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The nature of Yellowstone National Park’s plumbing system linking deep thermal fluids to its legendary thermal features is virtually unknown. The prevailing concepts of Yellowstone hydrology and chemistry are that fluids reside in reservoirs with unknown geometries, flow laterally from distal sources and emerge at the edges of lava flows 1 – 4 . Here we present a high-resolution synoptic view of pathways of the Yellowstone hydrothermal system derived from electrical resistivity and magnetic susceptibility models of airborne geophysical data 5 , 6 . Groundwater and thermal fluids containing appreciable total dissolved solids significantly reduce resistivities of porous volcanic rocks and are differentiated by their resistivity signatures 7 . Clay sequences mapped in thermal areas 8 , 9 and boreholes 10 typically form at depths of less than 1,000  metres over fault-controlled thermal fluid and/or gas conduits 11 – 14 . We show that most thermal features are located above high-flux conduits along buried faults capped with clay that has low resistivity and low susceptibility. Shallow subhorizontal pathways feed groundwater into basins that mixes with thermal fluids from vertical conduits. These mixed fluids emerge at the surface, controlled by surficial permeability, and flow outwards along deeper brecciated layers. These outflows, continuing between the geyser basins, mix with local groundwater and thermal fluids to produce the observed geochemical signatures. Our high-fidelity images inform geochemical and groundwater models for hydrothermal systems worldwide. High-resolution images derived from airborne geophysical data reveal critical aspects of the Yellowstone hydrothermal system, which can be used to assess geochemical models of the evolution of thermal fluids worldwide.

Time-domain Electromagnetics (TEM) is a powerful tool to image the conductivity structure of the subsurface. These systems can be ground-based or can be mounted on an airborne platform, which allows for greater data density and resolution. Airborne electromagnetic (AEM) surveys are continually being pushed to regions with increasing culture; regions such as producing oil-fields with a need of ground-water contaminant monitoring, populated agricultural regions for water resource management, and/or mineral exploration around existing developments. Culture and cultural noise are proportional, and powerlines are a common and persistent source of cultural noise. Powerlines present a unique signature in TEM data. AEM data from Iowa, contracted by the USGS, exemplify these effects. The affected data are smoothly elevated and contamination can be seen as far as 400+ m away from a powerline. Standard data processing techniques simply cull the affected data from the dataset yielding a data loss in excess of 25%. While the problem is well documented in the literature, the basic building blocks of the physics behind the problem are not well understood. This thesis is an attempt to characterize and understand the powerline coupling problem, both theoretically and experimentally. A critical component of this work is the conceptual idea of a Skywire—a vertical loop of wire, simulating powerline grounding structures and their earth return. This concept was tested experimentally—by building a Skywire and performing TEM surveys around it, and studied theoretically—through modeling the coupling of a Skywire to an idealized TEM system. Both approaches show that powerline grounding structures are indeed the culprit, but also suggest that the mutual inductance between the earth and the Skywire plays a large role in the contamination. While the modeling does not fully capture the amplitudes and spatial extent of the contamination observed in AEM or ground-based data, many aspects of the problem were investigated. These aspects include Skywire resistance, Skywire self-inductance, Skywire–earth mutual-inductance, and differing geometries between airborne- and ground-based systems and Skywires. A methodology to repair affected TEM data and recover the earth structure has yet to be developed, however, I present a modeling algorithm and a way to quantify contamination levels in TEM data.

Recent observations of nitrous acid (HONO) in the remote troposphere show much higher concentrations than can be explained through known sources, with important implications for air quality and climate. Laboratory evidence and modelling of field observations suggests that nitrate aerosol photolysis is the likely mechanism providing the additional HONO, offering a rapid route for recycling of NOx from nitric acid (HNO3). Previous studies of the global impact of this chemistry have used either very restricted HONO data or a “top-down” approach to parameterize the HONO source by reconciling simulated and observed NOx concentrations. Here, we use multiple, independent tropospheric HONO observations from different locations to parameterize nitrate photolysis, and evaluate its impacts on global atmospheric chemistry using GEOS-Chem. The simulations improve agreement between modelled and observed HONO concentrations relative to previous studies, decreasing the model bias by 5 %–20 %. The remaining (and large) underestimate of HONO in the model is due predominantly to an underestimate of total nitrate aerosol (−95 %) and is reduced to 20 % when accounting for low model nitrate. Despite the low bias in the model HONO, we find that nitrate aerosol photolysis leads to substantial global increases in NOx, O3 and OH concentrations, likely beyond the observational constraints. The additional source of NOx (∼ 48 Tg N yr−1 globally) is comparable to total NOx emissions from all sources (∼ 55 Tg yr−1). These HONO observations in the remote troposphere, thus imply a large uncertainty in the NOx budget and an incomplete understanding of atmospheric chemistry. Improved techniques to measure HONO at the low concentrations typical of remote areas, coupled with more measurements in these areas and improved process level understanding of nitrate photolysis are needed to provide quantitative assessment of its potentially global-scale atmospheric impacts.

Background and Objectives Successful clinical integration of genomic sequencing (GS) requires evidence of its utility. While GS potentially has benefits (utilities) or harms (disutilities) across multiple domains of life for both patients and their families, there is as yet no empirically informed conceptual model of these effects. Our objective was to develop an empirically informed conceptual model of perceived utility of GS that captures utilities and disutilities for patients and their families across diverse backgrounds. Methods We took a patient-centered approach, in which we began with a review of existing literature followed by collection of primary interview data. We conducted semi-structured interviews to explore types of utility in a clinically and sociopolitically diverse sample of 60 adults from seven Clinical Sequencing Evidence-Generating Research (CSER) consortium projects. Interviewees had either personally received, or were parents of a child who had received, GS results. Qualitative data were analyzed using thematic analysis. Findings from interviews were integrated with existing literature on clinical and personal utility to form the basis of an initial conceptual model that was refined based on expert review and feedback. Results Five key utility types that have been previously identified in qualitative literature held up as primary domains of utility and disutility in our diverse sample. Interview data were used to specify and organize subdomains of an initial conceptual model. After expert refinement, the five primary domains included in the final model are clinical, emotional, behavioral, cognitive, and social, and several subdomains are specified within each. Conclusion We present an empirically informed conceptual model of perceived utility of GS. This model can be used to guide development of instruments for patient-centered outcome measurement that capture the range of relevant utilities and disutilities and inform clinical implementation of GS.

HIV sensory neuropathy and distal neuropathic pain (DNP) are common, disabling complications associated with combination antiretroviral therapy (cART). We previously associated iron-regulatory genetic polymorphisms with a reduced risk of HIV sensory neuropathy during more neurotoxic types of cART. We here evaluated the impact of polymorphisms in 19 iron-regulatory genes on DNP in 560 HIV-infected subjects from a prospective, observational study, who underwent neurological examinations to ascertain peripheral neuropathy and structured interviews to ascertain DNP. Genotype-DNP associations were explored by logistic regression and permutation-based analytical methods. Among 559 evaluable subjects, 331 (59%) developed HIV-SN, and 168 (30%) reported DNP. Fifteen polymorphisms in 8 genes (p<0.05) and 5 variants in 4 genes (p<0.01) were nominally associated with DNP: polymorphisms in TF, TFRC, BMP6, ACO1, SLC11A2, and FXN conferred reduced risk (adjusted odds ratios [ORs] ranging from 0.2 to 0.7, all p<0.05); other variants in TF, CP, ACO1, BMP6, and B2M conferred increased risk (ORs ranging from 1.3 to 3.1, all p<0.05). Risks associated with some variants were statistically significant either in black or white subgroups but were consistent in direction. ACO1 rs2026739 remained significantly associated with DNP in whites (permutation p<0.0001) after correction for multiple tests. Several of the same iron-regulatory-gene polymorphisms, including ACO1 rs2026739, were also associated with severity of DNP (all p<0.05). Common polymorphisms in iron-management genes are associated with DNP and with DNP severity in HIV-infected persons receiving cART. Consistent risk estimates across population subgroups and persistence of the ACO1 rs2026739 association after adjustment for multiple testing suggest that genetic variation in iron-regulation and transport modulates susceptibility to DNP.

HIV-associated sensory neuropathy remains an important complication of combination antiretroviral therapy and HIV infection. Mitochondrial DNA haplogroups and single nucleotide polymorphisms (SNPs) have previously been associated with symptomatic neuropathy in clinical trial participants. We examined associations between mitochondrial DNA variation and HIV-associated sensory neuropathy in CNS HIV Antiretroviral Therapy Effects Research (CHARTER). CHARTER is a USA-based longitudinal observational study of HIV-infected adults who underwent a structured interview and standardized examination. HIV-associated sensory neuropathy was determined by trained examiners as ≥1 sign (diminished vibratory and sharp–dull discrimination or ankle reflexes) bilaterally. Mitochondrial DNA sequencing was performed and haplogroups were assigned by published algorithms. Multivariable logistic regression of associations between mitochondrial DNA SNPs, haplogroups, and HIV-associated sensory neuropathy were performed. In analyses of associations of each mitochondrial DNA SNP with HIV-associated sensory neuropathy, the two most significant SNPs were at positions A12810G [odds ratio (95 % confidence interval) = 0.27 (0.11–0.65); p  = 0.004] and T489C [odds ratio (95 % confidence interval) = 0.41 (0.21–0.80); p  = 0.009]. These synonymous changes are known to define African haplogroup L1c and European haplogroup J, respectively. Both haplogroups were associated with decreased prevalence of HIV-associated sensory neuropathy compared with all other haplogroups [odds ratio (95 % confidence interval) = 0.29 (0.12–0.71); p  = 0.007 and odds ratio (95 % confidence interval) = 0.42 (0.18–1.0); p  = 0.05, respectively]. In conclusion, in this cohort of mostly combination antiretroviral therapy-treated subjects, two common mitochondrial DNA SNPs and their corresponding haplogroups were associated with a markedly decreased prevalence of HIV-associated sensory neuropathy.