A model-based approach for the development of a bioelectrochemical sensor for biochemical oxygen demand in wastewater

Bioelectrochemical systems such as microbial fuel cells and microbial electrolysis cells are currently being researched for many different environmental engineering applications. Some of these applications include wastewater treatment coupled with electricity generation, wastewater treatment coupled with hydrogen production, powering of remote sensors, and as sensors for biochemical oxygen demand or volatile fatty acids. After introducing bioelectrochemical systems and the basic principles and mechanisms of their operation, this thesis will focus on a model-based approach to developing a sensor based on a microbial electrolysis cell to characterize wastewater biochemical oxygen demand. In a microbial electrolysis cell, a microbial biofilm growing on the anode of an electrochemical cell catalyzes the oxidation of organic matter and uses the anode as a terminal electron acceptor for respiration, thereby generating a measurable current. A polarization curve measures the response of the current generated to changes in the anode potential. In this study, four continuously operated microbial electrolysis cells with two different anode materials with differing surface properties have been used to model the relationship between acetate concentration in the bulk liquid and the shape of a polarization curve generated using low scan cyclic voltammetry. In terms of Monod kinetics, the anode potential determines the limitation placed on microbial respiration rate by the affinity of the electron acceptor for electrons, and is analogous to the effect of oxygen concentration on growth rate in an aerobic system. The Butler-Volmer Monod model is used to relate substrate concentration, anode potential, and generated current. Polarization curves generated at a range of different acetate concentrations were used to estimate the kinetic parameters of the model and to test its capability to predict substrate concentration. The results of this characterization of anode respiring biofilm respiration kinetics, presented in Chapter 3, show that this approach can differentiate between different substrate concentrations and that the fit and predictive capability of the model can be improved by optimizing the choice of anode materials and electrochemical techniques. This approach differs from other studies which attempt predict substrate concentration using only whole-cell current or total charge generated. Emphasis has also been placed on developing a sensor that is inexpensive and easy to operate, with the idea that such a sensor could allow better process monitoring and optimization at small or resource-limited wastewater treatment plants. To address this, a control and data acquisition system based on the Arduino Uno, an inexpensive microcontroller, was also developed. This study shows that an approach based on characterizing the kinetic parameters of an anode respiring biofilm in a microbial electrolysis cell and using the Butler-Volmer Monod model to estimate substrate concentration holds promise. To the best of this author’s knowledge, this is the first study to test the predictive capability of a kinetic model for bio-anode polarization curves. Other studies, discussed in Chapter 2, which have developed bioelectrochemical sensors for biochemical oxygen demand, chemical oxygen demand, specific substrates, or other wastewater quality parameters or conditions have shown that sensors based on microbial electrolysis cells and microbial fuel cells can correlate these parameters or conditions with current or total charge generated, and that such sensors have good long term stability and reasonably low response times. However, these biosensors are often subject to thermodynamic limitations on current production, leading to a very low upper detection limit. Furthermore, these previously developed biosensors do not account for the limitations that anode potential can impose on microbial respiration. A sensor based on a three-electrode microbial electrolysis cell and a kinetic respiration model for anode respiring biofilms such as the Butler-Volmer Monod model addresses the issues of thermodynamic limitations and anode potential effects. Future work to include characterization of the effects of other environmental conditions such as temperature, pH, and solution electroconductivity and to further refine the electrochemical techniques and electrode materials could be expected to dramatically improve biosensing capabilities for applications in wastewater treatment process monitoring and optimization

Tidal Modulation of Ice Streams: Effect of Periodic Sliding Velocity on Ice Friction and Healing

This is an experimental study of how temperature, normal stress and and a periodic forcing velocity influence ice-on-rock friction. The motivation for the study is that many glaciers and ice streams show downstream velocities that are modulated by the tides, but with various sensitivities and styles of sliding. We found that by varying amplitude and frequency we could replicate the entire slip response of glaciers, including stick-slip, earthquake-like behavior

Cyberinfrastructure for Life Sciences - iAnimal Resources for Genomics and Other Data Driven Biology

Whole genome sequence, SNPs, copy number variation, phenotypes and other “-omics” data underlie evidence-based estimations of breeding value. Unfortunately, the computational resources (data storage, high-performance computing, analysis pipelines, etc.) that exploit this knowledge are limited in availability – many investigations are therefore restricted to the commercial sector or well-funded academic programs. Cyberinfrastructure developed by the iPlant Collaborative (NSF-#DBI0735191) and its extension iAnimal (USDA-#2013-67015-21231) provides the animal breeding community a comprehensive and freely available platform for the storage, sharing, and analyses of large datasets – from genomes to phenotype data. iPlant/iAnimal tools support a variety of genotype-phenotype related analyses in a platform that accommodates every level of user – from breeder to bioinformatician. These tools have been used to develop scalable, accessible versions of common workflows required for applying sequencing to livestock genomics

Hearing the Unheard: An Interdisciplinary, Mixed Methodology Study of Women’s Experiences of Hearing Voices (Auditory Verbal Hallucinations)

This paper explores the experiences of women who “hear voices” (auditory verbal hallucinations). We begin by examining historical understandings of women hearing voices, showing these have been driven by androcentric theories of how women’s bodies functioned leading to women being viewed as requiring their voices be interpreted by men. We show the twentieth century was associated with recognition that the mental violation of women’s minds (represented by some voice-hearing) was often a consequence of the physical violation of women’s bodies. We next report the results of a qualitative study into voice-hearing women’s experiences (n = 8). This found similarities between women’s relationships with their voices and their relationships with others and the wider social context. Finally, we present results from a quantitative study comparing voice-hearing in women (n = 65) and men (n = 132) in a psychiatric setting. Women were more likely than men to have certain forms of voice-hearing (voices conversing) and to have antecedent events of trauma, physical illness, and relationship problems. Voices identified as female may have more positive affect than male voices. We conclude that women voice-hearers have and continue to face specific challenges necessitating research and activism, and hope this paper will act as a stimulus to such work

Reconciling mantle attenuation-temperature relationships from seismology, petrology, and laboratory measurements

Seismic attenuation measurements provide a powerful tool for sampling mantle properties. Laboratory experiments provide calibrations at seismic frequencies and mantle temperatures for dry melt-free rocks, but require ∼10²−10³ extrapolations in grain size to mantle conditions; also, the effects of water and melt are not well understood. At the same time, body wave attenuation measured from dense broadband arrays provides reliable estimates of shear wave attenuation (Q_S⁻¹), affording an opportunity for calibration. We reanalyze seismic data sets that sample arc and back-arc mantle in Central America, the Marianas, and the Lau Basin, confirming very high attenuation (Q_S ∼ 25–80) at 1 Hz and depths of 50–100 km. At each of these sites, independent petrological studies constrain the temperature and water content where basaltic magmas last equilibrated with the mantle, 1300–1450°C. The Q_S measurements correlate inversely with the petrologically inferred temperatures, as expected. However, dry attenuation models predict Q_S too high by a factor of 1.5–5. Modifying models to include effects of H₂O and rheology-dependent grain size shows that the effects of water-enhanced dissipation and water-enhanced grain growth nearly cancel, so H₂O effects are modest. Therefore, high H₂O in the arc source region cannot explain the low Q_S, nor in the back arc where lavas show modest water content. Most likely, the high attenuation reflects the presence of melt, and some models of melt effects come close to reproducing observations. Overall, body wave Q_S can be reconciled with petrologic and laboratory inferences of mantle conditions if melt has a strong influence beneath arcs and back arcs

Common Genetic Variants Are Associated with Accelerated Bone Mineral Density Loss after Hematopoietic Cell Transplantation

BACKGROUND: Bone mineral density (BMD) loss commonly occurs after hematopoietic cell transplantation (HCT). Hypothesizing that genetic variants may influence post-HCT BMD loss, we conducted a prospective study to examine the associations of single nucleotide polymorphisms (SNP) in bone metabolism pathways and acute BMD loss after HCT. METHODS AND FINDINGS: We genotyped 122 SNPs in 45 genes in bone metabolism pathways among 121 autologous and allogeneic HCT patients. BMD changes from pre-HCT to day +100 post-HCT were analyzed in relation to these SNPs in linear regression models. After controlling for clinical risk factors, we identified 16 SNPs associated with spinal or femoral BMD loss following HCT, three of which have been previously implicated in genome-wide association studies of bone phenotypes, including rs2075555 in COL1A1, rs9594738 in RANKL, and rs4870044 in ESR1. When multiple SNPs were considered simultaneously, they explained 5-35% of the variance in post-HCT BMD loss. There was a significant trend between the number of risk alleles and the magnitude of BMD loss, with patients carrying the most risk alleles having the greatest loss. CONCLUSION: Our data provide the first evidence that common genetic variants play an important role in BMD loss among HCT patients similar to age-related BMD loss in the general population. This infers that the mechanism for post-HCT bone loss is a normal aging process that is accelerated during HCT. A limitation of our study comes from its small patient population; hence future larger studies are warranted to validate our findings

Genetic determinants of co-accessible chromatin regions in activated T cells across humans.

Over 90% of genetic variants associated with complex human traits map to non-coding regions, but little is understood about how they modulate gene regulation in health and disease. One possible mechanism is that genetic variants affect the activity of one or more cis-regulatory elements leading to gene expression variation in specific cell types. To identify such cases, we analyzed ATAC-seq and RNA-seq profiles from stimulated primary CD4+ T cells in up to 105 healthy donors. We found that regions of accessible chromatin (ATAC-peaks) are co-accessible at kilobase and megabase resolution, consistent with the three-dimensional chromatin organization measured by in situ Hi-C in T cells. Fifteen percent of genetic variants located within ATAC-peaks affected the accessibility of the corresponding peak (local-ATAC-QTLs). Local-ATAC-QTLs have the largest effects on co-accessible peaks, are associated with gene expression and are enriched for autoimmune disease variants. Our results provide insights into how natural genetic variants modulate cis-regulatory elements, in isolation or in concert, to influence gene expression