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Summer Undergraduate Research

2018 Projects

Predictive Modeling and Analysis of Golf Using the Massey Method

Kevin Gannon & Dr. Amanda Harsy

The use of predictive modeling in the analysis of sports data is an exciting, but challenging task. Golf is particularly difficult to predict because it incorporates individual scores into a total team score. There are many mathematically inspired sports ranking systems, but the Massey Method is among the most elegant and simple. This method involves setting up and solving a system of equations using least squares. We can possibly improve this method by incorporating weights into the system. This project presents the results of a summer undergraduate research project which tested the predictive power of using a weighted Massey Method to predict golf results from the NCAA Division II Great Lakes Valley Conference (GLVC).

Investigating Amyloid Beta Peptide Aggregation in the Presence of Copper and Zinc

Rachel Lullo & Dr. Daniel Kissel

Alzheimer’s Disease (AD) is an irreversible neurodegenerative disease that leads to the loss of memory, thinking abilities, and simple tasks. The protein β-amyloid (Aβ) aggregates and contributes to the neurodegeneration of AD. Metals, such as zinc and copper, have also been shown to aggregate in patients with AD. The Aβ peptide has binding sites with Cu2+ and Zn2+, creating plaques. However, amino acids, such as Beta-alanine, have been shown to fight peptide aggregation. In this experiment, different concentrations of zinc, copper, and β-alanine were placed in different 100 μM Aβ peptides. The peptides were incubated at 37 ℃ and SDS-PAGE was performed over 72 hours. A Coomassie blue fixative stain was used. Using Odyssey Fc, the different bands from the peptides were analyzed by measuring the absorbance to show band density. The band density and molecular weight marker was then used to calculate kDa values and compare the concentrations of monomer, trimer, tetramer, and oligomers with the concentrations of metals and amino acids in that peptide. The data showed that copper produced more monomers than zinc, and zinc produced more oligomers than copper. Beta alanine showed high concentrations of both oligomers and monomers, but no trimers or tetramers. Over 72 hours, the amounts of monomer, trimer, tetramer, and oligomer either increased or decreased depending on the concentration of Cu2+, Zn2+, and β-alanine.

This project was supported by Dr. James Girard.

Supervised Machine Learning Based on Optimal Traffic Flows

Keller Dellinger & Dr. Piotr Szczurek

In this project, we developed a novel machine learning method based on the methods used in transportation forecasting. In general, machine learning is used for a broad variety of applications, including fraud detection, face recognition, and intrusion detection in cybersecurity. In this project, the idea is to generate a distributed representation of data, on which learning may be easier. It can be seen as an alternative method to the sparse coding process, which is thought to be how the human brain distributes information. Using the data, a network is formed, similarly to how it is done with artificial neural networks. However, this network is viewed in a transportation context with the goal of generating signal flows that would represent the data in a distributed fashion. This is done by using the Frank-Wolfe algorithm for generating optimal flows, just like it is done when attempting to forecast traffic in transportation networks. During the project, we implemented the proposed method using the Python programming language, based on an existing Franke-Wolfe algorithm implementation in MATLAB.

The Role of RNA Binding Protein, Drosha, in Disease Associated pre-mRNA Alternative Splicing and Cancer

Matthew Grimm, Danica Ujano, Alaa Ahmad & Dr. Mallory Havens

Cancer is a diverse disease for which new treatments are required. One of the most important factors in decreasing mortality would be to reduce metastasis, or the spread of cancer cells in the body. One protein that has dysregulated in cancer is Drosha, which has been shown to have increased expression in some cancers, and a decreased expression in others. Drosha cleaves precursors to form micro-RNAs, which are involved in alteration of gene expression. However, Drosha may have another role in regulating alternative splicing apart from the generation of microRNAs. It is unknown if this alternative function is cleavage dependent, or if binding is sufficient to cause the change in gene expression and mRNA splicing. In addition, it is not known if changes in Drosha expression and binding or cleavage ability alter metastatic properties of cancer cells. In order to change the levels of Drosha inside the cell, plasmids were transfected that held different forms of the protein, a wild-type version (Drosha) and a binding competent, cleavage incompetent form (TN Drosha). After transfection, cell growth rates and migration rates were taken as a measure of metastatic properties. RNA was extracted from the cells, and changes in RNA processing patterns and the total abundance, or gene expression, were then compared across several genes in order to determine if there was a difference between treatments.

This project was supported by the Doherty Center for Aviation and Health Research.

Generalized Bol-Moufang Groupoids

Jonathan Nelson & Dr. David Failing

Abstract Algebra is the study of axiomatically defined structures arising from concrete objects (such as the symmetries of a regular polygon), with the aim of establishing properties of those objects. Universal
Algebra, loosely construed, is the study of axiom systems for their own sake. With the help of the automated reasoning tool Prover9 (and some Python code) we generated sets of identities of the same general type, broke those identities into equivalence classes. The project examined the Generalized Bol– Moufang identities in the context of commutative, idempotent groupoids. The utilization of programs such as Prover9 and Python were discussed, as well as strengths and weaknesses of computer –assisted proof. Interfacing with Prover9 through Python and the necessity of doing so as well as the difficulty involved were presented.

Amino Acid Crosslink Biopolymeric Network for Wound Management Applications

Sarah Bettag, Carolyn Werr, Poulette Garcia, Dr. Jason Keleher& Dr. William Chura

Current wound treatment options are strictly one dimensional, focusing on either infection prevention or cell proliferation. However, scientific research now focuses on finding an alternative treatment that addresses both concerns. Current approaches focus on biomimicry to enhance both healing and protective characteristics, and hydrogels contain the necessary biomimetic components. Hydrogels are made with various polymeric materials cross-linked in a tight network with a tunable surface energy.
This project focused on the synthesis a hydrogel made with alginate and calcium +2 ions with the only drawback being the rigidity brought to the structure by the weakly crosslinked network. The hydrogel is allowed more flexibility and better biocompatibility by adding an amino acid, a building block of proteins. Various amino acids, such as arginine, beta-alanine, glycine, serine, tryptophan, and phenylalanine were used to demonstrate structural diversity. In order to determine the effect of these various structures on the matrix, each amino acid hydrogel was tested for swellability, mechanical strength, and skin cell viability. In general, an increased concentration of amino acids resulted in less variable properties, likely due to more cohesive interactions in the matrix.

Additionally, it is hypothesized that higher concentrations would result in even greater uniformity owing to a balanced molar ratio of matrix to amino acid. Although amino acid characteristics altered gel properties, the biomimetic features of the hydrogels remained uncompromised. Implementation of amino acids into the hydrogel matrix has proven to be supportive of cellular division; therefore, amino acid hydrogels are viable candidates for wound care management.

This project was supported by the Doherty Center for Aviation and Health Research.

Parallelizing Leakage-Abuse Attacks Against Searchable Encryption

Ryan Meeker & Dr. Jason Perry

Searchable encryption is a family of technologies that allows users to utilize the availability of cloud storage providers while maintaining the secrecy of their files. Despite this, information leakage may still occur when encrypting in a searchable manner. The process should allow a client to request files pertaining to a specified keyword, while the server may only know the number of files it returns. However, the server may learn what keyword the user is searching for based on the number of files returned for the unknown query and previously known queries. This can be a very long process, due to the need to work on one query solution at a time. We solve this using multithreading. The list of queries to match is divided amongst several threads, which attempt to find matches concurrent to one another.

The known query list is a shared resource that all threads rely on, opening the possibility of memory corruption due to race conditions. Local copies of known queries are made for each thread to avoid the need for excessive synchronization. When query matches are discovered, synchronization is used to add an entry to the shared known query list. After a thread finishes its pass in its working list, the local query list is updated. The list is then checked for newly discovered matches that may aid in the discovery in more query reconstructions. Parallelization appears to give around 30 - 50% speed up in execution, with no observed query reconstruction loss.

Ulterior Functionality of Cyclin D3 in Gene Regulation

Steven Zeko, Alyssa Large & Dr. Sarah Powers

Historically, cyclin D3 has been characterized as a protein important for cell cycle regulation. Previous research indicated that cyclin D3 has potential ulterior functionality in non-cell cycle roles, notably in transcriptional regulation. This research focused on investigating the possible role that cyclin D3 plays
in transcriptional regulation of different targeted genes. Targeted genes were selected based on their change in rate of transcription throughout B cell development. Genes were studied from the ProB.Fr.A to PreB.Fr.E timeline of a cell. The targeted genes selected were B Cell leukemia/lymphoma 11B
(Bcl11b), Interleukin 10 receptor, alpha (Il10ra), RAD21 cohesin complex (Rad21), and zinc finger protein (Zfp367). Experiments were then completed using a WEHI-231 immature B cell lymphoma cell line, which is not expected to express high levels of cyclin D3. If cyclin D3 has ulterior functions in transcription, it is expected that forced expression of wild type cyclin D3 in the WEHI-231 immature B cell lymphoma cells will change the rate of transcription of these target genes. Using ß-2-²Ñ¾±³¦°ù´Ç²µ±ô´Ç²ú³Ü±ô¾±²Ô as an internal control during PCR showed that running PCR at 45 cycles, with the quantity of cells used, is sufficient for future protocols. Future work testing the targeted genes will be conducted and examined for a rate of change in transcription due to the inclusion of a wild type cyclin D3 in a WEHI-231 immature B cell lymphoma cell line.

This project was supported by the Doherty Center for Aviation and Health Research.

Graph Theoretical Design Strategies for Modeling Self-Assembling DNA

Chandler Stimpert, Hector Dondiego & Dr. Amanda Harsy

Motivated by the recent advancements in nanotechnology and the discovery of new laboratory techniques using the Watson-Crick complementary properties of DNA strands, formal graph theory has recently become useful in the study of self-assembling DNA complexes. Construction methods stemming from undergraduate-level graph theory have resulted in significantly increased efficiency for laboratories. In this project, general forms of bipartite graphs were explored as well as specific families of bipartite graphs, including star graphs, path graphs, and crown graphs. Minimum pots, bond-types, and tile-types were discovered and verified using linear algebra techniques that satisfy three different laboratory constraints.

This project was supported by the Caterpillar Scholars Foundation.

Automation of Microvascular Blood Flow Measurement in the Human Conjunctiva for Noninvasive Diagnosis of Cardiac Disorders

Rob Izzo & Dr. Paul Kim

As our population steadily increases, so does the need for efficient methods to treat cardiac disorders.
The focus of this research was to determine the velocity of blood flow through the human conjunctiva to help predict and remedy select cardiac diseases. The hemodynamics in the brain are very similar to those of the vessels in the human eye. This convenient fact allowed us to measure axial blood velocity, vessel diameter, cross-sectional blood velocity, wall shear rate, and average volume flow so that physicians can be provided with accurate information to better treat strokes, sickle-cell disease, diabetes, cerebral vascular disease, and Alzheimer’s. Using MATLAB, we analyzed dozens of frames from patient videos to locate red blood cells. We generated space time images to measure pixel intensities of each frame to track the distance the cells traveled over a certain period. With trigonometry and geometry, we were able to make accurate readings of axial blood velocity, and subsequently, cross-sectional velocity. Results showed a blood flow velocity slower than normal, but still within the appropriate range of values obtained in similar studies. While there are other factors that impact how we prepare for and treat cardiac diseases, the blood flow through the human conjunctiva is not something that should be overlooked.

Investigating the Antimicrobial Properties of a Novel Copper-Cellulose Composite Material Created from the Reduction of the Copper-Based MOF-199

Maryam Zaffer & Dr. Daniel Kissel

Metal-organic frameworks (MOFs) are coordination polymers that consist of metal ion linked together by organic ligands. Due to their unique honeycomb shape, MOFs are porous materials, making them ideal for guest-host interactions. Research involving MOFs has focused on their application as adsorbent materials, such as gas sorption. This work focuses on a composite material created from MOF-199 for application as a self-cleaning adsorbent material for water filtration. The adsorbent material incorporates the reduced form of MOF-199, which was synthesized from copper (II) nitrate and 1,3,5-benzene tricarboxylic acid (BTC). Since copper is known to be a bacterial growth inhibitor, the antimicrobial properties of the composite material were investigated using a series of antibiotic tests. Results from these tests confirmed that the copper-cellulose material is capable of inhibiting growth of the Gram negative E. coli on contact.

This project was supported by Dr. James Girard.

Poster Presentations

1. “Analysis of Lead in Homemade Eyeliner” by Ashna Sran & Dr. Daniel Kissel
2. “Analyzation of the Aggregation of the Amyloid Beta 42 Peptide” by Amber Tabaka, Dina Nashed, Dr. Daniel Kissel, Dr. Jason Keleher & Dr. Mallory Havens
3. “Antimicrobial Post Synthetic Modification of HKUST-1” by Brenna Hyslop, Dr. Daniel Kissel, Dr. Jason Keleher & Dr. James Rago
4. “Apnea of Prematurity with a Focus on Caffeine Therapy” by Jessica King & Dr. Erin Zimmer 
5. “Characterization of Biomimetic Hydrogels Crosslinked with Amino Acids for Wound Management” by Poulette Garcia, Carolyn Werr, Eric Nelson, Dr. William Chura & Dr. Jason Keleher
6. “Characterizing the Effects of Reducing Agents on the Redox Properties of Ceria Nanoparticles Relevant to STI CMP” by Cynthia Saucedo, Madison Hill, Tanner Bedwell & Dr. Jason Keleher
7. “Cyclin D3 as a Transcription Regulator in B Cell Development” by Alyssa Large, Steven Zeko & Dr. Sarah Powers
8. “Dilated Cardiomyopathy May Lead to Chronic Heart Failure” by Jessica Ventura & Dr. William Chura
9. “Effects of Air Pollution on Pregnant Women” by Michael Geyer & Dr. William Chura
10. “The Effects of Diet and Exercise on Alzheimer’s Disease” by Morgan McGuire & Dr. Erin Zimmer
11. “Epi-Fluorescent Optical Tweezers for Antibacterial Characterization of Metal Nanoparticles” by Caroline Stefanon, Justin Vollmuth, Thomas Beckman, Dany Danhausen & Dr. Jason Keleher
12. “Integrating Arduino Sensors and Liquid Crystals to Prevent Laser Attacks on Aircrafts” by Pablo Nevarez, Daniel Maurer, Andrew Musielak, James Hofmann & Dr. Jason Keleher
13. “Investigating the Interactions Between Bacteria and Electrode Material in Correlation to Fuel Cell Performance” by Alana Dunne, Madalyn Puckett, Nicole Yuede & Dr. Jason Keleher
14. “The Molecular Mechanism and Effects of Mercury on Vertebrates” by Hussan Omar
15. “Mutations of Cyclin D3 and the Effects on Eukaryotic Cells” by Sarah Nelson, Dr. Jason Keleher & Dr. Sarah Powers
16. “Novel Nanocomposite Design for Enhanced Water Remediation Applications” by Samuel Baker, Heather Lange, Jonah Sprandel, Katelyn Lanasky & Dr. Jason Keleher
17. “Principles of Biofuel Production Activity Designed for the Lederman Science Center at Fermilab” by Seth Contreras & Dr. Lauren Rentfro
18. “Probing the Efficacy of Traditional and Novel Cleaning Solutions Relevant to Post-STI CMP” by Carolyn Graverson, Allie Mikos, Tala Zubi & Dr. Jason Keleher
19. “Research and Development Intern at Schulze & Burch: How job experience can be used in the classroom” by Samuel Boctor, Dr. Dorene Huvaere & Dr. Lauren Rentfro
20. “The Role of Drosha in Cell Migration and Growth in Cancer and Non-cancerous Cells” by Lulu Ahmad, Matthew Grimm, Danica Ujano & Dr. Mallory Havens
21. “The Role of Neutrophil Apoptosis in the Innate Immune Response and the Inflammatory Response” by John Rupar & Dr. Erin Zimmer
22. “Watch Your Step!” by Sean Giltmier & Dr. Jerry Kavouras

Undergraduate Research Experience Program - 2018 Participants

• Sarah Bettag (Biology)
• Keller Dellinger (Computer Science & Computer Engineering)
• Kevin Gannon (Computer Science)
• Matthew Grimm (Biology)
• Rob Izzo (Applied Physics)
• Rachel Lullo (Biology)
• Ryan Meeker (Computer Science)
• Jonathan Nelson (Mathematics)
• Chandler Stimpert (Mathematics)
• Maryam Zaffer (Biology)
• Steven Zeko (Biology & Secondary Education)

2018 Faculty Mentors

• Dr. William Chura (Biology)
• Dr. David Failing (Computer & Mathematical Sciences)
• Dr. Amanda Harsy (Computer & Mathematical Sciences)
• Dr. Mallory Havens (Biology)
• Dr. Paul Kim (Computer & Mathematical Sciences)
• Dr. Daniel Kissel (Chemistry)
• Dr. Jason Perry (Computer & Mathematical Sciences)
• Dr. Sarah Powers (S.U.R.E. Director, Biology)
• Dr. Piotr Szczurek (Computer & Mathematical Sciences)

Special Thanks:

• Dr. David Livingston, President
• Dr. Christopher Sindt, Provost
• Dr. Stephany Schlachter, Provost Emeritus

S.U.R.E. has been made possible by financial support from the Aileen S. Andrew Foundation, the Dr. Scholl Foundation, Dr. James Girard & Dr. Katie Hanley

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