J-Express: exploring gene expression data using Java

J-Express is a Java application that allows the user to analyze gene expression (microarray) data in a flexible way giving access to multidimensional scaling, clustering, and visualization methods in an integrated manner. Specifically, J-Express includes implementations of hierarchical clustering, k-means, principal component analysis, and self-organizing maps. At present, it does not include methods for comparing two or more experiments for differentially expressed genes. The application is completely portable and requires only that a Java runtime environment 1.2 is installed on the system. Its efficiency allows interactive clustering of thousands of expression profiles on standard personal computers.     

不同耕作措施对冬小麦-夏玉米复种连作系统土壤有机碳和水分利用效率的影响

在连续8年田间定位试验的基础上,分析了关中平原冬小麦 夏玉米复种连作系统2008—2009年连续两个生长季期间不同耕作措施(结合秸秆还田和不还田)对土壤有机碳和水分利用率的影响.结果表明: 相对于传统耕作,保护性耕作有利于土壤有机碳、水分利用效率和作物产量的提高,其中在“深松+秸秆还田”耕作模式下的增幅最高,土壤有机碳含量在0～30 cm土层增幅达到19.5%,水分利用效率和作物产量提高了16.9%和20.5%,而免耕模式则有效提高了0～10 cm土层有机碳含量.在该地区土壤和气候条件下,深松结合秸秆粉碎还田是最理想的耕作模式,最有利于土壤有机碳累积,并提高水分利用效率和作物产量.     

Brain angiotensin receptors and sympathoadrenal regulation during insulin-induced hypoglycemia

Simultaneous blockade of systemic AT1 and AT2 receptors or converting enzyme inhibition (CEI) attenuates the hypoglycemia-induced reflex increase of epinephrine (Epi). To examine the role of brain AT1 and AT2 receptors in the reflex regulation of Epi release, we measured catecholamines, hemodynamics, and renin during insulin-induced hypoglycemia in conscious rats pretreated intracerebroventricularly with losartan, PD-123319, losartan and PD-123319, or vehicle. Epi and norepinephrine (NE) increased 60-and 3-fold, respectively. However, the gain of the reflex increase in plasma Epi (Deltaplasma Epi/Deltaplasma glucose) and the overall Epi and NE responses were similar in all groups. The ensuing blood pressure response was similar between groups, but the corresponding bradycardia was augmented after PD-123319 (P < 0.05 vs. vehicle) or combined losartan and PD-123319 (P < 0.01 vs. vehicle). The findings indicate 1) brain angiotensin receptors are not essential for the reflex regulation of Epi release during hypoglycemia and 2) the gain of baroreceptor-mediated bradycardia is increased by blockade of brain AT2 receptors in this model.     

Preconditioning by 17beta-estradiol in isolated rat heart depends on PI3-K/PKB pathway, PKC, and ROS

To study the cell signaling events leading to 17beta-estradiol (E(2))-induced acute cardioprotection, we subjected isolated rat hearts to three 5-min cycles of 10 microM E(2) before 30 min of regional ischemia, followed by 2 h of reperfusion. Protection was judged by changes in infarct size in percentage of risk zone volume. To test the importance of phosphoinositide 3-kinase (PI3-K), protein kinase C (PKC), or reactive oxygen species (ROS) in E(2)-induced protection, we combined wortmannin (1 microM), chelerythrine (2 microM), and 2-mercaptopropionylglycine (300 microM), respectively, with E(2) exposure. Changes in phosphorylation of protein kinase B (PKB) and selected PKC isoforms were tested by immunoblotting of total lysates and subcellular fractions, along with assessment of PKC translocation from soluble to membrane fraction of heart tissue homogenates. Intracellular ROS levels induced by E(2) preconditioning were investigated. E(2) preconditioning led to significant reduction in infarct size from 31.8 +/- 5.3 to 20.2 +/- 2.6% in male hearts and from 42.7 +/- 4.7 to 17.1 +/- 3.4% in female hearts (P < 0.05). Protection was abolished by wortmannin (30.0 +/- 3.2%), chelerythrine (45.1 +/- 4.4%), and 2-mercaptopropionylglycine (36.8 +/- 4.7%). E(2) preconditioning induced phosphorylation of PKB, PKCalpha, and PKCepsilon and membrane translocation of PKCepsilon and PKCdelta. Intracellular ROS levels were found elevated after transient treatment with hormone. Therefore, our data demonstrate the ability of E(2) to induce preconditioning-like cardioprotection via cell signaling events shared by classic ischemic preconditioning.     

L<Subscript>2</Subscript>-norm multiple kernel learning and its application to biomedical data fusion

Background  

This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields different extensions of multiple kernel learning (MKL) such as L _∞, L ₁, and L ₂ MKL. In particular, L ₂ MKL is a novel method that leads to non-sparse optimal kernel coefficients, which is different from the sparse kernel coefficients optimized by the existing L _∞ MKL method. In real biomedical applications, L ₂ MKL may have more advantages over sparse integration method for thoroughly combining complementary information in heterogeneous data sources.