UC Davis

Understanding the fate and transport of nitrogen through the vadose zone is vital to reduce nitrate leaching, protecting groundwater quality, and enhancing resource use efficiency. Currently, there is limited data on the continuous monitoring of nitrate transport through the deep vadose zone. The lack of high-quality data makes it difficult to evaluate the effectiveness of conservation practices aimed at reducing nitrate leaching. The vadose-zone monitoring system (VMS) serves as an innovative technology for near real-time monitoring of nitrate and other contaminants as they travel through the shallow and deep vadose zone to groundwater. The objective of this study was to evaluate the performance of the VMS technology at three sites using bromide (Br-) as a tracer and the unsaturated flow model HYDRUS 1D to understand underlying vadose zone water flow and solute transport processes. Site 1 was a field crop site near Esparto, CA, with a heavy Capay-clay soil and a groundwater depth of approximately 10 m. Site 2 was an almond orchard near Modesto, CA, with a moderately homogenous sandy loam in the top 2 m and a sandy clay loam down to 6 m and a water table at approximately 8 m. Site 3 was a citrus orchard near Orange Cove, CA, with a sandy loam soil at the shallow depths (0-2 meters) followed by sandy clay loam down to 7 m and a groundwater depth of approximately 25 m. The VMS was installed at all sites to collect soil pore water samples at approximately 1 m intervals to about 7 m depth. To test the system performance, approximately 380 L of a 500 ppm Br- solution was applied as a conservative tracer at the three sites. The applied tracer was either percolated by rain, irrigation, or a combination of the two. The site HYDRUS models demonstrated a complete breakthrough of Br- at each vadose sampling port depth. Measured pore-water from the VMS exhibited similar solute breakthroughs with varying time and concentrations. The bromide tracer results confirm that the VMS is capable of monitoring flow and transport processes in the deep vadose zone.

Neurons are highly energy-demanding cells, and their viability and functions rely heavily on proper mitochondrial function. Mitochondria functions include the regulation of calcium (Ca2+) homeostasis, ATP synthesis, apoptotic cell death, and reactive oxygen species (ROS) production. Given that mitochondria play various crucial roles in neurons and thus proper quality control of mitochondria is essential, removal of dysfunctional mitochondria, a process referred to as mitophagy, is critical to ensure maintenance of sufficient pools of healthy neuronal mitochondria. However, it remains an open question how dysfunctional mitochondria are effectively removed from long neuronal processes such as axons, far from the cell body, where many neuronal mitochondria reside. In this dissertation, I primarily focus on understanding how damaged mitochondria are eliminated from the long axons of neurons such as retinal ganglion cells (RGCs). I perturbed the mitophagy receptor Optineurin (OPTN) to determine how that affects mitochondria degradation within Xenopus laevis RGC axons. Live-imaging of the optic nerve revealed that while normally there is not much mitophagy occurring locally within the axons, expression of disease-associated versions of OPTN increases the local degradation of axonal mitochondria. Most importantly, whenever there is local axonal degradation of mitochondria, this is accomplished by unusual mitochondria shedding process that the Marsh-Armstrong lab had previously described, referred to as transmitophagy. This supports the view that under healthy conditions there is a low baseline of mitophagy within axons, but that mutations in mitophagy machinery result in large increases in the local degradation of axonal mitochondria. Most notably, however, under both the baseline and perturbed conditions a significant number of axonal mitochondria are degraded outside of the axons.The second part of the dissertation shows that β-amyloid peptides (Aβ), a key molecule in Alzheimer’s disease (AD) pathology where Aβ are accumulating within neuronal mitochondria and leading to dysregulated mitochondrial functions, move together with the mitochondria in RGC axons, and, in particular, a large amount of Aβ and mitochondria were stopped in the axons and some of them appeared to be outside the optic nerve similar to what was shown in glaucoma-associated E50K OPTN mutant, suggesting transmitophagy process. Overall, my work contributes to our understanding of how mitochondria debris and toxic peptides are cleared from the vertebrate nervous system. Besides advancing basic understanding of these processes, my work also may point the way towards therapeutic strategies for neurodegenerative diseases, for example, accelerating clearance of damaged mitochondria and Aβ through transmitophagy.

There are a disproportionate number of seriously mentally ill inmates in California jails. Rural and suburban communities incarcerate many inmates with significant mental health needs yet struggle to maintain sufficient mental health providers to treat this vulnerable population. Jail mental health providers have long faced staffing, treatment space and other resource obstacles in providing constitutionally appropriate care to mentally ill inmates, which were exacerbated by COVID-19. At the time of this study, many of California’s counties were undergoing new litigation and consent decrees to investigate and potentially improve jail safety conditions, including those related directly to mental health services. Guided by the Socio Ecological Model, this study aimed to explore the individual, interpersonal and organizational factors that support jail mental health providers in delivering mental health care services to inmates in rural and suburban California jails. Qualitative data were collected through individual telephone interviews with 14 rural and suburban jail mental health providers, which were recorded, transcribed and thematically analyzed. Themes were identified within 5 domains of the Socio Ecological Model (individual, interpersonal, organizational, community, and public policy levels). Two key findings emerged. First, the study identified needs for exposure to the jail environment as part of basic clinical education, and identified specific needs for mental health provider training, mentoring and clinical supervision that are both internal and external to the jail setting. Second, the study identified strengths of jail mental health providers and their networks to build upon including resiliency, collaboration and the support needed to navigate difficult experiences within the jail setting. Study findings highlight opportunities for educational institutions, county behavioral health and jail administrators, contracting agencies and correctional health care organizations to more fully understand how to train, mentor, recruit and retain jail mental health providers—especially for California’s rural and suburban counties.

In this study, a pilot scale slow sand filtration system was evaluated for biodegradation of the plant growth regulator paclobutrazol from recaptured irrigation leachate in a simulated greenhouse environment. Generated irrigation runoff containing 0.05 mg·L-1 paclobutrazol passed through 1-meter-deep slow sand filter sand beds for a period lasting 120 days. Evaluations through a broccoli hypocotyl length bioassay proved acutely sensitive to low concentrations of paclobutrazol, which is an affordable indicator of paclobutrazol presence in nursery runoff that can be utilized by nursery professionals. The SSF system proved ineffective in complete removal of PBZ as the bioassay indicated similar hypocotyl lengths grown with leachate before and after filtration.

Memory retrieval is well known to modify retention of not only retrieved material, but also related, non-retrieved material. This dissertation consists of two manuscripts that investigated retrieval phenomena in the learning of foreign language vocabulary and science education material. The testing effect–the retention benefit of practicing retrieval compared to studying–and the pretesting effect–incorrectly guessing a target before learning compared to studying–demonstrate the advantages of retrieval-based learning, but no extant theories have accounted for both of these effects. In Chapter 1, we investigated an error-driven learning account whereby retrieval-based learning serves to “stress test” the memory system, allowing it to learn to better predict a target from a cue, whereas in studying, there is no opportunity for the system to form a prediction. We predicted that inserting a small temporal “gap” between a foreign language word and its English translation should enhance retention when compared to simultaneous, “no gap,” presentation. In four experiments (N = 287) we consistently observed that “gap” conditions benefitted retention compared to “no gap” conditions, which supports the error-driven learning account. We observed that a gap as short as 600 ms benefitted retention one day later, one minute later, and in a pure list design. In Chapter 2, we investigated the sequalae of retrieval practice for non-practiced educational science text material. Some evidence suggests that retrieval practice of main ideas would lead to greater retention of non-practiced information, whereas other evidence suggests that retrieval practice of peripheral information would lead to impaired retention of non-practiced information, when compared to a control group that did not practice retrieval. In two experiments (N = 360) we observed robust testing effects, but we did not observe robust differences in non-practiced material, suggesting that the kind of focal retrieval practice used here has focal effects on science material retention.

This dissertation investigates learning and literacy as drivers of socioecological transformation, focusing specifically on the context of community-based watershed monitoring. Community-based monitoring is a form of citizen science, in which professional scientists and broader publics jointly engage in research or monitoring. Community-based monitoring is distinguished from other types of citizen science in that it is typically place-based and oriented toward local decision-making. The focal monitoring projects that this dissertation examines are situated within the specific context of dam removal and river restoration initiatives in Southern California and Western Montana, each of which carries the goal of increasing habitat connectivity to support threatened and endangered trout species, as well as overall watershed health. Addressing environmental problems - like the presence of obsolete dams - requires the collaboration of multiple groups wherein they collectively learn with and from each other to co-produce shared knowledge. This requires attention to issues of power, status, and rank, given the ways in which dominant science is typically privileged in environmental decision-making despite the robust forms of local knowledge found distributed within communities.

Leveraging sociocultural perspectives on learning and ethnographic methods, this dissertation takes up questions at the intersections of learning, literacy, power, science, and socioecological transformation. Chapter 1, the Introduction, synthesizes perspectives on these ideas from diverse fields such as education, science and technology studies, and political ecology. Chapter 2 empirically examines if and how power asymmetries mediate social learning trajectories as participants engage in deliberative dialogue in the Southern California case. The specific context is a project inspired by the principles of youth participatory action research in which educational researchers, students, educators, and land managers worked to co-design a community-based watershed monitoring initiative. Findings suggest that power asymmetries may constrain opportunities for learning in-the-moment by mediating joint activity, while simultaneously creating the conditions for expansive learning to later occur. Chapters 3 and 4 empirically examine the construct of community science literacy, examining how local residents engage in field-based data collection to assess the health of a local creek and share data with land managers and scientists to inform adaptive management in the Western Montana case. In conceptualizing science literacy as a collective phenomenon rather than an individual trait, Chapter 3 examines how the work of monitoring is distributed across individuals and social structures. Findings demonstrate how individuals contribute their respective knowledge and practices to monitoring through processes of coordination work, and how these processes are mediated by individuals’ opportunity to shift roles, the presence of brokers, and power relations. Chapter 4 builds on the findings from Chapter 3, taking up coordination work as an analytic lens to examine the role of material artifacts and the natural world in shaping processes of community science literacy. Findings from this chapter indicate that community science literacy, material artifacts, and the natural world are inextricably linked, suggesting community science literacy ought to be understood as a sociomaterial practice. Results from these three interrelated yet distinct chapters are synthesized in Chapter 5, the Conclusion.

In its entirety, this dissertation looks beyond the level of the individual to argue that community-based and place-based learning environments provide rich opportunities to activate the knowledge and practices found distributed within communities toward socioecological transformation. Doing so, however, requires disrupting hierarchies that privilege dominant scientific knowledge over other ways of knowing in both environmental management and in education. Honoring the local knowledge found in communities can support more equitable forms of learning that catalyze moves toward more healthy and just socioecological futures.

Amongst the Poxviridae family one viral species: Cowpox virus (CPXV) has exhibited the broadest known host range and is becoming increasingly of concern due to lethal outbreaks in various zoo animals, pets, and humans across 12 Eurasian countries. Modern phylogenetics has revealed CPXV to include at least 5 major clades, with species-level genetic differences that remain functionally uncharacterized, highlighting the dire need for more research to reclassify cowpox viruses (CPXVs) and understand what was once thought of as a monophyletic species. In this dissertation, we cover the history of CPXV naming with a comprehensive review regarding multiple facets of CPXVs, including phylogenetics, animal and molecular research, pathology, geographic and host range, modern outbreaks, and the potential threat of these viruses. Next, we explore this viral diversity by examining CPXV orthologs of the host range gene K3L which antagonizes the antiviral innate immune protein PKR, with orthologs found throughout the class Mammalia, mapping out how K3L sequence diversity is associated with different orthopoxviruses. We then functionally test 15 of 18 unique CPXV K3L in luciferase-based assays of PKR inhibition, identifying unique species-specific and K3L-specific patterns of PKR inhibition. We characterize CPXV K3Ls in vitro, generating congenic cell lines and CPXV K3L-containing vaccinia viruses and screening the effects on viral replication via viral EGFP expression and titrations on HeLa cells. Finally, we explore the interactions between E3L (another poxvirus PKR inhibitor) and K3L with PKRs of opposite susceptibility and resistance to E3L and K3L, using a split dual luciferase tag system to better understand the mechanism of inhibition of these important host range genes.

AbstractCalifornia walnut growers and processors sell product all across the globe, and like with any raw food, safety assurance is critically important. The walnut industry of California utilizes either a chemical method of pasteurization or heat pasteurization to provide an effective kill step on any surface bacteria that might be present on the walnuts. In this study I only focus on two heat pasteurization methods: continuous and batch. The impact of the heat pasteurization methods on walnut storage quality is unknown. My thesis research analyzed the impact each pasteurization method has on walnut quality during storage, and the effect low oxygen storage may have in mitigating potential negative impacts caused by each heat pasteurization method. Quality was analyzed in the lab by measuring lipid degradation compound accumulation (peroxide value, free-fatty acid content), kernel color change, volatile compound accumulation (hexanal), and vitamin E degradation (tocopherol). Additionally, a trained sensory panel created a lexicon of descriptors in order to analyze the walnuts for changes in aroma, taste, and texture. Results showed that continuous walnut pasteurization accelerated lipid degradation, degraded vitamin E content, and increased negative sensory characteristics such as rancidity. Low oxygen storage of continuous pasteurized walnuts significantly reduced the rate of lipid and tocopherol degradation, and resulted in a lower sensory scores for rancidity. However, low oxygen storage of continuous pasteurized walnuts had significantly lower nut quality in comparison to either unpasteurized or batch pasteurized walnuts. Batch pasteurized walnuts had reduced lipid degradation and an improved sensory profile compared to unpasteurized walnuts, while vitamin E content was unaffected. Low oxygen storage of batch pasteurized walnuts further reduced lipid degradation, and caused an even greater improvement on sensory characteristics especially compared to continuous pasteurized walnuts. The best method of pasteurization and storage was found to be batch pasteurization stored in low oxygen conditions.

Positron emission tomography (PET) imaging is a noninvasive imaging modality that provides in vivo visualization of biochemical processes in a living body through the use of radiotracers. With the latest state-of-the-art whole-body PET scanners using detector crystals of about 3 mm in size, the intrinsic spatial resolutions of PET scanners have been substantially improved. As a result, physiological motions, e.g., heart beating and respiratory motion, have become a limiting factor for PET spatial resolution in clinical practice. This thesis focuses on improving PET image quality by developing new methods for motion compensation and system modeling.Recently, deep learning has been successfully applied in various computer vision tasks, such as image segmentation, object detection, classification. First, we proposed a fully automatic data-driven gating approach using an unsupervised deep clustering network that exploits the autoencoder approach for respiratory gating. Second, we proposed a motion correction method of respiratory-gated PET images using a deep learning-based image registration framework. It does not require ground truth for training the network, which makes it very convenient to implement. We validated the proposed methods using simulation and clinical data and showed their ability to reduce the motion artifacts while utilizing all gated PET data. Furthermore, long axial field-of-view PET scanners provide high sensitivity and total-body coverage for accurate quantification of a wide range of physiological parameters in vivo using dynamic scans. We extended our proposed methods to obtain motion-frozen and motion-corrected total-body parametric images using deep learning-based data-driven gating and motion compensation techniques. Finally, we proposed a joint estimation framework incorporating deep learning-based image registration for motion estimation. In addition, a stochastic sampling method was developed to improve the spatial resolution of PET image reconstruction. This method enables efficient on-the-fly calculation of the detector response with DOI and we showed its potential to improve the spatial resolution efficiently for DOI-enabled high-resolution brain PET imaging.

This dissertation summarizes original work relevant to product predictions for Cytochrome P450 (CYP450) catalyzed transformations using a combination of computationally affordable methods, specifically modern force field and semi-empirical methods and protein-ligand docking. Additionally, it highlights multiple applications of Density Functional Theory (DFT) in collaboration with our synthetic chemistry colleagues to explore and explain photoisomerization, redox chemistry, and reaction mechanisms.Firstly, Cytochrome P450s (CYP450) are metabolically and synthetically important enzymes, catalyzing an array of oxidative transformations across all kingdoms of life. The prediction of oxidative products resulting from CYP450 catalyzed transformations is historically challenging and often relies only on enzyme-substrate fit and binding affinity estimates while neglecting measures of reactivity. Herein we present computationally affordable methodology for estimating epoxidation and hydroxylation barriers. When predicted hydroxylation barriers are paired with traditional protein-ligand docking, we improve on previously published prediction success rates and open the door to enzyme design in CYP450s for the purpose of achieving novel biosynthetic outcomes. In Chapter 1, epoxidation barriers were predicted using a multiple linear regression model with the fractional occupation number weighted density (FOD) and orbital weighted Fukui index (fw+) as descriptors localized to the vinylic carbon atom involved in the initial C–O bond formation event during epoxidation. Relative to previously computed epoxidation barriers using density functional theory in a panel of 36 compounds, mean absolute errors of 0.66 and 0.70 kcal/mol were achieved in the training and test sets, respectively, with coefficients of determination of ca. 0.80 were. This was done at the GFN2-xTB//GFN-FF level of theory. By performing electronic structure calculations on force field generated geometries, this approach is highly scalable. In Chapter 2, a single linear regression model was built to predict hydrogen atom transfer (HAT) barriers following the formation of Compound I, relevant to CYP450-mediated hydroxylations. The C–H bond dissociation energy involving a “frozen radical” – that is the removal of a hydrogen atom from an sp3 hybridized carbon in the substrate followed by single point energy calculations as doublets for the resulting unoptimized substrate radical and hydrogen atom – was found to correlate well with hydrogen atom transfer barriers previously computed with density functional theory. At the GFN2-xTB//GFN-FF level of theory for a panel of 24 sp3 hybridized carbon atoms across 21 substrates, mean absolute errors of ca. 1 kcal/mol were achieved in both training and test sets. By again leveraging force field and semi-empirical methods, this approach will scale to thousands of structures on even a modest computing resource. In Chapter 3, hydroxylation product predictions are made by combining enzyme-substrate docking and HAT barrier regression modelling. Hydroxylated product formation certainly relies significantly on the fit and binding affinity of a substrate with a CYP450 enzyme and not on the HAT barrier with Compound I alone. To this end, HAT barriers predicted using regression modeling were combined with Oheme–Hsubstrate constrained docking and pose clustering to make product predictions on a set of 25 substrates for the CYP101A1 camphor 5-monooxygenase enzyme. Using RxDock as an example utility used in high throughput virtual screening (HTVS), the prediction success rate for any hydroxylation product was 84% in the top two predictions when HAT barriers were included, compared to only 80% without the inclusion of HAT barriers. Combining HAT barriers and docking scores from Rosetta, any hydroxylation product was successfully predicted in the top two predictions in 92% of the 25 substrates studied. More importantly, the primary hydroxylation product prediction success rate was 84% in the top two predictions. Collectively, these findings meet or exceed the performance of previously published results in a non-parametric fashion. More importantly, the performance using Rosetta indicates our combination of docking and HAT barriers holds tremendous promise in the application of enzyme design. In the second half of this work, theoretical calculations were employed to rationalize experimental outcomes. Such retrospective analysis tends to be employed when experimental observations fail to meet our preconceived chemical intuition. By coupling wet experiment with quantum chemical theory, we can gain insight into underlying electronic structures and, in doing so, better understand and even predict spectroscopic or thermochemical properties in our systems of interest. To this end and in collaboration with the laboratory of David Olsen, we explored three series of experimental findings using Density Functional Theory in the sort of post-hoc fashion described above. These three efforts focused on the spectroscopic properties (and limitations) of azobenzene photoswitches,1 oxidation potentials relevant to Baeyer-Mills reactions,2 and the samarium-mediated rearrangement of vinyl aziridines to afford more complex heterocycles. In all three cases, computational efforts followed behind the experiment and aimed to generate models that explained the Olsen’s labs findings, as well as affording methodology that could be used to further expand their work ahead of experimental efforts. In Chapter 4, the photoisomerization of acylhydrazone-functionalized azobenzene derivatives is explored. With seemingly two photoswitchable motifs present, our collaborators only observed E to Z photoisomerization across the azobenzene substructure. Using Time-dependent Density Functional Theory (TD-DFT), the π to π* transition at approximately 380 nm is predicted to have a strongly localized electron density difference over the azo motif between the ground and excited state, with no discernable difference predicted over the acyl hydrazone functionality. Additionally, substituent effects were studied for a handful of electron withdrawing and donating cases explored synthetically, all showing no π to π* transition near 300 nm, inconsistent with other acylhydrazone photoswitches. This study rationalized the findings of our collaborators, and while retrospective analysis is useful, this study further highlights the opportunity to leverage computational techniques prospectively to guide synthetic efforts. In Chapter 5, retrospective analysis of synthetic findings was again conducted. In this application, the Bayer-Mills reaction is a traditional route to azobenzenes by way of a condensation reaction. However, azoxybenzene side products are also formed. Here, we attempted to correlate the formation of azoxybenzene with one electron oxidation potentials computed with DFT. In this work, electron-rich aniline derivatives with low oxidation potentials were found to produce undesirable levels of the azoxybenzene product, and we demonstrate that the computed oxidation potential from DFT with implicit solvation is a useful descriptor in predicting the outcome of the Baeyer-Mills reaction for given reactants. Lastly in Chapter 6, access to vinyl aziridines is explored mechanistically using traditional stationary point searching with DFT. Our collaborators discovered that vinyl aziridines could undergo ring expansion in the presence of samarium (II) iodide. While simple Lewis-acid promoted expansions are known, we explored a radical mechanism consistent with samarium (II) iodide mediated single electron transfer reactions observed in reductions and cross-couplings of ketones. From our analyses at the PBE0-D3BJ/def2-TZVP (ECP = Sm, I; SMD = toluene)//PBE0/def2-SVP (ECP = Sm, I) level of theory, a radical mechanism on the septet spin surface is achievable thermally at room temperature, with an overall free energy barrier of 25.1 kcal/mol and a strong thermodynamic driving force to favor the product-catalyst complex by 22.1 kcal/mol, both relative to the reactant-catalyst complex. These findings corroborate those of our synthetic colleagues and suggest that the transformation occurs according to a single electron transfer mechanism. This affords a mechanistically differentiated route to substituted 3-pyrrolines. In all, this work showcases multiple applications of computational chemistry that are relevant to protein engineering and medicinal chemistry, with an aim toward increased prospective use in the design of experiments.