2010-11 Levinson Scholar
Michael Choi is very interested in biological and biochemical research especially with applications towards helping patients. Since his freshman year, he has been investigating embryonic stem cells and stem cell maintenance in the Ruohola-Baker laboratory, particularly focusing on metabolism. Stem cells play a critical role in development and disease; by better understanding how these cells function in both normal and pathological conditions, scientists can learn how to control, treat, and cure disorders that arise. His undergraduate research experience and his majors in biochemistry and chemistry with a minor in mathematics have convinced him to pursue a career in science. In the future, he is interested in attending graduate school and plans to further investigate the biology of disease and research cures from a biochemical, chemical, and mathematical perspective.
Mentor: Hannele Ruohola-Baker, Biochemistry
Project Title: Characterizing the Metabolic State of Cancer and Embryonic Stem Cells
Abstract: Cancer cells grow rapidly and uncontrollably, invading normal tissue and metastasizing throughout the entire body. The proliferative ability of cancer cells is reminiscent of the properties of earlier stages of development, such as embryonic stem cells. Some of the most aggressive tumors have a similar gene expression signature to embryonic stem cells. Furthermore, low oxygen concentration and hypoxic environments are common among aggressive tumors. I have shown that a link between hypoxia and the activation of stem cell markers such as miR-302 exist. Hypoxia inducible factor, HIF, a transcription factor that is stabilized in hypoxia, can change a cell’s metabolic state and induce the expression of key stem cell markers. I am now testing whether human embryonic stem cells and cancer stem cells share a characteristic metabolic signature and whether this signature is acquired by HIF activation. For this analysis, I established a quantitative real time polymerase chain reaction based assay to determine the number of mitochondria in a cell. Furthermore, I show, in both human and mouse cells, that cells earliest in development have fewest mitochondria and as development progresses, mitochondria increase. However, these mitochondria do not seem to be active. We will proceed in testing the specific stage mitochondria are activated, and the specific role of HIF in creating this unique stem-cell-like metabolic state in pathological and normal conditions.
In his first year as an undergraduate, Elliot developed a strong interest in language learning as he took Psychology and Linguistics classes while studying Italian. His experience in research prior to these classes eventually led him to the Cognitive Neuroscience of Language laboratory at the University of Washington. Since joining the lab 2 years ago, Elliot has worked alongside Professor Lee Osterhout and his graduate students to explore how the brain’s electrophysiological response changes as adults increased exposure to a second language. In his senior year, he will continue to explore some of the questions on language learning through the study of English native speakers learning Italian. Although he is still exploring the options, Elliot plans to enter a graduate or professional program where he can continue research in neuroscience beyond the undergraduate level. He will graduate this spring with a B.A. in Romance Linguistics and a B.S. in Psychology through the departmental honors program.
Mentor: Lee Osterhout, Psychology
Project Title: Neurobiology of Language Learning
Abstract: Event-related potentials (ERPs) are variations in brain activity measured by changes in voltage over time on the scalp. ERPs reflect the summed activity of cortical pyramidal neurons in response to a given stimulus. Although localizing the sources of an ERP signal is problematic, we propose a method for using a measure of ERP additivity to determine whether individual stimulus parameters are processed by overlapping or independent neural sources. Applying this method to language will allow us to describe the functional segregation of linguistic processing in the brain, and compare hypothetical rules of grammatical structure to those which are neurally instantiated. Additive methodologies suggest that the degree to which the mathematical sum of the waveforms resulting from a single violation approximates the waveform from the double violation indicates the independence of neurocognitive resources engaged in the processing of the respective feature. In native speakers, grammatical anomalies elicit positive deflections of the ERP waveform, peaking approximately 600ms after the onset of the stimulus. In order to further examine whether the processing of multiple types of syntactic anomalies is the result of independent or overlapping neural generators, ERPs will be recorded from native Italian speakers and native English speakers learning Italian as they read sentences, a subset of which contained article-noun pairs which were ill-formed with respect to syntactic agreement. This paradigm allows for the direct comparison of neural responses to number and gender features within a single stimulus. We propose to expand this research by exploring the neural dynamics that occur when a second language is acquired. Our additivity paradigm will make it possible to evaluate not only when rules become syntactically realized, but also whether different syntactic features are encoded individually or as a whole.
Rebecca Emery moved to Seattle from her home state of Minnesota to attend the University of Washington. After declaring a psychology major, she became a member of the departmental honors program and began working under Dr. Kevin King, a child clinical psychologist. Through working with Dr. King, Rebecca became interested in the relationship between trait impulsivity and the binge eating behavior common to bulimia nervosa. Specifically, Rebecca is interested in better understanding the role of this distinct personality construct in the etiology of bulimia nervosa in addition to how it functions to support binge eating behavior. Currently, Rebecca is a senior working towards a double major in psychology and philosophy. After graduation, she intends to pursue a doctoral degree in clinical psychology and continue conducting research in attempts to better understand abnormal behavior.
Mentor: Kevin M. King, Psychology
Project Title: Binge Eating Behavior: An Inestigation on the Moderating Role of Negative Urgency in Relation to the Dual Pathway Model
Abstract: Studies have shown that impulsivity is related to bulimic symptoms such as binge eating. However, the definition of impulsivity has been widely mixed and inconsistent throughout the literature. Recent research has shown impulsivity to consist of five distinct facets. Of these facets, negative urgency, defined as the tendency to act rashly when emotionally distressed, has been found to be related to bulimic symptoms. The proposed investigation will explore these findings in greater depth by examining the relationship between negative urgency and binge eating behavior in two different but related studies. The first study will collect data from a large sample of college female students through a web-based survey and will assess the moderating role of negative urgency on the two regulatory pathways of the dual pathway model of bulimia nervosa (i.e. dieting and negative affect). Findings from the first study will help to clarify the role of negative urgency in relation to binge eating behavior. The second study will also use a sample of female college students and will investigate the effects of negative urgency on food consumption after an experimentally induced negative mood to demonstrate a natural reaction to such a situation. Findings from the second study will attempt to provide a laboratory demonstration supporting the findings from the first study by showing that negative urgency increases binge eating within individuals. Overall, the combined results of these studies will help to inform the scientific community as to the effects of negative urgency on binge eating behavior in relation to bulimia nervosa, which may lead to clinical and therapeutic implications.
Adrian Laurenzi first became interested in the intersection of computation and biology when he was a senior in high school. He worked on a project in at a lab at the University of Arizona to understand a plant pathway used synthesized secondary metabolites. While working at the U of A he devised a computational method that helped to identify and isolate one of the enzymes in the pathway. Almost immediately after entering UW as a freshman Adrian joined Ram Samudrala’s computational biology group to pursue his interest in computational biology. As a member of Ram’s group Adrian has worked on a number of independent projects concerned primarily with drug discovery. By integrating software developed in Ram’s group Adrian developed a computational method to identify protein targets in the malaria parasite for which an inhibitory compound would produce minimal side effects in humans. More recently Adrian has been working to apply and adapt protein structure prediction software to expressed sequence tag (EST) databases in order to improve our ability to predict the functionality of novel genes within the databases. This could accelerate the discovery of novel genes and gene networks and has important implications in medicine and drug development. In the future Adrian plans to continue his work in biomedical computation by developing open source software as an independent consultant or academic scientist. Adrian feels that creating open source software is the most effective way to make an impact as a scientist because his software will help enable the discoveries of a potentially large number of other scientists. He strongly believes in creating software that is free and open so that it is available for other scientists to use and build upon.
Mentor: Ram Samudrala, Microbiology
Project Title: Optimization of protein structure prediction software for EST data
Abstract: Large databases of expressed sequence tags (ESTs) are available containing the expressed genes from a tremendous variety of organisms. Many projects such as the Gene Index Project at Harvard University are underway, databasing the expressed genes from a tremendous variety of organisms. There are over 60 million ESTs in GenBank representing well over half of all GenBank entries. To make efficient use of EST data computational techniques have been developed to analyze and organize EST databases. ESTs have been useful in discovering new genes, understanding gene expression and regulation, and constructing genome maps, all of which have important implications in medicine. However, the utility of EST data relies upon our ability to make accurate annotations that describe the functionality of the ESTs in the source organism. Presently most approaches used to annotate ESTs rely on sequence-based comparison methods such as BLAST. This is limiting because the function of a protein is dependent upon its tertiary (3-D) structure. Therefore, the ability to reliably predict the functionality of an EST could be improved if we were able to accurately predict the structure of the proteins that ESTs encode. We have demonstrated that ProtinfoAB and Rosetta3.1 can reliably predict the structures of parts of proteins encoded by sequences that contain approximately 75% or more of the full-length protein sequence suggesting these methods would be useful in annotating at least a subset of sequences from an EST database. We propose to optimize prediction of partial structures of proteins encoded by ESTs by combining ab initio and template-based protein structure prediction methods: ProtinfoAB and ProtinfoCM. Optimization of structure prediction methods for EST data will enhance our ability to predict the functionality of ESTs enabling more informed bench experiments and expediting the discovery of new genes with potential utility in medicine.
Currently a student in the Department of Bioengineering, Chris Mount’s research interests involve developing drug delivery systems to achieve targeted delivery of chemotherapeutics and contrast agents for treatment and imaging of cancer. He has pursued this research under the mentorship of Dr. Suzie Pun, also in the Department of Bioengineering. Collaborating with other researchers in the lab, Chris has recently been working to develop nanoparticles composed of a synthetic polymer for drug delivery applications. With the support of the Levinson scholarship, he hopes to elucidate the morphologies of these particles and evaluate their potential for enhancing the efficacy of anticancer agents. Following graduation, Chris plans to enter a combined M.D./Ph.D. program to train for a career in biomedical research.
Mentor: Suzie Pun, Bioengineering
Project Title: Design of polymeric filomicelles for enhances efficacy of chemotherapeutic delivary
Abstract: Despite decades of research in cancer biology, current therapeutic options for cancer patients remain limited. The administration of chemotherapeutic compounds remains one of the preeminent tools used by oncologists, but these treatments are nonspecific and tend to result in widespread systemic toxicity, limiting the maximum dose that can safely be administered. Moreover, the efficacy of these agents is limited by poor tissue penetration, multidrug resistant cancers, and solubility. Encapsulating chemotherapeutics within polymeric micelles provide one route to overcoming these challenges. Encapsulation enhances solubility, can inhibit P-glycoprotein membrane transporters responsible for multidrug resistance, and achieve specific delivery to tumor sites by exploiting the Enhanced Permeability and Retention (EPR) effect. Recent literature has highlighted the importance of micelle architecture in the effectiveness of polymeric micelle drug carriers, with notable attention to filament-type micelles, or filomicelles. We propose the use of polymeric filomicelles consisting of a poly(ethylene oxide) -poly(hydroxybutyrate) diblock copolymer for encapsulation of the chemotherapeutic doxorubicin to enhance its efficacy as an anti-cancer agent. Diblock composition will be designed to achieve optimal doxorubicin content, release kinetics, and cytotoxic efficiency in vitro. Doxorubicin-loaded filomicelles are anticipated to display enhanced chemotherapeutic efficacy against multidrug-resistant cancerous cell lines and exhibit enhanced tissue penetration ability in three-dimensional multicellular spheroid tumor models. This research is therefore expected to contribute a valuable, novel delivery vehicle for enhancing the effectiveness of chemotherapeutic agents.