The actuarial postbiopsy graft survival varied by cluster (p = 0.002). CAN and CNI toxicity were common diagnoses in each cluster (and did not differentiate clusters). Similarly, C4d and presence of donor specific antibody were frequently observed across clusters. We conclude that for recipients with new-onset late graft dysfunction, cluster analysis of Banff scores distinguishes meaningful subgroups with differing outcomes.”
“P>Soil salinity affects a large proportion of the land worldwide, forcing plants to evolve a number of mechanisms to cope Selleckchem Apoptosis Compound Library with salt stress. Cytokinin

plays a role in the plant response to salt stress, but little is known about the mechanism by which cytokinin controls this process. We used a molecular genetics approach to examine the influence

of cytokinin on sodium accumulation and salt sensitivity in Arabidopsis thaliana. Cytokinin application was found to increase DZNeP research buy sodium accumulation in the shoots of Arabidopsis, but had no significant affect on the sodium content in the roots. Consistent with this, altered sodium accumulation phenotypes were observed in mutants of each gene class of the cytokinin signal transduction pathway, including receptors, phospho-transfer proteins, and type-A and type-B response regulators. Expression of the gene encoding Arabidopsis high-affinity K+ transporter 1;1 (AtHKT1;1), a gene responsible for removing sodium ions from the root xylem, was repressed by cytokinin treatment, but showed significantly elevated expression in the cytokinin response double mutant arr1-3 arr12-1. Our data suggest that cytokinin, acting through the transcription Entinostat factors ARR1 and ARR12, regulates sodium accumulation in the shoots by controlling the expression of AtHKT1;1 in

the roots.”
“Identification of regulatory relationships between transcription factors (TFs) and their targets is a central problem in post-genomic biology. In this paper, we apply an approach based on the support vector machine (SVM) and gene-expression data to predict the regulatory interactions in Arabidopsis. A set of 125 experimentally validated TF-target interactions and 750 negative regulatory gene pairs are collected as the training data. Their expression profiles data at 79 experimental conditions are fed to the SVM to perform the prediction. Through the jackknife cross-validation test, we find that the overall prediction accuracy of our approach achieves 88.68%. Our approach could help to widen the understanding of Arabidopsis gene regulatory scheme and may offer a cost-effective alternative to construct the gene regulatory network. (C) 2011 Elsevier Masson SAS. All rights reserved.