Dysregulation of microRNAs in adrenocortical tumors.
ABSTRACT MicroRNAs (miRNAs) are short non-coding RNAs that are involved in the epigenetic regulation of cellular processes. Different malignancies are often associated with the deregulation of specific sets of miRNAs. The prognosis of adrenocortical cancers (ACCs) is very poor as compared to adrenocortical adenomas (ACAs), and even within ACCs there are cases with better disease specific survival. An improved understanding of the pathobiology of this disease will therefore be useful in facilitating better management of ACCs as well as distinguishing high risk versus low risk subgroups. One third of coding genes are regulated by miRNAs and therefore changes in miRNA expression may be associated with cancer development and progression. In this review we summarize the current understanding of miRNAs in adrenocortical tumors, and highlight their potential in differentiating between ACCs and ACAs, risk stratification and prognosis.
- International Journal of Geographical Information Science. 01/1997; 11:199-212.
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ABSTRACT: Digital elevation models (DEMs) represent the topography that drives surface flow and are arguably one of the more important data sources for deriving variables used by numerous hydrologic models. A considerable amount of research has been conducted to address uncertainty associated with error in digital elevation models (DEMs) and the propagation of error to derived terrain parameters. This review brings together a discussion of research in fundamental topical areas related to DEM uncertainty that affect the use of DEMs for hydrologic applications. These areas include: (a) DEM error; (b) topographic parameters frequently derived from DEMs and the associated algorithms used to derive these parameters; (c) the influence of DEM scale as imposed by grid cell resolution; (d) DEM interpolation; and (e) terrain surface modification used to generate hydrologically-viable DEM surfaces. Each of these topical areas contributes to DEM uncertainty and may potentially influence results of distributed parameter hydrologic models that rely on DEMs for the derivation of input parameters. The current state of research on methods developed to quantify DEM uncertainty is reviewed. Based on this review, implications of DEM uncertainty and suggestions for the GIS research and user communities emerge.01/2007;
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ABSTRACT: Primary topographic attributes play a critical role in determining watershed hydrologic characteristics for water resources modeling with raster-based digital elevation models (DEM). The effects of DEM resolution on a set of important topographic derivatives are examined in this study, including slope, upslope contributing area, flow length and watershed area. The focus of the study is on how sensitive each of the attributes is to the resolution uncertainty by considering the effects of overall terrain gradient and bias from resampling. Two case study watersheds of different gradient patterns are used with their 10 m USGS DEMs. A series of DEMs up to 200 m grid size are produced from the base DEMs using three commonly used resampling methods. All the terrain variables tested vary with the grid size change. It is found that slope angles decrease and contributing area values increase constantly as DEMs are aggregated progressively to coarser resolutions. No systematic trend is observed for corresponding changes of flow path and watershed area. The analysis also suggests that gradient profile of the watershed presents an important factor for the examined sensitivities to DEM resolution.Applied Geography. 01/2008;