Mid- to late-Holocene paleoceanographic changes on the southeastern Brazilian shelf based on grain size records

; High-resolution grain size analyses of three AMS (14)C-dated cores from the Southeastern Brazilian shelf provide a detailed record of mid- to late-Holocene environmental changes in the Southwestern Atlantic Margin. The cores exhibit millennial variability that we associate with the previously described southward shift of the Inter Tropical Convergence Zone (ITCZ) average latitudinal position over the South American continent during the Holocene climatic maximum. This generated changes in the wind-driven current system of the SW Atlantic margin and modified the grain size characteristics of the sediments deposited there. Centennial variations in the grain size are associated with a previously described late-Holocene enhancement of the El Nino-Southern Oscillation (ENSO) amplitude, which led to stronger NNE trade winds off eastern Brazil, favouring SW transport of sediments from the Paraiba do Sul River. This is recorded in a core from off Cabo Frio as a coarsening trend from 3000 cal. BP onwards. The ENSO enhancement also caused changes in precipitation and wind pattern in southern Brazil, allowing high discharge events and northward extensions of the low-saline water plume from Rio de la Plata. We propose that this resulted in a net increase in northward alongshore transport of fine sediments, seen as a prominent fine-shift at 2000 cal. BP in a core from similar to 24 degrees S on the Brazilian shelf. Wavelet-and spectral analysis of the sortable silt records show a significant similar to 1000-yr periodicity, which we attribute to solar forcing. If correct, this is one of the first indications of solar forcing of this timescale on the Southwestern Atlantic margin.

A feature selection approach for identification of signature genes from SAGE data

Abstract Background One goal of gene expression profiling is to identify signature genes that robustly distinguish different types or grades of tumors. Several tumor classifiers based on expression profiling have been proposed using microarray technique. Due to important differences in the probabilistic models of microarray and SAGE technologies, it is important to develop suitable techniques to select specific genes from SAGE measurements. Results A new framework to select specific genes that distinguish different biological states based on the analysis of SAGE data is proposed. The new framework applies the bolstered error for the identification of strong genes that separate the biological states in a feature space defined by the gene expression of a training set. Credibility intervals defined from a probabilistic model of SAGE measurements are used to identify the genes that distinguish the different states with more reliability among all gene groups selected by the strong genes method. A score taking into account the credibility and the bolstered error values in order to rank the groups of considered genes is proposed. Results obtained using SAGE data from gliomas are presented, thus corroborating the introduced methodology. Conclusion The model representing counting data, such as SAGE, provides additional statistical information that allows a more robust analysis. The additional statistical information provided by the probabilistic model is incorporated in the methodology described in the paper. The introduced method is suitable to identify signature genes that lead to a good separation of the biological states using SAGE and may be adapted for other counting methods such as Massive Parallel Signature Sequencing (MPSS) or the recent Sequencing-By-Synthesis (SBS) technique. Some of such genes identified by the proposed method may be useful to generate classifiers.