Biochar is the product of biomass that undergoes pyrolysis, the process of thermal degradation in the absence of oxygen and is a type of charcoal. Research has shown biochar to be an effective soil amendment but the optimal levels of incorporation are unknown. This study examines if an optimal level for plant growth exists and to determine if introducing a stress factor will alter the optimal point. Five levels of biochar amendments at 0%, 1%, 3%, 5%, 10%, and 15% by volume have been made into root media with high or low nutrient availability as a stress factor. Sweet peppers plants were grown from seed in flats for one month and seedlings were transferred to larger pots with appropriate biochar level. They will be grown for two months and destructively harvested for dry biomass data. We hypothesize the pepper plants will have an optimal biochar level for growth and this level will change with plant stress.

In recent years, the unique optical properties supported by noble metal nanostructures have fostered great interest in the field of biosensing. Studies have concluded that incident light can excite collective electron oscillations, called surface plasmon polaritons (SPP), which propagate as waves along planar metal film surfaces. When confined to sub-wavelength physical features, these waves resonate and produce tremendous, localized electric fields that significantly enhance optical phenomenon. Surface-enhanced Raman spectroscopy (SERS) arises from the concentrated electric fields supported by irradiated nanostructured noble metal films. Due to its chemical specificity, and extraordinary Raman signal intensification, SERS has emerged as powerful tool for chemical and biological sensing applications. Our group utilizes lithographic techniques to manufacture arrays of quasi three-dimensional (Q3D) nanostructured patterns with precise geometric dimensions. The physical dimensions of Q3D nanostructures may be tuned such that incident light selectively induces electric field enhancement on the top, continuous gold surface that contains nanoholes, or in the bottom, discontinuous phase comprised of gold nanodisks. As a consequence, Q3D nanostructured arrays may be specifically designed to detect larger analytes (e.g. microorganisms) that contact the top continuous phase, or molecular species capable of passing through nanoholes to contact the nanodisks. In this study, Q3D nanostructures designed for nanodisk enhancement are utilized to detect pesticide molecules at low concentrations in aqueous solution. Results from this research may aid in the development of a microfluidic device for on-site environmental monitoring of river systems. 

Embryonic stem cells are isolated from the early developing embryo and are capable of forming the different cell types found in the body. Understanding how these cells develop and maintain their specialized state is critical to understanding how they function. We hypothesize that embryonic stem cells acquire a unique metabolic state that aids them in maintaining their specialized state. Using two distinct mouse pluripotent states, embryonic stem cells (ESC’s) and epiblast stem cells (EpiSC’s) representing cells isolated from the inner cell mass of the blastocyst and the epiblast, a later stage in embryonic development, we found that EpiSC’s are much more glycolytic in terms of their energy usage compared to ESC’s as measured by oxygen consumption and extracellular acidification rates. Furthermore, using quantitative polymerase chain reaction experiments, we found that genes key to regulating and maintaining high rates of glycolysis are significantly upregulated in EpiSC’s compared to ESC’s. We showed that the overexpression of HIF1α, a known key regulator of these glycolytic genes, in ESC’s is able to shift the ESC’s towards a more glycolytic metabolic state and cellular morphology reminiscent of EpiSC’s. In addition, transition of ESC’s to EpiSC’s using the known chemical inducers Activin and Fibroblast Growth Factor 2 revealed that changes in the expression of metabolic genes occur prior to changes in expression of cell fate markers, which suggest that a metabolic transition in the ESC’s may be key in its transition to an EpiSC-like state.

Inhibitor of differentiation (Id) is a transcription factor that negatively regulates basic helix-loop-helix (bHLH) transcription factors. Of four Ids identified (Id1-4), Id1 and Id3 have been shown to regulate glial development in the central nervous system. In the retina, there is a special type of glia called the Müller glia. Currently, it is not known whether the Ids are important for Müller glial development. Knockout studies in mice demonstrated that Id1/Id3 double knockout (KO) are embryonic lethal, while either Id1 or Id3 KO mice develop grossly normal. We investigated if Id1/Id3 are necessary for Müller glial development by performing Id1 shRNA knockdown (KD) in Id3 KO retinas. Five Id1 shRNAs were tested for their efficiency in NIH 3T3 cells (mouse fibroblast cell line), and the Western blot results showed over 90% decrease in Id1 expression using three shRNAs. We will electroporate Id3 KO retinal explants with these Id1 shRNAs and determine the effects of Id1/Id3 loss on Muller glial development. We expect to see a reduction in the number of Müller glia if Id1/Id3 play a role in their development.

According to the 2011 Urban Mobility Report, roadway congestion cost a total of $101 billion dollars and a total delay of 4.8 billion hours in the US in 2010, with approximately 60% of the congestion occurring on freeways. Given the severity and economic costs of freeway congestion, strategies to mitigate congestion based on real-time data and cutting edge technologies have obtained broad attention. Integrated Corridor Management (ICM) is an emerging management strategy in this category. ICM aims to understand how non-recurrent congestion causes, such as incidents, affect both freeway and nearby arterial corridors, and how network-wide congestion could be mitigated by diverting traffic to nearby arterials with extra capacity. This study investigates the effectiveness of the ICM technology and possible impacts on local streets for the Seattle Department of Transportation. A microscopic simulation model was built in VISSIM (a software often utilized to model the study area and traffic behavior) to conduct what-if analyses under the ICM strategy. The model studies the SODO area network, which includes northbound I-5 and the nearby major parallel arterials. To simulate practical and reliable results, the model first needs to be calibrated to ensure the model output can replicate observed field data. The sensitivity analysis between different driving behavior parameters in VISSIM, such as headway time, standstill distance, and maximum deceleration for lane changing, and the modeled vehicle throughput was performed during the calibration process. Results of this research can be useful by providing logical rationale for how driving behavior parameters can be adjusted to achieve desired volume results. This specific calibrated model serves as the stepping-stone for future research in the ICM project, where dynamic routing is implemented to investigate how traffic is diverged during accidents within the study network.

Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease in the United States and much of the world. NAFLD resembles alcohol-induced liver injury, but occurs in patients with little to no history of alcohol consumption. It is a fairly benign condition, but can progress to a more advanced disease known as nonalcoholic steatohepatitis (NASH); many factors have been implicated in the pathogenesis of this transition (ER stress, mitochondrial dysfunction, insulin resistance, oxidative damage), but the exact mechanism remains unclear. Iron, although essential to many cellular processes, leads to increased oxidative stress and may be significant to NASH development via dysregulation of microRNA expression. To test our hypothesis, we measured microRNAs known to regulate processes marking the transition of NAFLD to NASH, such as apoptosis, inflammation, and lipid metabolism with real-time reverse-transcription PCR in a NAFLD mouse model. By comparing microRNA levels from the liver tissue of iron-treated vs. non-iron-treated NAFLD mice, we can survey effect of iron in exacerbating NAFLD via differential microRNA expression. As a regulator of cellular gene expression by transcriptional inhibition of messenger RNA, microRNA have the capacity to predict cellular processes before physiological changes are seen in the affected tissue. Thus, our results can more specifically describe differentially regulated genes during NASH development in the context of iron. After profiling our treatment groups, we will use bioinformatics to identify gene targets of the significant microRNA and validate the relationship of microRNAs and target genes in vitro. We will also compare the microRNA expression profiles of liver tissue and serum to identify serum biomarkers of NASH. In addition to the mechanistic insights elucidating the pathogenesis of NASH, our findings may lead to alternative non-invasive methods for NASH diagnosis, as liver biopsy is currently the only method for diagnosing NASH.

Domoic acid (DA) is a toxin that accumulates in edible shellfish through filter feeding and is the causing agent of a serious neurological condition known as amnesic shellfish poisoning. The increasing intensity and frequency of DA-producing algal blooms has drawn more attention to develop fast and effective ways to detect and quantify DA. At Yu Lab, we developed an effective method for the fast detection and quantification of DA using a surface plasmon resonance coupler and disperser (SPRCD) sensor. The SPRCD sensor is an optical instrument based on the coupling of light to electronic oscillations at the interface between a gold surface and a dielectric material. The sensor measures changes in the optical properties of the interface caused by the binding of a specific molecule to the gold surface. By modifying the gold surface such that only the molecule of interest adsorbs, we are able to detect and quantify low concentrations of the toxin in a sample. Using our method, we can detect concentrations of DA as low as 0.1ng/ml and quantify DA in concentrations ranging from 5ng/ml to 10ug/ml.

The ability of the semiconductor FeS₂, or iron pyrite, to absorb sunlight makes it a cheap and abundant potential material for use in solar cells. Current photovoltaic studies using nanocrystalline pyrite rely on the synthesis of small, uniform crystals. However, pyrite naturally takes different crystal shapes depending on the conditions of its formation. Even the same shapes can have different surface chemistry, which directly impacts crystal growth direction. The mechanisms behind pyrite synthesis are not fully understood and are difficult to discern out of the complexity of real reaction mixtures. Density functional theory (DFT), a method for simplifying and calculating the quantum mechanics behind a physical system, allows for the numerical approximation of pyrite’s material properties. Our group performed DFT calculations of two common pyrite surfaces using the supercell approach. Slabs of pyrite separated by artificial vacuums were allowed to come to energy minimums. We hypothesized that the energetic and electronic properties of real pyrite surfaces would match those of the DFT-optimized supercells. Preliminary results agreed with published experimental data. After ensuring that our computations could reproduce physical properties, we put small molecules that could be found in reaction mixtures into contact with the lowest-energy pyrite surface and optimized using the same methods. The most-favorable interaction sites between pyrite and the reactants needed to make it are key components to the mechanisms of pyrite growth. Once these mechanisms are known, synthesis conditions can be controlled to produce only crystals fit for use in photovoltaic cells.

Complexity of today’s financial markets and its services demand high degree of financial knowledge than ever before from individuals in order to make prudent financial decision. Early studies have shown that financial illiteracy is widespread and that those who are financially illiterate display both poor borrowing and saving behavior. Using household data from HRS (Health and Retirement Study), I test the hypothesis that financial literacy is a strong determinant of accumulation of wealth. That is, those who possess greater financial knowledge accumulate more wealth than those who have low or no financial knowledge. Moreover, I extend the analysis in an attempt to answer what drives individuals to acquire financial knowledge. My first hypothesis is that poor living circumstances at young age make individuals become more aware of the importance of finance: hence, it is a driver of financial knowledge. My second hypothesis is that past experiences (loss of portfolio value from recession and poor health) play a role. Data on several components of wealth, financial literacy, and past information were compiled and will be used to run regression to answer underlying questions. Finally, I explain what it means to be financially literate. The purpose of this analysis is to stress the importance of being financially literate and that finance class should be part of school’s core curriculum. This will better prepare our descendents for far more complex financial markets that lie ahead.