Tissue Engineering

Despite recent developments enabling the fabrication of engineered tissue constructs with controllable microarchitecture and macroscopic geometry, few engineered tissue products are currently on the market. This is, in part, due to the need for proper conditions for the cell dependent process of tissue maturation, especially in larger constructs. It has been established that chemical and mechanical environmental stimuli influence cell behavior. There remains a need to understand the impact of flow field modulation on the organization of cell populations in large tissue engineering (TE) constructs. In this project we are tracking the real-time response of cell populations cultured in thick 3D scaffolds to flow patterns modulated in time and space. This is achieved using a perfusion bioreactor (shown below) capable of generating and controlling arbitrary flow patterns over tissue length scales --- while compensating for changes in scaffold permeability --- and while monitoring cell density and viability using real-time feedback from magnetic resonance imaging (MRI). The combination of flow field control and non-invasive tissue culture (TC) monitoring allows cell population dynamics to be examined under spatiotemporally complex flow patterns at all times. Our group has had to develop MRI techniques for noninvasive 3D cell density and cell viability assays, as well as AI-based optimal control algorithms for reactor design and real-time flow field control. Applications to ischemia are of interest to us.

Magnetic Contrast Agents

Magnetic resonance imaging (MRI) generates images by detecting nuclear magnetic signals from water molecules. However, its sensitivity is inherently low. To circumvent this limitation, contrast agents were developed to improve the image contrast and highlight differences between normal and diseased tissue. MRI contrast agents typically work by enhancing the relaxation times (T1, T2) of nearby water molecules. However, gadolinium (Gd)-based commercial contrast agents have low per-particle (or per-molecule) relaxivity, requiring fairly large (millimolar) concentrations of particles injected to observe signal enhancement, raising toxicity concerns. The objective of this project is to address the need for less toxic contrast agents by developing Fe-based nanocrystalline contrast agents, with optimized atomic and phase content, possessing much higher relaxivity. Our previous results have shown that pure, oxide-free Gd metal cores fabricated using nanosphere lithography result in much higher magnetization, and therefore, substantially improved MRI relaxation-time enhancement, enabling detection at picomolar levels. This level of sensitivity is unprecedented. To reduce toxicity, we are developing Fe cores in oxide-free (reduced) form, capped to prevent oxidation. Fe contrast agents will have better magnetic properties than Gd at room temperature. We have developed nanofabrication processes (shown below) that result in the strongest magnetic particles possible. Stronger magnetism yields: 1) better MRI contrast, 2) lower injected doses for the same contrast, 3) lower dose means reduced toxicity. Research projects currently focus on translating to the clinic and exploring strategies for surface modification and targeting. Our recent work has combined multiple functionalities inside a single probe, such as MRI detection (proton and xenon-based detection), optical detection, photodynamic therapy, redox therapy and drug delivery.

Condensed Matter NMR

Topological insulators (TI) are narrowgap semiconductors made of heavy elements with strong spin-orbit coupling (SOC) giving rise to a quantum spin Hall state where the bulk is insulating and the surface is conducting. The surface electrons are topologically protected and backscattering is reduced leading to greater electronic mobility. Furthermore, linear momentum of the election (k) is locked to its spin (s). Spin-momentum locking endows them with potential uses in spintronic devices. Magnetic doping of the TIs can also lead to exotic physics, such as the quantum anomalous Hall effect and axion electrodynamics. Standard methods of characterization of TIs include transport (Shubnikov de Haas oscillations) as well as ARPES (angle-resolved photo-electron spectroscopy). Such measurements require high quality samples, and typically n-type conductivity. For p-type semiconductors we have been developing NMR methods. NMR, which probes electronic density of states at the Fermi level, also works with lower quality, and non-crystalline or amorphous materials, thereby potentially enlarging the class of TI materials that can be studied. Our group has carried out the first NMR studies of topological insulators (TI) and topological crystalline insulators (TCI). With NMR both the bulk and surfaces of these materials can be probed. For surface states, we used the beta-detected NMR (ß-NMR) method developed at TRIUMF (Vancouver, Canada). A beam of 8Li+ ions is decelerated to a desired energy, implanted into the material, and the NMR properties of the ions' nuclei are recorded as function of temperature, field strength and beam energy. Low energies lead to shallow implantation, providing a method to prove the surface states. Our studies have unveiled band inversion mechanisms in TCIs, Curie's Law in nanoscale surface layers, superconductivity mechanisms and the role of bulk defects on the material's properties. This project aims at further developing these NMR methodologies to the study of interesting and emerging topological materials.

Biological Sensing

Cells sense and respond to stimuli to maintain homeostasis and drive the evolution of transduction mechanisms. Signaling relies on dynamic protein macro-assemblies and networks that receive, transmit and modulate information from sensors to response elements. Cell signaling pathways are made of modular protein domains that mediate protein-protein interactions. Interacting proteins form signaling assemblies such as G-protein-coupled receptor-receptor tyrosine kinases (GPCR-RTK) that yield differential responses in different cell types. Controlled modulation of GPCR-RTK complexes and cellular signaling could enable manipulation of biological processes on-demand by accessing their native control systems. The field of optogenetics (over 27,400 search results in Google scholar) has been developing tools to control biological processes using light. Light control schemes may leverage multiple degrees of freedom such as temporal or spatial modulation, coherence, wavelength, power and polarization. However, the reliance on genetics is an obstacle to medical translation. Currently, genome modification is performed by either transient or stable delivery of nucleic acids that encode genome modifying components to target cells. This nucleic-acid-based approach has a number of drawbacks, including low efficiency, toxicity, prolonged expression, off target effects, and potential delay in modification due to transcription and translation post-delivery. Our group develops nanodiamond (ND)-based strategies for sensing and interacting with biological cells. NDs are biocompatible (non-cytotoxic and don't photobleach), can be targeted to specific macromolecular assemblies, and can be used for protein and drug delivery. Furthermore, they can be used for magnetic-, electric-field and temperature sensing at the nanoscale, meaning that a readout of the local ND environment is possible. In this project we develop nanoprobes for biological sensing and controlling cell function.

Operando Methods in Catalysis

Over 85% of all chemical industry products are made using catalysts, with the overwhelming majority of these employing heterogeneous catalysts functioning at the gas-solid interface. Consequently, optimizing catalytic reactor design attracts much effort. Such optimization relies on heat transfer and fluid dynamics modeling coupled to surface reaction kinetics. The complexity of these systems demands many approximations, which can only be tested with experimental observations of quantities such as temperature, pressure, concentrations, flow rates, etc. One essential measurement is a map of the spatial variation in temperature throughout the catalyst bed, not only because accurate control of temperature is required for optimal operation, but also because temperature gradients in the reacting fluid reveal the energetics of a reaction in the presence of flow. Our group develops imaging methods to probe the properties of reacting fluids in situ and in real-time. For example, we have developed the first non-invasive maps of gas temperatures in catalyst-filled reactors, including high spatial resolution maps in microreactors enabled by parahydrogen. By exploiting the motional averaging under a weak applied magnetic-field gradient, the NMR linewidths are inversely related to temperature. This technique provides a non-invasive tool to locate hot and cold spots in catalyst-packed reactors, offering unique capabilities for testing the approximations used in reactor modeling. The unexpected temperature dependence of the linewidth in gases has led to new models for the NMR signal in the presence of field gradients. Namely, we can now probe unique aspects of gas self-diffusion, such as non-Markovian effects. This project is a roughly equal mix of theory and experiments, presently aimed at modeling diffusion in the presence of boundaries.

Parahydrogen-Induced Polarization

MRI has excellent soft tissue contrast and resolution (~0.1-1 mm), but is sensitivity-limited to imaging water protons. Such images do not contain chemical information and are of limited value for early stage disease detection. Molecular imaging (MI) capabilities would be desirable. Chemical-shift MRI suffers from sensitivity issues preventing the detection of tracer concentrations (far below the mM level) in vivo. Substantial signal enhancement by up to 4 orders of magnitude by hyperpolarization methods could enable detection of µM concentrations of exogenous probe after injection. The method of parahydrogen-induced polarization (PHIP) can lead to such signal enhancements at a fraction of the cost of competing methods such as DNP (dynamic nuclear polarization). However, PHIP lacks useful contrast agents (CA). Our group is developing MRI contrast agents polarizable by PHIP that yield molecular-level information about binding and metabolism. Another effort in our group is the development of water-soluble heterogeneous catalysts for PHIP (HET-PHIP). For clinical translation both the molecular probe and catalyst must result in a biocompatible product that can be injected. The importance of heterogeneous catalyst stems from the ability to remove them from solution thereby mitigating toxicity issues. . Recent heterogeneous catalyst development has produced high polarization in water using parahydrogen with biologically relevant contrast agents. We recently introduced a novel heterogeneous ligand-stabilized Rh catalyst capable of achieving ¹⁵N polarization of 12.2 ± 2.7% by hydrogenation of neurine into a choline derivative. This is the highest ¹⁵N polarization of any parahydrogen method in water to date. Notably, this was performed using a deuterated quaternary amine with an exceptionally long spin-lattice relaxation time (T₁) of 21.0 ± 0.4 minutes. These results open the door to the possibility of ¹⁵N in vivo imaging using nontoxic similar model systems because of the biocompatibility of the production media and the stability of the heterogeneous catalyst using PHIP as the hyperpolarization method.

Machine Learning

Our group develops algorithms for distributed and accelerated learning. Distributed learning is useful in embedded device applications and in federated learning. Hierarchical neural networks have been developed that can be trained on independent servers that do not communicate with each other. Such situations may be imposed for many reasons, for example, data privacy. Another application is large-scale deep learning across computer nodes. While this project is mostly theoretical and computational, there exist opportunities to incorporate experimental design. We have applied our new algorithms to the solution of inverse problem in fluid dynamics, radiofrequency spectrum management, and radar target identification and landslide susceptibility assessment (some of these are collaborative projects with other groups). Students with theoretical and computational abilities are welcome to inquire about this project with the PI.

Quantum Computing

This project has both experimental and theoretical components. On the experimental side, we are developing new solid state qubits in silicon with potential for room-temperature operation. On the theoretical side we are developing strategies for quantum control that are based on extended algebras, global optimization and machine learning. Contact PI for more information on these research directions.

Immuno-Engineering

T-cell immunotherapy is a promising approach for cancer, infection, and autoimmune diseases. However, significant challenges hamper its therapeutic potential, including insufficient activation, delivery, and clonal expansion of T-cells into the tumor environment. Our team is devoted to addressing these issues by understanding and improving T cell-antigen presenting cell (APC) interactions. As the first step towards better in vitro activation and expansion of T-cells we have developed core–shell microparticles for sustained delivery of cytokines. The controlled delivery of cytokines is used to steer lineage specification of cultured T-cells. This approach enables differentiation of T-cells into central memory and effector memory subsets. It is found that CD8+ T-cells that received IL-2 from microparticles are more likely to gain effector functions as compared with traditional administration of IL-2. Moreover, we have shown that culture of T-cells within 3D scaffolds that contain IL-2-secreting microparticles enhances proliferation as compared with traditional, 2D approaches. This yields a new method to control the fate of T-cells and ultimately to new strategies for immune therapy. Since it is known that T cell receptors (TCRs) are mechanosensory, we have shown that T cells can recognize forces arising from the mechanical rigidity of their microenvironment. We fabricated 3D scaffold matrices with mechanical stiffness tuned to the range 4–40 kPa and engineered them to be microporous, independently of stiffness. We cultured T cells and antigen presenting cells within the matrices and studied T-cell activation by flow cytometry and live-cell imaging. We found that there was an augmentation of T-cell activation, proliferation, and migration speed in the context of mechanically stiffer 3D matrices as compared to softer materials. These results show that T cells can sense their 3D mechanical environment and alter both their potential for activation and their effector responses in different mechanical environments. A 3D scaffold of tunable stiffness and consistent micro-porosity offers a biomaterial advancement for both translational applications and reductionist studies on the impact of tissue micro-environmental factors on cellular behavior. Followed by the optimization of our T cell activation and expansion platform in vitro we then sought to optimize our 3D scaffold in the in vivo mouse melanoma model. To be able to offer a platform that supports and enhances T cell activation our team decorated the optimized 3D platforms with required signals for recruitment, activation, and proliferation of endogenous T cells around the tumor microenvironment. Moreover, since one of the major roadblocks in most solid tumors is the abundance of regulatory T cells (Tregs) in tumor microenvironment, we embedded nanoparticles within our scaffolds that release inhibitory molecules which block the formation of Tregs and allow for the CD8+ T cells to have a higher chance of winning the war against cancer cells. The platform that we developed proved to be highly successful in suppressing tumor formation in the super aggressive mouse B16-F10 melanoma model. This implantable 3D platform synergizes with CAR-T therapies and systemic immunomodulatory therapies, and thus in combination these approaches offer the potential to radically rewrite the punitive rules of solid tumors.