Isolation and Identification of Eutypa lata from Pistacia vera in Greece

The fungus Eutypa lata (syn. E. armeniacae), known as the causal agent of the death of many different woody plants, was found on dead branches of pistachio (Pistacia vera L.) in Greece. Isolations from diseased branches yielded consistently typical colonies of the asexual stage of the fungus (Libertella blepharis, syn. Cytosporina sp.), which proved to be undistinguishable from other cultures of the pathogen obtained from 15 different hosts. Furthermore, all isolates from pistachio tested for pathogenicity on apricot were pathogenic and yielded characteristic cankers.     

Genetic Analysis of the Epidermal Differentiation Complex (EDC) on Human Chromosome 1q21: Chromosomal Orientation, New Markers, and a 6-Mb YAC Contig

The epidermal differentiation complex (EDC) unites a remarkable number of structurally, functionally, and evolutionarily related genes that play an important role in terminal differentiation of the human epidermis. It is localized within 2.05 Mb of region q21 on human chromosome 1. We have identified and characterized 24 yeast artificial chromosome (YAC) clones by mapping individual EDC genes, sequence-tagged site (STS) markers (D1S305, D1S442, D1S498, D1S1664), and 10 new region-specific probes (D1S3619–D1S3628). Here we present a contig that covers about 6 Mb of 1q21 including the entire EDC. Fluorescencein situhybridization on metaphase chromosomes with two YACs flanking the EDC determined its chromosomal orientation and established, in conjunction with physical mapping results, the following order of genes and STSs: 1cen–D1S442–D1S498–S100A10–THH–FLG–D1S1664–IVL–SPRR3–SPRR1–SPRR2–LOR–S100A9–S100A8–S100A7–S100A6–S100A5–S100A4–S100A3–S100A2–S100A1–D1S305–1qtel. These integrated physical, cytogenetic, and genetic mapping data will be useful for linkage analyses of diseases associated with region 1q21 and for the identification of novel genes and regulatory elements in the EDC.     

Immune network behavior—II. From oscillations to chaos and stationary states

Two types of behavior have been previously reported in models of immune networks. The typical behavior of simple models, which involve B cells only, is stationary behavior involving several steady states. Finite amplitude perturbations may cause the model to switch between different equilibria. The typical behavior of more realistic models, which involve both B cells and antibody, consists of autonomous oscillations and/or chaos. While stationary behavior leads to easy interpretations in terms of idiotypic memory, oscillatory behavior seems to be in better agreement with experimental data obtained in unimmunized animals. Here we study a series of models of the idiotypic interaction between two B cell clones. The models differ with respect to the incorporation of antibodies, B cell maturation and compartmentalization. The most complicated model in the series has two realistic parameter regimes in which the behavior is respectively stationary and chaotic. The stability of the equilibrium states and the structure and interactions of the stable and unstable manifolds of the saddle-type equilibria turn out to be factors influencing the model's behavior. Whether or not the model is able to attain any form of sustained oscillatory behavior, i.e. limit cycles or chaos, seems to be determined by (global) bifurcations involving the stable and unstable manifolds of the equilibrium states. We attempt to determine whether such behavior should be expected to be attained from reasonable initial conditions by incorporating an immune response to an antigen in the model. A comparison of the behavior of the model with experimental data from the literature provides suggestions for the parameter regime in which the immune system is operating.     

Physical mapping of the human T-cell receptor beta gene complex,using yeast artificial chromosomes

Yeast artificial chromosomes (YACs) were used to construct a physical map of the germline human T-cell chain gene complex (TCRB). Variable region genes (BV) for the 25 known subfamilies were used as probes to screen the ICRF AM4x YAC library. Of the five positive YACs identified, one YAC designated B3, 820 kilobase pairs (kbp) in size, scored positive for all 25 TCRBV subfamilies plus the constant region genes (BC) when analyzed by pulse field gel electrophoresis. Restriction enzyme mapping of B3 located TCRBV and TCRBC gene regions to 4 Sfi I fragments of 280 110, 90, and 125 kbp and was in accordance with published data. In addition comparison of hybridization results of Sfi I-restricted B3 and genomic DNA from the parental cell line GM1416B revealed identical banding patterns. The data thus showed YAC B3 encoded a complete and unrearranged TCRB gene locus of some 600–620 kbp. The map was further resolved by locating restriction sites for Sal I and Bss HII on B3, giving more precise localization of the individual TCRBV gene families. Flourescent in situ hybridization of B3 to spreads of human metaphase chromosomes localized B3 to 7q35. However, two additional signals were obtained; one attributable to the TCRBV orphon cluster on 9p21, the second to the long arm of chromosome 2. Polymerase chain reaction amplification of a chromosome 2 somatic cell hybrid, using primers for all 25 TCRBV gene families, revealed that the signal was not attributable to a second orphon cluster. It is suggested that B3 is a chimeric YAC with an intact TCRB locus flanked by chromosome 2 sequences.     

Specific delta-opioid antagonists exert an agonist-independent inhibitory effect,similar to the agonist,on the release of GnRHIn Vitro

Summary 1. Inin vitro studies with adult male rats we have recently shown that the delta-opioid agonist DTLET inhibits the release of the Gonadotropin-Releasing Hormone (GnRH) from hypothalamic fragments containing the arcuate nucleus and the median eminence. This effect is receptor mediated and eicosanoid dependent (Gerozissiset al., 1993).2. In the present study we report that the delta-opioid antagonists with negative intrinsic activity, Diallyl-G and ICI 174864, applied under the same experimental conditions (30 min static incubations at 37°C, in a potassium rich milieu), in the absence of the agonist DTLET, also exert a similar to the agonist inhibitory effect on the release of GnRH.3. The dose-dependent inhibitory effect of Diallyl-G on GnRH release is reversed by increasing concentrations of DTLET. The mu and delta opioid antagonist, naloxone is without effect in the absence of DTLET. However, naloxone acts as an antagonist on the Diallyl-G-induced inhibition of GnRH release.4. Diallyl-G also inhibits the release of prostaglandin E₂ (PGE₂). In the presence of indomethacin or nordihydroguaiaretic acid, Diallyl-G is ineffective to further inhibit the release of GnRH. These latter observations taken together with the results of eicosanoid estimation suggest that PGE₂ but not leukotrienes participate in the agonist-independent effects of Diallyl-G on GnRH release.5. Therefore these results support the hypothesis that delta-opioid antagonists with negative intrinsic activity exert agonist-independent biological responses similar to those of the agonists.     

Optimized Null Model for Protein Structure Networks

Much attention has recently been given to the statistical significance of topological features observed in biological networks. Here, we consider residue interaction graphs (RIGs) as network representations of protein structures with residues as nodes and inter-residue interactions as edges. Degree-preserving randomized models have been widely used for this purpose in biomolecular networks. However, such a single summary statistic of a network may not be detailed enough to capture the complex topological characteristics of protein structures and their network counterparts. Here, we investigate a variety of topological properties of RIGs to find a well fitting network null model for them. The RIGs are derived from a structurally diverse protein data set at various distance cut-offs and for different groups of interacting atoms. We compare the network structure of RIGs to several random graph models. We show that 3-dimensional geometric random graphs, that model spatial relationships between objects, provide the best fit to RIGs. We investigate the relationship between the strength of the fit and various protein structural features. We show that the fit depends on protein size, structural class, and thermostability, but not on quaternary structure. We apply our model to the identification of significantly over-represented structural building blocks, i.e., network motifs, in protein structure networks. As expected, choosing geometric graphs as a null model results in the most specific identification of motifs. Our geometric random graph model may facilitate further graph-based studies of protein conformation space and have important implications for protein structure comparison and prediction. The choice of a well-fitting null model is crucial for finding structural motifs that play an important role in protein folding, stability and function. To our knowledge, this is the first study that addresses the challenge of finding an optimized null model for RIGs, by comparing various RIG definitions against a series of network models.     

New Insights into Handling Missing Values in Environmental Epidemiological Studies

Missing data are unavoidable in environmental epidemiologic surveys. The aim of this study was to compare methods for handling large amounts of missing values: omission of missing values, single and multiple imputations (through linear regression or partial least squares regression), and a fully Bayesian approach. These methods were applied to the PARIS birth cohort, where indoor domestic pollutant measurements were performed in a random sample of babies'' dwellings. A simulation study was conducted to assess performances of different approaches with a high proportion of missing values (from 50% to 95%). Different simulation scenarios were carried out, controlling the true value of the association (odds ratio of 1.0, 1.2, and 1.4), and varying the health outcome prevalence. When a large amount of data is missing, omitting these missing data reduced statistical power and inflated standard errors, which affected the significance of the association. Single imputation underestimated the variability, and considerably increased risk of type I error. All approaches were conservative, except the Bayesian joint model. In the case of a common health outcome, the fully Bayesian approach is the most efficient approach (low root mean square error, reasonable type I error, and high statistical power). Nevertheless for a less prevalent event, the type I error is increased and the statistical power is reduced. The estimated posterior distribution of the OR is useful to refine the conclusion. Among the methods handling missing values, no approach is absolutely the best but when usual approaches (e.g. single imputation) are not sufficient, joint modelling approach of missing process and health association is more efficient when large amounts of data are missing.     

The expression of Galectin-3 in endometrial cancer: a systematic review of the literature

Molecular Biology Reports - Galectin-3 is part of a protein group called lectins and acts as a multifunctional glycoprotein due to its expression location. Galectin-3 is expressed by different...     

Noncanonical Role of the 9-1-1 Clamp in the Error-Free DNA Damage Tolerance Pathway

1. Download : Download high-res image (310KB)
2. Download : Download full-size image

Highlights? 9-1-1 and Exo1 are components of the error-free RAD6 pathway ? 9-1-1 promotes postreplicative template switching ? Polyubiquitylated PCNA and 9-1-1 cooperate in the error-free RAD6 pathway ? 9-1-1’s role in the error-free RAD6 pathway is uncoupled from checkpoint functions