Despite the central role of quantitative PCR (qPCR) in the quantification of mRNA transcripts, most analyses of qPCR data are still delegated to the software that comes with the qPCR apparatus. This is especially true for the handling of the fluorescence baseline. This article shows that baseline estimation errors are directly reflected in the observed PCR efficiency values and are thus propagated exponentially in the estimated starting concentrations as well as ‘fold-difference’ results. Because of the unknown origin and kinetics of the baseline fluorescence, the fluorescence values monitored in the initial cycles of the PCR reaction cannot be used to estimate a useful baseline value. An algorithm that estimates the baseline by reconstructing the log-linear phase downward from the early plateau phase of the PCR reaction was developed and shown to lead to very reproducible PCR efficiency values. PCR efficiency values were determined per sample by fitting a regression line to a subset of data points in the log-linear phase. The variability, as well as the bias, in qPCR results was significantly reduced when the mean of these PCR efficiencies per amplicon was used in the calculation of an estimate of the starting concentration per sample.
Background: PCR has the potential to detect and precisely quantify specific DNA sequences, but it is not yet often used as a fully quantitative method. A number of data collection and processing strategies have been described for the implementation of quantitative PCR. However, they can be experimentally cumbersome, their relative performances have not been evaluated systematically, and they often remain poorly validated statistically and/or experimentally. In this study, we evaluated the performance of known methods, and compared them with newly developed data processing strategies in terms of resolution, precision and robustness.
Sprouting induces activation and de novo synthesis of hydrolytic enzymes that make nutrients available for plant growth and development. Consumption of sprouted grains is suggested to be beneficial for human health. Positive consumer perceptions about sprouted cereals have resulted in new food and beverage product launches. However, because there is no generally accepted definition of “sprouting,” it is unclear when grains are to be called sprouted. Moreover, guidelines about how much sprouted grain material food products should contain to exert health benefits are currently lacking. Accordingly, there is no regulatory base to develop appropriate food labeling for “sprouted foods.” This review describes the nutritional and technological properties of sprouted grains in relation to processing conditions and provides guidelines to optimize sprouting practices in order to maximize nutritive value. Relatively long sprouting times (3 to 5 days) and/or high processing temperatures (25 to 35 °C) are needed to maximize the de novo synthesis and/or release of plant bioactive compounds. Nutrient compositional changes resulting from sprouting are often associated with health benefits. However, supportive data from clinical studies are very scarce, and at present it is impossible to draw any conclusion on health benefits of sprouted cereals. Finally, grains sprouted under the above‐mentioned conditions are generally unfit for use in traditional food processing and it is challenging to use sprouted grains as ingredients without compromising their nutrient content. The present review provides a basis for better defining what “sprouting” is, and to help further research and development efforts in this field as well as future food regulations development.
Reversal of the silencing of a tetracycline-regulated minimal promoter requires a chromatin-remodeling activity for subsequent promoter activation by the Tet-VP16 fusion protein. Thus, distinct regulatory elements may be combined to obtain long-term regulation and persistent expression of exogenous genes in eukaryotic cells.
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