This project explores a grassroots organic food movement in Chengdu, China through a case study of an organic co-op in Anlong Village in the outskirts of the city. Due to its small size and inadequacy of official organic certification standards, the Anlong farmers refer to their produce “ecological” vegetables, as opposed to “organic” vegetables. Since the farms converted to “ecological” production in 2006, small, but growing number of Chengdu urbanites has turned to Anlong farms for a source of healthy and fresh organic produce while other affluent urban consumers enjoy organic products at metropolitan supermarkets. Given that the produce of these farms in Anlong is not officially certified, and given the fact that the cost of the produce is still on par with certified organic produce, why are they gaining popularity among urban customers who could easily buy similar produce at a shopping center nearby? Based on analyses of semi-structured interviews I conducted with Anlong farmers and customers and field observation, I argue that the consumption of Anlong products carries significance that extends beyond actual processes of production to suggest a symbolic purity untainted by the government association. In China, due to a series of reports on counterfeit food labels and the limited success of government regulations on food industry, government certified labels hardly evince moral attributes of organic foods, but generate negative interpretations. Anlong’s produce absent an official label shuns such suspicion and validates honest values that the organic agriculture elicits. 

Variation in river flow results in the expansion and contraction of the main channel, off-channel habitat, and the physical connections between these components. Hence, rivers are characterized by a mosaic of habitat conditions that shift across space and time. Here, we explore how a stream-dwelling fish integrates across spatial and temporal shifts in the availability of thermal and trophic resources. Across multiple years of variable flow, juvenile coho salmon (Oncorhynchus kisutch) have been observed feeding on an ephemeral food source in the cold main channel at night; returning to warm off-channel habitat during the day where their ability to metabolize large meals is greater. We hypothesize that an analogous tracking strategy is used to take advantage of in-situ prey and a shifting distribution of thermally optimal habitat within a single season. During the early summer in southwest Alaska, high lake levels flood the lower reaches of a third-order stream. As summer progresses, lake levels subside and the spatial distribution of thermal resources and connectivity of habitats within the stream is reduced. Preliminary analysis shows that juvenile coho prey heavily on stoneflies, which are concentrated in the cold main channel. Using snorkel surveys, PIT tagging, and gastric lavage, we will monitor changes in the spatial distribution and diet composition of fish over the course of a day and a season. We will compare these observations with changes in the distribution of warm habitat – recorded by i-button temperature loggers – to assess the ability of coho to integrate across shifts in resource availability. We aim to document the frequency of resource tracking in juvenile coho during this early summer period. The results have implications for understanding the importance of environmental complexity to endangered salmon populations and associated species in systems where humans have homogenized floodplains.

River-dwelling organisms inhabit ecosystems characterized by an assortment of habitats that vary in their nutrient availability, temperature, flow, food resources, and risk to predation. Specific habitats rarely offer the optimal conditions for all of these variables so mobile organisms typically use habitat combinations that offer complementary risks and benefits. I hypothesize that tributary junctions within river networks are particularly profitable for fish because they offer complementary resources across small spatial scales. To test this hypothesis, I conducted snorkel surveys during the heat of the day around nine tributaries divided equally among three spatial segments in a river system in Idaho. Each river segment displayed a varying degree of historically active wildfires and provides a mosaic of heterogeneity in riparian cover and nutrient inputs. Fish were counted downstream and upstream of tributary junctions to obtain a total density per stream reach area. Nitrogen and phosphorous concentrations of incoming tributary water were measured as a proxy of primary productivity in each environment. I also measured water temperature at tributary junctions to quantify potential temperature gradients for fish to use as a thermal refuge. My preliminary results suggest that fish tend to aggregate at the junctions of tributaries that are different in temperature and nutrient status from the main stem. As climate changes, it is important to understand how river networks provide prosperous options for fish. My work will hopefully contribute to efforts designed to prioritize river habitats for protection and restoration.

Current medical diagnostic gold standard, the Enzyme-Linked Immune-Sorbent Assay (ELISA), requires additional labels and amplification to determine the existence of interested molecules. Such process is extremely time consuming and expensive, and thus a fast and low-cost alternative is in demand. Our project aims to develop a rapid and affordable diagnostic biosensor platform that can be administered in the Point-Of-Care (POC) setting. In our silicon photonic sensor chip, we exploit a unique aspect of light when it is confined into a waveguide much smaller than its own wavelength. Since different molecules have different refraction index, the portion of light travels outside the waveguide, called evanescent field, is capable of sensing molecules binding on the sensor surface. While the design and fabrication of these biosensing devices can be done quickly and affordably, characterizing and experimenting the devices remains challenging because of the complexity of testing submicron-scale components. Chips require careful alignment of the optical I/O fibers with micron-tolerances. Microfluidics must be integrated to deliver reagents to specific regions of the chip. Real-time processing of optical spectra is needed to facilitate user operation. Hence we have customized a low-cost test bench to perform experiments and characterizations on the silicon photonic biosensors. I have designed the software, which employs industrial standard Model-View-Controller (MVC) architecture, for instruments integration, experiments orchestration as well as data acquisition and analysis. This software has greatly enhanced the efficiency of the biosensor platform development and future improvement is foreseeable because of the ongoing progress of full automation of experiment preparation. I have characterized multiple sensor devices through optical data acquisition, analysis, model fitting and key parameters’ estimation this software provides. Characterization results show great promise on the sensing capability of the platform and we will soon proceed to biomolecules (e.g. protein), and even cell (e.g. cancer cell) sensing.

 In silicon photonics, light propagation along a narrow silicon waveguide at the nanoscale produces an electromagnetic field that extends beyond the waveguide surface. Microrings can “couple” light from an incident waveguide at certain wavelengths. Silicon microring resonators can detect changes in the effective refractive index at the sensor’s surface by producing minute shifts in the peak resonance frequency. For biosensing applications, this resonance frequency shift is utilized to quantify the binding of biological analytes to the microring surface. Combined with a microfluidic platform for directing chemical and biological reagents over the microring resonators, silicon photonics offer a promising method of determining the concentrations and binding activities of analytes of interest in biological assays. However, protein fouling- the non-specific accumulation of protein molecules on a surface- in blood samples presents a significant challenge in the translation of these assays toward clinical adoption. Ongoing research has aimed to significantly reduce non-specific adsorption by coating the chip surface with polymer chains, resulting in a hydrated surface which resists protein fouling. In this study, charged polymer layers were grown on the chip surface by atom-transfer radical polymerization (ATRP), producing a coating of polymer brushes of high density and uniform length. Microring sensors were then functionalized by conjugating biological capture elements using standard carbodiimide chemistry to the terminal carboxylic acid residues of a surface-grafted polymer. The polymerization reaction conditions were optimized to minimize the thickness of the polymer layer while maintaining the non-fouling properties of the surface as a whole. Non-fouling properties were observed in the residual resonance shift following plasma and buffer rinse flows via a microfluidic platform. By minimizing the surface polymer thickness, we increase the physical limit of analyte detection on the microring surface, thereby maximizing the sensitivity of the biosensor while reducing “biological noise” due to non-specific protein adsorption.

As scientific studies have been focusing on generating alternative renewable energy sources, attention has been drawn to the need to store energy from the sun. One strategy is to develop catalysts capable of producing the energy-dense molecule hydrogen from the reduction of water. This kind of solar fuels system would allow for on-demand release of the energy that is stored in the chemical bonds of hydrogen through environmentally benign, carbon-free combustion. We are interested in the potential of catalyzing proton reduction with cobalt in a diimine-dioximato ligand framework. Previous studies on cobalt diglyoxime complexes have demonstrated the viability of such catalysts for proton reduction. Our research is focused on synthesizing bimetallic complexes using the same framework and studying the effect of another metal center on catalytic activity. Our entry into this chemistry relies on the initial synthesis of a doubly-deprotonated diimine dioximate complex of cobalt as a starting material, which can be considered as a “metalloligand”. The physical and electronic properties of this cobalt metalloligand and its multimetallic derivatives are studied by X-ray crystallography, 1H- and 13C-NMR, UV-visible spectroscopy, and cyclic voltammetry.

Thirty-five million people worldwide currently live with HIV. Despite the availability of highly-active antiretroviral therapy (HAART) which may prolong the lifespan of HIV patients, HAART does not target the latent viral reservoir in infected cells, enabling viral rebound in the absence of treatment. Introducing genetically-engineered DNA cleavage enzymes (endonucleases) into HIV-infected cells may disrupt the integrated provirus. The HIV-directed site-specific DNA cutting activity of these endonucleases operating in conjunction with cellular error-prone DNA repair mechanisms can introduce targeted mutations in the integrated HIV genome that prevent viral reactivation. We are investigating three classes of engineered endonucleases: homing endonucleases (HEs), zinc finger nucleases (ZFNs) and transcriptional activator-like effector nucleases (TALENS). While the DNA binding domains of these endonucleases allow for customization to a desired target sequence, delivering these enzymes to HIV-infected cells poses a challenge. TALENS in particular require a DNA coding sequence beyond the capacity of many viral vectors. Thus, a method of co-transduction must be pursued, whereby two halves of the endonuclease coding sequence are delivered by separate viral vectors and coordinately expressed in the target cell. My project aims to determine the optimal capsid serotype, promoter, and multiplicity of infection (MOI) for co-transducing HIV-infected cells using adeno-associated virus (AAV) vectors. I first determined AAV-1 to be the optimal serotype of AAV for infecting SupT1 cells, a cell line used as a model for HIV-infected T-cells. I then constructed two sets of AAV-1 viral vectors to express either Green Fluorescent Protein (GFP) or a red fluorescent protein (mCherry) as surrogates for endonuclease genes and infected SupT1 cells with both sets of vectors at variable MOIs, using flow cytometry to determine the rate of co-transduction. Through this method, I have successfully co-transduced cells with two AAV vectors. These results will have applications in future HIV research and clinical therapy.

Colorectal cancer (CRC) is the third most prevalent (136,830 new cases estimated for 2014) and fatal cancers (50,310 deaths estimated) in the world, according to the American Cancer Society. Despite an expanding knowledge of its molecular pathogenesis during the past two decades, robust biomarkers to enable surveillance, screening, and primary prevention of CRC are still lacking. In the present study, we propose a targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based metabolic profiling approach for highly sensitive and specific colorectal cancer (CRC) detection using human serum samples. 158 metabolites from 25 metabolic pathways of potential significance were monitored. 234 serum samples from three groups of patients (66 CRC patients, 76 polyp patients, and 92 healthy controls) were analyzed. We detected 113 metabolites out of the 158 monitored, with 42 of them showing statistical significance between CRC cancer and healthy controls, 48 showing statistical difference between CRC cancer and polyp patients, and 8 between healthy controls and polyp patients. Partial least squares-discriminate analysis (PLS-DA) models established using 13 or 14 metabolites proved to be powerful for distinguishing CRC patients from either healthy controls or polyp patients, respectively. Receiver operator characteristic (ROC) curves generated based on these PLS-DA models gave high sensitivities, good specificities, low false discovery rates, and excellent areas under the curve (0.93 and 0.95 respectively, for differentiating CRC patients from healthy controls or polyp patients). Monte Carlo cross validation (MCCV) was also applied, demonstrating the robust diagnostic power of this metabolic profiling approach. To the best of our knowledge, this is the first time that an LC-MS/MS targeted serum metabolic profiling approach has been applied for comparing CRC patients to healthy controls and polyp patients, and our results demonstrate that a panel of serum metabolites enhanced by clinical factors (age, gender, smoking and alcohol status), can potentially serve as novel disease biomarkers for CRC diagnosis.

As renewable energy constitutes a greater portion of the generation fleet, so does the importance of modeling uncertainty as part of integration studies. In pursuit of optimal system operations, it is important to capture not only the definitive behavior of power plants but also the risks associated with system wide interactions. Load forecasting is an area of renewable energy integration studies that is often neglected, chiefly because of a lack of available data. In this research, the dependence of load forecast errors on external predictor variables such as temperature, day type, and time of day was examined. The analysis was utilized to create statistically relevant instances of sequential load forecasts with only a time series of historic, measured load available. The creation of such load forecasts relies on Bayesian techniques for informing and updating the model, thus providing a basis for networked and adaptive load forecast models in future operational applications.

Landscape Architecture professor Daniel Winterbottom leads a Design Build studio program, that spans two quarters, for graduating 3rd year undergraduate students every year. During Winter Quarter, students are split into teams to come up with schematic designs for a real client, and real build site. This year, the Japanese Cultural and Community Center, a non-profit organization, enlisted the help of Daniel and the 3rd year Landscape Architecture students to design an outdoor garden for their community. It was required that the garden be symbolic of the Japanese history, and culture, yet have aesthetic qualities of the Pacific Northwest. After a series of reviews, a final design which pulls ideas from each team is synthesized. Construction drawings are then created in preparation for Spring Quarter during which the students, with help from volunteers, will construct the project. Three years of learning design principles and disciplines are culminated in the final six months before graduation, where by June 2014 the garden will be open to the public.

Learning and memory are influenced both by adult neurogenesis and circadian rhythmicity; however, it is unclear if and how the biological clock influences neurogenesis. The BMAL1 protein is an essential component in the molecular clock. Transgenic Bmal1 -/- (knock out) mice, which lack the gene to produce this protein, are completely arrhythmic. Furthermore, the Bmal1 knockout mouse demonstrates poor learning and memory compared to its wild type littermate control which retains both Bmal1 alleles. As an animal that is both arrhythmic and exhibits deficits in learning and memory, the Bmal1 knockout mouse provides the opportunity to investigate the potential interaction of the molecular clock and neurogenesis. I hypothesized that the rate of adult neurogenesis in the hippocampus of the Bmal1 knockout mouse would be reduced as compared with wild type littermate controls. To quantify this, I used immunohistochemistry to fluorescently mark proliferating cells with bromodeoxyuridine (BrdU) in the subgranular zone (SGZ) of the hippocampus. BrdU is a synthetic nucleotide, intraperitonealy (IP) injected prior to brain collection, and incorporated into the DNA of newly dividing cells. I found that the Bmal1 knockout hippocampus had significantly reduced rates of cell proliferation and survival compared with wild type controls. Thus, BMAL 1 is required for adult neurogenesis in the hippocampus. This finding now invites the consideration of whether BMAL 1 protein plays a direct cellular role in adult neurogenesis, or if it is the disruption to systemic circadian rhythmicity which compromises neurogenesis.