Structural investigations and biological activity of inositol sphingophospholipids from Phytophthora capsici

Inositol sphingophospholipids that protect pepper (Capsicum annuum c.v. Yolo Wonder) against pathogen have been isolated by chromatographic methods from the mycelium of Phytophthora capsici. The structure of the major compound was determined by chemical methods and mass spectrometry. Phosphodiester bond cleavage of the phospholipid by mild alkaline hydrolysis liberated a ceramide which contained a C16-sphingosine. This long-chain base was identified by gas chromatography and mass spectrometry of its trimethylsilyl derivative. One of the amide-linked fatty acids was found to be 4-hydroxy-2 docosenoic acid. Fast-atom-bombardment mass spectrometry and fast-atom-bombardment collison-induced tandem mass spectrometry were used to characterize the ceramide as N(4-hydroxy-2-docosenoyl)C16-sphingosine. These sphingolipids have a protective effect on cotyledons of young peppers against necrotic lesions induced by the pathogen P. capsici.     

8-Azidoadenosine and ribonucleotide reductase.

Inhibitors of ribonucleotide reductase are potential antiproliferative agents, since they deplete cells from DNA precursors. Substrate nucleoside analogues, carrying azido groups at the base moiety, are shown to have strong cytostatic properties, as measured by the inhibition of the incorporation of thymidine into DNA. One compound, 8-azidoadenosine, inhibits CDP reduction in cytosolic extracts from cancer cells. The corresponding diphosphate behaves as a substrate for ribonucleotide reductase while the triphosphate is an allosteric effector.     

Can Zipf's law be adapted to normalize microarrays?

Background  

Normalization is the process of removing non-biological sources of variation between array experiments. Recent investigations of data in gene expression databases for varying organisms and tissues have shown that the majority of expressed genes exhibit a power-law distribution with an exponent close to -1 (i.e. obey Zipf's law). Based on the observation that our single channel and two channel microarray data sets also followed a power-law distribution, we were motivated to develop a normalization method based on this law, and examine how it compares with existing published techniques. A computationally simple and intuitively appealing technique based on this observation is presented.