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Background Quantitative PCR (qPCR) aims to measure the DNA or RNA concentration in diagnostic and biological samples based on the quantification cycle (Cq) value observed in the amplification curves. Results of qPCR experiments are regularly calculated as if all assays are 100% efficient or reported as just Cq, ΔCq, or ΔΔCq values. Contents When the reaction shows specific amplification, it should be deemed to be positive, regardless of the observed Cq. Because the Cq is highly dependent on amplification efficiency that can vary among targets and samples, accurate calculation of the target quantity and relative gene expression requires that the actual amplification efficiency be taken into account in the analysis and reports. PCR efficiency is frequently derived from standard curves, but this approach is affected by dilution errors and hampered by properties of the standard and the diluent. These factors affect accurate quantification of clinical and biological samples used in diagnostic applications and collected in challenging conditions. PCR efficiencies determined from individual amplification curves avoid these confounders. To obtain unbiased efficiency-corrected results, we recommend absolute quantification with a single undiluted calibrator with a known target concentration and efficiency values derived from the amplification curves of the calibrator and the unknown samples. Summary For meaningful diagnostics or biological interpretation, the reported results of qPCR experiments should be efficiency corrected. To avoid ambiguity, the Minimal Information for Publications on Quantitative Real-Time PCR Experiments (MIQE) guidelines checklist should be extended to require the methods that were used (1) to determine the PCR efficiency and (2) to calculate the reported target quantity and relative gene expression value.

BACKGROUND In the past decade, the search for circulating microRNA (miRNA) biomarkers has yielded numerous associations between miRNAs and different types of disease. However, many of these relations could not be replicated in subsequent studies under similar experimental conditions. Although this lack of replicability may be explained by the variation in experimental design and analysis methods, guidelines on the most appropriate design and analysis methods to study circulating miRNAs are scarce. CONTENT miRNA biomarker experiments generally consist of a discovery phase and a validation phase. In the discovery phase, typically hundreds of miRNAs are measured in parallel to identify candidate biomarkers. Because of the costs of such high-throughput experiments, the number of individuals included in those studies is often too small, which can easily lead to false positives and false negatives. In the validation phase, a small number of identified biomarker candidates are measured in a large cohort of cases and controls, generally by quantitative PCR (qPCR). Although qPCR is a sensitive method to measure miRNAs in the circulation, experimental design and qPCR data analysis remain challenging. Omitting some crucial steps in the design and analysis of the qPCR experiment or performing them incorrectly can cause serious biases, ultimately leading to false conclusions. SUMMARY In this review, we aim to expose and discuss the most common sources of interstudy variation in miRNA research from a methodological point of view and to provide guidelines on how to perform these steps correctly to increase replicability of studies on circulating miRNAs.

Treatment with the anticancer drug taxol (TXL), which polymerizes the cytoskeleton protein tubulin, may evoke cardiac arrhythmias based on reduced human cardiac sodium channel (Na(v)1.5) function. Therefore, we investigated whether enhanced tubulin polymerization by TXL affects Na(v)1.5 function and expression and whether these effects are beta(1)-subunit-mediated. Human embryonic kidney (HEK293) cells, transfected with SCN5A cDNA alone (Na(v)1.5) or together with SCN1B cDNA (Na(v)1.5 + beta(1)), and neonatal rat cardiomyocytes (NRCs) were incubated in the presence and in the absence of 100 mu M TXL. Sodium current (I-Na) characteristics were studied using patch-clamp techniques. Na(v)1.5 membrane expression was determined by immunocytochemistry and confocal microscopy. Pre-treatment with TXL reduced peak I-Na amplitude nearly two-fold in both Na(v)1.5 and Na(v)1.5 + beta(1), as well as in NRCs, compared with untreated cells. Accordingly, HEK293 cells and NRCs stained with anti-Na(v)1.5 antibody revealed a reduced membrane-labelling intensity in the TXL-treated groups. In addition, TXL accelerated I-Na decay of Na(v)1.5 + beta(1), whereas I-Na decay of Na(v)1.5 remained unaltered. Finally, TXL reduced the fraction of channels that slow inactivated from 31% to 18%, and increased the time constant of slow inactivation by two-fold in Na(v)1.5. Conversely, slow inactivation properties of Na(v)1.5 + beta(1) were unchanged by TXL. Enhanced tubulin polymerization reduces sarcolemmal Na(v)1.5 expression and I-Na amplitude in a beta(1)-subunit-independent fashion and causes I-Na fast and slow inactivation impairment in a beta(1)-subunit-dependent way. These changes may underlie conduction-slowing-dependent cardiac arrhythmias under conditions of enhanced tubulin polymerization, e.g. TXL treatment and heart failure

Motivation: SAGE enables the determination of genome-wide mRNA expression profiles. A comprehensive analysis of SAGE data requires software, which integrates (statistical) data analysis methods with a database system. Furthermore, to facilitate data sharing between users, the application should reside on a central server and be accessed via the internet. Since such an application was not available we developed the USAGE package. Results: USAGE is a web-based application that comprises an integrated set of tools, which offers many functions for analysing and comparing SAGE data. Additionally, USAGE includes a statistical method for the planning of new SAGE experiments. USAGE is available in a multi-user environment giving users the option of sharing data. USAGE is interfaced to a relational database to store data and analysis results. The USAGE query editor allows the composition of queries for searching this database. Several database functions have been included which enable the selection and combination of data. USAGE provides the biologist increased functionality and flexibility for analysing SAGE data. Availability: USAGE is freely accessible for academic institutions at http://www.cmbi.kun.nl/usage/. The source code of USAGE is freely available for academic institutions on request from the first author. Contact: a.h.vankampen@amc.uva.nl To whom correspondence should be addressed.