A distinct plasmablast and naive B-cell phenotype in primary immune thrombocytopenia

Obtained from the Haematologica Journal website http://www.haematologica.org/content/101/6/698.full.pdf+html Material published in Haematologica is covered by copyright. All rights reserved to Ferrata Storti Foundation. Copies of articles are allowed for personal or internal use. A permission in writing by the publisher is requested for any other use.Primary funding for this study was from GSK. SMF was funded by a Translational Medicine and Therapeutics PhD studentship jointly funded by the Wellcome Trust and GSK. The UK ITP Registry (www.ukitpregistry.com) is supported through unrestricted educational grants from GSK and Amgen

The impact of different DNA extraction kits and laboratories upon the assessment of human gut microbiota composition by 16S rRNA gene sequencing

Peer reviewedPublisher PD

Does publication bias inflate the apparent efficacy of psychological treatment for major depressive disorder? A systematic review and meta-analysis of US national institutes of health-funded trials

Background The efficacy of antidepressant medication has been shown empirically to be overestimated due to publication bias, but this has only been inferred statistically with regard to psychological treatment for depression. We assessed directly the extent of study publication bias in trials examining the efficacy of psychological treatment for depression. Methods and Findings We identified US National Institutes of Health grants awarded to fund randomized clinical trials comparing psychological treatment to control conditions or other treatments in patients diagnosed with major depressive disorder for the period 1972–2008, and we determined whether those grants led to publications. For studies that were not published, data were requested from investigators and included in the meta-analyses. Thirteen (23.6%) of the 55 funded grants that began trials did not result in publications, and two others never started. Among comparisons to control conditions, adding unpublished studies (Hedges’ g = 0.20; CI95% -0.11~0.51; k = 6) to published studies (g = 0.52; 0.37~0.68; k = 20) reduced the psychotherapy effect size point estimate (g = 0.39; 0.08~0.70) by 25%. Moreover, these findings may overestimate the "true" effect of psychological treatment for depression as outcome reporting bias could not be examined quantitatively. Conclusion The efficacy of psychological interventions for depression has been overestimated in the published literature, just as it has been for pharmacotherapy. Both are efficacious but not to the extent that the published literature would suggest. Funding agencies and journals should archive both original protocols and raw data from treatment trials to allow the detection and correction of outcome reporting bias. Clinicians, guidelines developers, and decision makers should be aware that the published literature overestimates the effects of the predominant treatments for depression

Effects of Coleus Forskohlii Supplementation on Body Composition and Hematological Profiles in Mildly Overweight Women

<p>Abstract</p> <p>Purpose</p> <p>This study investigated the effects of <it>Coleus Forskohlii </it>(CF) on body composition, and determined the safety and efficacy of supplementation.</p> <p>Methods</p> <p>In a double blind and randomized manner, 23 females supplemented their diet with ForsLean™ (250 mg of 10% CF extract, (n = 7) or a placebo [P] (n = 12) two times per day for 12-wks. Body composition (DEXA), body weight, and psychometric instruments were obtained at 0, 4, 8 & 12 weeks of supplementation. Fasting blood samples and dietary records (4-d) were obtained at 0 and 12-wks. Side effects were recorded on a weekly basis. Data were analyzed by repeated measures ANOVA and are presented as mean changes from baseline for the CF and placebo groups, respectively.</p> <p>Results</p> <p>No significant differences were observed in caloric or macronutrient intake. CF tended to mitigate gains in body mass (-0.7 ± 1.8, 1.0 ± 2.5 kg, p = 0.10) and scanned mass (-0.2 ± 1.3, 1.7 ± 2.9 kg, p = 0.08) with no significant differences in fat mass (-0.2 ± 0.7, 1.1 ± 2.3 kg, p = 0.16), fat free mass (-0.1 ± 1.3, 0.6 ± 1.2 kg, p = 0.21), or body fat (-0.2 ± 1.0, 0.4 ± 1.4%, p = 0.40). Subjects in the CF group tended to report less fatigue (p = 0.07), hunger (p = 0.02), and fullness (p = 0.04). No clinically significant interactions were seen in metabolic markers, blood lipids, muscle and liver enzymes, electrolytes, red cells, white cells, hormones (insulin, TSH, T3, and T4), heart rate, blood pressure, or weekly reports of side effects.</p> <p>Conclusion</p> <p>Results suggest that CF does not appear to promote weight loss but may help mitigate weight gain in overweight females with apparently no clinically significant side effects.</p

A Copine family member, Cpne8, is a candidate quantitative trait gene for prion disease incubation time in mouse

Prion disease incubation time in mice is determined by many factors including genetic background. The prion gene itself plays a major role in incubation time; however, other genes are also known to be important. Whilst quantitative trait loci (QTL) studies have identified multiple loci across the genome, these regions are often large, and with the exception of Hectd2 on Mmu19, no quantitative trait genes or nucleotides for prion disease incubation time have been demonstrated. In this study, we use the Northport heterogeneous stock of mice to reduce the size of a previously identified QTL on Mmu15 from approximately 25 to 1.2 cM. We further characterised the genes in this region and identify Cpne8, a member of the copine family, as the most promising candidate gene. We also show that Cpne8 mRNA is upregulated at the terminal stage of disease, supporting a role in prion disease. Applying these techniques to other loci will facilitate the identification of key pathways in prion disease pathogenesis

Cell-to-Cell Stochastic Variation in Gene Expression Is a Complex Genetic Trait

The genetic control of common traits is rarely deterministic, with many genes contributing only to the chance of developing a given phenotype. This incomplete penetrance is poorly understood and is usually attributed to interactions between genes or interactions between genes and environmental conditions. Because many traits such as cancer can emerge from rare events happening in one or very few cells, we speculate an alternative and complementary possibility where some genotypes could facilitate these events by increasing stochastic cell-to-cell variations (or ‘noise’). As a very first step towards investigating this possibility, we studied how natural genetic variation influences the level of noise in the expression of a single gene using the yeast S. cerevisiae as a model system. Reproducible differences in noise were observed between divergent genetic backgrounds. We found that noise was highly heritable and placed under a complex genetic control. Scanning the genome, we mapped three Quantitative Trait Loci (QTL) of noise, one locus being explained by an increase in noise when transcriptional elongation was impaired. Our results suggest that the level of stochasticity in particular molecular regulations may differ between multicellular individuals depending on their genotypic background. The complex genetic architecture of noise buffering couples genetic to non-genetic robustness and provides a molecular basis to the probabilistic nature of complex traits

Identification of QTLs controlling gene expression networks defined a priori

BACKGROUND: Gene expression microarrays allow the quantification of transcript accumulation for many or all genes in a genome. This technology has been utilized for a range of investigations, from assessments of gene regulation in response to genetic or environmental fluctuation to global expression QTL (eQTL) analyses of natural variation. Current analysis techniques facilitate the statistical querying of individual genes to evaluate the significance of a change in response, also known as differential expression. Since genes are also known to respond as groups due to their membership in networks, effective approaches are needed to investigate transcriptome variation as related to gene network responses. RESULTS: We describe a statistical approach that is capable of assessing higher-order a priori defined gene network response, as measured by microarrays. This analysis detected significant network variation between two Arabidopsis thaliana accessions, Bay-0 and Shahdara. By extending this approach, we were able to identify eQTLs controlling network responses for 18 out of 20 a priori-defined gene networks in a recombinant inbred line population derived from accessions Bay-0 and Shahdara. CONCLUSION: This approach has the potential to be expanded to facilitate direct tests of the relationship between phenotypic trait and transcript genetic architecture. The use of a priori definitions for network eQTL identification has enormous potential for providing direction toward future eQTL analyses

High-Resolution Mapping of Gene Expression Using Association in an Outbred Mouse Stock

Quantitative trait locus (QTL) analysis is a powerful tool for mapping genes for complex traits in mice, but its utility is limited by poor resolution. A promising mapping approach is association analysis in outbred stocks or different inbred strains. As a proof of concept for the association approach, we applied whole-genome association analysis to hepatic gene expression traits in an outbred mouse population, the MF1 stock, and replicated expression QTL (eQTL) identified in previous studies of F2 intercross mice. We found that the mapping resolution of these eQTL was significantly greater in the outbred population. Through an example, we also showed how this precise mapping can be used to resolve previously identified loci (in intercross studies), which affect many different transcript levels (known as eQTL “hotspots”), into distinct regions. Our results also highlight the importance of correcting for population structure in whole-genome association studies in the outbred stock

Expression of Trichoderma reesei cellulases CBHI and EGI in Ashbya gossypii

To explore the potential of Ashbya gossypii as a host for the expression of recombinant proteins and to assess whether protein secretion would be more similar to the closely related Saccharomyces cerevisiae or to other filamentous fungi, endoglucanase I (EGI) and cellobiohydrolase I (CBHI) from the fungus Trichoderma reesei were successfully expressed in A. gossypii from plasmids containing the two micron sequences from S. cerevisiae, under the S. cerevisiae PGK1 promoter. The native signal sequences of EGI and CBHI were able to direct the secretion of EGI and CBHI into the culture medium in A. gossypii. Although CBHI activity was not detected using 4- methylumbelliferyl-β-D-lactoside as substrate, the protein was detected by Western blot using monoclonal antibodies. EGI activity was detectable, the specific activity being comparable to that produced by a similar EGI producing S. cerevisiae construct. More EGI was secreted than CBHI, or more active protein was produced. Partial characterization of CBHI and EGI expressed in A. gossypii revealed overglycosylation when compared with the native T. reesei proteins, but the glycosylation was less extensive than on cellulases expressed in S. cerevisiae.Fundação para a Ciência e a Tecnologia (FCT