Cloning and functional analysis of the rhesus macaque ABCG2 gene. Forced expression confers an SP phenotype among hematopoietic stem cell progeny in vivo

Hematopoietic cells can be highly enriched for repopulating ability based upon the efflux of the fluorescent Hoechst 33342 dye by sorting for SP (side population) cells, a phenotype attributed to expression of ABCG2, a member of the ABC transporter superfamily. Intriguingly, murine studies suggest that forced ABCG2 expression prevents hematopoietic differentiation. We cloned the full-length rhesus ABCG2 and introduced it into a retroviral vector. ABCG2-transduced human peripheral blood progenitor cells (PBPCs) acquired the SP phenotype but showed significantly reduced growth compared with control. Two rhesus macaques received autologous PBPCs split for transduction with the ABCG2 or control vectors. Marking levels were similar between fractions with no discrepancy between bone marrow and peripheral blood marking. Analysis for the SP phenotype among bone marrow and mature blood populations confirmed ABCG2 expression at levels predicted by vector copy number long term, demonstrating no block to differentiation in the large animal. In vitro studies showed selective protection against mitoxantrone among ABCG2-transduced rhesus PBPCs. Our results confirm the existence of rhesus ABCG2, establish its importance in conferring the SP phenotype, suggest no detrimental effect of its overexpression upon differentiation in vivo, and imply a potential role for its overexpression as an in vivo selection strategy for gene therapy applications.     

Miotic action of tramadol is determined by CYP2D6 genotype

Polymorphic CYP2D6 is the enzyme that activates the opioid analgesic tramadol by O-demethylation to its active metabolite O-demethyltramadol (M1). Our objective was to determine the opioid effects measured by pupillary response to tramadol of CYP2D6 genotyped volunteers in relation to the disposition of tramadol and M1 in plasma. Tramadol displayed phenotypic pharmacokinetics and it was possible to identify poor metabolizers (PM) with >99% confidence from the metabolic ratio (MR) in a single blood sample taken between 2.5 and 24 h post-dose. Homozygous extensive metabolizers (EM) differed from PM subjects by an almost threefold greater (P=0.0014) maximal pupillary constriction (Emax). Significant correlations between the AUC and Cmax values of M1 versus pupillary constriction were found. The corresponding correlations of pharmacokinetic parameters for tramadol itself were weaker and negative. The strongest correlations were for the single-point metabolic ratios at all sampling intervals versus the effects, with rs ranging from 0.85 to 0.89 (p<0.01). It is concluded that the concept of dual opioid/non-opioid action of the drug, though considerably stronger in EMs, is valid for both EM and PM subjects. This is the theoretical basis for the frequent use and satisfactory efficacy of tramadol in clinical practice when given to genetically non-selected population.     

Conservative whole‐organ scaling contrasts with highly labile suborgan scaling differences among compound eyes of closely related Formica ants

Static allometries determine how organ size scales in relation to body mass. The extent to which these allometric relationships are free to evolve, and how they differ among closely related species, has been debated extensively and remains unclear; changes in intercept appear common, but changes in slope are far rarer. Here, we compare the scaling relationships that govern the structure of compound eyes of four closely related ant species from the genus Formica. Comparison among these species revealed changes in intercept but not slope in the allometric scaling relationships governing eye area, facet number, and mean facet diameter. Moreover, the scaling between facet diameter and number was conserved across all four species. In contrast, facet diameters from distinct regions of the compound eye differed in both intercept and slope within a single species and when comparing homologous regions among species. Thus, even when species are conservative in the scaling of whole organs, they can differ substantially in regional scaling within organs. This, at least partly, explains how species can produce organs that adhere to genus wide scaling relationships while still being able to invest differentially in particular regions of organs to produce specific features that match their ecology.     

High expression of transgene protein in Spirodela

The monocot family Lemnaceae (duckweed) is composed of small, edible, aquatic plants. Spirodela oligorrhiza SP is a duckweed with a biomass doubling time of about 2 days under controlled, axenic conditions. Stably transformed Spirodela plants were obtained following co-cultivation of regenerative calli with Agrobacterium tumefaciens. GFP activity was successfully monitored in different subcellular compartments of the plant and correlated with different targeting sequences. Transgenic lines were followed for a period of at least 18 months and more than 180 vegetative doublings (generations). The lines are stable in morphology, growth rate, transgene expression, and activity as measured by DNA–DNA and immunoblot hybridizations, fluorescence activity measurements, and antibiotic resistance. The level of transgene expression is a function of leader sequences rather than transgene copy number. A stable, transgenic, GFP expression level >25% of total soluble protein is demonstrated for the S. oligorrhiza system, making it among the higher expressing systems for nuclear transformation in a higher plant.     

Empirical power and sample size calculations for cluster-randomized and cluster-randomized crossover studies

In recent years, the number of studies using a cluster-randomized design has grown dramatically. In addition, the cluster-randomized crossover design has been touted as a methodological advance that can increase efficiency of cluster-randomized studies in certain situations. While the cluster-randomized crossover trial has become a popular tool, standards of design, analysis, reporting and implementation have not been established for this emergent design. We address one particular aspect of cluster-randomized and cluster-randomized crossover trial design: estimating statistical power. We present a general framework for estimating power via simulation in cluster-randomized studies with or without one or more crossover periods. We have implemented this framework in the clusterPower software package for R, freely available online from the Comprehensive R Archive Network. Our simulation framework is easy to implement and users may customize the methods used for data analysis. We give four examples of using the software in practice. The clusterPower package could play an important role in the design of future cluster-randomized and cluster-randomized crossover studies. This work is the first to establish a universal method for calculating power for both cluster-randomized and cluster-randomized clinical trials. More research is needed to develop standardized and recommended methodology for cluster-randomized crossover studies.