Technical Note: The normal quantile transformation and its application in a flood forecasting system.

The Normal Quantile Transform (NQT) has been used in many hydrological and meteorological applications in order to make the Cumulated Distribution Function (CDF) of the observed, simulated and forecast river discharge, water level or precipitation data Gaussian. It is also the heart of the meta-Gaussian model for assessing the total predictive uncertainty of the Hydrological Uncertainty Processor (HUP) developed by Krzysztofowicz. In the field of geo-statistics this transformation is better known as the Normal-Score Transform. In this paper some possible problems caused by small sample sizes when applying the NQT in flood forecasting systems will be discussed and a novel way to solve the problem will be outlined by combining extreme value analysis and non-parametric regression methods. The method will be illustrated by examples of hydrological stream-flow forecasts.

Distribution analysis of the putative cancer marker S100A4 across invasive squamous cell carcinoma penile tissue

MS-based proteomic methods were utilised for the first time in the discovery of novel penile cancer biomarkers. MALDI MS imaging was used to obtain the in situ biomolecular MS profile of squamous cell carcinoma of the penis which was then compared to benign epithelial MS profiles. Spectra from cancerous and benign tissue areas were examined to identify MS peaks that best distinguished normal epithelial cells from invasive squamous epithelial cells, providing crucial evidence to suggest S100A4 to be differentially expressed. Verification by immunohistochemistry resulted in positive staining for S100A4 in a sub-population of invasive but not benign epithelial cells.