As an immune-privileged site, the brain represents a particularly challenging area when it comes to controlling infection and inflammation. Toxoplasma gondii provides us with a model of a chronic infection in the CNS that represents an efficient and balanced response from the healthy immune system. The effector functions of immune cells coupled with the ability to effectively migrate to and within the brain to sites of infection is essential in controlling the replication of the parasite in the brain. Impairment of this immune response results in parasite reactivation and fatal encephalitis, as seen in AIDS patients. Immune-compromised patients are currently subject to lifelong drug therapies that do not result in cyst clearance, presenting a constant danger of reactivation. Therefore, the identification of new mechanisms of cyst control is particularly important as it may lead to new and effective therapies. This dissertation examines two novel mechanisms of parasite control in the CNS during chronic infection.

Previously published data has shown that a reticular network of fibers is present in Toxoplasma infected brains and absent in naïve brains which T cells migrate along. SPARC (secreted protein acidic and rich in cysteine) is a multifunctional glycoprotein that has been shown to be involved in the production and maintenance of similar fiber networks. Here, data will be presented demonstrating upregulation of SPARC in the brain following infection and association of this molecule with a seminal fibrous network in the CNS as well as with cysts and migrating cells. Furthermore, a requirement for SPARC in protective immunity and matrix assembly will be demonstrated in vivo, using infection studies with SPARC-null mice and live imaging in the brain.

The exact mechanisms and cells involved in the clearance and control of cysts from the brain remain poorly defined. Data presented here will demonstrate the presence of a population of alternatively activated macrophages (AAMϕ) in the infected brain that maintain control of the cyst burden through the secretion of the chitolytic enzyme, acidic mammalian chitinase (AMCase). This mechanism is demonstrated in vitro by both chemical and genetic inhibition of the enzyme and the requirement for protective immunity is shown through infection of AMCase-null mice.

These mechanisms of parasite control during chronic T. gondii infection represent two novel areas of study that provide hopeful therapeutic targets in combating this chronic infection.

Magnetism plays a significant role in the field of computing, both as a medium on which data is stored, as well a physical phenomenon by which next-generation, non-boolean computation is conducted. Most computing applications that utilize magnetism rely on ferromagnetic materials, electric current-based write methods, and steady-state excitation. While these choices have served us well up to this point, our computing needs are changing more now than ever. The need for more energy efficient computer memory, and the goal of producing powerful next-generation computing architectures like neural networks, require investigation into new magnetic materials, new methods of magnetic control, and new excitation schemes. It is the focus of this dissertation to investigate these topics in the context of three computing applications, image recognition, neuromorphic computing, and magnetic memory. Hardware solutions that are suitable for solving the quadratic optimization problems associated with image recognition are currently under development with the goal of replacing slow, expensive software algorithms. One example utilizes an array of nanomagnetic elements to solve this quadratic optimization problem, but faces an issue of array programmability. Here, dynamic application of spin-orbit torque is investigated as an energy efficient method of magnetic array programmability to enable array re-usability in this non-boolean computing architecture. In the field of neuromorphic computing, there is a need for a high-speed, energy efficient programmable synapse for use in AI systems that must adapt in real-time to continuous data streams. On this front, the utility of a multiferroic antiferromagnetic material is studied, and an upper bound on strain-mediated antiferromagnetic programming is determined. Finally, the last area focused on in this work is magnetic memory. In the current state of the art, magnetic elements with perpendicular anisotropy are switching between binary states using spin-orbit torque. This type of switching requires breaking OOP symmetry, with many mechanisms of symmetry breaking having been proposed. In this work, a symmetry breaking mechanism utilizing intrinsic material properties is studied in combination with voltage-induced strain, with the goal of reducing the dependency on electric current in magnetic memory applications.