Background. Memory consolidation occurs during sleep, providing an opportunity to enhance upper extremity (UE) function in people with residual impairments post-stroke. Targeted memory reactivation (TMR) has been used to enhance this process, which involves pairing auditory cues with task performance and subsequent cue replay during sleep. TMR application during sleep leads to increased task-related brain network connectivity and behavioral performance in healthy young adults. Yet it remains unknown whether TMR can enhance sensorimotor performance in individuals with stroke. Methods. Healthy younger and older adults and individuals with chronic stroke were trained on a non-dominant (or non-paretic) UE throwing task before a period of waking or sleeping consolidation, with some receiving TMR throughout the consolidation period. Study 1 involved the use of TMR throughout the first two slow wave sleep periods over a full night of sleep with young adults. Studies 2, 3, and 4 investigated whether TMR throughout a one-hour nap was sufficient to influence sensorimotor performance in young adults, older adults, and people with a history of stroke, respectively. Results. All studies found that TMR application during sleep enhanced sensorimotor performance. In addition, TMR during wake did not influence sensorimotor performance (Studies 1 and 2), and enhanced performance of a cognitive aspect of the trained task (Study 2). Additional generalization and transfer tests helped to support the hypothesis that TMR enhanced a task-specific motor program, as improvements were seen within the trained task but not un-trained, but similar tasks. Lastly, sleep alone appears to stabilize sensorimotor performance variability, but this process demonstrates an age-related decline. Conclusion. This dissertation has shown that the use of TMR during sleep is a useful method for enhancing sensorimotor performance in healthy young and old adults, as well as individuals with a history of stroke. Future research may lead to an adjunct to traditional physical rehabilitation protocols.

In the study of learning and decision-making in animals and humans, the field of Reinforcement Learning (RL) offers powerful ideas and tools for exploring the control mechanisms that underlie behavior. In this dissertation, we use RL to examine the questions of (i) how rats represent information about a complex, changing, task; (ii) what are the relevant variables underlying their decision-making processes; and (iii) whether those variables are encoded in the firing rates of neurons in the orbitofrontal cortex (OFC). We addressed these questions by making inquiries across three levels of understanding: computational theory, algorithmic representation, and physical implementation. Within this tri-level framework, we hypothesize that the subjects are engaged in a form of approximately optimal adaptive control. This involves their tracking critical, task-relevant, features of their environment as these features change, and then making appropriate choices accordingly. Two classes of RL algorithms were constructed, embodying different structural assumptions. One class of so-called return-based algorithms is based on elaborations of a standard Q-learning algorithm. The other, novel, class of income-based algorithms is based on a rather weaker notion of action-outcome contingency. Both classes of algorithm were parametrized and other factors were included such as perseveration. We t the algorithms to behavioral data from subjects using complexity-controlled empirical Bayesian inference. Internal variables from our algorithms were then used to predict neural ring rates of OFC neurons that were recorded as subjects performed the task. Linear regression, randomization testing, and false discovery rate analysis were used to determine statistically significant correlations between the predictors and neural activity. We found that income-class algorithms augmented with perseveration offered the best predictions of behavior. For the least restrictive statistical test (linear regression, p < 0.05), as many as 24% of the neurons were significantly correlated with variables associated with the best-fitting algorithm. By contrast, for our most restrictive test (randomized false discovery rate < 0.05), only 3% of the neurons passed as significant for one or more of our predictor variables. Other forms of neuronal dependence were apparent, including neurons that appeared to change their computational function dynamically depending on the state of the task.

Molecular dynamics (MD) simulations have been widely applied to study biomolecular systems. While MD simulations have been used in a variety of applications, the accuracy of the results depends strongly on the force field (FF) used. The commonly used FFs are additive or non-polarizable FFs. However, one limitation of the additive FFs is the lack of electronic polarizability to treat molecules. To overcome this, an attractive approach is to introduce the explicit treatment of electronic polarizability into the potential energy function known as polarizable FFs. In Chapter 1, an overview of the CHARMM empirical FF as well as the development and application of the polarizable CHARMM FF based on the classical Drude oscillator is presented. As noncovalent halogen bonding interactions between halogenated ligands and proteins are important in drug design, a well-parametrized polarizable FF for halogen containing compounds is required to perform more accurate modeling of halogenated molecules. During the course of this development, a significant contribution of halogen-hydrogen bond donor (X-HBD) interactions to ligand-protein complexes was uncovered in addition to halogen bond (XB) interactions (Chapter 2). In Chapter 3, the development of halogen polarizable FF to both aliphatic and aromatic systems using halogenated ethane and benzene model compounds is illustrated, with emphasis on optimizing both X-HBD and XB interactions as discussed in Chapter 2. To assure good reproduction of X-HBD interactions with proteins, further optimization of atom pair-specific Lennard-Jones (LJ) parameters is required for both the polarizable and non-polarizable halogen FFs (Chapter 4). Finally, Chapter 5 presents the current optimization of polarizable protein FF to yield a more accurate description of the polarization response in simulations. The resulting protein FF, referred to as Drude-2019, will be more applicable in the study of biomolecular systems. Overall, the advances made in this dissertation will facilitate important discoveries of a range of chemical and biological phenomena.

A protective immune response requires naïve CD8+ T cells to differentiate into effector cells, some of which persist as a memory population to protect against future threats. This differentiation program is controlled by a transcriptional network involving the T-box transcription factors T-bet and Eomesodermin (Eomes). These factors are in turn differentially regulated by cytokines in the local milieu. The precise architecture of this regulatory network in terms of the individual, synergistic and redundant roles of T-bet, Eomes and critical cytokines is still poorly understood. Here we sought to clarify these regulatory pathways, using mice deficient in T-bet, Eomes or both. Our studies identify a key role for Eomes, but not T-bet, in regulating IL-10 expression by CD8+ T cells early after activation. We further reveal a feedback loop where Eomes and IL-10 cooperatively enhance the expression of the lymph-node homing selectin CD62L. Consistent with the importance of CD62L in promoting memory T cell homing to secondary lymphoid organs (SLOs), we identify a role for CD8+ T cell-intrinsic IL-10 in promoting the long-term persistence of memory cells in vivo. In contrast, T cells that home away from the SLOs become terminal effector T cells. Using tumor and infectious disease models, we report that these cells experience a second wave of T-bet induction in the tissue, which may contribute to a heightened effector response. We also define distinct roles for T-bet and Eomes in regulating effector and memory genes, highlighting their redundant role in repressing Tc2 and Tc17 differentiation in CD8+ T cells. Finally, we demonstrate that in the context of a tumor-specific immune response, the absence of both T-box transcription factors severely limits tumor infiltration without significant alteration in early proliferation or effector functions. Taken together, these findings offer new insights into how T-bet, Eomes and IL-10 regulate effector and memory responses in distinct tissues during the immune response. Future developments targeting individual aspects of T-box and cytokine signaling in T cells may help engineer precise outcomes in the context of tumor immunotherapies, vaccination and transplantation.

Ovarian cancer is the leading cause of death among gynecological cancers in the United States. Ovarian cancer employs a unique mode of metastasis, as tumor cells disseminate within the peritoneal cavity, colonizing in several sites and driving the accumulation of ascites. Tumor recurrence and metastasis are significant factors contributing to poor prognosis. The membrane-anchored serine protease testisin is aberrantly expressed in ovarian tumors and it’s only known substrate, protease activated receptor-2 (PAR-2), is also overexpressed in ovarian tumors. In this study I have examined 1) the role of testisin and PAR-2 signaling in ovarian tumor metastasis and 2) determined whether testisin and other membrane-anchored serine proteases may be anti-cancer therapeutic targets. We generated human ovarian ES-2 tumor lines that express testisin or the catalytically inactive testisin mutant S238A and explored the role of constitutive testisin expression in late stage ovarian cancer. We show that testisin stimulates the activation and internalization of PAR-2 resulting in decreased expression of ANG2 and ANGPTL4. Using a preclinical xenograft model of late stage ovarian cancer, we find that testisin activity in ovarian cancer cells reduces intra-peritoneal tumor dissemination, tumor burden and ascites formation. Analyses of the tumors showed that testisin activity downregulates the expression of ANG2 and ANGPTL4 in vivo as well as in vitro. To examine membrane-anchored serine proteases as therapeutic targets in cancer, we utilized an engineered anthrax toxin pro-drug strategy requiring proteolytic cleavage of a protective antigen (PrAg) for activation. We explored the efficacy of these engineered PrAg toxins in several intraperitoneal models of ovarian cancer metastasis and show PrAg treatment reduced tumor burden in both an intraperitoneal NCI/ADR-Res xenograft and an ES-2 minimal residual disease model, which replicates debulking surgery in ovarian cancer patients, but had no effect in a syngeneic ID-8-Luc xenograft model of ovarian cancer. Additionally, we found that engineered PrAg toxins are capable of inducing lung and pancreatic cancer cellular death in vitro. Data presented herein provide new insight into the potential role of testisin and PAR-2 signaling in ovarian cancer metastasis and suggests membrane-anchored serine proteases as a potential therapeutic target for metastatic ovarian cancer.

Globally, vector-borne diseases account for 17% of all infectious diseases. Most vectors are blood-feeding arthropods, which transmit bacterial, viral, and parasitic diseases to humans and animals. The tick Ixodes scapularis transmits seven pathogens, including Borrelia burgdorferi, the agent of Lyme disease. Lyme disease is the most important vector-borne disease in the United States and causes an estimated 329,000 infections annually. Best described in the model organism Drosophila melanogaster, the arthropod immune deficiency (IMD) pathway responds to microbial infection through activation of Relish, a nuclear factor (NF)-κB family transcription factor. In I. scapularis ticks, the E3 ubiquitin ligase X-linked inhibitor of apoptosis (XIAP) regulates the IMD pathway through ubiquitylation. Yet, the tick genome notably lacks homologs to genes encoding key IMD pathway proteins as described in Drosophila. How XIAP activates the IMD pathway in response to microbial infection is poorly characterized and targets of XIAP-mediated ubiquitylation remain unknown. In this study, we identified the XIAP enzymatic substrate p47 as a positive regulator of the I. scapularis IMD network. XIAP polyubiquitylates p47 in a lysine (K)63-dependent manner and interacts with the ubiquitin-like (UBX) domain of p47. p47 also binds to Kenny (IKKγ/NF-κB essential modulator [NEMO]), the regulatory subunit of the inhibitor of NF-κB kinase (IKK) complex. Replacement of the amino acid lysine with arginine in the p47 linker region completely abrogated molecular interactions with Kenny. Furthermore, reduction of p47 transcription levels through RNA interference in I. scapularis limited Kenny accumulation, reduced phosphorylation of IKKβ (IRD5), and impaired cleavage of the NF-κB molecule Relish. Accordingly, disruption of p47 expression increased microbial colonization of the tick-transmitted spirochete B. burgdorferi and the rickettsial agent Anaplasma phagocytophilum. In summary, we demonstrated that XIAP ubiquitylates p47 in a K63-dependent manner, culminating in Relish activation and antimicrobial responses. Manipulating immune signaling cascades in I. scapularis may lead to innovative approaches to reducing the burden of tick-borne diseases.