The world's first wiki where authorship really matters (Nature Genetics, 2008). Due credit and reputation for authors. Imagine a global collaborative knowledge base for original thoughts. Search thousands of articles and collaborate with scientists around the globe.

wikigene or wiki gene protein drug chemical gene disease author authorship tracking collaborative publishing evolutionary knowledge reputation system wiki2.0 global collaboration genes proteins drugs chemicals diseases compound
Hoffmann, R. A wiki for the life sciences where authorship matters. Nature Genetics (2008)

Prediction of nephrotoxicant action and identification of candidate toxicity-related biomarkers.

A vast majority of pharmacological compounds and their metabolites are excreted via the urine, and within the complex structure of the kidney,the proximal tubules are a main target site of nephrotoxic compounds. We used the model nephrotoxicants mercuric chloride, 2-bromoethylamine hydrobromide, hexachlorobutadiene, mitomycin, amphotericin, and puromycin to elucidate time- and dose-dependent global gene expression changes associated with proximal tubular toxicity. Male Sprague-Dawley rats were dosed via intraperitoneal injection once daily for mercuric chloride and amphotericin (up to 7 doses), while a single dose was given for all other compounds. Animals were exposed to 2 different doses of these compounds and kidney tissues were collected on day 1, 3, and 7 postdosing. Gene expression profiles were generated from kidney RNA using 17K rat cDNA dual dye microarray and analyzed in conjunction with histopathology. Analysis of gene expression profiles showed that the profiles clustered based on similarities in the severity and type of pathology of individual animals. Further, the expression changes were indicative of tubular toxicity showing hallmarks of tubular degeneration/regeneration and necrosis. Use of gene expression data in predicting the type of nephrotoxicity was then tested with a support vector machine (SVM)-based approach. A SVM prediction module was trained using 120 profiles of total profiles divided into four classes based on the severity of pathology and clustering. Although mitomycin C and amphotericin B treatments did not cause toxicity, their expression profiles were included in the SVM prediction module to increase the sample size. Using this classifier, the SVM predicted the type of pathology of 28 test profiles with 100% selectivity and 82% sensitivity. These data indicate that valid predictions could be made based on gene expression changes from a small set of expression profiles. A set of potential biomarkers showing a time- and dose-response with respect to the progression of proximal tubular toxicity were identified. These include several transporters (Slc21a2, Slc15, Slc34a2), Kim 1, IGFbp-1, osteopontin, alpha-fibrinogen, and Gstalpha.[1]


  1. Prediction of nephrotoxicant action and identification of candidate toxicity-related biomarkers. Thukral, S.K., Nordone, P.J., Hu, R., Sullivan, L., Galambos, E., Fitzpatrick, V.D., Healy, L., Bass, M.B., Cosenza, M.E., Afshari, C.A. Toxicologic pathology. (2005) [Pubmed]
WikiGenes - Universities