147 research outputs found

    The Contemporary Encyclopedic Novel

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    This dissertation will define the contemporary American encyclopedic novel and the significant role that irony plays in shaping meaning. The dissertation constructs a model of the encyclopedic novel based upon the history of the encyclopedia – from Denis Diderot\u27s Enlightenment influenced Encyclopédie – and Northrop Frye\u27s conception of the encyclopedic form. It claims (1) that the contemporary encyclopedic novel continues in the cycle of modal progression toward mythic integration that Frye proposes in Anatomy of Criticism; and (2) that the encyclopedic novel utilizes different forms of irony to challenge authoritative discourse and elevate marginal discourse. The first chapter defines the encyclopedic novel by examining the history of the encyclopedia and existing criticism on the encyclopedic text in literature. It draws on theorists such as Denis Diderot and Richard Yeo to define an “encyclopedic project” that adopts a dialogic rhetorical style and seeks to democratize access to information. This chapter also defines the encyclopedic novel as a generic form that combines other forms into a unified whole and utilizes irony as a tool for integration. The second and third chapters form a thematic pairing that shows the self-reflexive progression of the encyclopedic novel from individualistic to humanistic focus. The second chapter argues that Thomas Pynchon\u27s Gravity\u27s Rainbow is an “anarchistic encyclopedic novel” that promotes associational thinking – in the form of paranoia, open forms, and horizontal transmission of knowledge. Gravity\u27s Rainbow adopts a disintegrative irony to empower the oppressed individual against industry-state collusion in the post-WWII era. The third chapter argues that David Foster Wallace\u27s Infinite Jest seeks to reinvent irony as an integrative force and redirect Pynchon\u27s individualistic anarchism toward an inclusive humanism. The fourth chapter demonstrates a break from both of the preceding chapter and argues that Leon Forrest\u27s Divine Days adopts a syndetic model of composition that further works to incorporate forms and integrate irony. Using Northrop Frye\u27s “interpenetration,” I argue that Divine Days integrates competing traditions and discourses by demonstrating their mutual-necessity. In the concluding chapter, I examine “meta-encyclopedic” by Jorge Luis Borges and Roberto Bolaño as an extension of the dissertation

    Multi-Walled Carbon Nanotube-Induced Gene Expression Biomarkers for Medical and Occupational Surveillance

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    As the demand for multi-walled carbon nanotube (MWCNT) incorporation into industrial and biomedical applications increases, so does the potential for unintentional pulmonary MWCNT exposure, particularly among workers during manufacturing. Pulmonary exposure to MWCNTs raises the potential for development of lung inflammation, fibrosis, and cancer among those exposed; however, there are currently no effective biomarkers for detecting lung fibrosis or predicting the risk of lung cancer resulting from MWCNT exposure. To uncover potential mRNAs and miRNAs that could be used as markers of exposure, this study compared in vivo mRNA and miRNA expression in lung tissue and blood of mice exposed to MWCNTs with in vitro mRNA and miRNA expression from a co-culture model of human lung epithelial and microvascular cells, a system previously shown to have a higher overall genome-scale correlation with mRNA expression in mouse lungs than either cell type grown separately. Concordant mRNAs and miRNAs identified by this study could be used to drive future studies confirming human biomarkers of MWCNT exposure. These potential biomarkers could be used to assess overall worker health and predict the occurrence of MWCNT-induced diseases

    A Predictive 7-Gene Assay and Prognostic Protein Biomarkers for Non-small Cell Lung Cancer

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    This study aims to develop a multi-gene assay predictive of the clinical benefits of chemotherapy in non- small cell lung cancer (NSCLC) patients, and substantiate their protein expression as potential therapeutic tar- gets. Patients and methods: The mRNA expression of 160 genes identified from microarray was analyzed in qRT-PCR assays of independent 337 snap-frozen NSCLC tumors to develop a predictive signature. A clinical trial JBR.10 was included in the validation. Hazard ratio was used to select genes, and decision-trees were used to construct the predictive model. Protein expression was quantified with AQUA in 500 FFPE NSCLC samples. Results: A 7-gene signature was identified from training cohort (n = 83) with accurate patient stratification (P = 0.0043) and was validated in independent patient cohorts (n = 248, P b 0.0001) in Kaplan-Meier analyses. In the predicted benefit group, there was a significantly better disease-specific survival in patients receiving adjuvant chemotherapy in both training (P = 0.035) and validation (P = 0.0049) sets. In the predicted non-benefit group, there was no survival benefit in patients receiving chemotherapy in either set. The protein expression of ZNF71 quantified with AQUA scores produced robust patient stratification in separate training (P = 0.021) and validation (P = 0.047) NSCLC cohorts. The protein expression of CD27 quantified with ELISA had a strong correlation with its mRNA expression in NSCLC tumors (Spearman coefficient = 0.494, P b 0.0088). Multiple sig- nature genes had concordant DNA copy number variation, mRNA and protein expression in NSCLC progression. Conclusions: This study presents a predictive multi-gene assay and prognostic protein biomarkers clinically appli- cable for improving NSCLC treatment, with important implications in lung cancer chemotherapy and immunotherapy

    Hybrid Models Identified a 12-Gene Signature for Lung Cancer Prognosis and Chemoresponse Prediction

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    Lung cancer remains the leading cause of cancer-related deaths worldwide. The recurrence rate ranges from 35-50% among early stage non-small cell lung cancer patients. To date, there is no fully-validated and clinically applied prognostic gene signature for personalized treatment.From genome-wide mRNA expression profiles generated on 256 lung adenocarcinoma patients, a 12-gene signature was identified using combinatorial gene selection methods, and a risk score algorithm was developed with Naïve Bayes. The 12-gene model generates significant patient stratification in the training cohort HLM & UM (n = 256; log-rank P = 6.96e-7) and two independent validation sets, MSK (n = 104; log-rank P = 9.88e-4) and DFCI (n = 82; log-rank P = 2.57e-4), using Kaplan-Meier analyses. This gene signature also stratifies stage I and IB lung adenocarcinoma patients into two distinct survival groups (log-rank P<0.04). The 12-gene risk score is more significant (hazard ratio = 4.19, 95% CI: [2.08, 8.46]) than other commonly used clinical factors except tumor stage (III vs. I) in multivariate Cox analyses. The 12-gene model is more accurate than previously published lung cancer gene signatures on the same datasets. Furthermore, this signature accurately predicts chemoresistance/chemosensitivity to Cisplatin, Carboplatin, Paclitaxel, Etoposide, Erlotinib, and Gefitinib in NCI-60 cancer cell lines (P<0.017). The identified 12 genes exhibit curated interactions with major lung cancer signaling hallmarks in functional pathway analysis. The expression patterns of the signature genes have been confirmed in RT-PCR analyses of independent tumor samples.The results demonstrate the clinical utility of the identified gene signature in prognostic categorization. With this 12-gene risk score algorithm, early stage patients at high risk for tumor recurrence could be identified for adjuvant chemotherapy; whereas stage I and II patients at low risk could be spared the toxic side effects of chemotherapeutic drugs
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