have potential for treating thrombosis. Fibrin fibers form the backbone of blood clots that are highly responsible for thrombotic conditions, such as Deep Vein Thrombosis. As shown by turbidity measurements, clots treated with nitrite and far-red light synergistically alters the kinetics of fibrin fiber formation as measured by optical turbidity to aid in thrombotic conditions 1,2. These studies were originally done with platelet-poor plasma so as to follow the standardized turbidity assay, however, so as to make it more biophysically relevant, it was extended to platelet-rich plasma. We hypothesize that far-red light (FR) potentiates the effects of nitrite on clot kinetics including clot lag time (CLT) and clot fibrinolysis time (CFT). Turbidity measurements of clot formation and clot lysis were performed on both platelet poor and platelet-rich plasma samples with or without nitrite (10 µM) as well as FR light exposure (660 nm) using a microplate reader spectrophotometer. It was found that clots treated with nitrite had a longer CLT prior to clotting (p = 0.098) as well as a considerably shorter CFT (P = 0.025). Furthermore, clots that were treated with nitrite and FR light had a significantly longer CLT than just the nitrite treatment itself (p < 0.05) while the dual treatment also elicited a shorter CFT (P = 0.035). These results further indicate that the NO donor, nitrite, in hypoxic conditions, contains potential value for treating thrombotic conditions that could be enhanced with FR light.
Reaction-Diffusion Models of Biological and Chemical Systems
Grace Hofmann, Wake Forest University
Population dynamics described by the Lotka-Volterra systems and the fast-slow dynamics of two chemical processes, the Belousov-Zhabotinsky (BZ) reaction and Van der Pol (VDP) oscillator, are studied. The stability of competitive interactions that contain a coexistence steady state solution is analyzed, and a Turing bifurcation is shown to exist. As a proxy for the BZ reaction, the VDP oscillator with diffusion is studied. In this model, the existence of travelling wave solutions, which lead to spaciotemporal spiral waves, is shown. Numerical simulations which account for spatial and temporal evolution of the Lotka-Volterra-Guase system and BZ reaction are presented.
Grace Hofmann, Wake Forest University
Population dynamics described by the Lotka-Volterra systems and the fast-slow dynamics of two chemical processes, the Belousov-Zhabotinsky (BZ) reaction and Van der Pol (VDP) oscillator, are studied. The stability of competitive interactions that contain a coexistence steady state solution is analyzed, and a Turing bifurcation is shown to exist. As a proxy for the BZ reaction, the VDP oscillator with diffusion is studied. In this model, the existence of travelling wave solutions, which lead to spaciotemporal spiral waves, is shown. Numerical simulations which account for spatial and temporal evolution of the Lotka-Volterra-Guase system and BZ reaction are presented.
Poster Presentations
Investigation of Carbonic Acid Kinetics Under Physiological Conditions
Anna Sheinberg, Elon University
Carbonic acid is one of the primary buffer components in the human blood system and is integral in maintaining a proper pH throughout the bloodstream. However, aqueous carbonic acid is particularly unstable in solution due to a rapid bidirectional decomposition equilibrium. Given this, many of its chemical properties in aqueous solution are unknown. This study aims to describe the kinetic properties of the aqueous carbonic acid system, specifically determining the rate constant for the dissociation of carbonic acid into water and carbon dioxide under physiological conditions. Using high resolution Raman scattering spectroscopy, we have shown that it is possible to spectroscopically differentiate between bicarbonate, carbonic acid, and the buffer components in solution. Because carbonic acid is so short-lived in aqueous solution, this study utilizes a high-speed liquid mixing system wherein carbonic acid is generated in situ, allowing us to accurately measure the decomposition rate of carbonic acid into water and carbon dioxide. Future studies will focus on quantitatively determining the kinetic mechanism and associated rate constant of carbonic acid within a system that mimics the pH of the human bloodstream.
Anna Sheinberg, Elon University
Carbonic acid is one of the primary buffer components in the human blood system and is integral in maintaining a proper pH throughout the bloodstream. However, aqueous carbonic acid is particularly unstable in solution due to a rapid bidirectional decomposition equilibrium. Given this, many of its chemical properties in aqueous solution are unknown. This study aims to describe the kinetic properties of the aqueous carbonic acid system, specifically determining the rate constant for the dissociation of carbonic acid into water and carbon dioxide under physiological conditions. Using high resolution Raman scattering spectroscopy, we have shown that it is possible to spectroscopically differentiate between bicarbonate, carbonic acid, and the buffer components in solution. Because carbonic acid is so short-lived in aqueous solution, this study utilizes a high-speed liquid mixing system wherein carbonic acid is generated in situ, allowing us to accurately measure the decomposition rate of carbonic acid into water and carbon dioxide. Future studies will focus on quantitatively determining the kinetic mechanism and associated rate constant of carbonic acid within a system that mimics the pH of the human bloodstream.
Ex Vivo Bioreactor System Simulating Peripheral Arterial Motion
Will Chen, Wake Forest University
In the U.S. Peripheral Artery Disease (PAD) affects 3 million people a year. PAD is the narrowing and restriction of blood flow of the peripheral arteries, specifically in the legs. This is caused by the buildup of plaque in the arterial wall. The current surgical treatment is an angioplasty balloon that is inflated at the disease site. This compresses the plaque outwards and opens up the artery. A stent can then be placed there to hold the artery open, however stents have shown to be ineffective due to stent fracture due to vascular motion. Specifically, the twisting and shortening of the artery. Currently, biological testing of these devices is mostly limited to in-vivo animal models. While the pharmacokinetic data obtained from these procedures are effective, in-vivo animal testing is deficient in many areas. Surgical procedures are expensive, time consuming, and a large quantity of animals is needed to achieve statistically significant results. Ex vivo models provide an opportunity to replicate pre-clinical and clinical settings in a bench-top setting. Our goal is to design and build a peripheral-simulating machine that will model the twisting, bending and shortening movements to the artery while maintaining temperature and flow conditions as would be experienced in the body.
Will Chen, Wake Forest University
In the U.S. Peripheral Artery Disease (PAD) affects 3 million people a year. PAD is the narrowing and restriction of blood flow of the peripheral arteries, specifically in the legs. This is caused by the buildup of plaque in the arterial wall. The current surgical treatment is an angioplasty balloon that is inflated at the disease site. This compresses the plaque outwards and opens up the artery. A stent can then be placed there to hold the artery open, however stents have shown to be ineffective due to stent fracture due to vascular motion. Specifically, the twisting and shortening of the artery. Currently, biological testing of these devices is mostly limited to in-vivo animal models. While the pharmacokinetic data obtained from these procedures are effective, in-vivo animal testing is deficient in many areas. Surgical procedures are expensive, time consuming, and a large quantity of animals is needed to achieve statistically significant results. Ex vivo models provide an opportunity to replicate pre-clinical and clinical settings in a bench-top setting. Our goal is to design and build a peripheral-simulating machine that will model the twisting, bending and shortening movements to the artery while maintaining temperature and flow conditions as would be experienced in the body.
She’s Not My Boss Unless She’s a Mother: The Potential Benefits of Being Both Agentic and Communal in Roles Traditionally Held by Men
Caraline Malloy, University of North Carolina - Greensboro
In jobs traditionally held by men, hiring decisions largely depend on perceptions of competence, capability, and assertiveness. Such agentic traits are traditionally associated with masculinity. As a result, many women think that exhibiting more agentic traits makes them more hirable. However, this practice often leads to “backlash” against women because agentic women are perceived as lacking the more communal traits stereotypically expected of women. As highlighted in prior literature (Haines & Stroessner, 2019), I argue that women’s behavior in the workplace must convey both traditionally masculine and feminine traits to avoid negative evaluations and to garner success. Female leaders in positions traditionally held by men were interviewed about their experiences displaying agentic and communal traits in the workplace. Findings suggested that communality buffers against discrimination for women in positions traditionally held by men, meaning that both communal and agentic traits are needed for women to be effective in leadership positions. Ultimately, the current study provides recommendations for agentic women on how to avoid role-related discrimination in the workplace.
Caraline Malloy, University of North Carolina - Greensboro
In jobs traditionally held by men, hiring decisions largely depend on perceptions of competence, capability, and assertiveness. Such agentic traits are traditionally associated with masculinity. As a result, many women think that exhibiting more agentic traits makes them more hirable. However, this practice often leads to “backlash” against women because agentic women are perceived as lacking the more communal traits stereotypically expected of women. As highlighted in prior literature (Haines & Stroessner, 2019), I argue that women’s behavior in the workplace must convey both traditionally masculine and feminine traits to avoid negative evaluations and to garner success. Female leaders in positions traditionally held by men were interviewed about their experiences displaying agentic and communal traits in the workplace. Findings suggested that communality buffers against discrimination for women in positions traditionally held by men, meaning that both communal and agentic traits are needed for women to be effective in leadership positions. Ultimately, the current study provides recommendations for agentic women on how to avoid role-related discrimination in the workplace.
Overexpression of Arabidopsis thaliana PSY gene in cassava for enhanced carotenoid biosynthesis
Jade Lyons, University of North Carolina - Greensboro
Cassava is an important staple crop in tropical countries where it is mainly cultivated for its starchy tuberous roots. However, it is poor in vitamins, proteins, and minerals content. In this study we are proposing to improve the nutritional quality of cassava by increasing the β-carotene content through overexpression of Arabidopsis phytoene synthase (AtPSY) and ORANGE (AtOR) genes. PSY is an enzyme that catalyzes the first step in plant carotenoid biosynthesis, and its expression has been shown to be regulated by OR, a protein that enhances carotenoid biosynthesis. Expression cassettes of the genes were generated in modular vectors under the control of root-specific promoters. The cassettes were then assembled in binary vectors prior to transformation of cassava embryogenic calli via Agrobacterium-mediated transformation. Transgenic lines will be characterized using molecular and biochemical techniques. We expect to see an increase in carotenoid biosynthesis in transgenic tubers. Vitamin A enriched bioengineered cassava has great potential to address global issues related to malnutrition, health, and food security.
Jade Lyons, University of North Carolina - Greensboro
Cassava is an important staple crop in tropical countries where it is mainly cultivated for its starchy tuberous roots. However, it is poor in vitamins, proteins, and minerals content. In this study we are proposing to improve the nutritional quality of cassava by increasing the β-carotene content through overexpression of Arabidopsis phytoene synthase (AtPSY) and ORANGE (AtOR) genes. PSY is an enzyme that catalyzes the first step in plant carotenoid biosynthesis, and its expression has been shown to be regulated by OR, a protein that enhances carotenoid biosynthesis. Expression cassettes of the genes were generated in modular vectors under the control of root-specific promoters. The cassettes were then assembled in binary vectors prior to transformation of cassava embryogenic calli via Agrobacterium-mediated transformation. Transgenic lines will be characterized using molecular and biochemical techniques. We expect to see an increase in carotenoid biosynthesis in transgenic tubers. Vitamin A enriched bioengineered cassava has great potential to address global issues related to malnutrition, health, and food security.
Imagining Project Goals for a Project-Based Learning Experience in Elon University's Biomedical Engineering Curriculum
Emma Walker, Elon University
Current design projects in the Elon engineering curriculum are largely mechanically focused. With the development and evolution of functional devices from low-cost components, there is an opportunity to devise project-based learning experiences for students interested in biomedical engineering. We have partnered with Engineering World Health - a global non-profit organization that promotes biomedical engineering education - to expand the use of their heart rate monitor. This medical device will serve as the design project to create a project-based learning experience in Elon’s Engineering Design for Service course (EGR 221). When creating new learning experiences, it is important to ensure that the learning goals, activities, and assessments align. The goals-activities-products-assessments (GAPA) framework is one tool for achieving alignment in project-based learning. We will apply this framework as an analytical tool to understand the experiences of students enrolled in Engineering Design for Service. This also allows us to gain insight into how a specific project can contribute to student learning and to compare the same project across different engineering courses. This work aims to demonstrate the utility of a project goals framework in defining student-centered learning goals for a new learning experience.
Emma Walker, Elon University
Current design projects in the Elon engineering curriculum are largely mechanically focused. With the development and evolution of functional devices from low-cost components, there is an opportunity to devise project-based learning experiences for students interested in biomedical engineering. We have partnered with Engineering World Health - a global non-profit organization that promotes biomedical engineering education - to expand the use of their heart rate monitor. This medical device will serve as the design project to create a project-based learning experience in Elon’s Engineering Design for Service course (EGR 221). When creating new learning experiences, it is important to ensure that the learning goals, activities, and assessments align. The goals-activities-products-assessments (GAPA) framework is one tool for achieving alignment in project-based learning. We will apply this framework as an analytical tool to understand the experiences of students enrolled in Engineering Design for Service. This also allows us to gain insight into how a specific project can contribute to student learning and to compare the same project across different engineering courses. This work aims to demonstrate the utility of a project goals framework in defining student-centered learning goals for a new learning experience.
Myrica cerifera, a Medicinal Plant of the Lumbee Tribe, Has Antibacterial and Nematicidal Properties
Ashley Edwards, University of North Carolina - Pembroke
Currently threatening the world of medicine is a growing number of antibiotic resistant diseases. More specifically, bacteria and nematodes have gained resistance to many of the world’s leading antibiotics making infections more difficult to treat. Subsequently, these parasitic organisms are able to continue damaging crops and other living organisms like humans without strong interference. To help people and the environment, a new strain of antibiotics is vital. Previous research suggests phytochemicals are a potential solution that will help not only inhibit bacterial growth, but also reduce nematode survival. We hypothesized Myrica cerifera, a plant often used by the Lumbee tribe to treat illness, possesses antibacterial and nematicidal properties. The findings of this study show that this plant, more commonly referred to as wax myrtle, does significantly decrease the lifespan of C. elegans and the zone of inhibition for S. epidermidis and S. aureus. As such, chemical compounds in wax myrtle could potentially be used to treat bacterial and nematode infections.
Ashley Edwards, University of North Carolina - Pembroke
Currently threatening the world of medicine is a growing number of antibiotic resistant diseases. More specifically, bacteria and nematodes have gained resistance to many of the world’s leading antibiotics making infections more difficult to treat. Subsequently, these parasitic organisms are able to continue damaging crops and other living organisms like humans without strong interference. To help people and the environment, a new strain of antibiotics is vital. Previous research suggests phytochemicals are a potential solution that will help not only inhibit bacterial growth, but also reduce nematode survival. We hypothesized Myrica cerifera, a plant often used by the Lumbee tribe to treat illness, possesses antibacterial and nematicidal properties. The findings of this study show that this plant, more commonly referred to as wax myrtle, does significantly decrease the lifespan of C. elegans and the zone of inhibition for S. epidermidis and S. aureus. As such, chemical compounds in wax myrtle could potentially be used to treat bacterial and nematode infections.
Improved anti-Tumor Activity of the Fluoropyrimidine Polymer CF10 in pre-Clinical Colorectal Cancer Models thru Distinct Mechanistic and Pharmacological Properties
Will Snider and Kara Walser, Wake Forest University
Chemotherapy regimens that include 5-fluorouracil (5-FU) are central to colorectal cancer (CRC) treatment, however risk/benefit concerns limit 5-FU’s use, necessitating development of improved fluoropyrimidine (FP) drugs. In our study, we evaluated a 2nd generation nanoscale FP polymer, CF10, for improved anti-tumor activity. CF10 was more potent than the prototype FP polymer F10 and much more potent than 5-FU in multiple CRC cell lines including HCT-116, LS174T, SW480 and T84D. CF10 displayed improved stability to exonuclease degradation relative to F10 and reduced susceptibility to thymidine antagonism due to extension of the polymer with AraC. In CRC cells, CF10 strongly inhibited thymidylate synthase (TS), induced Top1 cleavage complex (Top1cc) formation and caused replication stress, while similar concentrations of 5-FU were ineffective. CF10 was well tolerated in vivo and invoked a reduced inflammatory response relative to 5-FU. Blood chemistry parameters in CF10 treated mice were within normal limits. In vivo, CF10 displayed anti-tumor activity in several CRC flank tumor models including HCT-116, HT-29, and CT-26. CF10’s anti-tumor activity was associated with increased plasma levels of FP deoxynucleotide metabolites relative to 5-FU. CF10 significantly reduced tumor growth and improved survival (84.5 days vs 32 days; p<0.0001) relative to 5-FU in an orthotopic HCT-116-luc CRC model that spontaneously metastasized to liver. Improved survival in the orthotopic model correlated with localization of a fluorescent CF10 conjugate to tumor. Together, our pre-clinical data support an early phase clinical trial of CF10 for treatment of CRC.
Will Snider and Kara Walser, Wake Forest University
Chemotherapy regimens that include 5-fluorouracil (5-FU) are central to colorectal cancer (CRC) treatment, however risk/benefit concerns limit 5-FU’s use, necessitating development of improved fluoropyrimidine (FP) drugs. In our study, we evaluated a 2nd generation nanoscale FP polymer, CF10, for improved anti-tumor activity. CF10 was more potent than the prototype FP polymer F10 and much more potent than 5-FU in multiple CRC cell lines including HCT-116, LS174T, SW480 and T84D. CF10 displayed improved stability to exonuclease degradation relative to F10 and reduced susceptibility to thymidine antagonism due to extension of the polymer with AraC. In CRC cells, CF10 strongly inhibited thymidylate synthase (TS), induced Top1 cleavage complex (Top1cc) formation and caused replication stress, while similar concentrations of 5-FU were ineffective. CF10 was well tolerated in vivo and invoked a reduced inflammatory response relative to 5-FU. Blood chemistry parameters in CF10 treated mice were within normal limits. In vivo, CF10 displayed anti-tumor activity in several CRC flank tumor models including HCT-116, HT-29, and CT-26. CF10’s anti-tumor activity was associated with increased plasma levels of FP deoxynucleotide metabolites relative to 5-FU. CF10 significantly reduced tumor growth and improved survival (84.5 days vs 32 days; p<0.0001) relative to 5-FU in an orthotopic HCT-116-luc CRC model that spontaneously metastasized to liver. Improved survival in the orthotopic model correlated with localization of a fluorescent CF10 conjugate to tumor. Together, our pre-clinical data support an early phase clinical trial of CF10 for treatment of CRC.
Viral impacts on marine cyanobacterium Synechococcus light harvesting complexes
Garrett Turner, Wake Forest University
Marine cyanobacteria of the genus Synechococcus account for roughly 17% of global oceanic net primary production and play an instrumental role in the global carbon cycle. In photosynthesis, Synechococcus utilize phycobilisome structures to bind different chromophores and consequently absorb light energy across the wavelength spectrum. Marine bacteriophages are known to alter this process via encoding auxiliary metabolic genes that manipulate Synechococcus photosynthesis pathways, presumably to enhance viral replication. However, the exact photophysiological impact of phage infection has yet to be determined. Here, we present data from four Synechococcus host-phage pairs collected by teams of students in a course-based undergraduate research experience. Using absorbance data from the different Synechococcus host-phage infection assays as a proxy for pigment composition, this project seeks to determine whether viral infection of Synechococcus affects pigment composition and if so, to characterize the phage impact on pigments over an infection time course.
Garrett Turner, Wake Forest University
Marine cyanobacteria of the genus Synechococcus account for roughly 17% of global oceanic net primary production and play an instrumental role in the global carbon cycle. In photosynthesis, Synechococcus utilize phycobilisome structures to bind different chromophores and consequently absorb light energy across the wavelength spectrum. Marine bacteriophages are known to alter this process via encoding auxiliary metabolic genes that manipulate Synechococcus photosynthesis pathways, presumably to enhance viral replication. However, the exact photophysiological impact of phage infection has yet to be determined. Here, we present data from four Synechococcus host-phage pairs collected by teams of students in a course-based undergraduate research experience. Using absorbance data from the different Synechococcus host-phage infection assays as a proxy for pigment composition, this project seeks to determine whether viral infection of Synechococcus affects pigment composition and if so, to characterize the phage impact on pigments over an infection time course.
Understanding viral impacts on non-host organisms in marine microbial food webs
Audrey Chrisman, Wake Forest University
Marine microbial communities reduce global warming by converting atmospheric carbon dioxide into particulate organic carbon that sinks to the deep sea in a process known as the biological carbon pump. The interactions among diverse marine microbes control carbon flux, but much remains unknown about these interactions. This study sought to quantify mixotroph responses within a simplified planktonic food web that included picophytoplankton, nanophytoplankton, mixotrophs, microzooplankton, macrozooplankton, heterotrophic bacteria, and viruses. Mixotrophic protists, those that acquire nutrients by both phototrophy and phagotrophy, are predicted to play key roles in transferring carbon and nutrients in the marine food webs because they form a critical link between phototrophs and larger heterotrophs, but little is known about their behavior. Marine viruses, estimated to have a concentration of 10^9 per milliliter of seawater, affect the biological carbon pump by diverting the flow of carbon and nutrients from the host organism into the dissolved phase. The release of dissolved organic compounds as a result of viral infection has been shown to increase feeding behaviors of larger predators such as the heterotrophic protist Oxyrrhis marina. The virus OtV5 infects and lyses the picoautotroph Ostreococcus tauri, increasing local dissolved organic carbon (DOC) concentrations. Enhancing Oxyrrhis marina predatory activity by the introduction of OtV5 can therefore reveal antipredatory measures of the mixotroph Ochromonas sp. One antipredation strategy is for single-celled organisms to form colonies and therefore become larger than the predator. We used fluorescence microscopy to quantify mixotroph Ochromonas sp. colony formation in virus-enriched and unenriched treatments. Studying microbial predator-prey interactions such as this can provide insight into the process of nutrient transfer through trophic levels.
Audrey Chrisman, Wake Forest University
Marine microbial communities reduce global warming by converting atmospheric carbon dioxide into particulate organic carbon that sinks to the deep sea in a process known as the biological carbon pump. The interactions among diverse marine microbes control carbon flux, but much remains unknown about these interactions. This study sought to quantify mixotroph responses within a simplified planktonic food web that included picophytoplankton, nanophytoplankton, mixotrophs, microzooplankton, macrozooplankton, heterotrophic bacteria, and viruses. Mixotrophic protists, those that acquire nutrients by both phototrophy and phagotrophy, are predicted to play key roles in transferring carbon and nutrients in the marine food webs because they form a critical link between phototrophs and larger heterotrophs, but little is known about their behavior. Marine viruses, estimated to have a concentration of 10^9 per milliliter of seawater, affect the biological carbon pump by diverting the flow of carbon and nutrients from the host organism into the dissolved phase. The release of dissolved organic compounds as a result of viral infection has been shown to increase feeding behaviors of larger predators such as the heterotrophic protist Oxyrrhis marina. The virus OtV5 infects and lyses the picoautotroph Ostreococcus tauri, increasing local dissolved organic carbon (DOC) concentrations. Enhancing Oxyrrhis marina predatory activity by the introduction of OtV5 can therefore reveal antipredatory measures of the mixotroph Ochromonas sp. One antipredation strategy is for single-celled organisms to form colonies and therefore become larger than the predator. We used fluorescence microscopy to quantify mixotroph Ochromonas sp. colony formation in virus-enriched and unenriched treatments. Studying microbial predator-prey interactions such as this can provide insight into the process of nutrient transfer through trophic levels.
Testing to Determine the Effects of Biochar on the Survival of Beneficial Nematodes (Steirmena carpocapse)
Samantha Cranford, University of North Carolina at Pembroke
Beneficial nematodes, though most invisible to the naked eye, can significantly aid plant growth by killing destructive grubs that attempt to feed on the root systems of plants. Biochar, a porous and carbon-rich material, is being increasingly used as a soil amendment for crop production. Previous research has focused on biochar's ability to kill/repel harmful nematodes due to their crop yield impact. However, the effect that biochar may have on beneficial nematode populations in the world is unknown. A 4-week lab study was conducted to determine the survivability that S. carpocapse has when incubated with approximately 10 g of pure wood-derived biochar, biochar + field soil, biochar + mushroom compost, and field soil. Each incubation had low moisture (5 mL), high moisture (10 mL) treatment, and repeated measures of mortality rates were taken every two days across the 4-week experiment. The procedure for checking mortality was: 0.2 g was taken from the incubation contents of the Petri dishes, 2 mL of water was added, shaken, and then a few diluted drops were viewed under a microscope. At the end of the 4 weeks experiment, it was determined from the data that the field soil-only combination had the lowest mortality counts. Overall, nematodes tended to have low mortality in low moisture conditions. The biochar-only combination had adverse effects on the survival of nematodes. These effects appeared to be subsided in Petri dishes that had field soil or compost added to them. Further research should be conducted to determine the impact beneficial nematodes have on soil pests in biochar-mended soil. To further expand upon this research, studies can be upscaled into a greenhouse and added to a horticulture system. The plants' health can be monitored alongside the nematode count to see the effects of biochar on a farm environment.
Samantha Cranford, University of North Carolina at Pembroke
Beneficial nematodes, though most invisible to the naked eye, can significantly aid plant growth by killing destructive grubs that attempt to feed on the root systems of plants. Biochar, a porous and carbon-rich material, is being increasingly used as a soil amendment for crop production. Previous research has focused on biochar's ability to kill/repel harmful nematodes due to their crop yield impact. However, the effect that biochar may have on beneficial nematode populations in the world is unknown. A 4-week lab study was conducted to determine the survivability that S. carpocapse has when incubated with approximately 10 g of pure wood-derived biochar, biochar + field soil, biochar + mushroom compost, and field soil. Each incubation had low moisture (5 mL), high moisture (10 mL) treatment, and repeated measures of mortality rates were taken every two days across the 4-week experiment. The procedure for checking mortality was: 0.2 g was taken from the incubation contents of the Petri dishes, 2 mL of water was added, shaken, and then a few diluted drops were viewed under a microscope. At the end of the 4 weeks experiment, it was determined from the data that the field soil-only combination had the lowest mortality counts. Overall, nematodes tended to have low mortality in low moisture conditions. The biochar-only combination had adverse effects on the survival of nematodes. These effects appeared to be subsided in Petri dishes that had field soil or compost added to them. Further research should be conducted to determine the impact beneficial nematodes have on soil pests in biochar-mended soil. To further expand upon this research, studies can be upscaled into a greenhouse and added to a horticulture system. The plants' health can be monitored alongside the nematode count to see the effects of biochar on a farm environment.
Deep Reinforcement Learning for Adaptive Exploration of Unknown Environments
Ashley Peake, Wake Forest University
Exploration of an unknown environment is an important task in many applications of mobile robotics. In large, outdoor environments, Unmanned Aerial Vehicles (UAVs) are regularly employed for exploration due to their ease of use and maneuverability. Often, UAVs on these missions must first build a map of the environment via pure exploration and then subsequently use or exploit it for downstream navigation tasks. Accomplishing these exploration and exploitation tasks in two separate steps is not always feasible for UAVs deployed in dynamically changing environments. In this project, we develop an adaptive exploration approach for simultaneous exploration and exploitation. The goal of this model is, given no prior knowledge about a particular region, to allow a UAV to efficiently explore a large, outdoor environment to collect data from as many areas of interest as quickly as possible. The proposed approach first employs a map segmentation technique to decompose the environment into smaller, tractable maps. We then train a Deep Reinforcement Learning model to direct UAV flight to optimize efficient information gain. We incorporate two neural networks, each selecting an action according to either the exploration or exploitation task, respectively. We control the trade-off between these tasks with an efficient information gain function that utilizes current knowledge that the UAV has collected throughout the mission. We test our approach in 3 different tasks against 4 baselines. The results demonstrate that the proposed approach is capable of navigating through randomly generated environments and covering more areas of interest in less time compared to the baselines.
Ashley Peake, Wake Forest University
Exploration of an unknown environment is an important task in many applications of mobile robotics. In large, outdoor environments, Unmanned Aerial Vehicles (UAVs) are regularly employed for exploration due to their ease of use and maneuverability. Often, UAVs on these missions must first build a map of the environment via pure exploration and then subsequently use or exploit it for downstream navigation tasks. Accomplishing these exploration and exploitation tasks in two separate steps is not always feasible for UAVs deployed in dynamically changing environments. In this project, we develop an adaptive exploration approach for simultaneous exploration and exploitation. The goal of this model is, given no prior knowledge about a particular region, to allow a UAV to efficiently explore a large, outdoor environment to collect data from as many areas of interest as quickly as possible. The proposed approach first employs a map segmentation technique to decompose the environment into smaller, tractable maps. We then train a Deep Reinforcement Learning model to direct UAV flight to optimize efficient information gain. We incorporate two neural networks, each selecting an action according to either the exploration or exploitation task, respectively. We control the trade-off between these tasks with an efficient information gain function that utilizes current knowledge that the UAV has collected throughout the mission. We test our approach in 3 different tasks against 4 baselines. The results demonstrate that the proposed approach is capable of navigating through randomly generated environments and covering more areas of interest in less time compared to the baselines.
Exploring the Hemodynamics of Novel, Non-FDA Approved ePTFE Pediatric Heart Valves
April Espinoza & Santi Leon Villegas, Wake Forest University
Every 36 seconds an individual dies from a cardiovascular disease in the United States, making cardiovascular diseases the leading cause of death in the US and worldwide. One category of cardiovascular diseases is congenital heart defects which includes valvular malfunctions, affecting approximately 40,000 children worldwide annually. When valvular dysfunction arises as the primary cause of cardiac disease in pediatric patients, surgery is often needed. Commercially available prosthetic heart valves such as the SAPIEN 3 or the Melody valve exist to treat such dysfunctions for adults and certain qualified pediatric patients. However, there is a narrow availability of tested prosthetic valves for children. In this study, the fluid mechanics of a non-FDA approved an expanded polytetrafluoroethylene (ePTFE) pediatric heart valve, designed by Dr. Yoshio Otaki who is a Pediatric Cardiac Surgeon collaborator at Wake Forest Baptist Health. Dr. Otaki’s ePTFE valve is a trileaflet valve designed for aortic valve replacement. This bioprosthetic valve will be numerically and experimentally analyzed to better inform valve selection for pediatric surgical procedures. Specifically, engineering qualifications such as Reynolds number will be calculated in comparison to clinical measurements of transvalvular pressures in order to assess valve performance.
April Espinoza & Santi Leon Villegas, Wake Forest University
Every 36 seconds an individual dies from a cardiovascular disease in the United States, making cardiovascular diseases the leading cause of death in the US and worldwide. One category of cardiovascular diseases is congenital heart defects which includes valvular malfunctions, affecting approximately 40,000 children worldwide annually. When valvular dysfunction arises as the primary cause of cardiac disease in pediatric patients, surgery is often needed. Commercially available prosthetic heart valves such as the SAPIEN 3 or the Melody valve exist to treat such dysfunctions for adults and certain qualified pediatric patients. However, there is a narrow availability of tested prosthetic valves for children. In this study, the fluid mechanics of a non-FDA approved an expanded polytetrafluoroethylene (ePTFE) pediatric heart valve, designed by Dr. Yoshio Otaki who is a Pediatric Cardiac Surgeon collaborator at Wake Forest Baptist Health. Dr. Otaki’s ePTFE valve is a trileaflet valve designed for aortic valve replacement. This bioprosthetic valve will be numerically and experimentally analyzed to better inform valve selection for pediatric surgical procedures. Specifically, engineering qualifications such as Reynolds number will be calculated in comparison to clinical measurements of transvalvular pressures in order to assess valve performance.
Constructing a Gene Model on the contig50 Project from the D. bipectinata Muller F element
Ashton Tillett, University of North Carolina at Pembroke
The last twenty years have allowed for a massive increase in the number of computationally derived genome assemblies for a variety of organisms. The Genome Education Partnership (GEP) has developed software capable of annotating genes in those already sequenced genomes. The fourth and smallest chromosome of D. melanogaster known as the Muller F element is packaged as heterochromatin, thus theoretically indicating that it should not be capable of transcription and translation. However, there are approximately 80 genes that code for specific proteins in this chromosome. Surprisingly, these F element genes exhibit expression levels like those of euchromatic genes. This suggests they have amassed exclusive features that bolster their functionality independent of their heterochromatic nature. In addition, the F element, despite being similarly sized in many Drosophila species is shockingly larger in more than four species. This project examined, through the annotation of the coding regions, the evolutionary significance of variation in chromosome size and the identification of components that facilitate the functionality of heterochromatic genes in D. bipectinata contig50 relative to D. melanogaster genes. The GEP UCSC Genome Browser ‘BLASTX Alignment to D. Melanogaster Proteins’ feature indicated that there are several proteins in D. melanogaster that have sequence similarity to contig50 of D. bipectinata. By utilizing other features such as BLASTP, the predicted protein sequences in D. bipectinata were compared to those of D. melanogaster to determine the putative orthologs in those genes. Investigation of the contig50 project illustrated that there is at least one putative ortholog in D. melanogaster. This ortholog is denoted as dpr7-RG. It is by examining the amino acids in each frame of the contig50 sequence and other indicative features such as the phases, exon-intron boundaries, RNA-Seq data, etc., that the definite coordinates for each CDS of dpr7-RG and other orthologs were determined.
Ashton Tillett, University of North Carolina at Pembroke
The last twenty years have allowed for a massive increase in the number of computationally derived genome assemblies for a variety of organisms. The Genome Education Partnership (GEP) has developed software capable of annotating genes in those already sequenced genomes. The fourth and smallest chromosome of D. melanogaster known as the Muller F element is packaged as heterochromatin, thus theoretically indicating that it should not be capable of transcription and translation. However, there are approximately 80 genes that code for specific proteins in this chromosome. Surprisingly, these F element genes exhibit expression levels like those of euchromatic genes. This suggests they have amassed exclusive features that bolster their functionality independent of their heterochromatic nature. In addition, the F element, despite being similarly sized in many Drosophila species is shockingly larger in more than four species. This project examined, through the annotation of the coding regions, the evolutionary significance of variation in chromosome size and the identification of components that facilitate the functionality of heterochromatic genes in D. bipectinata contig50 relative to D. melanogaster genes. The GEP UCSC Genome Browser ‘BLASTX Alignment to D. Melanogaster Proteins’ feature indicated that there are several proteins in D. melanogaster that have sequence similarity to contig50 of D. bipectinata. By utilizing other features such as BLASTP, the predicted protein sequences in D. bipectinata were compared to those of D. melanogaster to determine the putative orthologs in those genes. Investigation of the contig50 project illustrated that there is at least one putative ortholog in D. melanogaster. This ortholog is denoted as dpr7-RG. It is by examining the amino acids in each frame of the contig50 sequence and other indicative features such as the phases, exon-intron boundaries, RNA-Seq data, etc., that the definite coordinates for each CDS of dpr7-RG and other orthologs were determined.
Influence of Restricted Oxygen and Increased Glucose on Growth of Escherichia coli (E. coli)
Allison Delgado, Forsyth Technical Community College
The influence of increasing the concentration of glucose and restricting the concentration of oxygen in different combinations on the growth of the bacteria Escherichia coli, commonly known as E. coli, was observed in this experiment. What we hoped to accomplish was to determine which combination would result in the largest zone of inhibition. For this to be found, three different agars—one plain, one nutritional, and one nutritional with glucose added—were poured into Petri dishes, and then each Petri dish was divided into four quadrants with either a disk of sanitizer, erythromycin, or penicillin placed in their middles with the fourth quadrant being empty as a control. Parafilm was used to seal half of the total Petri dishes to restrict the bacteria’s exposure to oxygen. After growing for a day, their areas of inhibition were measured. The findings showed that with erythromycin, the higher the concentration of glucose, the smaller the area of inhibition; with penicillin, the area of inhibition was mostly the same when comparing the Petri dishes with nutritional agar to the dishes with nutritional agar plus added glucose; with the sanitizer, regardless of the controlled conditions, there was no zone of inhibition around the disks; and, besides there being more bacterial growth in general, the results for the control were the same as the sanitizer. The Petri dishes covered with parafilm—and thereby whose access to oxygen was restricted—had smaller areas of inhibition compared to the Petri dishes that were not covered with parafilm. Perhaps, in the future, repeated experiments could use more Petri dishes to solidify that the results were accurate, or another form of oxygen restriction, other than the use of parafilm, could be used. Hypothesis: Petri dishes with an increased concentration of glucose will have more bacterial growth than Petri dishes with lower concentrations of glucose, and Petri dishes with restricted oxygen will exhibit less bacterial growth than those with lower concentrations of glucose.
Allison Delgado, Forsyth Technical Community College
The influence of increasing the concentration of glucose and restricting the concentration of oxygen in different combinations on the growth of the bacteria Escherichia coli, commonly known as E. coli, was observed in this experiment. What we hoped to accomplish was to determine which combination would result in the largest zone of inhibition. For this to be found, three different agars—one plain, one nutritional, and one nutritional with glucose added—were poured into Petri dishes, and then each Petri dish was divided into four quadrants with either a disk of sanitizer, erythromycin, or penicillin placed in their middles with the fourth quadrant being empty as a control. Parafilm was used to seal half of the total Petri dishes to restrict the bacteria’s exposure to oxygen. After growing for a day, their areas of inhibition were measured. The findings showed that with erythromycin, the higher the concentration of glucose, the smaller the area of inhibition; with penicillin, the area of inhibition was mostly the same when comparing the Petri dishes with nutritional agar to the dishes with nutritional agar plus added glucose; with the sanitizer, regardless of the controlled conditions, there was no zone of inhibition around the disks; and, besides there being more bacterial growth in general, the results for the control were the same as the sanitizer. The Petri dishes covered with parafilm—and thereby whose access to oxygen was restricted—had smaller areas of inhibition compared to the Petri dishes that were not covered with parafilm. Perhaps, in the future, repeated experiments could use more Petri dishes to solidify that the results were accurate, or another form of oxygen restriction, other than the use of parafilm, could be used. Hypothesis: Petri dishes with an increased concentration of glucose will have more bacterial growth than Petri dishes with lower concentrations of glucose, and Petri dishes with restricted oxygen will exhibit less bacterial growth than those with lower concentrations of glucose.
Oral Presentations
Room 1
10:05 - 10:20: Using Surfactants to Solubilize Luminescors to Aid in the Detection of Explosives Through Fluorescence Quenching
Tristan Torres, Elon University
Tristan Torres, Elon University
10:20 - 10:35: Slot-die Coater and Organic Field-effect Transistors
Arina Yu, Wake Forest University
Arina Yu, Wake Forest University
Effects of Nitric Oxide and Far-red Light on Thrombosis
Fernando Rigal, Wake Forest University
Fernando Rigal, Wake Forest University
Room 2
10:05 - 10:20: Parking Traffic Analysis Using Machine Learning
Jake Haines, University of North Carolina - Asheville
Jake Haines, University of North Carolina - Asheville
10:20 - 10:35: Force Plate Data Machine Learning Analysis
Morgan A Glisson and Blythe Layne, University of North Carolina - Wilmington
Morgan A Glisson and Blythe Layne, University of North Carolina - Wilmington
Computing the Value of Data in Machine Learning Applications
Jasmine Xu, Wake Forest University
Jasmine Xu, Wake Forest University
Room 3
10:05 - 10:20: A Statistical Analysis of COVID-19 Mental Health Data
Lucas Hansen, Wake Forest University
Lucas Hansen, Wake Forest University
10:20 - 10:35: Numerical Approach to Pricing Exotic Options
Scott Crowley, Wake Forest University
Scott Crowley, Wake Forest University
10:35 - 10:50: Reaction-Diffusion Models of Biological and Chemical Systems
Grace Hofmann, Wake Forest University
Grace Hofmann, Wake Forest University
Room 4
10:05 - 10:20: Cell-type Identification using Supervised and Unsupervised Machine Learning
Nathan Whitener, Wake Forest University
Nathan Whitener, Wake Forest University
10:20 - 10:35: Musical Influence on Skin Conductivity & Emotional Frequency in Type II Diabetes
Adunoluwa Akinola, Forsyth Technical Community College
Adunoluwa Akinola, Forsyth Technical Community College
Poster Presentations
Room 1
She’s Not My Boss Unless She’s a Mother: The Potential Benefits of Being Both Agentic and Communal in Roles Traditionally Held by Men
Caraline Malloy, University of North Carolina - Greensboro
Caraline Malloy, University of North Carolina - Greensboro
Imagining Project Goals for a Project-Based Learning Experience in Elon University's Biomedical Engineering Curriculum
Emma Walker, Elon University
Emma Walker, Elon University
Deep Reinforcement Learning for Adaptive Exploration of Unknown Environments
Ashley Peake, Wake Forest University
Ashley Peake, Wake Forest University
Room 2
Ex Vivo Bioreactor System Simulating Peripheral Arterial Motion
Will Chen, Wake Forest University
Will Chen, Wake Forest University
Understanding viral impacts on non-host organisms in marine microbial food webs
Audrey Chrisman, Wake Forest University
Audrey Chrisman, Wake Forest University
Myrica cerifera, a Medicinal Plant of the Lumbee Tribe, Has Antibacterial and Nematicidal Properties
Ashley Edwards, University of North Carolina - Pembroke
Ashley Edwards, University of North Carolina - Pembroke
Constructing a Gene Model on the contig50 Project from the D. bipectinata Muller F element
Ashton Tillett, University of North Carolina at Pembroke
Ashton Tillett, University of North Carolina at Pembroke
Room 3
Improved anti-Tumor Activity of the Fluoropyrimidine Polymer CF10 in pre-Clinical Colorectal Cancer Models thru Distinct Mechanistic and Pharmacological Properties
Will Snider and Kara Walser, Wake Forest University
Will Snider and Kara Walser, Wake Forest University
Exploring the Hemodynamics of Novel, Non-FDA Approved ePTFE Pediatric Heart Valves
April Espinoza & Santi Leon Villegas, Wake Forest University
April Espinoza & Santi Leon Villegas, Wake Forest University
Testing to Determine the Effects of Biochar on the Survival of Beneficial Nematodes (Steirmena carpocapse)
Samantha Cranford, University of North Carolina at Pembroke
Samantha Cranford, University of North Carolina at Pembroke
Room 4
Overexpression of Arabidopsis thaliana PSY gene in cassava for enhanced carotenoid biosynthesis
Jade Lyons, University of North Carolina - Greensboro
Jade Lyons, University of North Carolina - Greensboro
Viral impacts on marine cyanobacterium Synechococcus light harvesting complexes
Garrett Turner, Wake Forest University
Garrett Turner, Wake Forest University
Influence of Restricted Oxygen and Increased Glucose on Growth of Escherichia coli (E. coli)
Allison Delgado, Forsyth Technical Community College
Allison Delgado, Forsyth Technical Community College
IRIS 2021 will be a fully virtual conference in the Spring of 2021. Sign up to attend below!
If you registered but lost or never received the Zoom link, send an email to [email protected] right away.
Schedule:
8:30am: Zoom room open
9-10am: Keynote Speaker, Dr. Rebecca Alexander
10:05-10:50: Oral Presentations
11:00-11:45: Poster Presentations
12-12:45: Careers in Academia Panel
1-1:45: Careers in Industry Panel
1:45-2: Closing and Feedback
8:30am: Zoom room open
9-10am: Keynote Speaker, Dr. Rebecca Alexander
10:05-10:50: Oral Presentations
11:00-11:45: Poster Presentations
12-12:45: Careers in Academia Panel
1-1:45: Careers in Industry Panel
1:45-2: Closing and Feedback
Oral Presentation Schedule
10:05 - 10:20 |
10:20 - 10:35 |
10:35-10:50 |
|
Room 1 |
Tristan Torres |
Arina Yu |
Fernando Rigal |
Room 2 |
Jake Haines |
Morgan A Glisson & Blythe Layne |
Jasmine Xu |
Room 3 |
Lucas Hansen |
Scott Crowley |
Grace Hofmann |
Room 4 |
Adunoluwa Akinola |
Nathan Whitener |
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Poster Presentation Rooms
Room 1 |
Caraline Malloy |
Emma Walker |
Ashley Peake |
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Room 2 |
Will Chen |
Audrey Chrisman |
Ashley Edwards |
Ashton Tillett |
Room 3 |
Will Snider & Kara Walser |
April Espinoza |
Samantha Cranford |
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Room 4 |
Jade Lyons |
Allison Delgado |
Garrett Turner |
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