PURPOSE: The aim of this study is to characterize the patterns of medication use by early-stage breast cancer (ESBC) survivors from diagnosis to 1 year post-chemotherapy. METHODS: A single-center longitudinal study was conducted with ESBC patients diagnosed between December 2011 and June 2014. Data on the medication use of individual patients were retrieved from prescription databases, supplemented by records from the National Electronic Health Records. The data covered the period from ESBC diagnosis to 1 year post-chemotherapy. Medication types were classified according to the World Health Organizations Anatomical Therapeutic Chemical classification system, and medication for chronic diseases was created by adapting a list of 20 chronic diseases provided by the U.S. Department of Human and Health Services. RESULTS: Of the 107 patients involved in the study (mean age 51.1 ± 8.4 years; 78.5 % Chinese), 46.7 % manifested non-cancer comorbidities, of which hypertension (24.3 %) was the most prevalent, followed by hyperlipidemia (13.1 %) and diabetes (5.6 %). Calcium channel blockers (12.1 %) and lipid-modifying agents (11.2 %) were the most common chronic medication types used before chemotherapy, and their use persisted during chemotherapy (10.3 and 11.2 %, respectively) and after chemotherapy (11.2 and 13.1 %, respectively). Hormonal therapy was the predominant post-chemotherapy medication (77.6 %). A statistically significant increase (p < 0.0001) was observed in the mean number of chronic disease medication classes prescribed to patients between the pre-chemotherapy (0.53 ± 1.04) and chemotherapy (0.62 ± 1.08) periods and between the chemotherapy and post-chemotherapy (1.63 ± 1.35) periods. CONCLUSIONS: There is an increase in trend of chronic medication usage in breast cancer survivors after cancer treatment. This study provides important insights into the design of medication management programs tailored to this population. Future studies should incorporate a control population to improve the interpretation of study results.

Mass spectrometry has revolutionized protein identification in the last decade. Efficient algorithms have been developed to identify peptides that are encoded in protein databases. This work presents novel methods for interpretation of mass spectrometry data on compounds that are not directly encoded in protein databases. One example of compounds that are not in protein databases are nonribosomal peptides. Because of the specialized machinery that synthesizes these compounds and their unique (often cyclic) structure, traditional database search tools cannot analyze these data. With new algorithmic developments, we show that mass spectrometry can speed up the process of characterization of cyclic peptides which are compounds of great interest in drug discovery. A second class of peptides that are not encoded in protein databases are peptides that are the product of fused proteins. This type of peptides can arise from cancer proteomes, where the peptide spans a fusion point. Again, traditional search tools cannot identify fusion peptides because they are not directly encoded in the databases. We also present an algorithm to identify such peptides. Finally, mutated and modified peptides are also not directly encoded in protein databases. Existing tools are particularly inefficient when searching for unexpected modifications. Although this problem has been addressed with "blind" database search tools, their running time is too demanding to be practical for large databases. We develop new methods to search for mutated and modified peptides that are orders of magnitude faster than existing tools. Overall, with new algorithmic developments we enable mass spectrometry to characterize novel compounds that evade identification with traditional MS/MS tools

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death worldwide; 80% of the cases are caused by chronic hepatitis B (HBV) infections that result in liver cirrhosis. Current disease models are composed primarily of cell lines transfected with HBx, a HBV protein shown to promote tumorigenesis. These models can be improved upon, as the transfected cell lines are usually cancerous or immortal already. Transfection of primary hepatocyte cell lines is ideal, but studies have demonstrated that the standard plasmid-based method has a very low targeting efficiency of ̃3%, and must be replenished due to the limited life span of the cells. Transfection of human embryonic stem cells (hESCs) using a bacterial artificial chromosome (BAC) recombineering system followed by differentiation of positive clones into hepatocytes can be a feasible alternative. Firstly, the BAC recombineering system has been shown to have a vastly improved targeting efficiency of ̃20%. Secondly, the immortal lifespan of stem cells ensures that transfection and screening only be performed once. Here, we have created a stem-cell model for HBV-dependent HCC by transfecting HUES 8 embryonic stem cell lines with HBx using a BAC recombineering system. Once differentiated into hepatocytes, they can serve as a cell culture model for HCC as well as an in vivo model via human hepatocyte repopulation in immunodeficient mice and subsequent development into cancerous human liver tissue

This music score was submitted for the Kaleidoscope 2020 Call for Scores, an open access collaboration with the UCLA Music Library.

This essay uses the lens of historical-structural analysis to examine how the history of municipal land use policies and urban agriculture in the U.S. informed the policy design of California’s Urban Agriculture Incentive Zones (“UAIZs”) and their resulting failure to increase land access and security for community food producers. It argues that UAIZs sit at the end of a long history of lot conversion programs that have been used for urban crisis management in the U.S. In this process, the essay examines the role that land insecurity has played in redevelopment and land commodification and financialization more broadly, how equitable urban agriculture requires both rearticulating the functions that community food production play in cities and reasserting the right not only to occupy but to manage land in a way that serves one’s community (land equity), and why practitioners and researchers need to reframe the questions they ask when designing food systems policies and research.

Face perception is the specialized ability to process information about faces. This skill is developed early in life; and as adults, we are experts at categorizing, searching and discriminating individual faces. In this dissertation, we investigated mechanisms selective for processing important facial properties - gender, ethnicity, and individual identity - using a combination of psychophysical and fMRI adaptation method. In Chapter 2, we found that there exist both singly (selective for either gender or ethnicity) and jointly (selective for both gender and ethnicity) tuned mechanisms. Using a functional magnetic resonance imaging (fMRI) adaptation paradigm in Chapter 3, we identified cortical regions selective for the gender, ethnicity and identity of individual faces. Finally, in Chapter 4, we examined whether our face adaptation technique on performance in search and discrimination tasks, and found that adaptation had no discernible effects on performance on these tasks