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Background: The risk of hepatocarcinoma in HCV cirrhotic patient responders after treatment with DAAs decrease, but HCC still occurs. A correlation between specific miRNAs and the development of hepatocarcinoma have been highlighted. Aim: To investigate miRNA expression in HCV-infected cirrhotic patients treated with DAAs, regarding whether or not they developed HCC at follow-up. Methods: A total of 73 outpatients with HCV-related cirrhosis treated with DAAs were enrolled, 28 of which had HCC. Samples were collected at the start and at the end of treatment. In the screening phase, 172 miRNAs were analyzed at baseline. Differentially expressed miRNAs were validated in the entire cohort. Results: In the validation phase, at baseline and in patients treated for 12 weeks, miR-28-5p was confirmed to be more highly expressed in the HCC group compared to the non-HCC group. In all of the patients treated for 12 weeks, at end of the treatment we found a significant downregulation in miR-132-3p, miR-133b-3p, miR-221-3p and miR-324-3p. In the HCC group, miR-28-5p was significantly downregulated after DAA therapy as well as in HCC patients treated for 24 weeks. Conclusion: In the HCC group, miR28-5p was differently expressed both at baseline and at the end of therapy with DAAs. This difference in expression should suggest its involvement in HCC development. [ABSTRACT FROM AUTHOR]

This study provides the first inter-comparison of different state-of-the-art approaches and frameworks that share a commonality in their utilization of satellite remote-sensing data to quantify irrigation at a regional scale. The compared approaches vary in their reliance on either soil moisture or evapotranspiration data or their joint utilization of both. The two compared frameworks either extract irrigation information from residuals between satellite observations and rainfed hydrological models in a baseline framework or use soil water balance modeling in a soil-moisture-based inversion framework. The inter-comparison is conducted over the lower Ebro catchment in Spain where observed irrigation amounts are available for benchmarking. Our results showed that within the baseline framework, the joint approach using both soil moisture and evapotranspiration (ET) remote-sensing data only differed by + 37 mm from the irrigation benchmark (922 mm) during the main irrigation season over 2 years and by + 47 and - 208 mm for approaches relying solely on soil moisture and ET, respectively. A comparison of the different frameworks showed that the main advantage of the more complex baseline framework was the consistency between soil moisture and ET components within the hydrological model, which made it unlikely that either one ended up representing all irrigation water use. However, the simplicity of the soil-moisture-based inversion framework, coupled with its direct conversion of soil moisture changes into actual water volumes, effectively addresses the key challenges inherent in the baseline framework, which are associated with uncertainties related to an unknown remote-sensing observation depth and the static depth of the soil layers in a conceptual model. The performance of the baseline framework came closest to the irrigation benchmark and was able to account for the precipitation input, which resulted in more plausible temporal distributions of irrigation than what was expected from the benchmark observations. [ABSTRACT FROM AUTHOR]

Background. The aim of the present study was to determine the prevalence and incidence of diabetic retinopathy (DR) and its changes in the last 20 years in type 2 diabetes mellitus (T2DM) patients in Spain. Methods. A systematic review with a meta-analysis was carried out on the studies published between 2001–2020 on the prevalence and incidence of DR and sight-threatening diabetic retinopathy (STDR) in Spain. The articles included were selected from four databases and publications of the Spanish Ministry of Health and Regional Health Care System (RHCS). The meta-analysis to determine heterogeneity and bias between studies was carried out with the MetaXL 4.0. Results. Since 2001, we have observed an increase in the detection of patients with DM, and at the same time, screening programs for RD have been launched; thus, we can deduce that the increase in the detection of patients with DM, many of them in the initial phases, far exceeds the increased detection of patients with DR. The prevalence of DR was higher between 2001 and 2008 with values of 28.85%. These values decreased over the following period between 2009 and 2020 with a mean of 15.28%. Similarly the STDR prevalence decrease from 3.67% to 1.92% after 2008. The analysis of the longitudinal studies determined that the annual DR incidence was 3.83%, and the STDR annual incidence was 0.41%. Conclusion. In Spain, for T2DM, the current prevalence of DR is 15.28% and 1.92% forSTDR. The annual incidence of DR is 3.83% and is 0.41% for STDR. [ABSTRACT FROM AUTHOR]

Objective: To assess the impact of a telemedicine visit using the platform Diabetic compared with a face-to-face visit on clinical outcomes, patients' health-related quality of life (HRQoL), and physicians' satisfaction in patients with type 1 diabetes.Research Design and Methods: PLATEDIAN (Telemedicine on Metabolic Control in Type 1 Diabetes Mellitus Andalusian Patients) (NCT03332472) was a multicenter, randomized, 6-month follow-up, open-label, parallel-group controlled study performed in patients with type 1 diabetes with suboptimal metabolic control (HbA1c <8% [<64 mmol/mol]), treated with multiple daily injections. A total of 388 patients were assessed for eligibility; 379 of them were randomized 1:1 to three face-to-face visits (control cohort [CC]) (n = 167) or the replacement of an intermediate face-to-face visit by a telemedicine visit using Diabetic (intervention cohort [IC]) (n = 163). The primary efficacy end point was the mean change of HbA1c levels from baseline to month 6. Other efficacy and safety end points were mean blood glucose, glucose variability, episodes of hypoglycemia and hyperglycemia, patient-reported outcomes, and physicians' satisfaction.Results: At month 6, the mean change in HbA1c levels was -0.04 ± 0.5% (-0.5 ± 5.8 mmol/mol) in the CC and 0.01 ± 0.6% (0.1 ± 6.0 mmol/mol) in the IC (P = 0.4941). The number of patients who achieved HbA1c <7% (<53 mmol/mol) was 73 and 78 in the CC and IC, respectively. Significant differences were not found regarding safety end points at 6 months. Changes in HRQoL between the first visit and final visit did not differ between cohorts, and, regarding fear of hypoglycemia (FH-15 score ≥28), statistically significant differences observed at baseline remained unchanged at 6 months (P < 0.05).Conclusions: The use of telemedicine in patients with type 1 diabetes with HbA1c <8% (<64 mmol/mol) provides similar efficacy and safety outcomes as face-to-face visits. [ABSTRACT FROM AUTHOR]

The analysis of the spatial-temporal variability of soil moisture can be carried out considering the absolute (original) soil moisture values or relative values, such as the percent of saturation or temporal anomalies. Over large areas, soil moisture data measured at different sites can be characterized by large differences in their minimum, mean, and maximum absolute values, even though in relative terms their temporal patterns are very similar. In these cases, the analysis considering absolute compared with percent of saturation or temporal anomaly soil moisture values can provide very different results with significant consequences for their use in hydrological applications and climate science. In this study, in situ observations from six soil moisture networks in Italy, Spain, France, Switzerland, Australia, and United States are collected and analyzed to investigate the spatial soil moisture variability over large areas (250-150,000 km2). Specifically, the statistical and temporal stability analyses of soil moisture have been carried out for absolute, temporal anomaly, and percent of saturation values (using two different formulations for temporal anomalies). The results highlight that the spatial variability of the soil moisture dynamic (i.e., temporal anomalies) is significantly lower than that of the absolute soil moisture values. The spatial variance of the time-invariant component (temporal mean of each site) is the predominant contribution to the total spatial variance of absolute soil moisture data. Moreover, half of the networks show a minimum in the spatial variability for intermediate conditions when the temporal anomalies are considered, in contrast with the widely recognized behavior of absolute soil moisture data. The analyses with percent saturation data show qualitatively similar results as those for the temporal anomalies because of the applied normalization which reduces spatial variability induced by differences in mean absolute soil moisture only. Overall, we find that the analysis of the spatial-temporal variability of absolute soil moisture does not apply to temporal anomalies or percent of saturation values. [ABSTRACT FROM AUTHOR]

Soil moisture is widely recognized as a fundamental variable governing the mass and energy fluxes between the land surface and the atmosphere. In this study, the soil moisture modelling at sub-daily timescale is addressed by using an accurate representation of the infiltration component. For that, the semi-analytical infiltration model proposed by Corradini et al. (1997) has been incorporated into a soil water balance model to simulate the evolution in time of surface and profile soil moisture. The performances of this new soil moisture model [soil water balance module-semi-analytical (SWBM-SA)] are compared with those of a precedent version [SWBM-Green-Ampt (GA)] where the GA approach was employed. Their capability to reproduce in situ soil moisture observations at three sites in Italy, Spain and France is analysed. Hourly observations of quality-checked rainfall, temperature and soil moisture data for a 2-year period are used for testing the modelling approaches. Specifically, different configurations for the calibration and validation of the models are adopted by varying a single parameter, that is, the saturated hydraulic conductivity. Results indicate that both SWBMs are able to reproduce satisfactorily the hourly soil moisture temporal pattern for the three sites with root mean square errors lower than 0.024 m3/m3 both in the calibration and validation periods. For all sites, the SWBM-SA model outperforms the SWBM-GA with an average reduction of the root mean square error of ~20%. Specifically, the higher improvement is observed for the French site for which in situ observations are measured at 30 cm depth, and this is attributed to the capability of the SA infiltration model to simulate the time evolution of the whole soil moisture profile. The reasonable models performance coupled with the need to calibrate only a single parameter makes them useful tools for soil moisture simulation in different regions worldwide, also in scarcely gauged areas. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Aim: To analyze the clinical effect of continuous subcutaneous insulin infusion (CSII) in type 1 diabetes mellitus (T1D) patients in the Spanish real-world scenario. Methods: All T1D patients on CSII registered in the SPAnish Insulin Pump (SPAIP) registry were included. The primary efficacy outcome was change in HbA1c during follow-up. Secondary efficacy outcomes included: insulin pump indications, diabetes complication rates, insulin and pump use, and continuous glucose monitoring (CGM) glycometrics. Patient data were typed through the web-based SPAIP registry. Results: Data from 2979 T1D patients treated with CSII were analyzed. The median age was 44 years (interquartile range [IQR] 34-52 years), and T1D duration was 27 years (IQR 18-35 years). The median duration of CSII therapy was 6 years (IQR 3-10 years). The main indications for treatment were suboptimal glycemic control (33.8%), hypoglycemia (22.1%), and increased glycemic variability (18.8%). Glycated hemoglobin decreased by 6 mmol/mol (95% CI, -5 to -6 mmol/mol, P < 0.001) [-0.5%, 95% CI, -0.4 to -0.5, P < 0.001] during the follow-up. The percentage of patients with severe hypoglycemia decreased from 14.9% to 0.9% (P < 0.001). We observed an inverse correlation between final HbA1c levels and CGM adherence (R = -0.24, P < 0.001) or percentage of time with active hybrid closed-loop functions (R = -0.25, P < 0.001). Conclusions: CSII treatment was associated with a sustained improvement in glycemic control in the Spanish population. This benefit was greater among patients with higher CGM or active hybrid closed-loop functions adherence. The protocol was publicly registered at ClinicalTrials.gov (NCT04761094). [ABSTRACT FROM AUTHOR]

Despite irrigation being one of the main sources of anthropogenic water consumption, detailed information about water amounts destined for this purpose are often lacking worldwide. In this study, a methodology which can be used to estimate irrigation amounts over a pilot area in Spain by exploiting remotely sensed soil moisture is proposed. Two high-resolution DISPATCH (DISaggregation based on Physical And Theoretical scale CHange) downscaled soil moisture products have been used: SMAP (Soil Moisture Active Passive) and SMOS (Soil Moisture and Ocean Salinity) at 1 km. The irrigation estimates have been obtained through the SM2RAIN algorithm, in which the evapotranspiration term has been improved to adequately reproduce the crop evapotranspiration over irrigated areas according to the FAO (Food and Agriculture Organization) model. The experiment exploiting the SMAP data at 1 km represents the main work analyzed in this study and covered the period from January 2016 to September 2017. The experiment with the SMOS data at 1 km, for which a longer time series is available, allowed the irrigation estimates to be extended back to 2011. For both of the experiments carried out, the proposed method performed well in reproducing the magnitudes of the irrigation amounts that actually occurred in four of the five pilot irrigation districts. The SMAP experiment, for which a more detailed analysis was performed, also provided satisfactory results in representing the spatial distribution and the timing of the irrigation events. In addition, the investigation into which term of the SM2RAIN algorithm plays the leading role in determining the amount of water entering into the soil highlights the importance of correct representation of the evapotranspiration process. [ABSTRACT FROM AUTHOR]

Despite the key role of irrigation in the Earth system, we lack fundamental information regarding the distribution of irrigated fields, irrigation timing and the amount of water utilized. In the past years, the SM_Delta and SM_Inversion approaches have been independently developed to provide estimates of irrigation timing and water amounts based on satellite soil moisture data. The SM_Delta approach retrieves irrigation from variations in soil moisture between an individual pixel and the surrounding rainfed area, while the SM_Inversion approach estimates the total amount of water entering the soil, then irrigation is derived by subtracting precipitation. In this study, we perform a comprehensive assessment of irrigation estimates from the SM_Delta and SM_Inversion algorithms based on Sentinel-1 surface soil moisture retrievals at 1 km resolution. Our analysis focuses on the Ebro basin, an irrigated region in Spain covering 83000 km2, during the period 2017–2019. We assess the ability of the two methods to discriminate irrigated and rainfed pixels, then we quantify the agreement of irrigation timing and water volumes with reference irrigation data. An inter-comparison between estimates from the SM_Delta and SM_Inversion methods is carried out considering both temporal and spatial features, i.e., monthly irrigation peaks and spatial irrigation patterns. Finally, we explore two potential applications of satellite-derived irrigation estimates: attributing irrigation water volumes to specific irrigation systems and to individual crops. We observe that both methods erroneously retrieve irrigation over rainfed pixels, and are therefore not suitable to map irrigated and rainfed fields. However, when auxiliary information on irrigated fields is available, we find a satisfactory agreement between district-scale reference data and satellite-retrieved irrigation, using both the SM_Delta and SM_Inversion approaches (Pearson R equal to 0.67 and 0.71, bias equal to −4.99 and −4.75 mm/15 days, respectively). When aggregated in space or time, the irrigation estimates exhibit coherent temporal dynamics and spatial patterns. For instance, estimates from both SM_Delta and SM_Inversion capture the delayed irrigation that occurred in 2018 due to wetter than usual conditions in spring. However, at the pixel-scale, limited consistency exists between irrigation estimates from the two methods due to different assumptions and parameterizations, e.g., use of constant vs pixel-specific soil water capacity (in the SM_Delta and SM_Inversion, respectively). Overall, the study demonstrates the reliability of irrigation estimates derived from the SM_Delta and SM_Inversion approaches, especially when shifting from small spatial and short temporal scales (pixel level, sub-weekly) to larger and longer scales (district level, seasonal). Hence, satellite-based irrigation estimates could inform water resources managers and basin authorities, as well as serve the modelling community by providing reliable information on the timing and the amounts of water employed at the basin level. • Assessment of two irrigation retrieval approaches based on Sentinel-1 soil moisture. • Good agreement between satellite-based and in-situ irrigation at district-scale. • Irrigation from satellite data captures inter- and intra-annual temporal dynamics. • Limited consistency among irrigation estimates from the two approaches at pixel-scale. • Satellite-based irrigation estimates are reliable when aggregated in space or time. [ABSTRACT FROM AUTHOR]

Irrigation is the most impacting and uncertain human intervention on the water resource. The possibility of retrieving information on irrigation practices through remote sensing technology opens unprecedented perspectives on the monitoring of anthropized basins. This study is aimed at assessing the impact of different approaches to model the contribution of the evapotranspiration in retrieving the amounts of water applied for irrigation through a soil-moisture-based (SM-based) inversion algorithm; such a contribution is conclusive especially over semi-arid regions. Three modeling approaches relying on both calculated and remotely sensed actual and potential evapotranspiration (ET and PET) data sets were implemented to represent the evapotranspiration rate within the SM-based inversion method, which allows backward estimation of irrigation through the soil water balance inversion. By combining the different evapotranspiration data sources and modeling approaches, seven experiments aimed at inverting DISPATCH (DISaggregation based on Physical And Theoretical scale CHange) downscaled SMAP (Soil Moisture Active Passive) soil moisture at 1 km to estimate irrigation over four heavily irrigated agricultural districts located in Spain (Aragon and Catalonia) were compared. The results highlighted that the application of the FAO56 guidelines parametrization relying on the use of optical data as proposed by the authors in a previous study remains the most reliable configuration. In fact, the implementation of a simplified approach not considering the transpiration component of the specific crop led to irrigation underestimates. Finally, it is interesting to note that the application of the method with remotely sensed ET from MODIS (MODerate-resolution Imaging Spectroradiometer) produced reliable district-aggregated irrigation estimates, thus opening the perspective of an algorithm configuration forced with remote sensing data only. [Display omitted] • ET data from several sources were tested in an algorithm aimed at quantifying irrigation. • Underestimates occurred when the specific crop-type transpiration component was neglected. • Potential for an algorithm configuration forced with remote sensing data only was highlighted. [ABSTRACT FROM AUTHOR]

[Display omitted] • Temporal stability derived indices describe the spatiotemporal dynamics of soil moisture. • The L-band passive microwave downscaled products are able to detect irrigation. • A method to map irrigated areas through the K-means algorithm is proposed. • The method is able to distinguish irrigated areas from rainfed agricultural areas. • The land surface model does not add information for irrigation mapping. Although irrigation practices affect food production and water resource management, with ever more impacting effects under climate change and population increasing scenarios, detailed knowledge of irrigation is still lacking. In fact, explicit information on the spatial occurrence of irrigation and on the amounts of water used for this purpose is often not available, thus making irrigation the missing variable to comprehensively understand the hydrological cycle dynamics over agricultural areas. Nevertheless, remote sensing techniques can be used to delimit the irrigation extent. In this study, the capability of five remotely sensed soil moisture products to detect the irrigation signal over an area intensely equipped for irrigation in the North East of Spain is investigated; moreover, a method to map the actually irrigated areas based on the K-means clustering algorithm is proposed. The remote sensing soil moisture data sets used in this study are SMOS (Soil Moisture and Ocean Salinity) at 1 km, SMAP (Soil Moisture Active Passive) at 1 km and 9 km, Sentinel-1 at 1 km, and ASCAT (Advanced SCATterometer) at 12.5 km. The 1 km resolution versions of SMOS and SMAP are obtained by downscaling coarser SMOS and SMAP data through the DISPATCH (DISaggregation based on Physical And Theoretical scale CHange) algorithm. The analyses are supported by an additional data set of soil moisture at 1 km resolution simulated by the SURFEX-ISBA (SURFace EXternalisée – Interaction Sol Biosphère Atmosphère) land surface model. Among all the considered data sets, the L-band passive microwave downscaled products show the best performances in detecting the irrigation signal over the pilot area, especially SMAP at 1 km. The proposed maps of irrigated areas derived by exploiting soil moisture from SMAP at 1 km data set agree well (up to 78%) with the ground truth derived irrigated areas. Furthermore, the method is able to well distinguish the actually irrigated areas from rainfed agricultural areas, thus representing a useful tool to obtain reliable spatial information about the areas where irrigation actually occurs. [ABSTRACT FROM AUTHOR]

• Available rainfall data are characterized by different time resolution, "ta" • A database involving metadata from many geographic areas is presented. • The "ta" history of rainfall data in a variety of rain gauges is reconstructed. • The registration methods of the rainfall data changed over the years. • Currently about 50% of rain gauge stations provide data with any "ta" Collected rainfall records by gauges lead to key forcings in most hydrological studies. Depending on sensor type and recording systems, such data are characterized by different time-resolutions (or temporal aggregations), t a. We present an historical analysis of the time-evolution of t a based on a large database of rain gauge networks operative in many study areas. Globally, t a data were collected for 25,423 rain gauge stations across 32 geographic areas, with larger contributions from Australia, USA, Italy and Spain. For very old networks early recordings were manual with coarse time-resolution, typically daily or sometimes monthly. With a few exceptions, mechanical recordings on paper rolls began in the first half of the 20th century, typically with t a of 1 h or 30 min. Digital registrations started only during the last three decades of the 20th century. This short period limits investigations that require long time-series of sub-daily rainfall data, e.g, analyses of the effects of climate change on short-duration (sub-hourly) heavy rainfall. In addition, in the areas with rainfall data characterized for many years by coarse time-resolutions, annual maximum rainfall depths of short duration can be potentially underestimated and their use would produce errors in the results of successive applications. Currently, only 50% of the stations provide useful data at any time-resolution, that practically means t a = 1 min. However, a significant reduction of these issues can be obtained through the information content of the present database. Finally, we suggest an integration of the database by including additional rain gauge networks to enhance its usefulness particularly in a comparative analysis of the effects of climate change on extreme rainfalls of short duration available in different locations. [ABSTRACT FROM AUTHOR]