Reverse micelles in protein separation: the use of silica for the back-transfer process

In order to use reverse micellar solutions successfully for the separation of proteins, good methods are needed to recover the biomolecules into an aqueous environment after solubilization into organic micellar media. Usually the recovery is accomplished by equilibrating the protein-loaded reverse micellar solution with a water phase containing an appropriate salt (back-transfer). In this article we describe an alternative "back extraction" procedure which is based on the addition of silica to the protein-containing reverse micellar solution. In this way, the water is stripped from the reverse micellar solution. [i.e., bis(2-ethylhexyl) sodium sulfosuccinate (AOT)/isooctane/water] and the proteins adsorb to the silica particles. The adsorption process is shown to be practically quantitative. The subsequent recovery of the proteins form the silica into an aqueous solution turns out to be most efficient at alkaline pH (pH 8); 60-80 of the total protein (alpha-chymotrypsin or trypsin) could be recovered. The specific enzyme activity at the end of the whole cycle can be as high as 80-100%. The procedure is applied also for the back extraction from micellar solutions in which, instead of AOT, a biocompatible surfactant such as a synthetic short-chain lecithin was used. It is shown that the recovery of a alpha-chymotrypsin and trypsin is also achievable under these conditions in quite good yield and under good maintenance of the enzyme's catalytic activity. (c) 1993 John Wiley & Sons, Inc.     

Implications for molecular mechanisms of glycoprotein hormone receptors using a new sequence-structure-function analysis resource

Comparison between wild-type and mutated glycoprotein hormone receptors (GPHRs), TSH receptor, FSH receptor, and LH-chorionic gonadotropin receptor is established to identify determinants involved in molecular activation mechanism. The basic aims of the current work are 1) the discrimination of receptor phenotypes according to the differences between activity states they represent, 2) the assignment of classified phenotypes to three-dimensional structural positions to reveal 3) functional-structural hot spots and 4) interrelations between determinants that are responsible for corresponding activity states. Because it is hard to survey the vast amount of pathogenic and site-directed mutations at GPHRs and to improve an almost isolated consideration of individual point mutations, we present a system for systematic and diversified sequence-structure-function analysis (http://www.fmp-berlin.de/ssfa). To combine all mutagenesis data into one set, we converted the functional data into unified scaled values. This at least enables their comparison in a rough classification manner. In this study we describe the compiled data set and a wide spectrum of functions for user-driven searches and classification of receptor functionalities such as cell surface expression, maximum of hormone binding capability, and basal as well as hormone-induced Galphas/Galphaq mediated cAMP/inositol phosphate accumulation. Complementary to known databases, our data set and bioinformatics tools allow functional and biochemical specificities to be linked with spatial features to reveal concealed structure-function relationships by a semiquantitative analysis. A comprehensive discrimination of specificities of pathogenic mutations and in vitro mutant phenotypes and their relation to signaling mechanisms of GPHRs demonstrates the utility of sequence-structure-function analysis. Moreover, new interrelations of determinants important for selective G protein-mediated activation of GPHRs are resumed.     

每搏量变异度在围手术期容量治疗监测中的应用

每搏量变异度是动态的容量监测指标.机械通气患者心肺的相互作用是每搏量变异度的产生基础,通过动脉压力波形分析技术可以进行连续监测.每搏量变异度能够准确预测容量治疗反应,与静态的血流动力学参数相比,对于优化心输出量和组织氧供更有优势,但也存在一定的局限性.每搏量变异度受多种因素影响且不能用于自主呼吸和心律失常的患者.临床应用时应该综合考虑其影响因素,结合其他的指标和方法指导容量治疗.     

Gene mention normalization and interaction extraction with context models and sentence motifs

Background:

The goal of text mining is to make the information conveyed in scientific publications accessible to structured search and automatic analysis. Two important subtasks of text mining are entity mention normalization - to identify biomedical objects in text - and extraction of qualified relationships between those objects. We describe a method for identifying genes and relationships between proteins.

Results:

We present solutions to gene mention normalization and extraction of protein-protein interactions. For the first task, we identify genes by using background knowledge on each gene, namely annotations related to function, location, disease, and so on. Our approach currently achieves an f-measure of 86.4% on the BioCreative II gene normalization data. For the extraction of protein-protein interactions, we pursue an approach that builds on classical sequence analysis: motifs derived from multiple sequence alignments. The method achieves an f-measure of 24.4% (micro-average) in the BioCreative II interaction pair subtask.

Conclusion:

For gene mention normalization, our approach outperforms strategies that utilize only the matching of genes names against dictionaries, without invoking further knowledge on each gene. Motifs derived from alignments of sentences are successful at identifying protein interactions in text; the approach we present in this report is fully automated and performs similarly to systems that require human intervention at one or more stages.

Availability:

Our methods for gene, protein, and species identification, and extraction of protein-protein are available as part of the BioCreative Meta Services (BCMS), see http://bcms.bioinfo.cnio.es/.

     

GandrKB--ontological microarray annotation and visualization

SUMMARY: The Gandr (gene annotation data representation) knowledgebase is an ontological framework for laboratory-specific gene annotation. Gandr uses Protege 2000 for editing, querying and visualizing microarray data and annotations. Genes can be annotated with provided, newly created or imported ontological concepts. Annotated genes can inherit assigned concept properties and can be related to each other. The resulting knowledgebase can be visualized as interactive network of nodes and edges representing genes and their functional relationships. This allows for immediate and associative gene context exploration. Ontological query techniques allow for powerful data access.