No abstract

Statistical distributions of annual extreme and long dry spells for the Iberian Peninsula are investigated by using a daily database compiled from 43 rain gauges, with the recording period extending from 1951 to 1990 and with a minor lack of data. Dry spell lengths are derived for three different daily rainfall thresholds of 0.1, 1.0 and 5.0 mm/day. On one hand, the generalised extreme value (GEV) and generalised Pareto (GP) distributions are considered for modelling the series of annual extreme (AE) dry spells. On the other hand, both theoretical distributions are assumed for the partial duration (PD) series, which are derived from the dry spell lengths exceeding the 95th percentile. In both cases, a robust estimation of the three parameters of the GEV and GP distributions is obtained by L-moments. The fit between empirical and theoretical distributions is evaluated by using the 95% confidence bands of the Kolmogorov-Smirnov test and the L-skewness-kurtosis distance. Even though AE spells are quite well fitted by the GEV model, the GP distribution is a better option for some rain gauges. The PD series are usually better fitted by the GP distribution, only a few cases being better modelled by the GEV distribution. The basis for climatic drought risk assessment in the Iberian Peninsula is then established for dry spell lengths associated with return periods of 2, 5, 10, 25 and 50 years and accurately reviewed by comparing with results deduced from the AE and PD sampling strategies. As a general feature, both the spatial distribution of the statistical parameters and the dry spell lengths for the different return periods depict a north to south gradient. Some local deviations of this behaviour could be due to the vicinity to the Mediterranean Sea and the Atlantic Ocean.

No abstract

Current prognostic tools for non-muscle invasive bladder cancer (NMIBC) do not have enough discriminative capacity to predict the risk of tumour progression. This study aimed to identify urinary cell microRNAs that may be useful as non-invasive predictive biomarkers of tumour progression in NMIBC patients. To this end, 210 urine samples from NMIBC patients were included in the study. RNA was extracted from urinary cells and expression of 8 microRNAs, previously described by our group, was analysed by quantitative PCR. A tumour progression predicting model was developed by Cox regression analysis and validated by bootstrapping. Regression analysis identified miR-140-5p and miR-92a-3p as independent predictors of tumour progression. The risk score derived from the model containing these two microRNAs was able to discriminate between two groups with a highly significant different probability of tumour progression (HR, 5.204; p<0.001) which was maintained when patients were stratified according to tumour risk. The algorithm was also able to identify two groups with different cancer-specific survival (HR, 3.879; p=0.021). Although the data needs to be externally validated, miRNA analysis in urine appears to be a valuable prognostic tool in NMIBC patients.