Plastid genome characterisation in Brassica and Brassicaceae using a new set of nine SSRs

The objective of the present study was to identify favourable exotic Quantitative Trait Locus (QTL) alleles for the improvement of agronomic traits in the BC₂DH population S42 derived from a cross between the spring barley cultivar Scarlett and the wild barley accession ISR42-8 (Hordeum vulgare ssp. spontaneum). QTLs were detected as a marker main effect and/or a marker × environment interaction effect (M × E) in a three-factorial ANOVA. Using field data of up to eight environments and genotype data of 98 SSR loci, we detected 86 QTLs for nine agronomic traits. At 60 QTLs the marker main effect, at five QTLs the M × E interaction effect, and at 21 QTLs both the effects were significant. The majority of the M × E interaction effects were due to changes in magnitude and are, therefore, still valuable for marker assisted selection across environments. The exotic alleles improved performance in 31 (36.0%) of 86 QTLs detected for agronomic traits. The exotic alleles had favourable effects on all analysed quantitative traits. These favourable exotic alleles were detected, in particular on the short arm of chromosome 2H and the long arm of chromosome 4H. The exotic allele on 4HL, for example, improved yield by 7.1%. Furthermore, the presence of the exotic allele on 2HS increased the yield component traits ears per m² and thousand grain weight by 16.4% and 3.2%, respectively. The present study, hence, demonstrated that wild barley does harbour valuable alleles, which can enrich the genetic basis of cultivated barley and improve quantitative agronomic traits.     

CbgA, a protein involved in cortex formation and stress resistance in Myxococcus xanthus spores

CbgA plays a role in cortex formation and the acquisition of a subset of stress resistance properties in Myxococcus xanthus spores. The cbgA mutant produces spores with thin or no cortex layers, and these spores are more sensitive to heat and sodium dodecyl sulfate than their wild-type counterparts.     

DESCRIPTION OF VIRIDILOBUS MARINUS (GEN. ET SP. NOV.), A NEW RAPHIDOPHYTE FROM DELAWARE'S INLAND BAYS

Delaware's Inland Bays (DIB), USA, are subject to blooms of potentially harmful raphidophytes, including Heterosigma akashiwo. In 2004, a dense bloom was observed in a low salinity tributary of the DIB. Light microscopy initially suggested that the species was H. akashiwo; however, the cells were smaller than anticipated. 18S rDNA sequences of isolated cultures differed substantially from all raphidophyte sequences in GenBank. Phylogenetic analysis placed it approximately equidistant from Chattonella and Heterosigma with only ~96% sequence homology with either group. Here, we describe this marine raphidophyte as a novel genus and species, Viridilobus marinus (gen. et sp. nov.). We also compared this species with H. akashiwo, because both species are superficially similar with respect to morphology and their ecological niches overlap. V. marinus cells are ovoid to spherical (11.4 × 9.4 μm), and the average number of chloroplasts (4 per cell) is lower than in H. akashiwo (15 per cell). Pigment analysis of V. marinus revealed the presence of fucoxanthin, violaxanthin, and zeaxanthin, which are characteristic of marine raphidophytes within the family Chattonellaceae of the Raphidophyceae. TEM and confocal microscopy, however, revealed diagnostic microscopic and ultrastructural characteristics that distinguish it from other raphidophytes. Chloroplasts were in close association with the nucleus and thylakoids were arranged either parallel or perpendicular to the cell surface. Putative mucocysts were identified, but trichocysts were not observed. These features, along with DNA sequence data, distinguish this species from all other raphidophyte genera within the family Chattonellaceae of the Raphidophyceae.     

Measurement of a model of implementation for health care: toward a testable theory

ABSTRACT: BACKGROUND: Greenhalgh et al. used a considerable evidence-base to develop a comprehensive model of implementation of innovations in healthcare organizations [1]. However, these authors did not fully operationalize their model, making it difficult to test formally. The present paper represents a first step in operationalizing Greenhalgh et al.'s model by providing background, rationale, working definitions, and measurement of key constructs. METHODS: A systematic review of the literature was conducted for key words representing 53 separate sub-constructs from six of the model's broad constructs. Using an iterative process, we reviewed existing measures and utilized or adapted items. Where no one measure was deemed appropriate, we developed other items to measure the constructs through consensus. RESULTS: The review and iterative process of team consensus identified three types of data that can been used to operationalize the constructs in the model: survey items, interview questions, and administrative data. Specific examples of each of these are reported. CONCLUSION: Despite limitations, the mixed-methods approach to measurement using the survey, interview measure, and administrative data can facilitate research on implementation by providing investigators with a measurement tool that captures most of the constructs identified by the Greenhalgh model. These measures are currently being used to collect data concerning the implementation of two evidence-based psychotherapies disseminated nationally within Department of Veterans Affairs. Testing of psychometric properties and subsequent refinement should enhance the utility of the measures.     

Improving efficiency of breeding for higher crop yield

Summary Exclusive selection for yield raises, the harvest index of self-pollinated crops with little or no gain in total bipmass. In addition to selection for yield, it is suggested that efficient breeding for higher yield requires simultaneous selection for yield's three major, genetically controlled physiological components. The following are needed: (1) a superior rate of biomass accumulation. (2) a superior rate of actual yield accumulation in order to acquire a high harvest index, and (3) a time to harvest maturity that is neither shorter nor longer than the duration of the growing season. That duration is provided by the environment, which is the fourth major determinant of yield. Simultaneous selection is required because genetically established interconnections among the three major physiological components cause: (a) a correlation between the harvest index and days to maturity that is usually negative; (b) a correlation between the harvest index and total biomass that is often negative, and (c) a correlation between biomass and days to maturity that is usually positive. All three physiological components and the correlations among them can be quantified by yield system analysis (YSA) of yield trials. An additive main effects and multiplicative interaction (AMMI) statistical analysis can separate and quantify the genotype × environment interaction (G × E) effect on yield and on each physiological component that is caused by each genotype and by the different environment of each yield trial. The use of yield trials to select parents which have the highest rates of accumulation of both biomass and yield, in addition to selecting for the G × E that is specifically adapted to the site can accelerate advance toward the highest potential yield at each geographical site. Higher yield for many sites will raise average regional yield. Higher yield for multiple regions and continents will raise average yield on a world-wide basis. Genetic and physiological bases for lack of indirect selection for biomass from exclusive selection for yield are explained.     

The regulation of mortality and fecundity in Schistosoma mattheei following a single experimental infection in sheep.

The regulation of mortality and fecundity of Schistosoma mattheei in sheep was examined using a series of mathematical models applied to data culled from the literature. Parasite mortality (μ) was found to be an increasing linear function of the magnitude of the initial infection over the ranges of doses examined (200–91, 000 cercariae) where μ = 9.78 × 10⁻³ + 3.476 × 10^−7* infection dose. Parasite fecundity (λ) was found to be inversely related to the duration of the infection. The best fit model for parasite fecundity was one in which fecundity decreased exponentially with time since initial infection, λ = λ₀e^−δ1−r. There was no evidence for density-dependent regulation of fecundity.