Hersh Nanda

Development of a user-defined software for robust cardiomyocyte contraction analysis

Hersh Nanda, BASIS CHANDLER, High School Student

Cardiomyocytes, or cardiac muscle cells, make up heart tissue and are essential for normal cardiac function. Current research into the quantification and measurement of cardiomyocyte contraction is crucial for understanding cardiomyocyte physiology, pathology, and drug-induced response. Although methods for cardiomyocyte contraction analysis exist, most are time-consuming and require skilled manual intervention, extensive training, and expensive proprietary equipment. The purpose of our research was to eliminate these concerns with the feasible alternative of a user-defined software for robust cardiomyocyte contraction analysis.

This program contains two primary MATLAB functions: an integrateMonolayer function, and select BoundingBoxed function. The integrateMonolayer function was developed to perform an automated contraction analysis on cardiomyocyte monolayers. On the other hand, the select Bounding Boxes function was created as a user-friendly interface to allow users to manually draw bounding boxes on the monolayer video frames. Bounding boxes must be created to analyze specific regions of interest in which cardiomyocyte contractions have occurred. After the bounding boxes have been generated, the integrateMonolayer function performs the analysis and outputs cardiomyocyte contraction traces for parameter calculation.

The software was used to analyze two cardiomyocyte monolayers: a control monolayer (no treatment added) and an FSK monolayer (forskolin or FSK treatment was added to alter cardiomyocyte contraction rate). Post-analysis, the software generated reliable contraction traces which correctly displayed an abnormally high cardiomyocyte contraction rate in the forskolin (FSK) monolayer. Overall, the software successfully performed cardiomyocyte contraction analysis including contraction trace generation, processing, and display.

The software provides a reliable and user-friendly method for analysis, and the results validated the program’s capability and efficacy in analyzing cardiomyocyte contraction data. This software can be used for modeling of heart diseases including cardiovascular disease, cardiomyopathy, and cardiotoxicity. Using this software, cardiomyocyte monolayers can be compared and analyzed for the identification of pathological differences due to heart disease. This software can also be used for pharmacological applications including drug-testing and treatment development. Cardiac arrhythmia (irregular heartbeat), which is a strong indicator of heart failure, can also be detected through cardiomyocyte contraction analysis.

Note: This research project was performed under the guidance of Dr. Jared Churko as part of the University of Arizona KEYS program (June-July 2021)

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Hasina Shir

Non-Linear Analysis of Collagen in Murine Ovarian Samples Using Second Harmonic Generation
Hasina Shir, University of Arizona, Undergraduate Student

Title: Feasibility of Non-Imaging Second Harmonic Generation to Identify Early Ovarian Cancer in a Murine Model Analysis of Collagen in Murine Ovarian Samples Using Second Harmonic Generation

Ovarian cancer is the fifth leading cause of cancer death in women. Early detection can save lives, but no generally acceptable (accurate and inexpensive) method exists. Research conducted by us and others has shown that the morphology and density of collagen is altered in cancerous tissue. In this study, the ovaries of a transgenic (TAg) mouse model of ovarian cancer were quantitatively imaged, using second harmonic generation microscopy (SHG). SHG is a nonlinear optical technique that can provide information about collagen structure and organization, however, it utilizes complex and expensive scanning elements. We sought to determine if non-imaging, randomly sampled point intensity measurements could be used to distinguish TAg from normal wild type (WT) mice. Eighty four three-dimensional (3D) SHG image sets from 21 TAg mice and 72 3D image sets from 18 wild type (WT) mice were obtained and analyzed. 3D image sets were converted to two-dimensional (2D) images, with maximum intensity projection being the preferred method. Images were thresholded and masked to exclude non-collagen signal, and then image pixels were randomly chosen. We found that the average intensity of a random sampling of 1000 pixels was not significantly different than the average intensity of the entire 1 million pixel image. This finding indicates that a simple continuously sampling, point-measuring system may provide data equivalent to a scanning system. We also found that the 1000-random-pixel average intensities were significantly lower in the TAg than WT mice at 4 weeks of age, suggesting that collagen is being degraded in the cancerous ovaries. However, there was no significance between the average intensities at eight weeks of age, possibly because more advanced cancer is heterogenous in collagen content. Next steps include further investigating the collagen structure as a function of cancer type, and adding an endoscope to the SHG system, which would allow use in vivo without the need for scanning.

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Francisca Grill

Development of a quantitative antigen assay to detect coccidioidal chitinase-1 (CTS1) in human serum

Francisca Grill, Arizona State University, Graduate Student

Background Coccidioidomycosis is often diagnosed with a collection of tests that rely on the patient’s ability to mount an immune response to the fungus (antibody-based diagnostics), making diagnosis of this infection challenging. Here we present an antigen-based assay that detects and quantifies coccidioidal chitinase-1 (CTS1) in human serum.

Methods An inhibition-based enzyme-linked immunoassay (ELISA) was developed that utilizes a monoclonal antibody specific for coccidioidal CTS1. CTS1 was quantified in commercial antigen preparations using recombinant CTS1 as a standard. Sera from 192 individuals from an endemic area were tested which included 78 patients (40.6%) with proven or probable coccidioidomycosis.

Results The quantity of CTS1 in diagnostic commercial antigen preparations from different suppliers varied. CTS1 antigenemia was detected in 87.2% of patients with proven or probable coccidioidomycosis. Specificity was determined to be 96.94% using serum from individuals who reside in the Phoenix, Arizona area who did not have coccidioidomycosis. Levels of CTS1 correlated with low- and high-titer serology from patients with a coccidioidomycosis diagnosis.

Conclusions Since the CTS1 inhibition ELISA described in this report does not depend on the host immune response, it is a promising diagnostic tool to aid in diagnosis and disease monitoring of coccidioidomycosis.

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Chloe Rozalsky

An Analysis of RNA Solubility in Human Spinal Cord Samples from ALS Patients
Chloe Rozalsky, Paradise Valley High School (CREST Bioscience), High School Student

Amyotrophic Lateral Sclerosis (ALS), a progressive, heterogeneous neurodegenerative disease, causes nerve cell breakdown within the brain and spinal cord. RNA-binding protein TDP-43, contributes to 97% of ALS cases. TDP-43 recognizes UG-rich (Uracil and Guanine) sequences preferentially, prompting the question: Does UG richness play a role in RNA solubility in Human ALS spinal cord samples? Differential expression analysis was conducted on RNA sequenced from soluble and insoluble fractions of post-mortem spinal cord samples from an ALS patient. Average UG richness calculated for individual cDNAs between whole genome, soluble and insoluble fractions was compared, with and without sequence length normalization. Insoluble genes were generally more UG rich, though longer than soluble counterparts. After normalization, longer transcripts appear more likely to be insolubilized than shorter transcripts.

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Correa Wlodek and Matthew Oliwia

PHOTOSYNTHESIS AND BIDIRECTIONAL HYDROGENASE IN HYDROGEN PRODUCTION IN CYANOBACTERIA

Correa Wlodek and Matthew Oliwia, Grand Canyon University, Undergraduate Students

While traditional methods of hydrogen production are expensive and emit high levels of carbon dioxide, renewable bio-hydrogen production systems can be carbon neutral and less energy intensive. Photosynthetic species can use sunlight to produce molecular hydrogen by the bidirectional hydrogenase enzyme that can take electrons from the photosynthetic electron transport chain. The goal of this study is to explore photosynthetic potential of cyanobacteria as the source of energy for bioproduction of hydrogen.

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Brycelyn Whitman

Creation of AD-Relevant Isogenic Lines with the Gene Editing Method CasMasTREE

Brycelyn Whitman, Arizona State University, Undergraduate Student

Since 1901, Alzheimer’s disease (AD) claims at least 5.5 million individuals each year, making it the sixth leading cause of death in the United States. Alzheimer’s disease is an age-related neurodegenerative disorder denoted by severe memory deterioration due to amyloid beta and tau. These proteins are known for creating knots and tangles within the brain, ultimately causing neuronal death and memory loss. AD has two forms: familial AD (FAD) and sporadic AD (SAD). About 70% of the population is affected by SAD, meaning that AD can develop because of the interplay of many genes. Currently, there is no known cure or treatment for patients suffering with FAD and SAD. However, research has found that some genes, such as Apolipoprotein E (APOE) isoforms 2, 3, and 4, play a role in genetic risk of developing SAD. Specifically, the isoform, APOE 4, has been linked to the increased risk of developing AD, while the isoform, APOE 2, has been linked to decreased risk of developing AD. How these genes increase the risk of AD is not well understood, but every gene found linked to Alzheimers can increase the understanding of the disease forms. Since the majority of AD cases are sporadic, it makes this disease difficult to study in vitro. Thus, there is a need for the ability to create isogenic lines to study single genes and their roles in neurodegenerative diseases.

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Brian Pham

Amyloid-beta Analysis and Characterization using Gel Electrophoresis

Brian Pham, Arizona State University, Undergraduate Student

This study pertains to the analysis and characterization of different species within samples of amyloid-beta 40 and amyloid-beta 42. The amyloid-beta precursor protein is secreted by cells and normally plays a vital role in the functioning of the nervous system. However, when these proteins aggregate into larger oligomers, they form neurotoxic deposits in the brain. This has been correlated with the pathogenesis of Alzheimer’s disease. Characterizing amyloid-beta, however, proves demanding due to the heterogeneity of the aggregation states and its tendency to rapidly differentiate with time. Regardless, dedicating time to study the various amyloid-beta oligomeric states is critical and valuable to advancing knowledge on Alzheimer’s disease.

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Roshan Pillai

SAVR- Stroke and Cardiovascular Risk Assessment using Wearable Technology

Presented By Roshan Pillai, BASIS Scottsdale

Cardiovascular risk is the risk of a person developing cardiovascular diseases, often sudden. Heart disease is the leading cause of death for both men and women. Most of the current warning tools utilize the threshold level wherein, a warning is given when a patient’s symptom crosses a threshold. Unfortunately, this threshold method does not take into account other signs and symptoms demographic, or social factors, nor does it attain a 360-degree view of a patient’s
risk. Cardiovascular issues can appear rapidly and without warning. Heart attacks (Myocardial Infarction) and Strokes (Cerebrovascular Accidents) can cause irreversible damage and focus on prevention or early diagnosis is still needed.

Also, the current risk calculators and available tools do not provide results based on input from wearables/ live data and also do not incorporate the latest technology that’s available to the users to include information from their medical records. I created an app that utilizes an interoperable based approach where a patient/user can take their everyday data from a wearable, integrate the information available on their health app/health records and with user input, including their reported medical symptoms to screen and find out their relative risk for stroke/cardiovascular disease.

My design incorporated integration with Wearable Technology, the ability to integrate live data, and allow user input, as well as the ability to access health records (via PHI: Protected Health Information) in a HIPAA compliant manner to protect patient privacy. I formulated a hierarchical project architecture to create this application. My first layer was the data collection layer. Once I had obtained the data, I converted the data to .csv files for easier analysis. The next layer was the analytical model layer where I utilized machine learning, created a statistical model, and then combined the two models to create my algorithm. Once my algorithm generated both a viable and accurate structure for prediction, the next step was implementation. Lastly, I constructed an Intelligence Layer to access Wearable Technology as well as create SAVR (Stroke and Vascular Risk), my mobile application. For my machine learning algorithm, my unique approach was to mesh both statistical analyses through the use of Ensembling Models. The machine learning method used was XGBoost, an open-source, R and Python-based software library which is a versatile tool made to work through most regression, classification, and ranking problems as well as user-built objective functions. I chose XGBoost because it’s a library designed and optimized for boosted tree algorithms which are specifically tuned towards training an algorithm for software functionality. Also, XGBoost is known for its model performance/ accuracy and execution speed; both critical for this project. I then did the statistical model to add another layer to my algorithm accuracy. I did a linear regression and created a statistical model algorithm using Python. The algorithm plots all of its analyzed data then finds the most accurate linear line to its predictions. Then, I performed a linear regression to find out how my application should weigh different factors. After I generated both a machine learning model and a statistical model, I used Ensembling Models to combine the two. The combined algorithm revealed how different risk factors must be designed to create an accurate prediction for a patient.

Lastly, to build the SAVR Application, I used Ionic, a hybrid app development platform. Ionic is an open-source Java-Script-based Language. With Ionic, I combined the Analytical Model Layer and the Intelligence Layer to create the Presentation Layer, where the user could input their data and get a predicted Risk Score. This was SAVR, the wearable app that I hope that one day will be a tool that helps save lives.

Yakeleen Almazan and Asher Bankhead

Can Forensic Quality DNA be Extracted from Discarded Gum?

Presented by Yakeleen Almazan and Asher Bankhead, Pueblo High School

The purpose of our research is to determine whether forensic scientists can accurately use gum samples to extract Deoxyribonucleic Acid (DNA) and identify suspects. This research is especially helpful for forensic scientists who extract DNA to solve cases.

Evidence is a scarce resource for forensic scientists. We wish to determine if a mundane source like chewing gum can yield stable forensic quality DNA, and at what time frame. Furthermore, this involves the stability of the mitochondrial Cytochrome B gene over time.

DNA from the chewing gum was isolated and specific primers were used to amplify a part of Cytochrome B gene. Electrophoresis was performed with a gene ruler that allowed us to measure the gene product (measured by base pairs) and see if we isolated the correct gene. Other samples were sequenced and compared to the isolated part of the Cytochrome B gene.

The first set of results we got were our electrophoresis gels. There were two qualifiers that made the data forensic quality. The first qualifier being the amount of base pairs in our product. Nearly every sample was close to 230 base pairs. The other qualifier was the amount of DNA, which was determined by the brightness of the electrophoresis bands (products) which were variable. To judge them based on brightness, we created a scale from 1-5 based on the luminosity. The amount of DNA over time didn’t decrease by any meaningful amount. After visual analysis, we also received DNA sequencing on our gum samples. The sequencing found a 99% similarity to the part of the Cytochrome B gene we isolated. With the amount of DNA in the electrophoresis not decreasing, and our isolated genes being nearly identical, it is likely that gum found in DNA doesn’t decrease in quality up to a year, making it useful for forensic scientists.

Although we were focused on the mitochondrial DNA of the gum sample, it is unethical to use such analysis in a classroom because our work could potentially point us to an individual who has not committed a crime. Therefore, we used the cytochrome B gene in the mitochondrial DNA because its sequence is highly conserved and stable among humans. If we were to do forensic analysis on our gum samples, we would look at the variable region of the Mitochondrial DNA which would connect us to Haplogroups and eventually, a suspect. In the future we hope to conduct this experiment in various environments to examine how these variables impact the DNA stability.

Rebecca Jernigan

New Structural Insights into the Function of the Active Full-Length Human Taspase1: A Novel Anticancer Therapeutic Target

Presented by Rebecca Jernigan (Arizona State University – Graduate Student)

Taspase1 (threonine aspartase 1) is an endopeptidase overexpressed in primary human cancers that has been identified as a novel potentially potent anticancer drug target. Loss of Taspase1 activity has been demonstrated to disrupt proliferation of human cancer cells in vitro and in mouse tumor xenograft models of glioblastoma. By functioning as a non-oncogene addiction protease, Taspase1 coordinates cancer cell proliferation, invasion and metastasis. Taspase1 encodes a highly conserved 50 kDa inactive proenzyme that undergoes auto-proteolytic cleavage becoming an active heterodimer that displays an overall αββα structure. The crystallographic structures of the proenzyme and a truncated version of activated Taspase1 are known. In this study, the crystallographic structure of the full length active human Taspase1 is shown to 3.1Å. For the first time, a key structure element has been identified: a long helix of about 50 residues that was missing in previous reported structures of the activated enzyme. Previously his helix was predicted to have a helix-turn-helix conformation lying right on top the catalytic site of Taspase1; however the crystallographic structure of the full-length taspase1 shows a straight helix conformation. This opens new insights in the enzymatic mechanisms for possible substrate recruitment of Taspsae1 and suggest the long fragment as a novel target for the design of medical drugs that inhibit the function of Taspase1 enzyme.