1,566 research outputs found

    Exploring the lived experiences of online worshipers

    Get PDF
    This ongoing qualitative study uses long interviews to seek to understand the lived experiences of individuals who participate in online church services. Online church has rapidly grown in the past few years and many Americans have participated in, or are willing to participate in, alternatives to traditional worship. Many churches are adopting online formats as a way to address the interest of individuals in alternative worship experiences. This study seeks to understand how individuals use online worship and how it plays into their spiritual lives

    OvMark: a user-friendly system for the identification of prognostic biomarkers in publically available ovarian cancer gene expression datasets

    Get PDF
    Background: Ovarian cancer has the lowest survival rate of all gynaecologic cancers and is characterised by a lack of early symptoms and frequent late stage diagnosis. There is a paucity of robust molecular markers that are independent of and complementary to clinical parameters such as disease stage and tumour grade. METHODS: We have developed a user-friendly, web-based system to evaluate the association of genes/miRNAs with outcome in ovarian cancer. The OvMark algorithm combines data from multiple microarray platforms (including probesets targeting miRNAs) and correlates them with clinical parameters (e.g. tumour grade, stage) and outcomes (disease free survival (DFS), overall survival). In total, OvMark combines 14 datasets from 7 different array platforms measuring the expression of ~17,000 genes and 341 miRNAs across 2,129 ovarian cancer samples. RESULTS: To demonstrate the utility of the system we confirmed the prognostic ability of 14 genes and 2 miRNAs known to play a role in ovarian cancer. Of these genes, CXCL12 was the most significant predictor of DFS (HR = 1.42, p-value = 2.42x10-6). Surprisingly, those genes found to have the greatest correlation with outcome have not been heavily studied in ovarian cancer, or in some cases in any cancer. For instance, the three genes with the greatest association with survival are SNAI3, VWA3A and DNAH12. CONCLUSIONS/IMPACT: OvMark is a powerful tool for examining putative gene/miRNA prognostic biomarkers in ovarian cancer (available at http://glados.ucd.ie/OvMark/index.html). The impact of this tool will be in the preliminary assessment of putative biomarkers in ovarian cancer, particularly for research groups with limited bioinformatics facilities

    Noncyclic covers of knot complements

    Full text link
    Hempel has shown that the fundamental groups of knot complements are residually finite. This implies that every nontrivial knot must have a finite-sheeted, noncyclic cover. We give an explicit bound, Φ(c)\Phi (c), such that if KK is a nontrivial knot in the three-sphere with a diagram with cc crossings and a particularly simple JSJ decomposition then the complement of KK has a finite-sheeted, noncyclic cover with at most Φ(c)\Phi (c) sheets.Comment: 29 pages, 8 figures, from Ph.D. thesis at Columbia University; Acknowledgments added; Content correcte

    Mechanisms of mutant β-catenin in endometrial cancer progression

    Get PDF
    Endometrial carcinoma (EC) is the most diagnosed gynecological malignancy in Western countries. Both incidence and mortality rates of EC have steadily risen in recent years. Despite generally favorable prognoses for patients with the endometrioid type of EC, a subset of patients has been identified with decreased progression-free survival. Patients in this group are distinguished from other endometrioid EC patients by the presence of exon 3 hotspot mutations in CTNNB1, the gene encoding for the β-catenin protein. β-catenin is an evolutionarily conserved protein with critical functions in both adherens junctions and Wnt-signaling. The exact mechanism by which exon 3 CTNNB1 mutations drive EC progression is not well understood. Further, the potential contribution of mutant β-catenin to adherens junctions’ integrity is not known. Additionally, the magnitude of worsened progression-free survival in patients with CTNNB1 mutations is context dependent, and therefore the importance of this subset of patients can be obscured by improper categorization. This review will examine the history and functions of β-catenin, how these functions may change and drive EC progression in CTNNB1 mutant patients, and the importance of this patient group in the broader context of the disease

    OvMark: a user-friendly system for the identification of prognostic biomarkers in publically available ovarian cancer gene expression datasets

    Get PDF
    Background: Ovarian cancer has the lowest survival rate of all gynaecologic cancers and is characterised by a lack of early symptoms and frequent late stage diagnosis. There is a paucity of robust molecular markers that are independent of and complementary to clinical parameters such as disease stage and tumour grade. METHODS: We have developed a user-friendly, web-based system to evaluate the association of genes/miRNAs with outcome in ovarian cancer. The OvMark algorithm combines data from multiple microarray platforms (including probesets targeting miRNAs) and correlates them with clinical parameters (e.g. tumour grade, stage) and outcomes (disease free survival (DFS), overall survival). In total, OvMark combines 14 datasets from 7 different array platforms measuring the expression of ~17,000 genes and 341 miRNAs across 2,129 ovarian cancer samples. RESULTS: To demonstrate the utility of the system we confirmed the prognostic ability of 14 genes and 2 miRNAs known to play a role in ovarian cancer. Of these genes, CXCL12 was the most significant predictor of DFS (HR = 1.42, p-value = 2.42x10-6). Surprisingly, those genes found to have the greatest correlation with outcome have not been heavily studied in ovarian cancer, or in some cases in any cancer. For instance, the three genes with the greatest association with survival are SNAI3, VWA3A and DNAH12. CONCLUSIONS/IMPACT: OvMark is a powerful tool for examining putative gene/miRNA prognostic biomarkers in ovarian cancer (available at http://glados.ucd.ie/OvMark/index.html). The impact of this tool will be in the preliminary assessment of putative biomarkers in ovarian cancer, particularly for research groups with limited bioinformatics facilities

    Non-Neoplastic and Neoplastic Pleural Endpoints Following Fiber Exposure

    Get PDF
    Exposure to asbestos fibers is associated with non-neoplastic pleural diseases including plaques, fibrosis, and benign effusions, as well as with diffuse malignant pleural mesothelioma. Translocation and retention of fibers are fundamental processes in understanding the interactions between the dose and dimensions of fibers retained at this anatomic site and the subsequent pathological reactions. The initial interaction of fibers with target cells in the pleura has been studied in cellular models in vitro and in experimental studies in vivo. The proposed biological mechanisms responsible for non-neoplastic and neoplastic pleural diseases and the physical and chemical properties of asbestos fibers relevant to these mechanisms are critically reviewed. Understanding mechanisms of asbestos fiber toxicity may help us anticipate the problems from future exposures both to asbestos and to novel fibrous materials such as nanotubes. Gaps in our understanding have been outlined as guides for future research

    Is albumin gradient or fluid to serum albumin ratio better than the pleural fluid lactate dehydroginase in the diagnostic of separation of pleural effusion?

    Get PDF
    BACKGROUND: To determine the accuracy of serum-effusion albumin gradient (SEAG) and pleural fluid to serum albumin ratio (ALBR) in the diagnostic separation of pleural effusion into transudate and exudate and to compare SEAG and ALBR with pleural fluid LDH (FLDH) the most widely used test. METHODS: Data collected from 200 consecutive patients with a known cause of pleural effusion in a United Kingdom district general hospital. RESULTS: The median and inter quartile ranges (IQR) for SEAG 93.5 (33.8 to 122.5) g/dl, ALBR 0.49 (0.42 to 0.62) and FLDH 98.5 IU/L(76.8 to 127.5) in transudates were significantly lower than the corresponding values for exudates 308.5 (171 to 692), 0.77 (0.63 to 0.85), 344 (216 to 695) all p < 0.0001. The Area Under the Curve (AUC) with 95% confidence intervals (Cl) for SEAG, ALBR and FLDH were 0.81 (0.75 to 0.87), 0.79 (0.72 to 0.86) and 0.9 (0.87 to 0.96) respectively. The positive likelihood ratios with 95%CI for FLDH, SEAG, and ALBR were: 7.3(3.5–17), 6.3(3–15) 6.2(3–14) respectively. There was a significant negative correlation between SEAG and ALBR (r= -0.89, p < 0.0001). CONCLUSION: The discriminative value for SEAG and ALBR appears to be similar in the diagnostic separation of transudates and exudates. FLDH is a superior test compared to SEAG and ALBR

    Differences in the microbial profiles of early stage endometrial cancers between Black and White women

    Get PDF
    Objective: Black women suffer a higher mortality from endometrial cancer (EC) than White women. Potential biological causes for this disparity include a higher prevalence of obesity and more lethal histologic/molecular subtypes. We hypothesize that another biological factor driving this racial disparity could be the EC microbiome. Methods: Banked tumor specimens of postmenopausal, Black and White women undergoing hysterectomy for early stage endometrioid EC were identified. The microbiota of the tumors were characterized by bacterial 16S rRNA sequencing. The microbial component of endometrioid ECs in The Cancer Genome Atlas (TCGA) database were assessed for comparison. Results: 95 early stage ECs were evaluated: 23 Black (24%) and 72 White (76%). Microbial diversity was increased (p < 0.001), and Firmicutes, Cyanobacteria and OD1 phyla abundance was higher in tumors from Black versus White women (p < 0.001). Genus level abundance of Dietzia and Geobacillus were found to be lower in tumors of obese Black versus obese White women (p < 0.001). Analysis of early stage ECs in TCGA found that microbial diversity was higher in ECs from Black versus White women (p < 0.05). When comparing ECs from obese Black versus obese White women, 5 bacteria distributions were distinct, with higher abundance of Lactobacillus acidophilus in ECs from Black women being the most striking difference. Similarly in TCGA, Dietzia and Geobacillus were more common in ECs from White women compared to Black. Conclusion: Increased microbial diversity and the distinct microbial profiles between ECs of obese Black versus obese White women suggests that intra-tumoral bacteria may contribute to EC disparities and pathogenesis
    corecore