Blugold Biomedical Innovator Program

Research Project Summary

In collaboration with an interventional radiologist at Mayo Clinic Health System-Eau Claire, materials are being developed and tested for separation and protection of healthy organs and tissues during treatment of tumors by freezing or heating. These injectable foams are being tested for stability, mechanical stiffness, and incorporation of therapeutic components such as contrast agents and antibiotics. Testing includes the materials characterization of these foams, testing the foams in physiologic conditions, and animal studies. Undergraduate researchers are critical for creating and testing the foams, collecting and analyzing data, working with our collaborator, and communicating results to a variety of audiences.

Mayo collaborator: Dr. Jeremy McBride

Faculty Member

Dr. Liz Glogowski
Associate Professor — Materials Science and Biomedical Engineering

Research Project Summary

The number of older people in the United States continues to increase, highlighting the importance of understanding health factors associated with this population. Current data reveals that older people are more sensitive to alcohol’s effects compared to younger people. We have recently developed animal models to study the effect of alcohol in aged animals and have replicated the findings that aged rats are more sensitive to the effects of ethanol compared to younger animals. The current project is a multi-level analysis to investigate the neurobiological mechanism(s) that produce greater effects of alcohol in aged animals compared to younger animals.

Mayo collaborator: Dr. Doo-Sup Choi

Faculty Member

Dr. Doug Matthews
Professor — Psychology

Research Project Summary

Cancer now tops heart disease as the number one cause of death in the United States, and it is the second leading cause of death globally. The symptoms of cancer are often not specific and, in most cases, are not apparent in early stages. As early cancer detection is the hallmark of successful treatment, our research is focused on developing a rapid, reliable, inexpensive, and non-invasive method for cancer detection and screening. The student researchers working on this project will be using Raman Spectroscopy to identify cancer-specific biomarkers in saliva samples for the early diagnosis of cancer. In particular, Surface-Enhanced Raman Spectroscopy (SERS), a highly sensitive analytical tool, will be used for this study. Student researchers will be responsible for preparing samples, optimizing the experimental conditions, analyzing data, and sharing the findings of this study with others in the form of poster/oral presentations and manuscripts.

Mayo collaborator: Dr. Sandeep Basu

Faculty Member

Dr. Sanchita Hati
Professor — Chemistry

Research Project Summary

Fibrosis is the development of fibrous connective tissue in response to injury or organ damage. Mapping and quantification of fibrosis is a key factor in disease staging and also provides one of the best prognostic indicators of continued organ success. We investigate whether infrared imaging can allow for the rapid mapping and quantification of fibrosis in multiple organs without requiring dyes or stains and furthermore, whether we can extract additional biochemical information predicting rapid fibrosis progression in patients. A high throughput, real-time, Quantum Cascade Laser imaging system will be created for rapid imaging and diagnosis of fibrosis in heart, lung, kidney, and liver tissues. This system will include the ability to map and quantify the extent of fibrosis and include intelligent analysis software capable of automatic flagging of suspect areas. This will be performed as part of a collaborative study on paraffin-embedded unstained tissue that exist in the Mayo Clinic tissue archives.

Mayo collaborator: Dr. Rajeev Chaudhry and others TBD

Faculty Member

Dr. Michael Walsh
Assistant Professor — Materials Science and Biomedical Engineering

Research Project Summary

The human body is a complex system where disease in one part can cause new disease states in other parts of the body. For example, diabetes can cause hypertension, and hypertension may increase the risk of heart disease. Researchers have identified relationships among many such disease states. These relationships may also exist among complex diseases like schizophrenia, Alzheimer's disease, and cancer. Determining these relationships are of paramount importance and can be used for presumed diagnosis, early intervention, and the development of new medicine. The goal of this project is to develop a novel and robust machine learning approach to identify possible relationships among complex disease states by analyzing a multi-view biomedical dataset (e.g., DNA and organ images). Our goal is to accomplish the following three objectives: (1) identify relationships between complex disease states, (2) incorporate and propose machine learning techniques for complex disease prediction, and (3) develop software systems and disseminate those to the scientific community for various uses.

Mayo collaborator: Dr. Rajeev Chaudhry

Other collaborator: Dr. Ashad Alam, Tulane University, New Orleans, Louisiana

Faculty Member

Dr. Rakib Islam
Assistant Professor—Computer Science 

Research Project Summary

Our research involves using artificial intelligence (AI) methods like machine learning and deep learning to diagnose diseases and develop technologies to monitor health. Students in Dr. Gomes’ lab work with big data like CT scan images or human gene sequence text data and use high performance computing to run analyses. Presently, Dr. Gomes and five undergraduate students collaborate with Dr. Wildenberg on developing new AI technology to identify filters in a large vein, the inferior vena cava, in a patient’s CT scan. These filters are inserted to trap blood clots and prevent them from reaching the heart and lungs. Our vision is to automate filter detection with routine CT scans so that radiologists can follow-up on the health of these filters. Research with Dr. Garg is focused on developing an AI-oriented approach to identify pancreatic cancer from patient CT scans. Our vision is to automatically detect the stage of cancer, the disease progression, and the steps to be taken (such as chemotherapy or surgery) to address recovery. Dr. Gomes is also collaborating with researchers at North Dakota State University to analyze human gene sequence information and identify regions in the human genome that play a significant role in cancer progression.

Mayo collaborators: Dr. Joe Wildenberg and Dr. Sushil Garg

Other collaborators: North Dakota State University

Faculty Member

Dr. Rahul Gomes
Assistant Professor— Computer Science 

Research Project Summary

Considering a high prevalence of burnout syndrome in physicians (especially those in early career), we must first care for the providers before providing care to patients. Improved well-being of physicians will lead to healthy workforce in healthcare which naturally leads to an improvement in overall patient care. Among risk factors for burnout, sleep loss is an overlooked factor that impact mental fatigue and burnout. The proposed study utilizes a non-invasive inclinometer device (worn on mid-thigh) to better understand sleep patterns of residents during the week of overnight shifts and their impacts on acute mental fatigue and perceived burnout. Additionally, second part of the study will implement a tailored workplace exercise program as a countermeasure to manage stress, improve sleep patterns, and reduce chronic mental fatigue and burnout among family medicine residents who have extended work hours and overnight call responsibilities.

Mayo collaborator: Dr. Terri Nordin

Faculty Member

Dr. Saori Braun

Associate Professor — Kinesiology

Research Project Summary - 1

Polycystic kidney disease is a genetic disease, which affects approximately 12.4 million people worldwide (PKD Foundation). A major question in the field is “how precisely does a genetic change (a change in DNA) lead to the formation of cysts?” In other words, which pathways and processes in the cells are affected? In addition, patients develop a range of symptoms, and age of onset is variable. Our lab uses C. elegans and zebrafish as models to understand cystic kidney disease and more specifically to understand how primary cilia, which act as cellular antennae, contribute to health and disease.

Mayo collaborator: TBD

Research Project Summary - 2

Genetic testing of patients with suspected genetic disorders yields a wealth of sequence information that then must be interpreted to determine which variants (differences in the DNA sequence between a patient’s genome and a reference genome) affect the symptoms and pathology observed. This process of variant interpretation is challenging and complex. Our lab is initiating a project to analyze variants of uncertain significance identified during genetic testing to see whether these changes in the DNA result in a change in expression of the gene. Data from this project have the potential to improve patient outcomes by improving the ability of physicians and scientists to decipher which variants are clinically relevant.

Mayo collaborator: TBD

Faculty Member

Dr. Jamie Lyman Gingerich
Associate Professor — Biology

Research Project Summary

To improve surgical outcomes, physicians are moving to less invasive procedures that rely on better knowledge of the individual patient anatomy through advances in medical imaging, such as MRI, ultrasound, or CT scans. Technology now allows these data, that are typically displayed on 2D screens, to be displayed in three dimensions through 3D printing. These 3D printed models allow physicians to better visualize what they will encounter during surgery, test different instruments that may be used during surgery, and improve the surgical plan for the individual patient. This project will provide 3D printed models for use in the presurgical process of the Mini-thoracotomy Aortic Valve Replacement program at Mayo Clinic.

Mayo collaborator: Dr. Joseph Wildenberg

Faculty Member

Dr. Doug Dunham
Professor — Materials Science and Biomedical Engineering

Research Project Summary

How do changes in the environment contribute to brain formation and associated neurodevelopmental disorders? Students in the Carter laboratory investigate the effects of disorder-associated environmental compounds on neurodevelopment and then define mechanisms of action for compounds that cause brain abnormalities. We currently are focused on the neurodevelopmental impact of environmental factors that have been shown in public health studies to correlate with autism spectrum disorder (ASD) prevalence. We use zebrafish in our experiments and assess changes in physical development (microscopy), molecular biology (gene expression), and behavior (motor tracking).

Mayo collaborator: Dr. Ashley Holland, Dr. Scott Schmidt

Faculty Member

Dr. Brad Carter
Assistant Professor — Biology

Research Project Summary

In this project we aim to develop and build a prototype of a mechanically flexible and electrically powered cooing pad to help patients manage pain after surgery or injury. Pain management is a multi-billion-dollar industry in the U.S., but it is challenging to deliver localized pain relief in a way that is consistent and sustained over time, and that conforms to the patient body part requiring treatment. This project will combine considerations for patient care with practical engineering skills to design an optimum cooling pad, and students will have the opportunity to see the project through from initial design to a final project.

Mayo collaborator: Dr. Tiziano Taliarita

Faculty Member

Dr. Matthew Jewell
Department Chair and Professor — Material Science and Biomedical Engineering