Bio-SCoRes: A Smorgasbord Architecture for Coreference Resolution in Biomedical Text

Coreference resolution is one of the fundamental and challenging tasks in natural language processing. Resolving coreference successfully can have a significant positive effect on downstream natural language processing tasks, such as information extraction and question answering. The importance of coreference resolution for biomedical text analysis applications has increasingly been acknowledged. One of the difficulties in coreference resolution stems from the fact that distinct types of coreference (e.g., anaphora, appositive) are expressed with a variety of lexical and syntactic means (e.g., personal pronouns, definite noun phrases), and that resolution of each combination often requires a different approach. In the biomedical domain, it is common for coreference annotation and resolution efforts to focus on specific subcategories of coreference deemed important for the downstream task. In the current work, we aim to address some of these concerns regarding coreference resolution in biomedical text. We propose a general, modular framework underpinned by a smorgasbord architecture (Bio-SCoRes), which incorporates a variety of coreference types, their mentions and allows fine-grained specification of resolution strategies to resolve coreference of distinct coreference type-mention pairs. For development and evaluation, we used a corpus of structured drug labels annotated with fine-grained coreference information. In addition, we evaluated our approach on two other corpora (i2b2/VA discharge summaries and protein coreference dataset) to investigate its generality and ease of adaptation to other biomedical text types. Our results demonstrate the usefulness of our novel smorgasbord architecture. The specific pipelines based on the architecture perform successfully in linking coreferential mention pairs, while we find that recognition of full mention clusters is more challenging. The corpus of structured drug labels (SPL) as well as the components of Bio-SCoRes and some of the pipelines based on it are publicly available at https://github.com/kilicogluh/Bio-SCoRes. We believe that Bio-SCoRes can serve as a strong and extensible baseline system for coreference resolution of biomedical text.     

Evolutionary advances in the higher fungi

In this report the phrase evolutionary advances; is used in three ways: 1. to describe monophyletic changes perceived within a lineage; 2. to describe evolutionary sequences that appear to have become parallel/convergent; 3. to describe major transitions inferred between primary taxa. In monophyletic evolution the changes occur within a specific lineage that arises from a common ancestor, e.g., modern Man, horses, rusts. In parallel/convergent evolution different lineages respond similarly over time to environmental challenges and opportunities and come to acquire a great deal of comparability (e.g., Webster, 1987). Such lineages may be designated as separate taxa, e.g., similarities in marsupial and placental carnivores, or, if the polyphyleticism is cryptic, as a collective taxon, e.g., Aves, the class of birds, the obsolete Amentiferae for catkin bearing plants, the Gasteromycetes, and lichens. In major transitions there are significant paradigm shifts in which evolutionary changes from one predominant life style pattern to another are accompanied by increases in complexity (see Smith & Szatháry, 1995), e.g., symbiosis, the water to land transition, the changes between the phyla of land fungi. Three particular terms are used in evaluating evolutionary relationships (Moore, 1996a): homology, paramology, and analogy. Homology, from Darwin';s theory of common descent, is the phenomenon of having a common historical origin but not necessarily the same final structure or function (e.g., vertebrate forelimbs). Paramology (Moore, 1971) applies to inferred relationships in evolutionary schemes based on contemporary forms that lack fossil antecedents, e.g., the various phylogenetic interpretations of prokaryotes, algae, and fungi; Boekhout et al. (1993) have evaluated the taxonomic resolution of a variety of morphologic, biochemical, physiological, and molecular characters (Table 1). Analogy is generally applied to similar forms that are unrelated, e.g., insect/vertebrate wings; prokaryote/eukaryote flagella. It should also be borne in mind that, in a given taxon, biotrophism (Coffey, 1975) is an advanced character (Heath, 1987) over, respectively, weaker parasitism, symbiotism, commensalism, and freeliving and that seemingly simple or less differentiated forms can be, and more than likely than not are, reduced, polyphyletic, and specialized rather than ancient and rudimentary, e.g., yeasts (Hoog et al., 1988; Kurtzman & Fell, 1996; Moore, 1988b; 1996a).     

Ensemble-Biased Metadynamics: A Molecular Simulation Method to Sample Experimental Distributions

We introduce an enhanced-sampling method for molecular dynamics (MD) simulations referred to as ensemble-biased metadynamics (EBMetaD). The method biases a conventional MD simulation to sample a molecular ensemble that is consistent with one or more probability distributions known a priori, e.g., experimental intramolecular distance distributions obtained by double electron-electron resonance or other spectroscopic techniques. To this end, EBMetaD adds an adaptive biasing potential throughout the simulation that discourages sampling of configurations inconsistent with the target probability distributions. The bias introduced is the minimum necessary to fulfill the target distributions, i.e., EBMetaD satisfies the maximum-entropy principle. Unlike other methods, EBMetaD does not require multiple simulation replicas or the introduction of Lagrange multipliers, and is therefore computationally efficient and straightforward in practice. We demonstrate the performance and accuracy of the method for a model system as well as for spin-labeled T4 lysozyme in explicit water, and show how EBMetaD reproduces three double electron-electron resonance distance distributions concurrently within a few tens of nanoseconds of simulation time. EBMetaD is integrated in the open-source PLUMED plug-in (www.plumed-code.org), and can be therefore readily used with multiple MD engines.     

DisCons: a novel tool to quantify and classify evolutionary conservation of intrinsic protein disorder

Background

Analyzing the amino acid sequence of an intrinsically disordered protein (IDP) in an evolutionary context can yield novel insights on the functional role of disordered regions and sequence element(s). However, in the case of many IDPs, the lack of evolutionary conservation of the primary sequence can hamper the study of functionality, because the conservation of their disorder profile and ensuing function(s) may not appear in a traditional analysis of the evolutionary history of the protein.

Results

Here we present DisCons (Disorder Conservation), a novel pipelined tool that combines the quantification of sequence- and disorder conservation to classify disordered residue positions. According to this scheme, the most interesting categories (for functional purposes) are constrained disordered residues and flexible disordered residues. The former residues show conservation of both the sequence and the property of disorder and are associated mainly with specific binding functionalities (e.g., short, linear motifs, SLiMs), whereas the latter class correspond to segments where disorder as a feature is important for function as opposed to the identity of the underlying sequence (e.g., entropic chains and linkers). DisCons therefore helps with elucidating the function(s) arising from the disordered state by analyzing individual proteins as well as large-scale proteomics datasets.

Conclusions

DisCons is an openly accessible sequence analysis tool that identifies and highlights structurally disordered segments of proteins where the conformational flexibility is conserved across homologs, and therefore potentially functional. The tool is freely available both as a web application and as stand-alone source code hosted at http://pedb.vib.be/discons.     

Do women's preferences for symmetry change across the menstrual cycle?

In many species, symmetry enhances physical attractiveness of the face and body. In humans, facial attractiveness is also enhanced by symmetrical decoration in the form of facial paint [Cárdenas, R. A., & Harris, L. J. (2006)]. According to the good-genes hypothesis [e.g., Thornhill, R., & Gangestad, S. W. (1999)], symmetry is preferred because it is associated with mate quality. According to the receiver bias hypothesis [e.g., Enquist, M., & Johnstone, R. (1997)], it is a by-product of how the visual system is designed. Proponents of the good-genes hypothesis have suggested that a preference for symmetry may vary with fertility, namely, that it will be enhanced in women in the high-fertility phase of the menstrual cycle. Previous research does demonstrate that, during this phase, women prefer the scent of more symmetrical men [e.g., Gangestad, S. W., & Thornhill, R. (1998)]. However, research employing assessment of faces fails to find a similar effect [Koehler, N., Rhodes, G., & Simmons, L. W. (2002)]. Previous research asked subjects to judge faces one at a time during high fertility (around ovulation) and low fertility (menstruation). We used a different face-presentation method, tested women during the other low-fertility (midluteal) phase, and used decorated as well as undecorated faces. As in our prior study [Cárdenas, R. A., & Harris, L. J. (2006)], symmetry of facial features and symmetry of decoration enhanced attractiveness, but, contrary to the possible prediction of the good-genes hypothesis, the effects did not vary across the cycle. The results as they are, therefore, can be equally accommodated by both hypotheses.     

Further comments on analysis of covariance in insect dietary studies

Raubenheimer & Simpson (1992) recently discussed the advantages of using analysis of covariance in insect dietary studies as an alternative to the more conventional ratio-based nutritional indices. We expand on some interpretations of Raubenheimer & Simpson and illustrate our points with examples from published and unpublished data sets. Specifically, we show that an ANCOVA on biomass gain incorporating initial biomass as a covariate provides information not immediately available using the analysis suggested by Raubenheimer & Simpson (ANCOVA on final biomass incorporating initial biomass as a covariate). Second, we show that dietary studies in which the covariate (food consumption) is affected by diet can provide information about the relative importance of preingestive effects (e.g., deterrence) and postingestive effects (e.g., antibiosis) on performance. Cautions about this latter use of ANCOVA are discussed.     

Proportional hazards tests and diagnostics based on weighted residuals

Nonproportional hazards can often be expressed by extendingthe Cox model to include time varying coefficients; e.g., fora single covariate, the hazard function for subject i is modelledas exp {β(t)Zi(t)}. A common example is a treatment effectthat decreases with time. We show that the function βi(t)can be directly visualized by smoothing an appropriate residualplot. Also, many tests of proportional hazards, including thoseof Cox (1972), Gill & Schumacher (1987), Harrell (1986),Lin (1991), Moreau, O'Quigley & Mesbah (1985), Nagelkerke,Oosting & Hart (1984), O'Quigley & Pessione (1989),Schoenfeld (1980) and Wei (1984) are related to time-weightedscore tests of the proportional hazards hypothesis, and canbe visualized as a weighted least-squares line fitted to theresidual plot.     

CoMeta: Classification of Metagenomes Using k-mers

Nowadays, the study of environmental samples has been developing rapidly. Characterization of the environment composition broadens the knowledge about the relationship between species composition and environmental conditions. An important element of extracting the knowledge of the sample composition is to compare the extracted fragments of DNA with sequences derived from known organisms. In the presented paper, we introduce an algorithm called CoMeta (Classification of metagenomes), which assigns a query read (a DNA fragment) into one of the groups previously prepared by the user. Typically, this is one of the taxonomic rank (e.g., phylum, genus), however prepared groups may contain sequences having various functions. In CoMeta, we used the exact method for read classification using short subsequences (k-mers) and fast program for indexing large set of k-mers. In contrast to the most popular methods based on BLAST, where the query is compared with each reference sequence, we begin the classification from the top of the taxonomy tree to reduce the number of comparisons. The presented experimental study confirms that CoMeta outperforms other programs used in this context. CoMeta is available at https://github.com/jkawulok/cometa under a free GNU GPL 2 license.     

Neighbor-Dependent Ramachandran Probability Distributions of Amino Acids Developed from a Hierarchical Dirichlet Process Model

Distributions of the backbone dihedral angles of proteins have been studied for over 40 years. While many statistical analyses have been presented, only a handful of probability densities are publicly available for use in structure validation and structure prediction methods. The available distributions differ in a number of important ways, which determine their usefulness for various purposes. These include: 1) input data size and criteria for structure inclusion (resolution, R-factor, etc.); 2) filtering of suspect conformations and outliers using B-factors or other features; 3) secondary structure of input data (e.g., whether helix and sheet are included; whether beta turns are included); 4) the method used for determining probability densities ranging from simple histograms to modern nonparametric density estimation; and 5) whether they include nearest neighbor effects on the distribution of conformations in different regions of the Ramachandran map. In this work, Ramachandran probability distributions are presented for residues in protein loops from a high-resolution data set with filtering based on calculated electron densities. Distributions for all 20 amino acids (with cis and trans proline treated separately) have been determined, as well as 420 left-neighbor and 420 right-neighbor dependent distributions. The neighbor-independent and neighbor-dependent probability densities have been accurately estimated using Bayesian nonparametric statistical analysis based on the Dirichlet process. In particular, we used hierarchical Dirichlet process priors, which allow sharing of information between densities for a particular residue type and different neighbor residue types. The resulting distributions are tested in a loop modeling benchmark with the program Rosetta, and are shown to improve protein loop conformation prediction significantly. The distributions are available at http://dunbrack.fccc.edu/hdp.     

GenGIS 2: Geospatial Analysis of Traditional and Genetic Biodiversity,with New Gradient Algorithms and an Extensible Plugin Framework

GenGIS is free and open source software designed to integrate biodiversity data with a digital map and information about geography and habitat. While originally developed with microbial community analyses and phylogeography in mind, GenGIS has been applied to a wide range of datasets. A key feature of GenGIS is the ability to test geographic axes that can correspond to routes of migration or gradients that influence community similarity. Here we introduce GenGIS version 2, which extends the linear gradient tests introduced in the first version to allow comprehensive testing of all possible linear geographic axes. GenGIS v2 also includes a new plugin framework that supports the development and use of graphically driven analysis packages: initial plugins include implementations of linear regression and the Mantel test, calculations of alpha-diversity (e.g., Shannon Index) for all samples, and geographic visualizations of dissimilarity matrices. We have also implemented a recently published method for biomonitoring reference condition analysis (RCA), which compares observed species richness and diversity to predicted values to determine whether a given site has been impacted. The newest version of GenGIS supports vector data in addition to raster files. We demonstrate the new features of GenGIS by performing a full gradient analysis of an Australian kangaroo apple data set, by using plugins and embedded statistical commands to analyze human microbiome sample data, and by applying RCA to a set of samples from Atlantic Canada. GenGIS release versions, tutorials and documentation are freely available at http://kiwi.cs.dal.ca/GenGIS, and source code is available at https://github.com/beiko-lab/gengis.     

Fast and Accurate Discovery of Degenerate Linear Motifs in Protein Sequences

Linear motifs mediate a wide variety of cellular functions, which makes their characterization in protein sequences crucial to understanding cellular systems. However, the short length and degenerate nature of linear motifs make their discovery a difficult problem. Here, we introduce MotifHound, an algorithm particularly suited for the discovery of small and degenerate linear motifs. MotifHound performs an exact and exhaustive enumeration of all motifs present in proteins of interest, including all of their degenerate forms, and scores the overrepresentation of each motif based on its occurrence in proteins of interest relative to a background (e.g., proteome) using the hypergeometric distribution. To assess MotifHound, we benchmarked it together with state-of-the-art algorithms. The benchmark consists of 11,880 sets of proteins from S. cerevisiae; in each set, we artificially spiked-in one motif varying in terms of three key parameters, (i) number of occurrences, (ii) length and (iii) the number of degenerate or “wildcard” positions. The benchmark enabled the evaluation of the impact of these three properties on the performance of the different algorithms. The results showed that MotifHound and SLiMFinder were the most accurate in detecting degenerate linear motifs. Interestingly, MotifHound was 15 to 20 times faster at comparable accuracy and performed best in the discovery of highly degenerate motifs. We complemented the benchmark by an analysis of proteins experimentally shown to bind the FUS1 SH3 domain from S. cerevisiae. Using the full-length protein partners as sole information, MotifHound recapitulated most experimentally determined motifs binding to the FUS1 SH3 domain. Moreover, these motifs exhibited properties typical of SH3 binding peptides, e.g., high intrinsic disorder and evolutionary conservation, despite the fact that none of these properties were used as prior information. MotifHound is available (http://michnick.bcm.umontreal.ca or http://tinyurl.com/motifhound) together with the benchmark that can be used as a reference to assess future developments in motif discovery.     

Xanthomonas hortorum – beyond gardens: Current taxonomy,genomics, and virulence repertoires

TaxonomyBacteria; Phylum Proteobacteria; Class Gammaproteobacteria; Order Lysobacterales (earlier synonym of Xanthomonadales); Family Lysobacteraceae (earlier synonym of Xanthomonadaceae); Genus Xanthomonas; Species X. hortorum; Pathovars: pv. carotae, pv. vitians, pv. hederae, pv. pelargonii, pv. taraxaci, pv. cynarae, and pv. gardneri.Host range Xanthomonas hortorum affects agricultural crops, and horticultural and wild plants. Tomato, carrot, artichoke, lettuce, pelargonium, ivy, and dandelion were originally described as the main natural hosts of the seven separate pathovars. Artificial inoculation experiments also revealed other hosts. The natural and experimental host ranges are expected to be broader than initially assumed. Additionally, several strains, yet to be assigned to a pathovar within X. hortorum, cause diseases on several other plant species such as peony, sweet wormwood, lavender, and oak‐leaf hydrangea.Epidemiology and control X. hortorum pathovars are mainly disseminated by infected seeds (e.g., X. hortorum pvs carotae and vitians) or cuttings (e.g., X. hortorum pv. pelargonii) and can be further dispersed by wind and rain, or mechanically transferred during planting and cultivation. Global trade of plants, seeds, and other propagating material constitutes a major pathway for their introduction and spread into new geographical areas. The propagules of some pathovars (e.g., X. horturum pv. pelargonii) are spread by insect vectors, while those of others can survive in crop residues and soils, and overwinter until the following growing season (e.g., X. hortorum pvs vitians and carotae). Control measures against X. hortorum pathovars are varied and include exclusion strategies (i.e., by using certification programmes and quarantine regulations) to multiple agricultural practices such as the application of phytosanitary products. Copper‐based compounds against X. hortorum are used, but the emergence of copper‐tolerant strains represents a major threat for their effective management. With the current lack of efficient chemical or biological disease management strategies, host resistance appears promising, but is not without challenges. The intrastrain genetic variability within the same pathovar poses a challenge for breeding cultivars with durable resistance.Useful websites https://gd.eppo.int/taxon/XANTGA, https://gd.eppo.int/taxon/XANTCR, https://gd.eppo.int/taxon/XANTPE, https://www.euroxanth.eu, http://www.xanthomonas.org, http://www.xanthomonas.org/dokuwiki     

Integrated Analysis Platform: An Open-Source Information System for High-Throughput Plant Phenotyping

High-throughput phenotyping is emerging as an important technology to dissect phenotypic components in plants. Efficient image processing and feature extraction are prerequisites to quantify plant growth and performance based on phenotypic traits. Issues include data management, image analysis, and result visualization of large-scale phenotypic data sets. Here, we present Integrated Analysis Platform (IAP), an open-source framework for high-throughput plant phenotyping. IAP provides user-friendly interfaces, and its core functions are highly adaptable. Our system supports image data transfer from different acquisition environments and large-scale image analysis for different plant species based on real-time imaging data obtained from different spectra. Due to the huge amount of data to manage, we utilized a common data structure for efficient storage and organization of data for both input data and result data. We implemented a block-based method for automated image processing to extract a representative list of plant phenotypic traits. We also provide tools for build-in data plotting and result export. For validation of IAP, we performed an example experiment that contains 33 maize (Zea mays ‘Fernandez’) plants, which were grown for 9 weeks in an automated greenhouse with nondestructive imaging. Subsequently, the image data were subjected to automated analysis with the maize pipeline implemented in our system. We found that the computed digital volume and number of leaves correlate with our manually measured data in high accuracy up to 0.98 and 0.95, respectively. In summary, IAP provides a multiple set of functionalities for import/export, management, and automated analysis of high-throughput plant phenotyping data, and its analysis results are highly reliable.Plant bioinformatics faces the challenge of integrating information from the related “omics” fields to elucidate the functional relationship between genotype and observed phenotype (Edwards and Batley, 2004), known as the genotype-phenotype map (Houle et al., 2010). One of the main obstacles is our currently limited ability of systemic depiction and quantification of plant phenotypes, representing the so-called phenotyping bottleneck phenomenon (Furbank and Tester, 2011). To get a comprehensive genotype-phenotype map, more accurate and precise phenotyping strategies are required to empower high-resolution linkage mapping and genome-wide association studies in order to uncover underlying genetic variants associated with complex phenotypic traits, which aim to improve the efficiency, effectiveness, and economy of cultivars in plant breeding (Cobb et al., 2013). In the era of phenomics, automatic high-throughput phenotyping in a noninvasive manner is applied to identify and quantify plant phenotypic traits. Plants are bred in fully automated greenhouses under predefined environmental conditions with controlled temperature, watering, and humidity. To meet the demand of data access, exchange, and sharing, several phenomics-related projects in the context of several consortia have been launched, such as the International Plant Phenotyping Network (http://www.plantphenomics.com/), the European Plant Phenotyping Network (http://www.plant-phenotyping-network.eu/), and the German Plant Phenotyping Network (http://www.dppn.de/).Thanks to the development of new imaging and transport systems, various automated or semiautomated high-throughput plant phenotyping systems are being developed and used to examine plant function and performance under controlled conditions. PHENOPSIS (Granier et al., 2006) is one of the pioneering platforms that was developed to dissect genotype-environment effects on plant growth in Arabidopsis (Arabidopsis thaliana). GROWSCREEN (Walter et al., 2007; Biskup et al., 2009; Jansen et al., 2009; Nagel et al., 2012) was designed for rapid optical phenotyping of different plant species with respect to different biological aspects. Other systems in the context of high-throughput phenotyping include Phenodyn/Phenoarch (Sadok et al., 2007), TraitMill (Reuzeau et al., 2005; Reuzeau, 2007), Phenoscope (Tisné et al., 2013), RootReader3D (Clark et al., 2011), GROW Map (http://www.fz-juelich.de/ibg/ibg-2/EN/methods_jppc/methods_node.html), and LemnaTec Scanalyzer 3D. These developments enable the phenotyping of specific organs (e.g. leaf, root, and shoot) or of whole plants. Some of them are even used for three-dimensional plant analysis (Clark et al., 2011). Consequently, several specific software applications (a comprehensive list can be found at http://www.phenomics.cn/links.php), such as HYPOTrace (Wang et al., 2009), HTPheno (Hartmann et al., 2011), LAMINA (Bylesjö et al., 2008), PhenoPhyte (Green et al., 2012), Rosette Tracker (De Vylder et al., 2012), LeafAnalyser (Weight et al., 2008), RootNav (Pound et al., 2013), SmartGrain (Tanabata et al., 2012), and LemnaGrid, were designed to extract a wide range of measurements, such as height/length, width, shape, projected area, digital volume, compactness, relative growth rate, and colorimetric analysis.The huge amount of generated image data from various phenotyping systems requires appropriate data management as well as an appropriate analytical framework for data interpretation (Fiorani and Schurr, 2013). However, most of the developed image-analysis tools are designed for a specific task, for specific plant species, or are not freely available to the research community. They lack flexibility in terms of needed adaptations to meet new analysis requirements. For example, it would be desirable that a system could handle imaging data from different sources (either from fully automated high-throughput phenotyping systems or from setups where images are acquired manually), different imaging modalities (fluorescence, near-infrared, and thermal imaging), and/or different species (wheat [Triticum aestivum], barley [Hordeum vulgare], maize [Zea mays], and Arabidopsis).In this work, we present Integrated Analysis Platform (IAP), a scalable open-source framework, for high-throughput plant phenotyping data processing. IAP handles different image sources and helps to organize phenotypic data by retaining the metadata from the input in the result data set. In order to measure phenotypic traits in new or modified setups, users can easily create new analysis pipelines or modify the predefined ones. IAP provides various user-friendly interfaces at different system levels to meet the demands of users (e.g. software developers, bioinformaticians, and biologists) with different experiences in software programming.     

Reducing Specific Phobia/Fear in Young People with Autism Spectrum Disorders (ASDs) through a Virtual Reality Environment Intervention

Anxiety is common in children with autism spectrum disorders (ASD), with specific fears and phobias one of the most frequent subtypes. Specific fears and phobias can have a serious impact on young people with ASD and their families. In this study we developed and evaluated a unique treatment combining cognitive behaviour therapy (CBT) with graduated exposure in a virtual reality environment (VRE). Nine verbally fluent boys with an ASD diagnosis and no reported learning disability, aged 7 to 13 years old, were recruited. Each had anxiety around a specific situation (e.g. crowded buses) or stimulus (e.g. pigeons). An individualised scene was recreated in our ‘wrap-around’ VRE. In the VRE participants were coached by a psychologist in cognitive and behavioural techniques (e.g. relaxation and breathing exercises) while the exposure to the phobia/fear stimulus was gradually increased as the child felt ready. Each child received four 20–30 minute sessions. After participating in the study, eight of the nine children were able to tackle their phobia situation. Four of the participants completely overcame their phobia. Treatment effects were maintained at 12 months. These results provide evidence that CBT with VRE can be a highly effective treatment for specific phobia/fear for some young people with ASD.

Trial Registration

Controlled-Trials.com ISRCTN58483069.     

Structural features influential to enzymatic hydrolysis of cellulose-solvent-based pretreated pinewood and elmwood for ethanol production

Bioprocess and Biosystems Engineering - Dissolution of lignocelluloses in N-methylmorpholine-N-oxide (NMMO or NMO) at moderate conditions, e.g., 120 °C for 3 h under...     

Lipid Peroxidation in the Presence of Albumin,Inhibitory and Prooxidative Effects

Oxidative modifications of LDL are involved in atherogenesis. Previously we have developed a simple assay to evaluate the susceptibility of lipids to copper-induced peroxidation in the relatively natural milieu of unfractionated serum in the presence of excess citrate. Based on our previous results we have proposed that the inducer of peroxidation in our optimized assay is a copper-citrate complex. Recent investigations indicate that under certain conditions a copper-albumin complex may induce peroxidation of ascorbate. Two different complexes may be formed in albumin-containing systems (e.g. serum) namely 1:1 and 2:1 copper-albumin complexes. The aim of the present work was to evaluate the possibility that at least one of these complexes may be responsible for the induction of peroxidation of lipids in lipidic systems containing copper and albumin, including our optimized assay. Towards this end, we have investigated the dependence of copper-induced peroxidation on the concentration of added albumin in lipidic systems in the absence and presence of citrate. In all the systems investigated in this study (PLPC liposomes, LDL, HDL and mixtures of HDL and LDL) we found that at low concentrations of free copper (e.g. in the presence of excess citrate) the 2:1 copper-albumin complex is redox-active and that this complex is the major contributor to the initiation of lipid peroxidation in these systems and in our optimized assay. The possible relevance of the induction of peroxidation in vivo by the latter complex has yet to be studied. <footnote id="fn1"><no>*</no>This work was performed in partial fulfillment of the requirements for a Ph.D. degree of Dorit Samocha-Bonet, Sackler Faculty of Medicine, Tel-Aviv University, Israel. </footnote>     

N-Dithiasuccinoyl (Dts)-glycine: A novel oxidation reagent for the formation of intramolecular disulfide bridges under mild conditions

Summary Specific intramolecular cyclization to form disulfide bridges in peptides represents a major challenge to the synthetic art. The N-dithiasuccinoyl (Dts) function was originally proposed as an amino protecting group, removable under mild conditions by thiolysis [Barany, G. and Merrifield, R.B., J. Am. Chem. Soc., 99 (1977) 7363; 102 (1980) 3084]. We demonstrate here that this chemistry can be inverted, i.e., Dts-amines can be used as mild oxidation reagents that promote formation of intramolecular disulfide bridges. With oxytocin and deamino-oxytocin as models, and with Dts-glycine as the oxidant, we have shown the efficacy of this method under a variety of conditions: both components in solution; dithiol-peptide on a polymeric support and Dts-glycine in solution; and soluble dithiol-peptide with Dts-glycyl-resin. Kinetics have been determined under a range of conditions in mixtures of acetonitrile-phosphate buffer. The logarithm of the reaction rate (based on a simplified first-order assumption) varies linearly with pH; the slope of these correlations is 0.68±0.02. Under suboptimal conditions, by-products have been observed that include parallel and antiparallel dimers as well as trisulfide analogues. Optimized conditions give good yields and purities of the desired disulfides. Particular advantages of this approach include the lack of reactivity of Dts-glycine with all non-sulfhydryl side-chain functionalities found in peptides, and the fact that Dts-mediated oxidation is irreversible.This work was taken in part from the Ph.D. Thesis of L. Chen, University of Minnesota, Minneapolis, MN, U.S.A., January 1997 (in preparation). Preliminary reports of this work were made at the 14th American Peptide Symposium, Columbus, OH, U.S.A., June 18–23, 1995 (poster P-119), and at the Fourth International Symposium on Solid Phase Synthesis & Combinatorial Chemical Libraries, Edinburgh, Scotland, U.K., September 12–16, 1995 (Ref. 18).