The oceans are home to a diverse collection of animals producing intriguing materials. Mussels, barnacles, oysters, starfish, and kelp are examples of the organisms generating adhesive matrices for affixing themselves to the sea floor. Our laboratory is characterizing these biological materials, designing synthetic polymer mimics, and developing applications. Synthetic mimics of these bioadhesives begin with the chemistry learned from characterization studies and incorporate the findings into bulk polymers. For example, we are mimicking the cross-linking of DOPA-containing adhesive proteins by placing monomers with pendant catechols into various polymer backbones. Adhesion strengths of these new polymers can rival that of the cyanoacrylate “super glues.” Underwater bonding is also appreciable. Future efforts are planned in two different areas: A) Using biobased and biomimetic adhesives as the basis for making new plastic materials, such as systems like carbon fiber reinforced polymers, but with all components sourced sustainably. B) Developing new adhesive systems that function completely underwater.

Biological Characterization and Imaging, Composite Materials and Alloys, Material Processing and Characterization, Medical Science and Technology

• No Major Restriction

Chemistry

Jonathan Wilker

This project will involve developing models for coupling computational E-field dosimetry tools to neuron solvers. As part of this project students will learn to develop Finite Element Method (FEM) and neuron modeling tools. The student will implement cable model solvers for predicting response of neurons to E-fields.

Biological Simulation and Technology, Medical Science and Technology

• Electrical Engineering
• Biomedical Engineering
• Computer Engineering

Knowledge of Electromagnetics, Matlab, and ODEs is desired.

Electrical and Computer Engineering

Luis Gomez

Currently, most cancer diagnosis procedures include a diagnostic imaging process, such as a CT scan followed by a tumor biopsy. Tissue biopsy is an invasive and painful procedure and may pose health risks for patients such as those with kidney diseases. Liquid biopsy, the ability to detect and monitor disease through biofluids, is highly promising and may replace tissue biopsy with an immense potential public health impact. The use of liquid biopsy offers numerous advantages in the clinical setting, including its non-invasive nature, a suitable sample source for longitudinal disease monitoring, a better screenshot of tumor heterogeneity, and lower costs compared to tissue biopsy. Increasing evidence indicates an important cellular function of exosomes and other extracellular vesicle (EV) particles in tumor biology and metastasis, presenting them as intriguing sources for biomarker discovery and disease diagnosis. However, the vast majority of current exosome/EV studies focus on their miRNAs, with few studies on functional proteins such as phosphorylated proteins. As phosphorylation is a major player in cancer and other disease progression, EV phosphoproteins are expected to become actively pursued targets for in vitro disease diagnosis. We were the first group to demonstrate that many phosphoproteins in exosomes and microvesicles could be extracted from a small volume of biofluids, identified by high-resolution mass spectrometry (MS), and verified as potential cancer markers (Chen et al PNAS 2017). In this project, we will focus on non-invasive cancer detection by coupling CT scans with liquid biopsy to eliminate the need for surgery by more than 50%. The IU Urology team led by kidney surgeon Dr. Boris and Dr. Tao’s lab at Purdue University collaborated with prior funding have established specific biosignatures found in low- and high-grade clear cell RCC. An undergraduate student may be involved in the protein sample preparation from biofluids and tissues, maintenance of equipment, and/or bioinformatics analysis.

Big Data/Machine Learning, Biological Characterization and Imaging, Deep Learning, Medical Science and Technology, Nanotechnology

• Computer Science
• Biochemistry
• Biomedical Engineering
• Chemistry
• Biology

Certain coding skills and biostatistics are highly desirable but not required.

Biochemistry AND Chemistry

W. Andy Tao

Neurons convert biochemical information (through binding of a neurotransmitter) to electrical signal (via action potential) and back to biochemical signal (through the release of neurotransmitters). These distinct and separable processes can be reconstituted in a synthetic neuron by using natural and engineered proteins, and a synthetic neuron platform can be used to understand the rules governing the emergence of the present morphology of a neuron and the architecture of the neuronal system. This project thus aims to construct a synthetic neuron with a modular design and a programmable synthetic neuronal network capable of recapitulating basic functions of a natural neuronal system (e.g., action potential, synaptic communication, and basic computation) and with a long-term vision of incorporating more advanced computation and potentiation.

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

• No Major Restriction

GPA > 3.5, BME, ABE and CHE preferred

Davidson School of Chemical Engineering

Chongli Yuan

This project involves the analysis of motion capture data and the development of human motor learning metrics to evaluate a wearable system developed by a company sponsor. Specifically, the undergraduate role is to assist in data collection and analysis. The student must take ethics courses and training to be approved for limited participation in human research and be comfortable interacting with healthy human subjects.

Project is co-advised by Dr Laura Blumenschein and Deva Chan

Biological Characterization and Imaging, Human Factors, Learning and Evaluation, Medical Science and Technology, Other

• Biomedical Engineering
• Mechanical Engineering
• Kinesiology
• Health Science PreProfessional
• Health and Disease
• Occupational Health Science
• Rehabilitation Engineering
• Pre-physical Therapy
• Applied Exercise and Health (Pre)

Human subjects, physiology, data analysis, statistics, motor learning

Mechanical Engineering

Laura Blumenschein

Osteoarthritis affects over 32.5 million American adults, impacting mobility and quality of life, and costs over $16.5 billion in direct medical costs in hospitals within the United States. Osteoarthritis is hallmarked by degradation of the various tissues of the joint, formation of bony structures called osteophytes, and joint pain or stiffness – often in that order of progression. Knee osteoarthritis is most common among these, and approximately 1 in 8 cases of osteoarthritis are considered post-traumatic, meaning that degeneration of the tissues in the joint is precipitated from an injury, such as tearing of the anterior cruciate ligament (ACL). To model this disease process, our lab uses mechanical loading to rupture the ACL. We also use atomic force microscopy to characterize changes to the surface profile and biomechanical behavior of tissues. The student working on this project will use AFM to characterize the changes that occur in mouse articular cartilage after ACL injury.

Medical Science and Technology, Other

• Biomedical Engineering

Biomechanics, imaging and image processing, data analysis, technical writing and communication

Biomedical Engineering

Deva Chan

The goal of this Summer undergraduate research program is to develop cell-based immunotherapies for glioblastoma (GBM) with engineered natural killer (NK) cells by targeting mechanisms of immunosuppression in the tumor microenvironment. Specifically, the project is focused on engineering the immune functions of NK cells to generate CAR-NK and CRISPR KO variants of NK cells to multispecifically, via synthetic genetic circuits, interact with the tumor microenvironment and rescue NK cell activity from dysfunction. In this context, the project will characterize and optimize a multi-specific CAR-NK cell product for the treatment of glioblastoma, designed to co-target multiple elements of NK cell dysfunction in the tumor microenvironment. This project builds on the lab’s recent publication describing the very first triple-engineered NK cell platform for GBM addressing antigen escape and immunometabolic reprogramming via CD73, and will incorporate elements that reprogram the cells’ metabolic function via, among other oncometabolite and glutamine targeting. These engineered NK cells will be developed from induced pluripotent stem cells as well as peripheral blood.

The student’s role in the project will be to isolate and differentiate immune cells, characterize and learn how to effectively engineer these cells to express various multispecific constructs, learn how to manipulate NK cell activity in the context of metabolic modulation via adenosine and glutamine, and perform functional assays including cytotoxicity, degranulation and immunophenotyping.

The student will also be involved in learning some computational analysis to analyze RNAseq and CRISPR screen data. The student will learn skills incell-based immunotherapy and immunoengineering, cancer biology, cell therapy product development and formulation, synthetic biology and genetic engineering.

In terms of lab participation, the student will be involved in weekly lab meetings with the rest of the lab where they will present their findings, and in regular individual meetings with the PI. The student will be trained and mentored by a graduate student.

Cellular Biology, Medical Science and Technology

• No Major Restriction

Industrial and Physical Pharmacy

Sandro Matosevic

We are using mass spectrometry to study the localization of lipids, drugs, and proteins in biological tissues and to prepare novel functional interfaces using well-defined polyatomic ions. The student will work with a graduate student mentor to either perform nanocluster synthesis and characterization using mass spectrometry and electrochemical measurements or to develop new analytical approaches for quantitative analysis of biomolecules in biological samples. We are also developing computational approaches for connecting mass spectrometry imaging data with biochemical pathways. In both projects, the student will be trained to operate state-of-the-art mass spectrometers and perform independent data acquisition and analysis. The student will also work with scientific literature to obtain a broader understanding of the field.

Biological Characterization and Imaging, Medical Science and Technology, Nanotechnology

• No Major Restriction

general chemistry, calculus, analytical or physical chemistry

Chemistry

Julia Laskin

There is a need for testing tissues in vivo to enable the development of better diagnostic tools and treatments. Actuating on tissues under homeostatic conditions (i.e., under biologically functional conditions) is challenging due to the complex boundary conditions introduced by any device interacting with the tissue. Therefore, biological tissue testing is mostly conducted ex-vivo, implying the loss of homeostasis and capturing of less relevant material properties. An alternative approach is to develop membranes responsive to remote stimulus such as magnetic fields.
This project aims to determine the microstructure design of polymer membranes with magnetically responsive particles to actuate on biological tissues under biologically relevant conditions. Specifically, this implies optimizing the material microstructure by orienting magnetically-responsive particles across the cross-section of the membrane.

Specific tasks & deliverables
1. To familiarize with the fabrication process of polymeric membranes embedding magnetically responsive particles.
2. To fabricate and conduct mechanical tests of magnetically responsive membranes.
3. To test the adhesion properties of the developed membranes to animal skin.
4. To conduct actuation tests of membrane+skin (bilayer) patches under magnetic fields as a function of particle orientation.
5. Documentation of the fabrication process, adhesion tests, and magnetic actuation results. Production of a final report, compatible with further presentation as a poster or student paper.

Special project outcomes
1. Familiarization with fabrication of magnetically-responsive materials.
2. Replicate material testing protocols for the adhesion and in-plane stretching response of polymeric membranes.
3. Familiarization with magnetic actuation of bilayer membranes.
4. Familiarization with testing of biological tissues.

Biological Characterization and Imaging, Fabrication and Robotics, Material Processing and Characterization, Medical Science and Technology

• Biomedical Engineering
• Mechanical Engineering
• Materials Engineering

Desirable experience: Material characterization, prior experimental work on polymers

Mechanical Engineering

Adrian Buganza Tepole

The goal of the project is to design low-cost and user-friendly paper-based point-of-care (POC) diagnostics tests for the detection of a panel of infectious diseases.
These student will be involved directly in the research related to the fabrication and testing of these point-of-care technologies, designed to allow for sensitive, rapid, and repeatable multiplexed detection of a variety of food and waterborne pathogens with high precision and accuracy and minimal sample handling. Target pathogens include parasites such as P. falciparum, (malaria), and Cyclospora Cayetanensis (found in agricultural water that severely lacks detection technologies), along with bacteria-induced foodborne and waterborne infectious diseases such as E. Coli O157:H7, S. Typhimurium, Listeria spp. and Campylobacter Jejuni. These will be aptamer-enabled biosensors, which will be further amenable for the rapid and low cost detection of other diseases, such as inflammation marker panels for Troponin, CRP, IL-6, and TNF-α. Aptamers are DNA molecules with high stability, high affinity for both small molecules and whole-cell pathogens, and are robust when exposed to harsh environments.

The main biorecognition element for the detection of these whole-cell pathogens, responsible for infectious diseases of interest, will be aptamers, which will allow for whole-cell pathogen detection, without amplification or cell lysis. Blood serum samples will be loaded in the sample well, and will diffuse to the four testing areas, each labeled for one individual pathogen. The initially negative testing areas will display a pink color. A positive test for one of the pathogens will be recognized by a change of color from pink to purple. A 3D printed portable imaging box, equipped with an image capture system and embedded color recognition and analysis software will allow for images of the test strips to be taken at constant illumination, on site, at primary care clinics or anywhere at the patient’s home, regardless of time of the day and natural illumination conditions. The portable imaging device will be able to display the test results on the screen. Thus, the detection limit of the diagnostic devices will be pushed down to levels beyond the ones possible with the naked eye, considering the limitation of human vision performance, especially at low illumination levels. A negative test for one pathogen will display an unchanged pink color of the corresponding testing area. We will optimize the device that has already been demonstrated in preliminary work in Stanciu’s group for food samples for E. Coli O157:H7, Listeria monocytogenesis and Salmonella typhimurium, to serum samples for the four pathogens of interests. Ultimately, the project's objective is to establish device performance (detection limit, linear range) .

Chemical Catalysis and Synthesis, Internet of Things (IoT), Medical Science and Technology, Nanotechnology, System-on-a-Chip

• No Major Restriction

General chemistry or biochemistry laboratory training.

Materials Engineering

Lia Stanciu

There is a critical need for therapies to reduce tumor burden and promote bone repair in patients suffering from bone-metastatic prostate cancer, which affects thousands of IN residents each year. This project focuses on the development and evaluation of a novel nanoparticle formulation of cabozantinib (Cabo), a potent kinase inhibitor chemotherapeutic drug. Cabo is a poorly water-soluble small molecule drug that cannot be dosed intravenously and exhibits low bioavailability when administered orally.
We hypothesize that formulating Cabo into a fast-dissolving organic nanoparticle will improve its dissolution kinetics and oral bioavailability. This in turn is expected to translate to higher efficacy against bone-metastatic prostate tumors in vivo. To test this, the student will design Cabo nanoparticle formulations using the Ristroph lab’s scalable Flash NanoPrecipitation technology and demonstrate improved dissolution kinetics in vitro compared to crystalline drug. This will be the focus of the SURF project. If successful, we will then evaluate the efficacy of the best-performing Cabo nanoformulation in vivo in Prof. Marxa Figueiredo's lab, which has expertise with Cabo and has developed a bone metastatic model of prostate cancer.

Ingrid will prepare nanoparticles containing Cabo using Flash NanoPrecipitation, following standard methods. She will assess nanoparticle formulations in vitro for diameter and polydispersity, surface charge, stability over time, and Cabo dissolution rate using dynamic light scattering and HPLC. Milestones and expected outcomes include (1) the development a nanoparticle formulation with >95% Cabo encapsulation efficiency, >50% drug loading, and stability for >1 week (ETM: 5 weeks); (2) the demonstration of >80% Cabo dissolution within 3h in simulated intestinal fluid (ETM: 5 weeks); and (3) the preparation of sufficient material to support the efficacy study in mice (out of scope for the SURF project; I plan to hire Ingrid as an undergraduate researcher in the fall to continue this project).

Medical Science and Technology, Nanotechnology

• Chemical Engineering
• Biomedical Engineering
• Biological Engineering - multiple concentrations
• Biomedical Engineering
• Pharmacy

ABE

Kurt Ristroph

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. The students recruited will help to engineer stem cells with gene editing tools, differentiate stem cells into immune cells, and perform molecular and cellular assays to characterize the cells.

Cellular Biology, Medical Science and Technology

• No Major Restriction
• Chemical Engineering
• Biological Engineering - multiple concentrations
• Cell Molecular and Developmental Biology
• Biomedical Engineering

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

Davidson School of Chemical Engineering

Xiaoping Bao

Two projects are available. One involves the investigation of enhancing optical imaging resolution using single photon counting techniques. Conventional optical imaging has a hard limit on its spatial resolution, to about one half of the wavelength, and many situations can benefit from higher resolution. In addition, it is challenging to image through scattering media. By way of example, being able to sense with light deeper in the brain would be of enormous benefit in neuroscience. The statistics of photons emitted by or transmitted through an object contain valuable information about the object which could be used to enhance image resolution and possibly see through substantial background scatter. Experiments will be conducted using laser light and with a set of single photon avalanche detectors (SPADs) to measure photon correlations in time, over wavevector (direction), and between detectors in various imaging configurations. Results from these experiments will be used to assess the effectiveness of various techniques for enhancing spatial resolution in imaging applications. This work has a diverse set of potential applications including biological imaging, sensing defects in semiconductors, and imaging through fog. The other project relates to experimental work and the modeling of optical forces on structured membranes induced by a laser. The mechanical motion of a thin membrane deflected by laser light will be used to determine the membrane properties from experimental and simulated data. This will allow extraction of the mechanical material properties and more generally the validation of a theory for optomechanics that can then be used in design. The nascent field of optomechanics offers enormous impact scope, including remote actuation and propulsion, of importance in fields as diverse and molecular biology, communication, and transport. This project relates to attaining the underpinnings to move along such paths in engineering, as well as the basic physics of optical forces in material at small length scales.

Big Data/Machine Learning, Biological Characterization and Imaging, Biological Simulation and Technology, Composite Materials and Alloys, Deep Learning, Material Processing and Characterization, Medical Science and Technology, Nanotechnology

• Electrical Engineering
• Mechanical Engineering
• Physics
• Biomedical Engineering

Students with an interest in experimental or modeling work and some background in electromagnetics would be a good fit for this project. The undergraduate student will work with graduate students to perform experiments in an optics laboratory, modeling, data analysis using MATLAB or python, and review relevant literature.

Electrical Engineering

Kevin Webb

The goal of this project is to develop precision learning intervention technology that leverages semantic network science to support early language learning and early intervention for developmental language disorder (DLD). DLD affects approximately 7% of the population, and results in lifelong risks for poor biomedical, educational, and professional outcomes, leading to tremendous costs to individuals and society. Our group seeks to combine recent theoretical and technical advances to develop methods for early identification and intervention of this common, yet understudied condition. Student will participate in coding / development of automated tools that tune early language learning targets according to the knowledge of the learner and will help pilot and assess efficacy of different intervention approaches. Student will work with senior members of the lab (postdocs and lab manager) to develop and acquire data to support the submission of a larger grant application in the Fall.

Big Data/Machine Learning, Medical Science and Technology, Other

• No Major Restriction

Preferred qualifications include: proficiency in R and/or Python, familiarity with Gitlab, exposure to or interest in learning about network science, and an interest in using remote technology to create engaging and effective early learning interventions in children under the age of 5.

SLHS

Arielle Borovsky