Role of bacterial extracellular polymers in metal uptake in pure bacterial culture and activated sludge—I. Effects of metal concentration

A gel filtration technique afforded a good separation between metal complexed with bacterial extracellular polymers and free metal ions. The complexation of polymers extracted from cultures of Klehsiella aerogenes and activated sludge with cadmium, nickel, manganese and cobalt was demonstrated. The extraction of extracellular polymers from cultures of K. aerogenes and activated sludge reduced the capacity of the cells and flocs to adsorb metal. Adsorption and complexation of metals by cells of K. aerogenes and extracellular polymers extracted from activated sludge were fitted to Freundlich equilibrium isotherms. Saturation of activated sludge polymer binding sites occurred at 10 mg 1^?1 metal additions for all the metals studied except manganese which was complexed to a very limited extent. Cells of K. aerogenes exhibited no saturation effects in the range of metal concentrations studied.Precipitation of metals below a concentration of 1 mg 1^?1 was minimal, with the exception of cadmium precipitation. At a concentration of 10 mg 1^?1, precipitation of cadmium, cobalt and manganese may have been the major mechanism of metal removal. The more soluble metals generally displayed the lowest removals. Concentrations of extracellular polymers and soluble chelating agents may be important in controlling removals of metals which are largely soluble in activated sludge.     

A neutral loss activation method for improved phosphopeptide sequence analysis by quadrupole ion trap mass spectrometry

Recent advances in phosphopeptide enrichment prior to mass spectrometric analysis show genuine promise for characterization of phosphoproteomes. Tandem mass spectrometry of phosphopeptide ions, using collision-activated dissociation (CAD), often produces product ions dominated by the neutral loss of phosphoric acid. Here we describe a novel method, termed Pseudo MS(n), for phosphopeptide ion dissociation in quadrupole ion trap mass spectrometers. The method induces collisional activation of product ions, those resulting from neutral loss(es) of phosphoric acid, following activation of the precursor ion. Thus, the principal neutral loss product ions are converted into a variety of structurally informative species. Since product ions from both the original precursor activation and all subsequent neutral loss product activations are simultaneously stored, the method generates a "composite" spectrum containing fragments derived from multiple precursors. In comparison to analysis by conventional MS/MS (CAD), Pseudo MS(n) shows improved phosphopeptide ion dissociation for 7 out of 10 synthetic phosphopeptides, as judged by an automated search algorithm (TurboSEQUEST). A similar overall improvement was observed upon application of Pseudo MS(n) to peptides generated by enzymatic digestion of a single phosphoprotein. Finally, when applied to a complex phosphopeptide mixture, several phosphopeptides mis-assigned by TurboSEQUEST under the conventional CAD approach were successfully identified after analysis by Pseudo MS(n).     

Isolation,characterization, and quantitative analysis of Microviridin J,a new Microcystis metabolite toxic to Daphnia

This paper describes the purification and characterization of microviridin J, a newly discovered metabolite of Microcystis that causes a lethal molting disruption in Daphnia spp., upon ingestion of living cyanobacterial cells. Microviridin J consists of an acetylated chain of 13 amino acids arranged in three rings and two side chains. Unlike other known isoforms of microviridin, microviridin J contains arginine that imparts a unique solution conformation characterized by proximal hydrophobic interactions between Arg and other regions of the molecule. This eventually results in the formation and stabilization of an additional ring system. Microviridin J potently inhibits porcine trypsin, bovine chymotrypsin, and daphnid trypsin-like proteases. The activity against trypsin is most likely due to Arg and its distinctive conformational interactions. Overall, the data presented for microviridin J emphasize once again the ability of cyanobacteria to produce numerous and potent environmental toxins.     

Stability of feature selection algorithms: a study on high-dimensional spaces

With the proliferation of extremely high-dimensional data, feature selection algorithms have become indispensable components of the learning process. Strangely, despite extensive work on the stability of learning algorithms, the stability of feature selection algorithms has been relatively neglected. This study is an attempt to fill that gap by quantifying the sensitivity of feature selection algorithms to variations in the training set. We assess the stability of feature selection algorithms based on the stability of the feature preferences that they express in the form of weights-scores, ranks, or a selected feature subset. We examine a number of measures to quantify the stability of feature preferences and propose an empirical way to estimate them. We perform a series of experiments with several feature selection algorithms on a set of proteomics datasets. The experiments allow us to explore the merits of each stability measure and create stability profiles of the feature selection algorithms. Finally, we show how stability profiles can support the choice of a feature selection algorithm. Alexandros Kalousis received the B.Sc. degree in computer science, in 1994, and the M.Sc. degree in advanced information systems, in 1997, both from the University of Athens, Greece. He received the Ph.D. degree in meta-learning for classification algorithm selection from the University of Geneva, Department of Computer Science, Geneva, in 2002. Since then he is a Senior Researcher in the same university. His research interests include relational learning with kernels and distances, stability of feature selection algorithms, and feature extraction from spectral data. Julien Prados is a Ph.D. student at the University of Geneva, Switzerland. In 1999 and 2001, he received the B.Sc. and M.Sc. degrees in computer science from the University Joseph Fourier (Grenoble, France). After a year of work in industry, he joined the Geneva Artificial Intelligence Laboratory, where he is working on bioinformatics and datamining tools for mass spectrometry data analysis. Melanie Hilario has a Ph.D. in computer science from the University of Paris VI and currently works at the University of Geneva’s Artificial Intelligence Laboratory. She has initiated and participated in several European research projects on neuro-symbolic integration, meta-learning, and biological text mining. She has served on the program committees of many conferences and workshops in machine learning, data mining, and artificial intelligence. She is currently an Associate Editor of theInternational Journal on Artificial Intelligence Toolsand a member of the Editorial Board of theIntelligent Data Analysis journal.     

Towards a feminist empowerment model of forgiveness psychotherapy.

In recent years Enright and Fitzgibbon's (2000) process model of forgiveness therapy has received substantial theoretical and empirical attention. However, both the process model of forgiveness therapy and the social-cognitive developmental model on which it is based have received criticism from feminist theorists. The current paper considers feminist criticisms of forgiveness therapy and uses a feminist lens to identify potential areas for growth. Specifically, Worell and Remer's (2003) model of synthesizing feminist ideals into existing theory was consulted, areas of bias within the forgiveness model of psychotherapy were identified, and strategies for restructuring areas of potential bias were introduced. Further, the authors consider unique aspects of forgiveness therapy that can potentially strengthen existing models of feminist therapy. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Life on the line: Job demands, perceived co-worker support for safety, and hazardous work events.

The present study of 334 United Kingdom trackside workers tested an interaction hypothesis. We hypothesized, drawing on the job demands-resources framework, that perceived support for safety (from senior managers, supervisors, and coworkers) as job resources would weaken the relationship between higher job demands and more frequent hazardous work events. Consistent with social impact theory, we predicted that perceived coworker support for safety would be particularly influential when trackside workers faced higher job demands. Moderated multiple regression showed that, of all three sources of perceived support for safety, perceived coworker support for safety was most important for keeping employees safe in the face of high job demands. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The effect of ion implantation on the corrosion behaviour of pure iron—I. Argonion implantation

High purity iron has been implanted with relatively high (ca. 5 at.%) surface concentrations of argon by means of ion implantation. Using electrometric reduction it has been shown that at some stage during or after the implantation process the natural air-formed film on the iron is thickened, producing an oxide film comparable to a thermally grown film formed at low oxygen partial pressure (～ 30μN m^?2) at 475K. The factor responsible for this enhanced film growth has not been identified. Using a three sweep potentiokinetic polarization technique it has also been shown that once the thickened air formed film is removed by cathodic polarization there are no significant differences between the polarization behaviour of unimplanted and argon implanted iron that cannot be explained by changes in surface roughness associated with the implantation process.It is concluded that earlier reports that the implantation of metals with inert species such as argon confers enhanced corrosion resistance may be attributed to the thickening of the air-formed oxide film and not to the presence of the implant species per se. Furthermore, in the investigation of the effect of implantation of more active implant species it is necessary to take account of the film thickening that occurs during implantation.     

Distributing working memory resources during problem solving.

This study examines how problem solvers distribute working memory demands over internal and external resources. Participants recorded notes while performing an arithmetic task. They recorded a majority of intermediate results and labeled many of those results (e.g., "C?=?10"). When more effort was required to take notes, participants recorded fewer results. Participants with a consistent goal structure recorded fewer results and with practice labeled fewer recorded results than those with varied goal structures. When notes were displayed in a consistent spatial arrangement participants labeled fewer recorded results than when notes appeared in varied locations. These findings indicate that individuals use explicit and implicit strategies for indexing intermediate results. The data support the view that individuals flexibly distribute working memory over internal and external resources in response to situational cost-benefit considerations. (PsycINFO Database Record (c) 2010 APA, all rights reserved)