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Proteome-wide analysis pf allele-specific SNP-TF interactions relevant to Alzheimer's Disease
No full textProtein microarray technology is quite powerful as it allows for the profiling process of thousands of full-length proteins simultaneously. This artificial platform provides researchers opportunities to understand many molecular activities, including protein-protein interactions and protein-DNA interactions. Through use of a 1,720-feature transcription factor (TF) microarray, the binding activities between external proteins or DNA and TFs immobilized on the microarray can be clearly observed and analyzed. To this end, we have applied this technology towards the study of allele-specific TF-DNA interactions of GWAS Alzheimer’s Disease SNPs to reveal the casual mechanisms behind to better understand the pathology of AD.
Alzheimer’s Disease is one of the most widely known neurodegenerative disorders that affects the elderlies over seventy. Scientists are making efforts to develop an effective treatment for cure. GWAS can be utilized as a powerful tool in identifying novel risk factors for this disease. However, establishing a causal relationship remains a long way to go. Given that most of these risk factors fall within noncoding regions of the genome, we decided to understand allele-specific TF-DNA interactions to find those SNPs with potential abilities to alter gene expression in vitro and their linkages to the etiology of AD. In general, 21 allele pairs were competitively screened on the protein microarray, which led to the identification of 87 allele-specific interactions. Two allele pairs were chosen due to their strong TF-specific binding preferences for further validation. CRISPR and luciferase assay were performed
In Vitro Modeling of Cellular Interactions Between γδ T Cells and Fibroblasts Associated with Fibrotic Tissue Microenvironments
No full textThe foreign body reaction (FBR) remains one of the most common complications of surgical implants, such as cardiac pacemakers and breast implants. Recent studies have revealed that γδ T cells may be important drivers of the FBR and may recognize a wide range of ligands present in the fibrotic environment, as their activation is not restricted to MHC-presentation of peptide antigens. In this study, we developed an in vitro Transwell coculture platform to model the fibrotic microenvironment to assess whether the γδ T cells are actively contributing to the FBR by promoting fibroblast activation. We found that interleukin (IL)-17 producing γδ T cells alter the transcriptional expression of extracellular matrix and IL6-related genes in dermal fibroblasts in vitro. Further, we showed that IL17A secretion by IL17-producing γδ T cells is responsible for upregulating Il6 expression and its related signaling and activation pathways in dermal fibroblasts in vitro. These results demonstrate potential intercellular communication pathways between γδ T cells and fibroblast that may be functionally relevant to fibrotic tissue microenvironment
INTEGRATED GLYCOPROTEOMIC ANALYSIS OF N- AND O-LINKED GLYCOPROTEINS
No full textGlycoproteomics, the study of glycosylated proteins, holds immense promise in understanding biological systems and disease mechanisms, particularly in oncology. This thesis presents a comprehensive investigation into integrated glycoproteomic analyses for characterization of glycans and glycosylation sites using mass spectrometry, focusing on the challenges associated with separating and characterizing O-linked glycopeptides alongside N-linked glycopeptides. The study builds upon novel and existing methodologies, leveraging a combination of intact glycopeptide extraction techniques, enzymatic treatment, chromatographic separation, and mass spectrometry analysis. It examines how O-linked glycopeptides can be integrated with N-linked glycopeptide analysis, tracks the progression of individual glycopeptides throughout the procedure, and explores the feasibility of obtaining a sample enriched in N- and O-linked glycopeptides. Subsequent mass spectrometry analysis of each step in the glycopeptide breakdown process allows for the monitoring of glycopeptide trajectories and comprehensive structural identification
EVALUATING THE MECHANISMS OF THERAPY RESPONSE TO NOVEL ORAL SERDS IN ER+ BREAST CANCER
No full textIt has been known that estrogen receptor positive (ER+) metastatic breast cancer (MBC) develops resistance to ER targeted therapies such as aromatase inhibitors, selective estrogen receptor modulators (SERMs) and the first-generation selective estrogen receptor degrader (SERD) fulvestrant. The most well-known mechanism of resistance is ER (ESR1) mutations, contributing to 18-50% of the tumors that relapse after hormone therapy failure. Elacestrant, the first novel oral SERD was approved and developed against tumors with activated ER mutations, while other novel oral SERDs are at late clinical stages in development. However, it is still unknown whether novel SERDs are effective against other resistance mechanisms of ER targeted therapy. We hypothesized that novel oral SERDs would express distinct mechanisms of therapy response as compared to current therapies and amongst each other. To investigate this, we tested the responses to novel oral SERDs in models of ER therapy resistance we previously identified, namely activating ERBB2 mutations, ESR1 mutants, CCND1/CCNE2 amplifications, AKT1/2 amplifications and FGFR mutants, in ER+ cells. We found that ER+ cells with activated ERBB2 mutants, CCND1/CCNE2 amplifications, AKT1/2 amplifications and FGFR mutants confer resistance to novel oral SERDs alone and in combination with CDK4/6 inhibitors, AKT inhibitors and PI3K inhibitors. Moreover, ER+ cells with
activated ESR1 mutants are sensitized to novel oral SERDs alone and in combination with CDK4/6 inhibitors, AKT inhibitors and PI3K inhibitors. We also hypothesize that ER+ breast cancer will develop resistance to novel oral SERDs through distinct mechanisms other than the known mechanisms of resistance. To study this, we generated ER+ cell lines that are resistant to a set of novel oral SERDs, to compare resistance mechanisms to novel SERDs to mechanisms of resistance to older ER-targeted therapies. In conclusion, our data strongly suggests the need to discover and develop new targets of therapy in MBC to overcome resistance to novel oral SERDs. Our results can also allow for rapid clinical translation in patients with tumors expressing resistance in MBC
ENHANCE ROBUSTNESS OF DETRITYLATION STEP IN SOLID PHASE ANTISENSE OLIGONUCLEOTIDE SYNTHESIS
No full textAntisense Oligonucleotide (ASO) based drugs are now novel and promising therapeutics for treating a large variety of diseases. ASOs are single strand short nucleotides that are typically 15-25 nucleotides long. They target mRNAs instead of normal protein receptors and bring therapeutic interventions by altering the expression of disease-causing proteins. There are several different post-binding mechanisms that make it possible to either inhibit or restore protein synthesis, depending on the specific disease source. ASOs bind to target mRNA through Watson–Crick base pairing. This unique complementary binding grants ASO drugs with excellent targeting specificity comparing to tradition small molecule drugs. While having excellent therapeutic potentials, the synthesis technique of ASOs is of great significance to support ASO development and its clinic uses.
Solid Phase Synthesis (SPS) is now the predominant method for ASO synthesis. The oligonucleotide chains grow from 3’ end to 5’ end with addition of phosphoramidite monomers to a solid support stepwise. Within each synthesis cycle, protecting group on reactive site is firstly removed; then coupling step elongates the chain and forms phosphite linkages between nucleosides; the phosphorous (III) is then oxidized to phosphorous(V); and failure sequences are capped lastly. Reliable synthetic process for ASOs is important to obtain high quality products with good yield. However, glyoxylic acid is an impurity can be present in reagent used for ASO synthesis. It brings significant adverse impact to ASO synthesis by lowering product purity and yield. Quantitative impact of glyoxylic acid on a 20mer ASO sequence was studied, and scavengers are explored to effectively quench the impurity present
The role of FOXA1 mutations in ER+ breast cancer
Get PDFBreast cancer is a major public health burden worldwide and it is classified into subtypes based on hormone receptor expression, namely ER+ (estrogen receptor positive), PR+ (progesterone receptor positive), HER2+ (human epidermal growth factor receptor positive) and TNBC (triple negative breast cancer). Approximately 70% of breast cancer cases are classified as being ER+, making it an important diagnostic marker. Mutations in the pioneer transcription factor FOXA1 are a hallmark of ER+ breast cancer. FOXA1 is also known to recruit ER and control ER dependent transcription. Certain missense mutations in the FOXA1 protein which have previously been characterized, provide an acquired survival advantage to ER+ breast cancers upon treatment with aromatase inhibitors and these mutations have been enriched in metastatic tumors. A previous study identified two major mutational subgroups with their distinctive properties, namely the hypermorphic Wing2 mutants and neomorphic SY242CS mutants. Given the clinical relevance and high occurrence of ER+ breast cancer, elucidating mechanisms of resistance and characterizing mutational profiles in the pioneer transcription factor FOXA1 is essential. Our project aimed to characterize a novel and wider cohort of FOXA1 mutations, and we have hereby unraveled their distinct transcriptomic profiles using RNA-Seq, altered chromatin accessibility landscape using ATAC-Seq and other functional aspects which showed cellular characteristics such as proliferation and response to standard-of-care drug treatments using cytotoxicity assays
COLONIAL WORLDMAKING: RACIAL REGIMES OF PROPERTY, PRODUCTION, AND CIRCULATION IN THE INDO-ATLANTIC WORLD
No full textThis dissertation examines the making of the liberal-capitalist international order and its formation within empire. Parting ways with the conventional focus on cultural norms, rules, and institutions, it analyzes the political-economic tenets of liberalism upon which international order rests, including private property, free labor, and exchange. It argues that these liberal principles have been incubated within colonial settings and historically produced through empire, a formation that co-articulates the logics of race, class, and ecology through processes of land theft and degradation; racialized super-exploitation and social control; and carceral and necropolitical containment. The dissertation takes the abolition of the slave trade within the British empire in the early-nineteenth century as a pivotal moment in the making of this order. Abolition entrenches an order structured uniquely around liberal ideals of freedom, especially surrounding commerce. It also inaugurates the massive expansion of imperial capital across the lands and seas of the Atlantic and Indian Ocean worlds in order to sustain colonial production. These entanglements are often overlooked within liberal accounts of international order and critical theories of social relations under capitalism. These strands of scholarship tend to focus largely on cultural dynamics, isolate social processes, separate geographies along national lines, and obscure the productive force of empire in shaping the modern world. Drawing together critical International Relations theory, political theory, settler- and post-colonial studies, and racial capitalism, this dissertation examines the colonies as critical sites for the ordering of capitalist modernity. Specifically, the dissertation analyzes “colonial worldmaking,” or the colonial production of the dominant international economic order, through three processes: the early imposition of private property in the colonies through the degradation of native land and life-sustaining labor; the development of “free” labor through exploitative contracts hooked into regimes of policing and criminalization that ensured the unfreedom of workers; and the global circulation of capital through necropolitical infrastructures of carcerality and containment. By delving into the realm of colonial international relations, the dissertation offers a geographically expansive and materialist theorization of liberal world order that allows us to make better sense of our present conjuncture of multiple interlocking crises
Compressive Sensing Channel Estimation for Wireless Communications Systems with Massive Antenna Arrays
Get PDFEmerging and future wireless communications systems aim to provide connectivity for increasing numbers of users and devices. A Massive Multiple Input Multiple Output (MIMO) system has a base station with a large number of antennas that is much greater than the number of users and provides the ability for spatial division multiple access. Accurate channel estimation is a critical part of the communications design as it is necessary to compensate for the channel distortion and to compute the beamforming solutions for spatial division multiple access. Additionally, the use of the millimeter wave spectrum provides an opportunity for wider channel bandwidths to support high data rate applications.
When transformed into the virtual channel domain, Massive MIMO millimeter wave wireless channels are seen to be sparse due to the relatively small number of dominant multipath components in the physical channel when compared to the dimensions of the virtual channel. Compressive sensing theory offers opportunities to recover the channel impulse response with fewer measurements.
In this work, Massive MIMO millimeter wave channel estimation is formed as a compressive sensing problem where the virtual channel in the angular and delay domains is approximately sparse. Pilot subcarrier reduction is achieved through reconstruction of the virtual channel using Orthogonal Matching Pursuit. A lower bound on performance is derived and demonstrated in numerical simulation showing that once a minimum number of pilot subcarriers are is used, additional pilot subcarriers do not provide additional benefits in cases without basis mismatch. Super resolution deep learning techniques using convolutional neural networks are demonstrated as option to overcome the complexity and performance of compressive sensing approaches and overcome the impacts of basis mismatch
THE CHEVRON WAY: HOW CHEVRON CORPORATION IS CREATING A CLEANER ENERGY FUTURE
Get PDFAs the effects of climate change are continually displayed in extreme weather events, changing migration patterns, differences in sea levels and temperature, and other characteristics, a growing number of the world’s supermajor oil companies pledge emissions reductions and clean energy production. Among the small group of oil companies that control most of the world’s oil and gas products, Chevron has made changes in the past several years to shift its production to cleaner energy sources.
Chevron’s publicly available reports indicate the company’s clean energy investments, partnerships, and projects are part of a much larger move towards more environmentally friendly energy production. Chevron’s 2022 Annual Report reflects strong upstream and downstream business across stock performance, financial and operating highlights, and overall financial condition. Chevron retains strategic membership in several trade associations across the industry, and its recent acquisitions have positioned Chevron as a powerhouse of both traditional and clean energy production expertise.
With Chevron’s inception of its Chevron New Energies Corporation in 2021, the company launched a more formal clean energy business. The strategic partnerships and projects created since the new organization’s establishment signal Chevron’s earnest intent to shift toward cleaner energy production, including renewable fuel, carbon capture and sequestration, emissions intensity and monitoring, and hydrogen fuel production projects
MODELING CHOLERA TRANSMISSION DYNAMICS IN UVIRA, DEMOCRATIC REPUBLIC OF CONGO
Get PDFCholera is an enteric disease, with high burden in Sub-Saharan Africa where it is endemic to areas such as the Democratic Republic of Congo (DRC). In these endemic areas, cholera epidemiology is characterized by continuous low levels of transmission with seasonal outbreaks. The precise drivers of these outbreaks in endemic settings are not well-characterized, especially their relationship to environmental factors like rainfall.
Enhanced clinical surveillance of cholera in Uvira, a city in the Eastern DRC, has recorded several outbreaks between 2016 and 2020. We fit a mechanistic Susceptible-Exposed-Infectious-Asymptomatic-Recovered (SEIAR) model of cholera dynamics with time-varying transmission to this data in order elucidate changes in transmission and immune dynamics over time. Eleven models variations with different time-varying transmission parameters,\ \beta\left(t\right), were evaluated: two models where \ \beta\left(t\right) followed a periodic basis spline function and nine models where\ \beta\left(t\right) had a direct relationship to different rainfall metrics at different lags. Components of \beta\left(t\right) and the initial proportion in the R compartment were fit for each model using simulation-based inference. Fits were assessed by comparing simulated trajectories to the observed data and models were compared using the Akaike Information Criterion (AIC).
All mechanistic models showed similarly good fits, capturing the timing of outbreaks well but often underestimating their magnitudes. There were no clear differences in fit between the periodic and rainfall-driven approaches. Further, all models estimated a high proportion of individuals in the recovered compartment, with over 75% of the population in the compartment across the entire time series. Though values of \beta\left(t\right) varied substantially between models, values of the effective reproductive number, Rt(t), were largely aligned, driven by the proportion of the population susceptible to infection. Overall, the rainfall model using maximum rainfall and a 3-week lag had the lowest AIC.
Our findings suggest that while rainfall and immune dynamics are important components of long-term cholera transmission patterns in Uvira, mechanistic modelling relying only on these elements does not fully explain observed incidence. Nevertheless, this approach, which incorporates population immunity and long-term seasonality, can help generate counter-factual incidence scenarios to estimate the impact of public health interventions like vaccination campaigns