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)     

In vitro interactions between DMSA-coated maghemite nanoparticles and human fibroblasts: A physicochemical and cyto-genotoxical study

Although the current production of oxide nanoparticles may be modest, the wide range of proposed applications and forecasted growth in production has raised questions about the potential impact of these nanoparticles on the environment and human health. Iron oxide nanoparticles have been proposed for an increasing number of biomedical applications although in vitro toxicity depending on the particles coating has been evidenced. The aim of this study was to examine the potential in vitro cyto- and genotoxicity on human dermal fibroblasts of DMSA-coated maghemite nanoparticles (NmDMSA) as a function of well-defined physicochemical states. Well-stabilized NmDMSA produced weak cytotoxic and no genotoxic effects. This is attributed in part to the DMSA coating, which serves as a barrier for a direct contact between nano-oxide and fibroblasts, inhibiting a potential toxic effect.     

Monitoring biodegradation of ethene and bioremediation of chlorinated ethenes at a contaminated site using compound-specific isotope analysis (CSIA)

Chlorinated ethenes are commonly found in contaminated groundwater. Remediation strategies focus on transformation processes that will ultimately lead to nontoxic products. A major concern with these strategies is the possibility of incomplete dechlorination and accumulation of toxic daughter products (cis-1,2-dichloroethene (cDCE), vinyl chloride (VC)). Ethene mass balance can be used as a direct indicator to assess the effectiveness of dechlorination. However, the microbial processes that affect ethene are not well characterized and poor mass balance may reflect biotransformation of ethene rather than incomplete dechlorination. Microbial degradation of ethene is commonly observed in aerobic systems but fewer cases have been reported in anaerobic systems. Limited information is available on the isotope enrichment factors associated with these processes. Using compound-specific isotope analysis (CSIA) we determined the enrichment factors associated with microbial degradation of ethene in anaerobic microcosms (ε = -6.7‰ ± 0.4‰, and -4.0‰ ± 0.8‰) from cultures collected from the Twin Lakes wetland area at the Savannah River site in Georgia (United States), and in aerobic microcosms (ε = -3.0‰ ± 0.3‰) from Mycobacterium sp. strain JS60. Under anaerobic and aerobic conditions, CSIA can be used to determine whether biotransformation of ethene is occurring in addition to biodegradation of the chlorinated ethenes. Using δ(13)C values determined for ethene and for chlorinated ethenes at a contaminated field site undergoing bioremediation, this study demonstrates how CSIA of ethene can be used to reduce uncertainty and risk at a site by distinguishing between actual mass balance deficits during reductive dechlorination and apparent lack of mass balance that is related to biotransformation of ethene.     

Sorbent injection into a slipstream baghouse for mercury control: Project summary

A project led by the Energy and Environmental Research Center to test and demonstrate sorbent injection as a cost-effective mercury control technology for utilities burning lignites has shown effective mercury capture under a range of operating conditions. Screening, parametric, and long-term tests were carried out at a slipstream facility representing an electrostatic precipitator–activated carbon injection–fabric filter configuration (called a TOXECON™ in the United States). Screening tests of sorbent injection evaluated nine different sorbents, including both treated and standard activated carbon, to compare mercury capture as a function of sorbent injection rate. Parametric tests evaluated several variables including air-to-cloth (A/C) ratio, flue gas temperature, cleaning frequency, and dust loading to determine the effect on mercury control and systems operation. Long-term tests (approximately 2 months in duration) evaluated the sustainability of systems operation.     

Modeling improvements in booster seat use: a discrete choice conjoint experiment

Automobile crashes are the leading cause of death in children aged 1–14 years. Many children, however, are not properly restrained in safety seats that reduce serious injury and death. This study used a discrete choice conjoint experiment to study factors influencing the decision to use booster seats. Parents of 1714 children aged 4–9 years from nine Canadian provinces completed choice tasks presenting experimentally varied combinations of 15 4-level booster seat promotion attributes. Latent class analysis yielded three segments of parents. The choices of the Benefit Sensitive segment (50%) were most sensitive to the injury prevention benefits of booster seats. The choices of parents in the Context Sensitive segment (33.5%) were more likely to be influenced by installation complexity, oppositional behavior, and the prospect that their child may be teased for riding in booster seats. Parents in the High Risk segment (16.5%) were younger, less educated, and less knowledgeable about vehicle safety legislation. They anticipated fewer benefits, expected more barriers and were less likely to use booster seats. Simulations suggest that consistent enforcement coupled with advertising focusing on injury prevention and the use of booster seats by other parents would increase adoption.