A Continuous, In-situ, Near-time Fluorescence Sensor Coupled with a Machine Learning Model for Highly Accurate Detection of Fecal Contamination in Drinking Water: Design, Characterization, and Field Validation

Equitable access to reliable, affordable, and safe drinking water is essential to human health and livelihood. Globally, two billion people use a drinking water source that is contaminated with feces. Low-cost, field-deployable, near-time methods for assessing water quality are not available when and where waterborne infection risks are greatest. In this dissertation, I describe the development and testing of a novel device for the measurement of online, in-situ, and remotely reporting tryptophan-like fluorescence (TLF), making use of recent advances in deep-ultraviolet light emitting diodes (UV-LEDs) and sensitive silicon photomultipliers. TLF is an emerging indicator of microbial water quality that is associated with members of the coliform group of bacteria and therefore potential fecal contamination. After optimizing the sensor's sensitivity to 0.05 ppb tryptophan, I demonstrated the close correlation between TLF and E. coli in model waters and proof of principle with sensitivity of 33 0mL for lab grown E. coli and 10 CFU/100mL for E. coli in wastewater. I characterized the sensor's behavior to multiple fluorescence quenching parameters through benchtop analysis. Fluorescence response declined with water temperature and a correction factor was calculated. Inner filter effects were shown to have negligible impact in an operational context. Biofouling was demonstrated to increase the fluorescence signal by approximately 82%, while mineral scaling reduced the sensitivity of the sensor by approximately 5%. A training and validation data set for a machine learning model was built by installing four sensors on Boulder Creek, Colorado for 88 days and enumerating 298 grab samples for E. coli with membrane filtration. The machine learning model incorporated a proxy feature for fouling (time since last cleaning) which improved model performance. The model was able to predict high risk fecal contamination with 83% accuracy (95% CI: 78% - 87%), sensitivity of 80%, and specificity of 86%. A model distinguishing between all World Health Organization established risk categories performed with an overall accuracy of 64%. The sensor design combined with the highly skilled model has the ability to provide water service providers as well as individual consumers more reliable and informative data about fecal contamination risk in their drinking water. Findings to date suggest that this device represents a scalable solution for remote monitoring of drinking water supplies to identify high-risk fecal contamination in drinking water in near-time. Such information can be immediately actionable to reduce risks and would reduce cost of microbial testing greatly, improving health and wellness of consumers and enabling water service providers more access to funds that can be used to increase access to clean water.</p

Unmanned Aerial Vehicle Based Structure from Motion Biomass Inventory Estimates

Riparian vegetation restoration efforts demand cost effective, accurate, and replicable impact assessments. In this thesis a method is presented using an Unmanned Aerial Vehicle (UAV) equipped with a GoPro digital camera to collect photogrammetric data of a 2.02-acre riparian restoration. A three-dimensional point cloud was created from the photos using Structure from Motion (SfM) techniques. The point cloud was analyzed and compared to traditional, ground-based monitoring techniques. Ground truth data collected using the status-quo approach was collected on 6.3% of the study site and averaged across the entire site to report stem heights in stems/acre in three height classes, 0-3 feet, 3-7 feet, and greater than 7 feet. The project site was divided into four analysis sections, one for derivation of parameters used in the UAV data analysis, and the remaining three sections reserved for method validation. The most conservative of several methods tested comparing the ground truth data to the UAV generated data produced an overall error of 21.6% and indicated an r2 value of 0.98. A Bland Altman analysis indicated a 99% probability that the UAV stems/plot result will be within 159 stems/plot of the ground truth data. The ground truth data is reported with an 80% confidence interval of +/- 844 stems/plot, thus the UAV was able to estimate stems well within this confidence interval. Further research is required to validate this method longitudinally at this same site and across varying ecologies. These results suggest that UAV derived environmental impact assessments at riparian restoration sites may offer competitive performance and value

Duplex DNA from Sites of Helicase-Polymerase Uncoupling Links Non-B DNA Structure Formation to Replicative Stress

BACKGROUND: Replication impediments can produce helicase-polymerase uncoupling allowing lagging strand synthesis to continue for as much as 6 kb from the site of the impediment. MATERIALS AND METHODS: We developed a cloning procedure designed to recover fragments from lagging strand near the helicase halt site. RESULTS: A total of 62% of clones from a p53-deficient tumor cell line (PC3) and 33% of the clones from a primary cell line (HPS-19I) were within 5 kb of a G-quadruplex forming sequence. Analyses of a RACK7 gene sequence, that was cloned multiple times from the PC3 line, revealed multiple deletions in region about 1 kb from the cloned region that was present in a non-B conformation. Sequences from the region formed G-quadruplex and i-motif structures under physiological conditions. CONCLUSION: Defects in components of non-B structure suppression systems (e.g. p53 helicase targeting) promote replication-linked damage selectively targeted to sequences prone to G-quadruplex and i-motif formation

Demonstration of Tryptophan-Like Fluorescence Sensor Concepts for Fecal Exposure Detection in Drinking Water in Remote and Resource Constrained Settings

Low-cost, field-deployable, near-time methods for assessing water quality are not available when and where waterborne infection risks are greatest. We describe the development and testing of a novel device for the measurement of tryptophan-like fluorescence (TLF), making use of recent advances in deep-ultraviolet light emitting diodes (UV-LEDs) and sensitive semiconductor photodiodes and photomultipliers. TLF is an emerging indicator of water quality that is associated with members of the coliform group of bacteria and therefore potential fecal contamination. Following the demonstration of close correlation between TLF and E. coli in model waters and proof of principle with sensitivity of 4 CFU/mL for E. coli, we further developed a two-LED flow-through configuration capable of detecting TLF levels corresponding to &ldquo;high risk&rdquo; fecal contamination levels (&gt;10 CFU/100 mL). Findings to date suggest that this device represents a scalable solution for remote monitoring of drinking water supplies to identify high-risk drinking water in near-time. Such information can be immediately actionable to reduce risks.</p

Understanding the Effects of Both CD14-Mediated Innate Immunity and Device/Tissue Mechanical Mismatch in the Neuroinflammatory Response to Intracortical Microelectrodes

Intracortical microelectrodes record neuronal activity of individual neurons within the brain, which can be used to bridge communication between the biological system and computer hardware for both research and rehabilitation purposes. However, long-term consistent neural recordings are difficult to achieve, in large part due to the neuroinflammatory tissue response to the microelectrodes. Prior studies have identified many factors that may contribute to the neuroinflammatory response to intracortical microelectrodes. Unfortunately, each proposed mechanism for the prolonged neuroinflammatory response has been investigated independently, while it is clear that mechanisms can overlap and be difficult to isolate. Therefore, we aimed to determine whether the dual targeting of the innate immune response by inhibiting innate immunity pathways associated with cluster of differentiation 14 (CD14), and the mechanical mismatch could improve the neuroinflammatory response to intracortical microelectrodes. A thiol-ene probe that softens on contact with the physiological environment was used to reduce mechanical mismatch. The thiol-ene probe was both softer and larger in size than the uncoated silicon control probe. Cd14-/- mice were used to completely inhibit contribution of CD14 to the neuroinflammatory response. Contrary to the initial hypothesis, dual targeting worsened the neuroinflammatory response to intracortical probes. Therefore, probe material and CD14 deficiency were independently assessed for their effect on inflammation and neuronal density by implanting each microelectrode type in both wild-type control and Cd14-/- mice. Histology results show that 2 weeks after implantation, targeting CD14 results in higher neuronal density and decreased glial scar around the probe, whereas the thiol-ene probe results in more microglia/macrophage activation and greater blood–brain barrier (BBB) disruption around the probe. Chronic histology demonstrate no differences in the inflammatory response at 16 weeks. Over acute time points, results also suggest immunomodulatory approaches such as targeting CD14 can be utilized to decrease inflammation to intracortical microelectrodes. The results obtained in the current study highlight the importance of not only probe material, but probe size, in regard to neuroinflammation

Living Building Challenge

The Living Economy Sourcing imperative intends to promote growth of local economic structure while reducing negative transportation related effects on human and environmental health. Requirements for material sourcing distances are presented in this imperative, as seen in the map below, from Portland, OR. The manufacturer location is defined as the place where the final product is fabricated and assembled. A distribution facility does not qualify as a products’ manufacturer location. Methods of improving and localizing the total sourcing radius should be researched.https://pdxscholar.library.pdx.edu/research_based_design/1060/thumbnail.jp

Elemental Abundances of Kepler Objects of Interest in APOGEE DR17

The elemental abundances of planet host stars can shed light on the conditions of planet forming environments. We test if individual abundances of 130 known/candidate planet hosts in APOGEE are statistically different from those of a reference doppelgänger sample. The reference set comprises objects selected with the same T _eff , $\mathrm{log}g$ , [Fe/H], and [Mg/H] as each Kepler Object of Interest (KOI). We predict twelve individual abundances (X = C, N, O, Na, Al, Si, Ca, Ti, V, Cr, Mn, Ni) for the KOIs and their doppelgängers using a local linear model of these four parameters, training on ASPCAP abundance measurements for a sample of field stars with high-fidelity (signal-to-noise ratio > 200) APOGEE observations. We compare element prediction residuals (model–measurement) for the two samples and find them to be indistinguishable, given a high-quality sample selection. We report median intrinsic dispersions of ∼0.038 dex and ∼0.041 dex, for the KOI and doppelgänger samples, respectively, for these elements. We conclude that the individual abundances at fixed T _eff , $\mathrm{log}g$ , [Fe/H], and [Mg/H] are unremarkable for known planet hosts. Our results establish an upper limit on the abundance precision required to uncover any chemical signatures of planet formation in planet host stars

Demonstration of Tryptophan-Like Fluorescence Sensor Concepts for Fecal Exposure Detection in Drinking Water in Remote and Resource Constrained Settings

Low-cost, field-deployable, near-time methods for assessing water quality are not available when and where waterborne infection risks are greatest. We describe the development and testing of a novel device for the measurement of tryptophan-like fluorescence (TLF), making use of recent advances in deep-ultraviolet light emitting diodes (UV-LEDs) and sensitive semiconductor photodiodes and photomultipliers. TLF is an emerging indicator of water quality that is associated with members of the coliform group of bacteria and therefore potential fecal contamination. Following the demonstration of close correlation between TLF and E. coli in model waters and proof of principle with sensitivity of 4 CFU/mL for E. coli, we further developed a two-LED flow-through configuration capable of detecting TLF levels corresponding to &ldquo;high risk&rdquo; fecal contamination levels (&gt;10 CFU/100 mL). Findings to date suggest that this device represents a scalable solution for remote monitoring of drinking water supplies to identify high-risk drinking water in near-time. Such information can be immediately actionable to reduce risks