HIV/AIDS effects millions of people all over the world. The antiretroviral therapy used to treat HIV is effective, but HIV first must be diagnosed and then monitored to measure the treatment effectiveness to eliminate transmission to others and increase a patient’s quality of life. The Linnes Lab uses state of the art microfluidic technologies to prevent, detect, and understand the pathogenesis of diseases, such as HIV. This undergraduate summer research project will focus on developing new technology for HIV diagnostics that will also aid in diagnostics research of other bloodborne illnesses. The student will learn about biological sample preparation, nucleic acid amplification methods, microfluidic device design, fabrication, and testing, and rapid prototyping tools such as 3D printing and laser cutting. The researcher will develop a new tool for sample preparation of the blood that minimizes the number of user steps to integrate into an easy-to-use point-of-care diagnostic tool for people living with HIV to monitor their viral load within the convenience and privacy of their homes. The new tool design specifications include that it must be compatible with the smartphone imaging platform, microfluidic chip, and the HIV assay to diagnose the disease with high sensitivity and specificity.

Biological Characterization and Imaging, Fabrication and Robotics, Human Factors, Medical Science and Technology, Nanotechnology

• Biomedical Engineering
• Biochemistry
• Biological Engineering - multiple concentrations
• Microbiology

3d printing and prototyping, medical technology

Weldon School of Biomedical Engineering

Jacqueline Linnes

Breast cancer is the number one diagnosed cancer among women and affects over a quarter of a million people annually. The five-year survival rate is exceptional if the disease remains local, however, once breast cancer has metastasized, patient survival rates drop precipitously. There is a critical need to better understand the events required for breast cancer metastasis and how these events culminate in systemic tumor growth. During breast cancer metastasis, the composition and structure of the extracellular matrix (ECM) in the metastatic niche are dramatically altered before the arrival of colonizing cells. As such, the ECM is emerging as a potential therapeutic target for disrupting the metastatic process. Our goal is to determine how changes in the ECM are permissive to metastasis and to manipulate these events in order to inhibit metastatic disease. Our recent studies have demonstrated that Fibronectin (FN) is upregulated in the lungs before the arrival of metastatic cancer cells, and clinical evidence has shown that increased FN is predictive of decreased patient survival. Despite these findings, there remain fundamental gaps in determining how matrix remodeling events that occur during metastasis can dictate the cancer cell fate. In particular, the architecture of the FN matrix can induce phenotypic changes of invading cancer cells that can make the cells less sensitive to drug treatment. Additionally, changes in the local tissue architecture can direct a cell to enter a growth cycle or a dormant phenotype, which can diminish the clinical efficacy of ECM-targeted therapeutics.
Our group has recently observed that tumor-derived metastatic cancer cells express elevated levels of FN, but unlike fibroblasts and other stromal cells, the tumor cells do not deposit FN as a fibrillar matrix. Instead, tumor cells secrete FN in a soluble form which must be converted into insoluble fibrils through a cell-mediated event, exposing cryptic binding domains and transitioning the protein into a bioactive state. Our studies suggest that the assembly of fibrillar FN is dependent on a functional relationship between tumor cells and fibroblasts. Interestingly, we have demonstrated that the FN matrix produced and assembled by resident lung fibroblasts during pre-metastatic niche formation results in a highly aligned and organized FN matrix. However, the matrix formed by fibroblasts utilizing FN produced by tumor cells is less organized and more dispersed, which can significantly alter how forces are transmitted to local cells. To study the impact of FN architecture on the metastatic process independent of the confounding influence of other cell populations, our group has developed an advanced 3D cell culture platform that allows us to create a bioactive fibrillar FN network without the need for cell-mediated assembly. Utilizing this platform, we can tune the alignment of the resultant 3D fibrillar FN network to interrogate the role of the matrix on cell fate decisions. Based on our strong preliminary results, we hypothesize that dynamic changes in the FN network architecture will alter both biochemical and mechanical signaling within the niche, influencing the cell phenotype and dormancy and ultimately altering the cell sensitivity to drugs.

Through this project, we seek to evaluate the effect of FN architecture on dormancy. We will use genetic depletion strategies along with a rigorous panel of markers to determine the effect of matrix architecture on the entrance to or exit from dormancy.

Biological Characterization and Imaging, Cellular Biology, Medical Science and Technology

• No Major Restriction

BME

Luis Solorio

This project aims to develop drop-on-demand (aka inkjet) printing technology of soft biomaterials including cell-laden hydrogel and RNA containing materials. Specifically, the undergraduate student will formulate and characterize the mechanical and rheological properties of polymeric inks to print and cure for advanced tissue constructs or drug delivery systems.

Cellular Biology, Material Processing and Characterization, Medical Science and Technology, Nanotechnology

• Mechanical Engineering
• Chemical Engineering
• Biomedical Engineering

Course work of solid or fluid mechanics are required. Experience in LabVIEW, CAD software and Matlab are preferred. Cell biology background is plus but not required.

Mechanical Engineering

Bumsoo Han

Spinal cord injury is a significant human health problem affecting about 300,000 people in the US. Better treatment options are needed to overcome the limited regeneration potential of the human spinal cord. Zebrafish larvae are an emerging model system for drug screening for several reasons including large number of embryos per breeding, genetics, and availability of behavioral assays for drug testing. Our lab is conducting a large scale drug screen with an FDA-approved library to identify novel compounds that enhance functional recovery following injury as assessed by a swimming assay. The student will be involved with fish breeding, spinal cord injury, drug treatment, and behavioral assay. We hope that this work will identify new compounds with translational potential.

Biological Characterization and Imaging, Biological Simulation and Technology, Cellular Biology, Medical Science and Technology

• Biology
• Cell Molecular and Developmental Biology
• Biochemistry
• Neurobiology and Physiology
• Genetics
• Microbiology

Cell Biology, Neurobiology, fine motor skills, working with zebrafish

Biological Sciences

Daniel Suter

Loss of large volumes of skeletal muscle (volumetric muscle loss (VML)), as may occur with cancer resection or combat-related traumatic injury, represents an ongoing clinical challenge that affects both civilian and military populations. Because VML surpasses the body’s natural capacity for tissue repair and regeneration, affected individuals suffer long-term disabilities, with significant loss of musculoskeletal strength, mobility, and function. Present day standard of care for VML patients includes physical therapy and/or orthotics, both of which do not adequately address strength and tissue structural deficits. Surgical muscle transfers, where a working muscle from another location is placed in defect area, may also be performed; however, such procedures do not restore function owing to lack of graft “take” and reinnervation. While researchers continue to evaluate various potential skeletal muscle restoration options, only a few have progressed to large animal or human clinical studies, with only modest improvements being observed to date. As such, new therapeutic options are needed that support restoration and functional re-innervation of lost skeletal muscle, thereby improving functional strength, mobility, and overall quality of life for VML patients. The Harbin laboratory, which specializes in scaffold-forming (polymerizable) collagen, and Stacey Halum, a head and neck surgeon-scientist, who has developed a special population of nerve-attracting muscle stem cells, have enjoyed a long-standing collaboration focused, in part, on skeletal muscle regeneration, especially as it relates to head and neck surgery applications. By combining the collagen and muscle stem cells, the team has fashioned a skeletal muscle replacement that when used in preclinical studies for laryngeal muscle reconstruction restored skeletal muscle volume and associated muscle function. The engineered muscle replacement showed an exceptional bodily acceptance, characterized by noninflammatory cellularization, vascularization, reinnervation, and skeletal muscle generation. Based on these encouraging results to date, an ongoing goal is to further innovate and evaluate skeletal muscle restoration strategies for VML. An important next step for this translational research is to further development and evaluation of skeletal muscle replacements using electrophysiologic techniques and established small animal models of VML. Measured outcomes from these preclinical studies will include functional measures of muscle innervation and contraction, restoration of limb mobility and strength, as well as definition of the implant’s unique regenerative mechanism of action. This project team will be led by veterinary-scientist Sarah Brookes, operating under the co-mentorship of Prof. Harbin and Dr. Halum.

Medical Science and Technology

• Biomedical Engineering
• Mechanical Engineering

Coursework or skills related to biomaterials, biofabrication, biomechanical testing, protein and gene expression, preclinical animal models, in-vitro cell culture, other wet lab procedures.

Biomedical Engineering

Sherry Harbin

High physical and cognitive workload among surgeons and nurses are becoming more common. The purpose of this project is to examine the contributors to these and develop technology to understand and enhance their performance.

The SURF student will participate in data collection in the operating room at Indiana University School of Medicine, data analysis and interpretation, and write his/her results for a journal publication. The student will regularly communicate his/her progress and results with faculty, graduate mentors, and surgeon collaborators.
More information: https://engineering.purdue.edu/YuGroup

Big Data/Machine Learning, Human Factors, Learning and Evaluation, Medical Science and Technology

• No Major Restriction
• Industrial Engineering
• Computer Science
• Biomedical Engineering

Human Factors, Machine Learning, Sensors, Programming

Industrial Engineering

Denny Yu

Since the popularization of handheld communication devices and social media applications, opinion dynamics and social networks have played a more critical role in politics, economics, and public health issues. In particular, opinion polarization on vaccination has tolled thousands of lives in the recent pandemic. Consider the following question: "If you could only convince three nodes in a social network to get vaccinated, which nodes should you choose?"

This project will guide students to answer this resource allocation problem through analyzing the spread transmission network and the dynamic opinion network. The project will be composed of four parts:
1. Constructing epidemic spread simulators.
2. Designing a control strategy for epidemic mitigation.
3. Developing mathematical proofs which guarantee the algorithm's performance.
4. Applying the strategy to real networks generated from online COVID data as a case study.
Students who participated in the project will learn the basics of the epidemic modeling paradigm, network science, control theory, and Python/MATLAB programming skills.

Big Data/Machine Learning, Engineering the Built Environment, Learning and Evaluation, Medical Science and Technology

• No Major Restriction

Elmore Family School of Electrical Engineering

Philip E. Paré

As illustrated with the COVID vaccines, storage and stability of medications can limit widespread availability. We are developing innovative chemical imaging tools with ultrafast pulsed lasers capable of mapping transformations within medical formulations to model and inform stability and bioavailability. Depending on the interests of the students, project scope can range from: i) bench-science in sample preparation and characterization, ii) instrument design and optical path alignment, iii) data acquisition and image analysis algorithm development, iv) partnership with collaborators in the pharmaceutical industry. We have a vibrant and diverse cohort of current researchers dedicated to fostering a supportive and collaborative research environment for all.

Big Data/Machine Learning, Biological Characterization and Imaging, Material Processing and Characterization, Medical Science and Technology

• No Major Restriction

Chemistry

Garth Simpson

The goal is to collect data non-invasively from physiological signals that can be used as indicators of disorders in the motor cortex in subjects. Additionally, we hope to relate any abnormalities in these signals back to past behaviours and experiences such as demographics (e.g. age and gender), medication and head injuries (TBI). The aim for the summer is to create and test methods for obtaining a reliable, non-invasive measure of galvanic skin response from patients as well as to obtain patient test data from Parkinson's Disease at IU Health Physicians Neurology clinic in Indianapolis.

These methods will first replicate and then test conditions important for measuring motor function and size effects. Findings will be used as pilot data for possible future research.

Big Data/Machine Learning, Medical Science and Technology

• Biomedical Engineering

Human Subject Data Collection Experience Statistics Signal Processing

Psychological Sciences

Anne Sereno

Cancer is a major threat for humans worldwide, with over 18 million new cases and 9.6 million cancer-related deaths in 2019. Although most common cancer treatments include surgery, chemotherapy, and radiotherapy, unsatisfactory cure rates require new therapeutic approaches. Recently, adoptive cellular immunotherapies with chimeric antigen receptor (CAR) engineered T and natural killer (NK) cells have shown impressive clinical responses in patients with various blood and solid cancers. However, current clinical practices are limited by the need of large numbers of healthy immune cells, resistance to gene editing, lack of in vivo persistence, and a burdensome manufacturing strategy that requires donor cell extraction, modulation, expansion, and re-introduction per each patient. The ability to generate universally histocompatible and
genetically-enhanced immune cells from continuously renewable human pluripotent stem cell (hPSC) lines offers the potential to develop a true off-the-shelf cellular immunotherapy. While functional CAR-T and NK cells have been successfully derived from hPSCs, a significant gap remains in the scalability, time-consuming (5 or more weeks), purity and robustness of the differentiation methods due to the cumbersome use of serum, and/or feeder cells, which will incur potential risk for contamination and may cause batch-dependency in the treatment. This project thus aims to develop a novel, chemically-defined platform for robust production of CAR-T and CAR-NK cells from hPSCs.

Biological Characterization and Imaging, Biological Simulation and Technology, Cellular Biology, Genetics, Medical Science and Technology

• No Major Restriction
• Chemical Engineering
• Biological Engineering - multiple concentrations
• Biochemistry
• any related major

Previous experience with cell culture and molecular biology is a bonus, but NOT required.

Davidson School of Chemical Engineering

Xiaoping Bao