Immunity and Arginine Deprivation in Alzheimer's Disease

The pathogenesis of Alzheimer’s disease (AD) is a critical unsolved question, and while recent studies have demonstrated a strong association between altered brain immune responses and disease progression, the mechanistic cause of neuronal dysfunction and death is unknown. We have previously described the unique CVN-AD mouse model of AD, in which immune-mediated nitric oxide is lowered to mimic human levels, resulting in a mouse model that demonstrates the cardinal features of AD, including amyloid deposition, hyperphosphorylated and aggregated tau, behavioral changes and age-dependent hippocampal neuronal loss. Using this mouse model, we studied longitudinal changes in brain immunity in relation to neuronal loss and, contrary to the predominant view that AD pathology is driven by pro-inflammatory factors, we find that the pathology in CVN-AD mice is driven by local immune suppression. Areas of hippocampal neuronal death are associated with the presence of immunosuppressive CD11c+ microglia and extracellular arginase, resulting in arginine catabolism and reduced levels of total brain arginine. Pharmacologic disruption of the arginine utilization pathway by an inhibitor of arginase and ornithine decarboxylase protected the mice from AD-like pathology and significantly decreased CD11c expression. Our findings strongly implicate local immune-mediated amino acid catabolism as a novel and potentially critical mechanism mediating the age-dependent and regional loss of neurons in humans with AD.

There is a large interest in identifying, lineage tracing, and determining the physiologic roles of monophagocytes in Alzheimer’s disease. While Cx3cr1 knock-in fluorescent reporting and Cre expressing mice have been critical for studying neuroimmunology, mice that are homozygous null or hemizygous for CX3CR1 have perturbed neural development and immune responses. There is, therefore, a need for similar tools in which mice are CX3CR1+/+. Here, we describe a mouse where Cre is driven by the Cx3cr1 promoter on a bacterial artificial chromosome (BAC) transgene (Cx3cr1-CreBT) and the Cx3cr1 locus is unperturbed. Similarly to Cx3cr1-Cre knock-in mice, these mice express Cre in Ly6C-, but not Ly6C+, monocytes and tissue macrophages, including microglia. These mice represent a novel tool that maintains the Cx3cr1 locus while allowing for selective gene targeting in monocytes and tissue macrophages.

The study of immunity in Alzheimer’s requires the ability to identify and quantify specific immune cell subsets by flow cytometry. While it is possible to identify lymphocyte subsets based on cell lineage-specific markers, the lack of such markers in brain myeloid cell subsets has prevented the study of monocytes, macrophages and dendritic cells. By improving on tissue homogenization, we present a comprehensive protocol for flow cytometric analysis, that allows for the identification of several cell types that have not been previously identified by flow cytometry. These cell types include F4/80hi macrophages, which may be meningeal macrophages, IA/IE+ macrophages, which may represent perivascular macrophages, and dendritic cells. The identification of these cell types now allows for their study by flow cytometry in homeostasis and disease.

Participatory Methods for Climate Change and Mental Health Research: Photovoice in Nepal

Background: The relationship between mental health and climate change are poorly understood. Participatory methods represent ethical, feasible, and culturally-appropriate approaches to engage community members for mental health promotion in the context of climate change. Aim: Photovoice, a community-based participatory research methodology uses images as a tool to deconstruct problems by posing meaningful questions in a community to find actionable solutions. This community-enhancing technique was used to elicit experiences of climate change among women in rural Nepal and the association of climate change with mental health. Subjects and methods: Mixed-methods, including in-depth interviews and self-report questionnaires, were used to evaluate the experience of 10 women participating in photovoice. Quantitative tools included Nepali versions of Beck Depression Inventory (BDI) and Beck Anxiety Inventory (BAI) and a resilience scale. Results: In qualitative interviews after photovoice, women reported climate change adaptation and behavior change strategies including environmental knowledge-sharing, group mobilization, and increased hygiene practices. Women also reported beneficial effects for mental health. The mean BDI score prior to photovoice was 23.20 (SD=9.00) and two weeks after completion of photovoice, the mean BDI score was 7.40 (SD=7.93), paired t-test = 8.02, p<.001, n=10. Conclusion: Photovoice, as a participatory method, has potential to inform resources, adaptive strategies and potential interventions to for climate change and mental health.

Active Surface Deformation Technology for Management of Marine Biofouling

Biofouling, the accumulation of biomolecules, cells, organisms and their deposits on submerged and implanted surfaces, is a ubiquitous problem across various human endeavors including maritime operations, medicine, food industries and biotechnology. Since several decades, there have been substantial research efforts towards developing various types of antifouling and fouling release approaches to control bioaccumulation on man-made surfaces. In this work we hypothesized, investigated and developed dynamic change of the surface area and topology of elastomers as a general approach for biofouling management. Further, we combined dynamic surface deformation of elastomers with other existing antifouling and fouling-release approaches to develop multifunctional, pro-active biofouling control strategies.

This research work was focused on developing fundamental, new and environment-friendly approaches for biofouling management with emphasis on marine model systems and applications, but which also provided fundamental insights into the control of infectious biofilms on biomedical devices. We used different methods (mechanical stretching, electrical-actuation and pneumatic-actuation) to generate dynamic deformation of elastomer surfaces. Our initial studies showed that dynamic surface deformation methods are effective in detaching laboratory grown bacterial biofilms and barnacles. Further systematic studies revealed that a threshold critical surface strain is required to debond a biofilm from the surface, and this critical strain is dependent on the biofilm mechanical properties including adhesion energy, thickness and modulus. To test the dynamic surface deformation approach in natural environment, we conducted field studies (at Beaufort, NC) in natural seawater using pneumatic-actuation of silicone elastomer. The field studies also confirmed that a critical substrate strain is needed to detach natural biofilm accumulated in seawater. Additionally, the results from the field studies suggested that substrate modulus also affect the critical strain needed to debond biofilms. To sum up, both the laboratory and the field studies proved that dynamic surface deformation approach can effectively detach various biofilms and barnacles, and therefore offers a non-toxic and environmental friendly approach for biofouling management.

Deformable elastomer systems used in our studies are easy to fabricate and can be used as complementary approach for existing commercial strategies for biofouling control. To this end, we aimed towards developed proactive multifunctional surfaces and proposed two different approaches: (i) modification of elastomers with antifouling polymers to produce multifunctional, and (ii) incorporation of silicone-oil additives into the elastomer to enhance fouling-release performance.

In approach (i), we modified poly(vinylmethylsiloxane) elastomer surfaces with zwitterionic polymers using thiol-ene click chemistry and controlled free radical polymerization. These surfaces exhibited both fouling resistance and triggered fouling-release functionalities. The zwitterionic polymers exhibited fouling resistance over short-term (∼hours) exposure to bacteria and barnacle cyprids. The biofilms that eventually accumulated over prolonged-exposure (∼days) were easily detached by applying mechanical strain to the elastomer substrate. In approach (ii), we incorporated silicone-oil additives in deformable elastomer and studied synergistic effect of silicone-oils and surface strain on barnacle detachment. We hypothesized that incorporation of silicone-oil additive reduces the amount of surface strain needed to detach barnacles. Our experimental results supported the above hypothesis and suggested that surface-action of silicone-oils plays a major role in decreasing the strain needed to detach barnacles. Further, we also examined the effect of change in substrate modulus and showed that stiffer substrates require lower amount of strain to detach barnacles.

In summary, this study shows that (1) dynamic surface deformation can be used as an effective, environmental friendly approach for biofouling control (2) stretchable elastomer surfaces modified with anti-fouling polymers provides a pro-active, dual-mode approach for biofouling control, and (3) incorporation of silicone-oils additives into stretchable elastomers improves the fouling-release performance of dynamic surface deformation technology. Dynamic surface deformation by itself and as a supplementary approach can be utilized biofouling management in biomedical, industrial and marine applications.

Institutions, Innovation, and Grassroots Change: Alternatives to Transnational Governance in the Global South

Transnational governance has been advanced as a viable option for regulating commodities produced in emerging economies—where incapable or unwilling states may undersupply institutions requisite for overseeing supply chains consistent with the quality, safety, environmental, or social standards demanded by the global marketplace. Producers from these jurisdictions, otherwise left with few venues for securing market access and price premiums, ostensibly benefit from whatever pathways transnational actors offer to minimize barriers to entry—including voluntary certification for compliance with a panoply of public and private rules, such as those promulgated by NGOs like the Fair Trade Federation or multinational retailers like Wal-Mart. Yet, such transnational “sustainability” governance may neither be effective nor desirable. Regulatory schemes, like third-party certification, often privilege the interests of primary architects and beneficiaries—private business associations, governments, NGOs, and consumers in the global North—over regulatory targets—producers in the global South. Rather than engaging with the international marketplace via imported and externally-driven schemes, some producer groups are instead challenging existing rules and innovating homegrown institutions. These alternatives to commercialization adopt some institutional characteristics of their transnational counterparts yet deliver benefits in a manner more aligned with the needs of producers. Drawing on original empirical cases from Nicaragua and Mexico, this dissertation examines the role of domestic institutional alternatives to transnational governance in enhancing market access, environmental quality and rural livelihoods within producer communities. Unlike the more technocratic and expert-driven approaches characteristic of mainstream governance efforts, these local regulatory institutions build upon the social capital, indigenous identity, “ancestral” knowledge, and human assets of producer communities as new sources of power and legitimacy in governing agricultural commodities.

A Molecular-scale Programmable Stochastic Process Based On Resonance Energy Transfer Networks: Modeling And Applications

While molecular and cellular processes are often modeled as stochastic processes, such as Brownian motion, chemical reaction networks and gene regulatory networks, there are few attempts to program a molecular-scale process to physically implement stochastic processes. DNA has been used as a substrate for programming molecular interactions, but its applications are restricted to deterministic functions and unfavorable properties such as slow processing, thermal annealing, aqueous solvents and difficult readout limit them to proof-of-concept purposes. To date, whether there exists a molecular process that can be programmed to implement stochastic processes for practical applications remains unknown.

In this dissertation, a fully specified Resonance Energy Transfer (RET) network between chromophores is accurately fabricated via DNA self-assembly, and the exciton dynamics in the RET network physically implement a stochastic process, specifically a continuous-time Markov chain (CTMC), which has a direct mapping to the physical geometry of the chromophore network. Excited by a light source, a RET network generates random samples in the temporal domain in the form of fluorescence photons which can be detected by a photon detector. The intrinsic sampling distribution of a RET network is derived as a phase-type distribution configured by its CTMC model. The conclusion is that the exciton dynamics in a RET network implement a general and important class of stochastic processes that can be directly and accurately programmed and used for practical applications of photonics and optoelectronics. Different approaches to using RET networks exist with vast potential applications. As an entropy source that can directly generate samples from virtually arbitrary distributions, RET networks can benefit applications that rely on generating random samples such as 1) fluorescent taggants and 2) stochastic computing.

By using RET networks between chromophores to implement fluorescent taggants with temporally coded signatures, the taggant design is not constrained by resolvable dyes and has a significantly larger coding capacity than spectrally or lifetime coded fluorescent taggants. Meanwhile, the taggant detection process becomes highly efficient, and the Maximum Likelihood Estimation (MLE) based taggant identification guarantees high accuracy even with only a few hundred detected photons.

Meanwhile, RET-based sampling units (RSU) can be constructed to accelerate probabilistic algorithms for wide applications in machine learning and data analytics. Because probabilistic algorithms often rely on iteratively sampling from parameterized distributions, they can be inefficient in practice on the deterministic hardware traditional computers use, especially for high-dimensional and complex problems. As an efficient universal sampling unit, the proposed RSU can be integrated into a processor / GPU as specialized functional units or organized as a discrete accelerator to bring substantial speedups and power savings.