83 research outputs found

    Promotion of breast cancer by β-Hexachlorocyclohexane in MCF10AT1 cells and MMTV-neu mice

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    <p>Abstract</p> <p>Background</p> <p>Exposure to β-Hexachlorocyclohexane (β-HCH), a contaminant of the hexachlorohexane pesticide lindane, has been implicated as a risk factor in the development of breast cancers in epidemiological studies. Previous studies in our laboratory have demonstrated the ability of β-HCH to elicit its actions via a ligand-independent activation of the estrogen receptor through increased c-Neu (= erbB<sub>2 </sub>or HER-2) expression and kinase activation in both the BG-1 and MCF-7 cell lines. In addition, long term exposure (33 passages) to β-HCH was shown to promote the selection of MCF-7 cells which exhibit a more metastatic phenotype.</p> <p>Methods</p> <p>In this current study, we decided to investigate the long-term effects of β-HCH in both the MCF10AT1 cell line which was derived from a normal epithelial cell line by stably transfecting a mutated c-Ha-ras and a MMTV-Neu mouse model for mammary cancer <it>in vivo</it>. MCF10AT1 cells were exposed for 20 passages with β-HCH, 4-OH-Tamoxifen (Tam), or 17-β-estradiol (E<sub>2</sub>) after which cells were analyzed for proliferation rates and mRNA expression by RT-PCR. In our <it>in vivo </it>studies, MMTV-Neu mice were injected with β-HCH and observed for tumor formation over a 70 week period.</p> <p>Results</p> <p>β-HCH and Tam selected MCF10AT1 cells demonstrated increased mRNA expression of MMP-13 (collagenase-3) a marker of increased invasiveness. β-HCH treatment was also seen to increase the expression in a number of proto-oncogenes (c-Neu, Cyclin D1, p27), cell status markers (Met-1, CK19), and the inflammatory marker NFκB. Previous studies, have demonstrated the role of these markers as evidence of malignant transformations, and further illustrate the ability of β-HCH to be carcinogenic. To demonstrate β-HCH's tumorigenic properties in an <it>in vivo </it>system, we used an MMTV-Neu mouse model.</p> <p>MMTV-Neu is a c-Neu overexpressing strain which has been shown to spontaneously develop mammary tumors at later stages of aging. In this experiment, β-HCH exposure was shown to both accelerate the appearance (~8 weeks for median tumor-free period) and incidence (~25% increase at the end of the test period) of tumors when compared to control mice receiving only the corn-oil vehicle.</p> <p>Conclusion</p> <p>Based upon these results, it was concluded that β-HCH does act as a breast cancer promoter which exerts its tumorigenic activity via increased c-Neu expression.</p

    Complex systems and the technology of variability analysis

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    Characteristic patterns of variation over time, namely rhythms, represent a defining feature of complex systems, one that is synonymous with life. Despite the intrinsic dynamic, interdependent and nonlinear relationships of their parts, complex biological systems exhibit robust systemic stability. Applied to critical care, it is the systemic properties of the host response to a physiological insult that manifest as health or illness and determine outcome in our patients. Variability analysis provides a novel technology with which to evaluate the overall properties of a complex system. This review highlights the means by which we scientifically measure variation, including analyses of overall variation (time domain analysis, frequency distribution, spectral power), frequency contribution (spectral analysis), scale invariant (fractal) behaviour (detrended fluctuation and power law analysis) and regularity (approximate and multiscale entropy). Each technique is presented with a definition, interpretation, clinical application, advantages, limitations and summary of its calculation. The ubiquitous association between altered variability and illness is highlighted, followed by an analysis of how variability analysis may significantly improve prognostication of severity of illness and guide therapeutic intervention in critically ill patients

    Electrocardiogram Pattern Recognition and Analysis Based on Artificial Neural Networks and Support Vector Machines: A Review

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    Heavy metal intakes in Finland, especially during pregnancy and childhood

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