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Transposable elements (TEs), also known as “jumping genes”, are repetitive sequences with the capability of changing their location within the genome. They are key players in many different biological processes in health and disease. Therefore, a reliable quantification of their expression as transcriptional units is crucial to distinguish between their independent expression and the transcription of their sequences as part of canonical transcripts. TEs quantification faces difficulties of different types, the most important one being low reads mappability due to their repetitive nature preventing an unambiguous mapping of reads originating from their sequences. A large fraction of TEs fragments localizes within introns, which led to the hypothesis that intron retention (IR) can be an additional source of bias, potentially affecting accurate TEs quantification. IR occurs when introns, normally removed from the mature transcript by the splicing machinery, are maintained in mature transcripts. IR is a widespread mechanism affecting many different genes with cell type-specific patterns. We hypothesized that, in an RNA-seq experiment, reads derived from retained introns can introduce a bias in the detection of overlapping, independent TEs RNA expression. In this study we performed meta-analysis using public RNA-seq data from lymphoblastoid cell lines and show that IR can impact TEs quantification using established tools with default parameters. Reads mapped on intronic TEs were indeed associated to the expression of TEs and influence their correct quantification as independent transcriptional units. We confirmed these results using additional independent datasets, demonstrating that this bias does not appear in samples where IR is not present and that differential TEs expression does not impact on IR quantification. We concluded that IR causes the over-quantification of intronic TEs and differential IR might be confused with differential TEs expression. Our results should be taken into account for a correct quantification of TEs expression from RNA-seq data, especially in samples in which IR is abundant.

Background: Despite the effect of 25 years of evidence-based medicine, the problem of bias is still prevalent in clinical research and its publication and in clinical practice. Its effect can lead to flawed research, misleading publications and ultimately patient harm. Aim: To draw attention to the commonest types of bias and how they influence clinical research, thinking and practice. Methods: This is not a systematic review but draws on the authors’ personal experience as clinical researchers, teachers, systematic reviewers and as arbiters of conflicts of interest for Cochrane. We describe the ones most relevant to oncology and give examples mainly from the literature on pulmonary metastasectomy. Results: There are two broad kinds of bias: technical bias, seen in the way research is conducted and published, and cognitive bias, the way in which beliefs, previous experience and thinking influence practice. The examples illustrate how common and diverse they are. Conclusion: These biases are widespread and influential and may actually cause harm. We are all susceptible to them and need to recognise them in ourselves and others and in what we read.

This paper aims at measuring productivity and efficiency of China’s three most important grain crops–rice, wheat and maize–as well as identifying the main directions of technical change prevailing in their production. The bias-corrected Malmquist production indices are employed to measure the technical changes (TCs) in terms of input-saving or input-using in China’s grain production, by using provincial aggregate data obtained from the National Farm Production Costs and Returns Survey. The research covers the period of 2003–2013. Application of the bias-corrected Malmquist index showed a labor-saving technical change against all the remaining inputs for the three crops under analysis. The highest frequencies of fertilizer- and machinery-using, labor-saving technical changes were observed for wheat farming. Therefore, a reduction in labor intensity should be the most promising for wheat if compared with rice and maize.

Microbial single cell analysis has led to discoveries that are beyond what can be resolved with population-based studies. It provides a pristine view of the mechanisms that organize cellular physiology, unbiased by population heterogeneity or uncontrollable environmental impacts. A holistic description of cellular functions at the single cell level requires analytical concepts beyond the miniaturization of existing technologies, defined but uncontrolled by the biological system itself. This review provides an overview of the latest advances in single cell technologies and demonstrates their potential. Opportunities and limitations of single cell microbiology are discussed using selected application-related examples., Analyzing single microbial cells reveals functionalities inaccessible via bulk-population studies. Studying individual cells requires special tools, but it also opens new horizons. Our current mechanistic understanding of individual cell behavior is still limited by available technologies.

This paper considers a dynamic North South model of international trade and innovations in which firms can endogenously bias the direction of technological change. We show that, when there is a differential degree of protection of property rights between the two regions, innovating firms face a trade-off between delocalization in the South and more secure property rights in the North. For a certain range of products, the optimal response to this tradeoff is the emergence of endogenous technological bias towards skilled labour technologies. We discuss the implications of this trade induced technological bias on the dynamics of international trade and relative wages in the two regions. For some configurations of parameters, the model is able to generate, along the transition path, an increase in wage inequalities in both regions and skill upgrading of southern production compatible with small changes in import penetration rates in North.