Using ancillary statistics in on-line learning algorithms

Neural networks are usually curved statistical models. They do not have finite dimensional sufficient statistics, so on-line learning on the model itself inevitably loses information. In this paper we propose a new scheme for training curved models, inspired by the ideas of ancillary statistics and adaptive critics. At each point estimate an auxiliary flat model (exponential family) is built to locally accommodate both the usual statistic (tangent to the model) and an ancillary statistic (normal to the model). The auxiliary model plays a role in determining credit assignment analogous to that played by an adaptive critic in solving temporal problems. The method is illustrated with the Cauchy model and the algorithm is proved to be asymptotically efficient.

Expression profiling of type 2 diabetes susceptibility genes in the pancreatic islets, adipose tissue and liver of obese mice

Type 2 diabetes (T2D) is characterized by impaired beta cell function and insulin resistance. T2D susceptibility genes identified by Genome-wide association studies (GWAS) are likely to have roles in both impaired insulin secretion from the beta cell as well as insulin resistance. The aim of this study was to use gene expression profiling to assess the effect of the diabetic milieu on the expression of genes involved in both insulin secretion and insulin resistance. We measured the expression of 43 T2D susceptibility genes in the islets, adipose and liver of leptin-deficient Ob/Ob mice compared with Ob/+ littermates. The same panel of genes were also profiled in cultured rodent adipocytes, hepatocytes and beta cells in response to high glucose conditions, to distinguish expression effects due to elevated glycemia from those on the causal pathway to diabetes or induced by other factors in the diabetic microenviroment. We found widespread deregulation of these genes in tissues from Ob/Ob mice, with differential regulation of 23 genes in adipose, 18 genes in liver and one gene (Tcf7l2) in islets of diabetic animals (Ob/Ob) compared to control (Ob/+) animals. However, these expression changes were in most cases not noted in glucose-treated adipocyte, hepatocyte or beta cell lines, indicating that they may not be an effect of hyperglycemia alone. This study indicates that expression changes are apparent with diabetes in both the insulin producing beta cells, but also in peripheral tissues involved in insulin resistance. This suggests that incidence or progression of diabetic phenotypes in a mouse model of diabetes is driven by both secretory and peripheral defects. © J. A. Barth Verlag in Georg Thieme Verlag KG Stuttgart New York.