UC Davis

Carcinogenic volatile organic compounds (VOCs) from wildfires and wildland urban interface (WUI) fires are threatening the health and safety of firefighters. Cancer is the leading cause of death among firefighters, yet we do not know enough about the chemical constituents of wildfires to create targeted cancer prevention protocols. For this purpose, a portable air sampling device was developed to identify and quantify firefighters’ exposures to toxic VOCs over a 24-hour work period. The device mounts to the pump panel on a fire engine with a sheet metal cradle and travels with the firefighters as they work. It actively collects air samples through a pump system and concentrates VOCs onto four custom micro-preconcentrator (µPC) chemical adsorption chips. Additionally, the device has a simple user interface and records temperature, humidity, and global positioning sensor (GPS) location data on an SD card during the sampling. Ten devices were manufactured and verified to capture environmental VOCs in equal quantities and be robust under the high temperatures and movement that a fire engine experiences. Devices were deployed at the Franklin Fire in Malibu, California in December 2024. We present the successful collection of environmental and chemical data from one device that sampled during that fire.

This dissertation focuses on three main areas of study: (1) investigating the effects of 3-coordinate gold (I)-centered dimers with aurophilic interactions, (2) comparing these with 2- coordinate gold (I)-centered dimers in terms of their emission properties, and (3) exploring the impact of changes in the bridging ligand chain length (n), where n ≤ 3, across different solvates and non-coordinating anions.

This dissertation focuses on the engineering of mechanical cues and ligand presentation to regulate cellular signaling processes, using advanced nanotechnology approaches. We address three key areas: investigating the influence of local environments on cellular signaling by characterizing biomaterial’s structure and mechanical property in their aqueous environment, controlling molecular assembly via ligand presentation, and regulating cellular behavior through mechanical stimulation. Through these studies, we demonstrate how advanced nanotechnology facilitates detailed material characterization in physiologically relevant conditions, provides enhanced control over molecular organization during assembly, and enables precise regulation of cellular signaling processes such as membrane blebbing.Hydrogel materials, frequently used in 3D bioprinting, tissue repair, and regeneration, require high-resolution structural characterization in their native aqueous environment to establish structure-property-performance relationships. The first aspect of this thesis overcomes technical challenges in imaging hydrated alginate hydrogels using atomic force microscopy (AFM). By optimizing sample preparation and imaging protocols and combining a new sample preparation protocol with extremely gentle tapping mode AFM imaging, we reveal the structure of cross-linked alginate, from the egg-box dimers assembling into fibrils to their congregation and piling up for network formation. Both the morphology and regional mechanical properties of the hydrated alginate are characterized via AFM. These findings provide new insights into hydrogel characteristics at dimensions relevant to cell-material interactions that can significantly influence the cellular behavior and signaling process. This thesis further explores the role of ligand presentation and molecular assembly relevant to cell signaling processes by using an integrated AFM-based microfluidic delivery system. By incorporating precise temperature control during the delivery of ultrasmall droplets, we establish new strategies for controlling molecular assembly through delivery parameters. Our observations reveal that surface temperature directly impacts the spatial distribution and assembly behavior of solute molecules, leading to distinct deposition patterns upon drying. These findings demonstrate a controlled approach for molecular assembly and offer potential strategies for engineering 3D ligand presentation and nanoscale molecular architectures. Finally, we demonstrate how precisely controlled mechanical stimulation initiates and regulates cellular processes. Living cells respond to external mechanical stimulation, known as mechanical cues, both in vitro and in vivo. Using single cell compression, we demonstrate that accurately controlled transient mechanical cues can initiate and control continuous membrane blebbing in BV2 microglia cells. The degree of blebbing directly correlates with the magnitude of the applied force, with cells remaining viable and exhibiting dynamic blebbing for extended periods. This label-free and non-destructive approach reveals how transient mechanical cues activate the actomyosin machinery, regulate and control cell shape dynamics in BV2 microglial cells, and demonstrates the potential for programming cellular behavior through mechanical cues. Collectively, these studies demonstrate the versatility of advanced nanotechnology in characterizing biomaterial structure and mechanics, enabling ligand presentation through microfluidic surface patterning, and regulating cellular processes via controlled mechanical cues. These methodologies enable high-resolution characterization of hydrogels near physiological conditions, precise regulation of cell blebbing through controlled mechanical stimulation, and directed molecular assembly under temperature control. These approaches provide new tools for understanding and regulating cellular signaling processes, with potential applications in tissue engineering and mechanobiology.

Bioinformatics plays a crucial role in understanding neurodevelopmental genetics and genomics by integrating computational tools and large-scale datasets to analyze complex molecular interactions. This dissertation bridges experimental data and biological insights, uncovering genetic and epigenetic mechanisms underlying neurodevelopmental disorders.

Chapter 2 introduces Rocketchip, a novel bioinformatics tool designed to automate and streamline data analysis for chromatin immunoprecipitation assays, including ChIP-seq, CUT&RUN, and CUT&Tag. It addresses challenges in genetics by enhancing analysis rigor and ensuring reproducibility while promoting the use of publicly available datasets to foster scientific collaboration.

Chapter 3 applies Rocketchip to analyze newly generated ChIP-seq data targeting the transcription factor MeCP2, associated with Rett Syndrome, a neurodevelopmental disorder affecting approximately 1 in 10,000 females. This chapter investigates the DNA-binding activity of MeCP2 across various cell types and disease stages, highlighting genes and pathways contributing to Rett Syndrome progression.

Chapter 4 evaluates the impact of excess folic acid on neurodevelopment using RNA-seq and whole genome bisulfite sequencing (WGBS) data from mice exposed to excess folic acid, identifying dysregulated or differentially methylated genes that affect neurodevelopment.

Overall, these project chapters highlight the critical role of bioinformatics in advancing our understanding of neurodevelopmental genetics and genomics.

Topology is a study of continuous deformation of objects. Of particular interest to the physicists is the topological invariant, a quantity which is preserved under a continuous deformation. For example, a coffee cup (with a handle) can be deformed continuously into a donut, and the number of holes (which is called genus in mathematical language) remains untouched during the process. It would require a discontinuous deformation to create or remove a hole, i.e., to deform a solid sphere to a donut. In physics, certain physical observables can be represented mathematically by topological invariants. These topological invariants are preserved under continuous changes in the Hamiltonian, unless the system undergoes a topological phase transition that causes a discontinuous change of the corresponding topological invariant, which is the so-called ``topological protection''.

Topological materials represent a class of materials with unique electronic properties due to the unusual surface and edge states. Those states are protected by the topological invariants, making them robust against impurities and defects in the materials. The study of topological materials traces back to 1980s where people found quantum Hall effect, where the Hall conductance is quantized in units of e^2/h, regardless of the details of the Hamiltonian, such as strength of magnetic field and random disorder potential. Now it is well known that the quantized Hall conductance is related to a topological invariant called Chern number, which is the intrinsic nature of the electronic band structures. Later in 2000s, the discovery of topological insulator Bi2Se3, which exhibits dissipationless conduction of electricity on the surfuce while being insulating in the bulk, verifies the early theory of topological materials. Nowadays, the field of topological materials expands to topological superconductors, Weyl semimetals and Dirac semimetals. The topological nature in these materials gives rise to the exotic phenomena, for example, Weyl semimetals are characterized with Fermi arcs on the surface and exhibit unique electric transport properties such as Chiral anomaly and large anomalous Hall effect. Such unusual electronic properties offer promising applications in quantum computing and energy-efficient electronics.

This dissertation describes my research on two topological materials---Weyl semimetal Co3Sn2S2 and Kondo-Weyl compound CeCoGe3. Previous work on Co3Sn2S2 has revealed its interesting electric properties such as Chiral anomaly, anomalous Hall effect and a breaking-down of Ohm's Law. Our work shows it also exhibits unusual domain wall motion due to its magnetic structure. The second project is about CeCoGe3, which is a potential Weyl metal with the interplay of Kondo effect. Our detailed study on the electric properties of this compound reveals a giant intrinsic anomalous Hall conductance, which is the largest among all compounds according to our best knowledge. This manuscript is currently under review for publication.

This dissertation starts with an overview of fundamental physical principles related these compounds in chapter I, followed by a description of experimental techniques in chapter II. The detailed studies of Co3Sn2S2 and CeCoGe3 will be discussed in chapter III and chapter IV respectively.

The negative impact of age on clinical outcomes is well documented. Elderly individuals are almost universally at a higher risk of developing more severe pathology during immune challenges such as viral infections, and stimulatory immune therapies used to address afflictions that are experienced more by the elderly, such as cancer, have an elevated risk of adverse effects. Preclinical modeling could be highly useful in dissecting the aged immune system and responses, as well as investigating age specific therapeutics to target dysfunctional components, but most studies use young animals and attempt to extrapolate the data to the aged population, despite the well-known immunological differences incurred with aging. While studies have been performed with aged mice to study these phenomena, SPF conditions have led to longer lifespans in mice, and the definition of what constitutes an “aged” mouse, as well as robust immune characterization of mouse age groups as they grow older, has not been sufficiently performed or correlated to aged human data. Contrasting data has been noted in aged mice, with some studies finding that aged mice are protected against certain immune driven pathologies, while others have found the exact opposite. A critical difference in these studies was the age of the mice used, with some using 16 months (the NIA defined minimum for an “aged” mouse), and others using 20+ month old mice. While it is known that age exacerbates most morbidity, the mechanisms of how this occurs is not fully known, and the aged mouse model needs to be advanced to reflect the clinical paradigm.

This dissertation begins with a thorough review on the strengths and weaknesses of preclinical models such as mice, non-human primates, and ferrets, particularly in the context of aging and SARS-CoV-2. The second chapter details thymic rebound hyperplasia following stimulatory immunotherapy, a phenomenon in which the thymus acutely involutes and the periphery sees an expansion of memory T cells, with both the involution and memory expansion gradually reversing after the immunotherapy ceases, with the thymus eventually being even larger than at the start, and the naïve population being larger than at the start as the memory T cells contract. However, in aged mice, which already have involuted thymuses at a baseline, acute involution and memory expansion occurs and doesn’t reverse in the timespan of younger mice, indicating prolonged susceptibility to novel pathogens following immunotherapy. The third chapter details the fundamental immune differences between young, aged, and advance aged mice, with a focus on T and NK cells, and the differentials in immune responses to acute viral infections. The data presented implies that advanced aged mice have impaired antigen specific responses and compensate with non-antigen specific responses, particularly NK cells, which were found to have a significantly larger fold expansion and numbers in key organs effected by the viruses used. While this compensation controlled the virus comparably to younger groups, the advanced aged mice ultimately saw more pathology and mortality, which was likely immune driven due to overcompensation of the innate response. In both chapters, data is correlated to human data, showing translatability between mouse and human models.

This data advances our knowledge of the aged mouse model by defining how mice change over time, both at a fundamental level and in the context of immune challenge and immune therapy. This also provides targets for immune modulation / therapy for the aged immune response and addressing multiple levels of dysfunction as mice age. Critically, linking mouse and human data together and showing similar dysfunction at baselines and during immune response strengthens the translatability of the model, while also potentially addressing previous discrepancies of the aged immune response.

Offloading services and applications, deployed by the networking industry, designates the process of relocating the workflows’ computations, entirely or partially, to one or more dedicated resource-rich infrastructures; such as Network Interface Cards (NICs), Graphic Processing Units (GPUs), or Central Processing Units (CPUs). With the over-surpassingdemand for hardware resources, offloading techniques increase the device efficiency and improve the applications’ performance. An enormous number of proposals have been put forth for mobile data offloading and IoT devices, reducing the cellular network burden while promising a lower cost and power consumption solution. In this work howbeit, we focus on dynamic offloading solutions of server applications and network telemetry capable of detecting resource-intensive devices or spike momentum contingent on network downtime and SLA violation. Our work proposes novel offloading techniques and system architecture for computation offloading of wired edge networking switches and server applications. Particularly, we experiment with the adoption and offloading privilege of NVIDIA Bluefield SmartNICs due to its wide range of applications support through flexible data and control plane offloading. We aim to fully leverage the potential of such infrastructure along with any available compute resources throughout the network and servers. Some of the most controversial issues in computation offloading are selecting the most optimized nodes, workflow scheduling for the offloading process, and the degree of offloading. We demonstrate different distribution, offloading, and optimization techniques to tackle named challenges and conquer the overutilized nodes. Moving compute-heavy workloads off of or away from a resource-constrained device improves the flexibility of running tasks, and enhances the resource computation and performance of server utilization.

The global population, including individuals living with HIV, is experiencing an aging demographic shift, which is accompanied by chronic inflammation, heightened risk for co-morbidities, and increased strain on healthcare systems. HIV-infected individuals are prone to a range of chronic inflammatory lung diseases, such as emphysema and pulmonary arterial hypertension, which manifest earlier than in uninfected individuals despite antiretroviral therapy (ART). However, the underlying mechanisms promoting chronic inflammation and early onset of diseases in HIV-infected individuals remain poorly understood. This knowledge gap hinders the identification of intervention targets for developing effective treatment strategies. To address this, we investigated the contribution of macrophages to chronic inflammation during natural and accelerated aging, utilizing rhesus macaque models of SIV/AIDS and natural aging.Rhesus macaques are genetically and physiologically similar to humans, making them a valuable nonhuman primate species for biomedical research. SIV infection in rhesus macaques mimics HIV infection in humans, including accelerated aging and associated co-morbidities. We previously demonstrated a correlation between the turnover rate of blood monocytes and the development and progression of AIDS in SIV-infected macaques. The lungs are particularly affected, despite the effectiveness of ART in suppressing viral load in the blood, leading to opportunistic infections such as tuberculosis and Pneumocystis pneumonia. Macrophages play a crucial role as innate immune response cells in regulating inflammation, and their dysregulation is observed during aging. Persistence of viral reservoirs, even with effective ART, contributes to inflammation and associated co-morbidities in HIV/SIV-accelerated aging. Macrophages, along with CD4 T cells, contribute to the viral reservoir and need to be targeted for HIV cure. This dissertation investigates the use of young SIV-infected and ART treated rhesus macaques as a model of accelerated aging. Beyond the current approach of maintaining viral suppression in SIV-infected macaques, further therapy is needed to control and diminish the ongoing chronic inflammation and tissue modulation resulted from it. And ultimately, we need to develop therapies aiming to deplete monocyte/macrophage and T cells reservoirs in vivo to control persistent SIV lung infection and associated inflammatory activation. By examining resident macrophages as key players in the aging process and SIV reservoir in the lungs during ART-mediated inflammation, this research aimed to advance our understanding of host-pathogen interactions and contribute to the development of new therapeutic approaches. Specifically, we explored the role of alveolar macrophages (AMs) contribution to aging in both old and young SIV-infected and ART treated rhesus macaques. This research provides valuable insights into the role of macrophages in the aging process and their potential as therapeutic targets for viral reservoirs. Moreover, it enhances our understanding of host-pathogen interactions and paves the way for the development of new technologies for studying macrophages in aging and as therapeutic agents.

Armillaria mellea is the most virulent causal species of Armillaria root disease in California. Rootstocks widely used for the state’s almond orchards, namely peach (Prunus persica) genotypes, are highly susceptible. Here we report on resistance phenotyping of diverse genotypes from parents of wild plum species (Prunus cerasifera, Prunus munsoniana, and Prunus umbellata) and almond (Prunus dulcis). The phenotyping assay involved rooting clonal genotypes in semi-solid media, inoculating the media with two isolates of A. mellea, and weekly assessing plant mortality, canopy necrosis, and stem necrosis for 8 weeks. Controls were mock-inoculated with FF-Inoculating Fluid. Modifications to the assay, to inoculate different genotypes on different dates, were evaluated. The assay included resistant rootstocks ‘Krymsk 86’ and ‘MP-29’ (plum × peach hybrids), and ‘Marianna 2624’ (plum hybrid), and susceptible rootstock ‘Lovell’ (peach). At all timepoints, controls of ‘14-4’, ‘Hansen 536’, ‘Krymsk 86’, ‘Magnus’, ‘Marianna 2624’, ‘MP-29’, and ‘SG 1’ had 0 to 2% mortality. Higher percent mortality of controls of ‘Lovell’, ‘Rootpac R’, and ‘Viking’ by week 8 (8% to 20% mortality) may reflect intolerance of the assay. Among inoculated plants, a steep increase in mortality of all genotypes, except ‘Lovell’, after week 7 suggested that the medium’s dwindling nutrient supply might bias results; genotypes were thus compared at week 7. At week 7, inoculated ‘MP-29’ and ‘Hansen 536’ had the lowest mortality, canopy and stem necroses percentages, compared to ‘Lovell’, ‘Rootpac R’, and ‘Viking’. ‘14-4’, ‘SG 1’, and ‘Magnus’, genotypes not previously screened, had low percent mortality, but high canopy and stem necroses percentages. Ongoing field trials will help evaluate whether genotypes with low mortality, when used as rootstocks and grafted with almond scions, can improve survival and symptom severity.

Determining the factors that drive patterns of diversity across space and time is a major goal of ecology. Mountain lakes and ponds are uniquely suited for testing how environmental gradients shape the spatial and temporal patterns of population and community diversity. Additionally, mountains contain steep climate gradients and highly variable local contexts, both of which are likely to mediate how communities respond to climate warming. In this dissertation, I used a suite of theoretical and empirical frameworks to understand the factors shaping spatial patterns of population genetic diversity, patterns of community assembly among lakes and ponds, and community responses to a rapidly changing climate. For all chapters, the Sierra Nevada mountains of California served as the natural laboratory, while both historical and contemporary collections of littoral macroinvertebrates served as the subjects.

In Chapter 1, I used a common lentic mayfly species (Callibaetis ferrugineus hageni) to explore how spatial patterns of genetic and genomic variation are influenced by the interaction of steep climate gradients, the landscape matrix, and local environmental quality. By using a combination of landscape genetic network models and genomic tools, I found that both at-site and among-site factors influence patterns of gene flow among lakes, while higher elevation populations showed enhanced signatures of local adaptation. Taken together, landscape-restricted gene flow likely allows for selection pressures to facilitate local adaptation in the mayfly populations of higher elevation lakes. In Chapter 2, I used a historical dataset of macroinvertebrates to understand how daily and seasonal temperature variation influence community assembly in lakes versus ponds. Relative to lakes, I found that ponds filter for taxa with wider thermal tolerance, which then constrains the diversity of functional traits in pond communities. My results also suggest that daily temperature variation may be a particularly important abiotic filter for pond communities, though future incorporation of in situ data will help confirm the relative roles of daily, seasonal, and interannual climate variation across categories of ecosystem size. In Chapter 3, I used both historical and contemporary datasets of lake macroinvertebrates to ask 1) if lake communities are responding to climate warming through colonizations by warm-adapted taxa, local extinctions of cold-adapted taxa, or both (i.e. thermophilization) and 2) if current responses to climate warming result in reduced beta diversity (i.e. homogenization). Over 20 years of declining winter snowpack and rising air temperatures, I found that colonizations by predators drove thermophilization in contemporary macroinvertebrate communities, but that thermophilization did not lead to significant homogenization in either taxonomic or functional measures.

Collectively, my dissertation demonstrates the unique ways in which mountain environments shape freshwater populations and communities, while also mediating community responses to rapid climate warming.