An assessment of donor-to-recipient transmission patterns of human cytomegalovirus by analysis of viral genomic variants.

BACKGROUND: We studied human cytomegalovirus (CMV) donor-to-recipient transmission patterns in organ transplantation by analyzing genomic variants on the basis of CMV glycoprotein B (gB) genotyping. METHODS: Organ transplant recipients were included in the study if they had CMV viremia, if they had received an organ from a CMV-seropositive donor, and if there was at least 1 other recipient of an organ from the same donor who developed CMV viremia. Genotypes (gB1-4) were determined by real-time polymerase chain reaction. RESULTS: Forty-seven recipients of organs from 21 donors developed CMV viremia. Twenty-three recipients had a pretransplant donor/recipient (D/R) CMV serostatus of D(+)/R(+), and 24 had a serostatus of D(+)/R(-). The prevalences of genotypes in recipients were as follows: for gB1, 51% (n = 24); for gB2, 19% (n = 9); for gB3, 9% (n = 4); for gB4, 0% (n = 0); and for mixed infection, 21% (n = 10). Recipients of an organ from a common donor had infection with CMV of the same gB genotype in 12 (57%) of 21 instances. Concordance between genotypes was higher among seronegative (i.e., D(+)/R(-)) recipients than among seropositive (D(+)/R(+)) recipients, although discordances resulting from the transmission of multiple strains were seen. In seropositive recipients, transmission of multiple strains from the donor could not be differentiated from reactivation of a recipient's own strains. CONCLUSION: Our analysis of strain concordance among recipients of organs from common donors showed that transmission of CMV has complex dynamic patterns. In seropositive recipients, transmission or reactivation of multiple CMV strains is possible.

Genomic and proteomic approaches towards an understanding of sleep.

The basic functions of sleep are still unclear, however, recent advances in genomics and proteomics have begun to contribute to our understanding of both normal and pathological sleep. In this review, we focus primarily on normal sleep and wake that have been studied in model organisms such as mice. Mice have been especially valuable since many different inbred strains exist that differ in sleep-related traits, and genes can be altered by either mutagenesis or targeted approaches. Advances in QTL (Quantitative Trait Loci) analysis have also helped to identify important sleep related genes, and several other QTLs have been mapped as a first step toward finding the genes that underlie basic sleep traits. In addition to more traditional genetic approaches, the abundance of different mRNAs across sleep and wake can now be studied and compared in different brain regions much more thoroughly using microarray methods. Progress at the protein level has been more difficult, but a few studies have begun to investigate changes in proteins during sleep and wake, and we present some of our own preliminary data in this area. A knowledge of which genes and proteins control or respond to changes in sleep will not only help answer fundamental questions, but may also suggest novel drug targets for improving multiple aspects of sleep and wake.

Conceiving Comparative Policy Analysis : Implementing Air Quality Improvement Programs

The comparative analysis of air quality control policies provides an interesting field for studies of comparative policy analysis including program formulation and implementation processes. In European countries, the problem is comparable, whereas implementation structures, programs and policy impacts vary to a considerable extent. Analysis testing possibilities and constraints of air control policies under varying conditions are likely to contribute to a further development of a theory of policy analysis. This paper presents the analytical framework applied in a continuing empirical study explaining program formulation and implementation processes with respect to the different actors involved. Concrete emitter behavior can be explained by interaction processes at the very local level, by program elements of national legislation, and by structural constraints under which such programs are produced.

Intracellular excision and reintegration dynamics of the ICEclc genomic island of Pseudomonas knackmussii sp. strain B13.

Genomic islands are DNA elements acquired by horizontal gene transfer that are common to a large number of bacterial genomes, which can contribute specific adaptive functions, e.g. virulence, metabolic capacities or antibiotic resistances. Some genomic islands are still self-transferable and display an intricate life-style, reminiscent of both bacteriophages and conjugative plasmids. Here we studied the dynamical process of genomic island excision and intracellular reintegration using the integrative and conjugative element ICEclc from Pseudomonas knackmussii B13 as model. By using self-transfer of ICEclc from strain B13 to Pseudomonas putida and Cupriavidus necator as recipients, we show that ICEclc can target a number of different tRNA(Gly) genes in a bacterial genome, but only those which carry the GCC anticodon. Two conditional traps were designed for ICEclc based on the attR sequence, and we could show that ICEclc will insert with different frequencies in such traps producing brightly fluorescent cells. Starting from clonal primary transconjugants we demonstrate that ICEclc is excising and reintegrating at detectable frequencies, even in the absence of recipient. Recombination site analysis provided evidence to explain the characteristics of a larger number of genomic island insertions observed in a variety of strains, including Bordetella petri, Pseudomonas aeruginosa and Burkholderia.

Inference about the number of contributors to a DNA mixture: Comparative analyses of a Bayesian network approach and the maximum allele count method.

In the forensic examination of DNA mixtures, the question of how to set the total number of contributors (N) presents a topic of ongoing interest. Part of the discussion gravitates around issues of bias, in particular when assessments of the number of contributors are not made prior to considering the genotypic configuration of potential donors. Further complication may stem from the observation that, in some cases, there may be numbers of contributors that are incompatible with the set of alleles seen in the profile of a mixed crime stain, given the genotype of a potential contributor. In such situations, procedures that take a single and fixed number contributors as their output can lead to inferential impasses. Assessing the number of contributors within a probabilistic framework can help avoiding such complication. Using elements of decision theory, this paper analyses two strategies for inference on the number of contributors. One procedure is deterministic and focuses on the minimum number of contributors required to 'explain' an observed set of alleles. The other procedure is probabilistic using Bayes' theorem and provides a probability distribution for a set of numbers of contributors, based on the set of observed alleles as well as their respective rates of occurrence. The discussion concentrates on mixed stains of varying quality (i.e., different numbers of loci for which genotyping information is available). A so-called qualitative interpretation is pursued since quantitative information such as peak area and height data are not taken into account. The competing procedures are compared using a standard scoring rule that penalizes the degree of divergence between a given agreed value for N, that is the number of contributors, and the actual value taken by N. Using only modest assumptions and a discussion with reference to a casework example, this paper reports on analyses using simulation techniques and graphical models (i.e., Bayesian networks) to point out that setting the number of contributors to a mixed crime stain in probabilistic terms is, for the conditions assumed in this study, preferable to a decision policy that uses categoric assumptions about N.