Genome-wide analysis of WRKY gene family in Cucumis sativus

<p>Abstract</p> <p>Background</p> <p>WRKY proteins are a large family of transcriptional regulators in higher plant. They are involved in many biological processes, such as plant development, metabolism, and responses to biotic and abiotic stresses. Prior to the present study, only one full-length cucumber WRKY protein had been reported. The recent publication of the draft genome sequence of cucumber allowed us to conduct a genome-wide search for cucumber WRKY proteins, and to compare these positively identified proteins with their homologs in model plants, such as <it>Arabidopsis</it>.</p> <p>Results</p> <p>We identified a total of 55 WRKY genes in the cucumber genome. According to structural features of their encoded proteins, the cucumber WRKY (<it>CsWRKY</it>) genes were classified into three groups (group 1-3). Analysis of expression profiles of <it>CsWRKY </it>genes indicated that 48 WRKY genes display differential expression either in their transcript abundance or in their expression patterns under normal growth conditions, and 23 WRKY genes were differentially expressed in response to at least one abiotic stresses (cold, drought or salinity). The expression profile of stress-inducible <it>CsWRKY </it>genes were correlated with those of their putative <it>Arabidopsis WRKY (AtWRKY) </it>orthologs, except for the group 3 WRKY genes. Interestingly, duplicated group 3 <it>AtWRKY </it>genes appear to have been under positive selection pressure during evolution. In contrast, there was no evidence of recent gene duplication or positive selection pressure among <it>CsWRKY </it>group 3 genes, which may have led to the expressional divergence of group 3 orthologs.</p> <p>Conclusions</p> <p>Fifty-five WRKY genes were identified in cucumber and the structure of their encoded proteins, their expression, and their evolution were examined. Considering that there has been extensive expansion of group 3 WRKY genes in angiosperms, the occurrence of different evolutionary events could explain the functional divergence of these genes.</p

A web-based Alcohol Clinical Training (ACT) curriculum: Is in-person faculty development necessary to affect teaching?

<p>Abstract</p> <p>Background</p> <p>Physicians receive little education about unhealthy alcohol use and as a result patients often do not receive efficacious interventions. The objective of this study is to evaluate whether a free web-based alcohol curriculum would be used by physician educators and whether in-person faculty development would increase its use, confidence in teaching and teaching itself.</p> <p>Methods</p> <p>Subjects were physician educators who applied to attend a workshop on the use of a web-based curriculum about alcohol screening and brief intervention and cross-cultural efficacy. All physicians were provided the curriculum web address. Intervention subjects attended a 3-hour workshop including demonstration of the website, modeling of teaching, and development of a plan for using the curriculum. All subjects completed a survey prior to and 3 months after the workshop.</p> <p>Results</p> <p>Of 20 intervention and 13 control subjects, 19 (95%) and 10 (77%), respectively, completed follow-up. Compared to controls, intervention subjects had greater increases in confidence in teaching alcohol screening, and in the frequency of two teaching practices – teaching about screening and eliciting patient health beliefs. Teaching confidence and teaching practices improved significantly in 9 of 10 comparisons for intervention, and in 0 comparisons for control subjects. At follow-up 79% of intervention but only 50% of control subjects reported using any part of the curriculum (p = 0.20).</p> <p>Conclusion</p> <p>In-person training for physician educators on the use of a web-based alcohol curriculum can increase teaching confidence and practices. Although the web is frequently used for disemination, in-person training may be preferable to effect widespread teaching of clinical skills like alcohol screening and brief intervention.</p

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases

Non-standard errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants