Correction of metabolic acidosis improves thyroid and growth hormone axes in haemodialysis patients

Background. Chronic metabolic acidosis (CMA) in normal adults results in complex endocrine and metabolic alterations including growth hormone (GH) insensitivity, hypothyroidism, hyperglucocorticoidism, hypoalbuminaemia and loss of protein stores. Similar alterations occur in chronic renal failure, a prototypical state of CMA. We evaluated whether metabolic acidosis contributes to the endocrine and metabolic alterations characteristic of end-stage renal disease. Methods. We treated 14 chronic haemodialysis patients with daily oral Na-citrate for 4 weeks, yielding a steady-state pre-dialytic plasma bicarbonate concentration of 26.7 mmol/l, followed by 4 weeks of equimolar Na-chloride, yielding a steady-state pre-dialytic plasma bicarbonate of 20.2 mmol/l. Results. Blood pressure, body weight and dialysis adequacy were equivalent in the two protocols. Na-citrate treatment corrected CMA, improved GH insensitivity, increased and normalized plasma free T3 concentration, and improved plasma albumin. Correction of CMA had no significant effect on measured cytokines (interleukin-1β and -6, tumour necrosis factor-α) or acute phase reactants (C-reactive protein, serum amyloid A, α2-macroglobulin). Conclusion. CMA contributes to the derangements of the growth and thyroid hormone axes and to hypoalbuminaemia, but is not a modulator of systemic inflammation in dialysis patients. Correcting CMA may improve nutritional and metabolic parameters and thus lower morbidity and mortalit

Correction of metabolic acidosis improves thyroid and growth hormone axes in haemodialysis patients

Background. Chronic metabolic acidosis (CMA) in normal adults results in complex endocrine and metabolic alterations including growth hormone (GH) insensitivity, hypothyroidism, hyperglucocorticoidism, hypoalbuminaemia and loss of protein stores. Similar alterations occur in chronic renal failure, a prototypical state of CMA. We evaluated whether metabolic acidosis contributes to the endocrine and metabolic alterations characteristic of end-stage renal disease. Methods. We treated 14 chronic haemodialysis patients with daily oral Na-citrate for 4 weeks, yielding a steady-state pre-dialytic plasma bicarbonate concentration of 26.7 mmol/l, followed by 4 weeks of equimolar Na-chloride, yielding a steady-state pre-dialytic plasma bicarbonate of 20.2 mmol/l. Results. Blood pressure, body weight and dialysis adequacy were equivalent in the two protocols. Na-citrate treatment corrected CMA, improved GH insensitivity, increased and normalized plasma free T3 concentration, and improved plasma albumin. Correction of CMA had no significant effect on measured cytokines (interleukin-1β and -6, tumour necrosis factor-α) or acute phase reactants (C-reactive protein, serum amyloid A, α2-macroglobulin). Conclusion. CMA contributes to the derangements of the growth and thyroid hormone axes and to hypoalbuminaemia, but is not a modulator of systemic inflammation in dialysis patients. Correcting CMA may improve nutritional and metabolic parameters and thus lower morbidity and mortalit

Understanding incentives for prefix aggregation in BGP

Proceeding of: ReArch'09, Proceedings of the 2009 workshop on Re-architecting the internet, (49-54), 1 December 2009, Rome, Italy.Over the last few years, a significant amount of the effort of the Future Internet architecture is devoted in order to improve the scalability of the next generation routing architecture. In this paper, we study providers’ incentives to perform prefix aggregation or deaggregation of non-customers routes. This is essentially a tradeoff between reduced router memory and reduced capacity of attracting customer traffic. We study the case where two ISPs compete for attracting traffic, by using game theory. In particular, we propose a game-theoretic model and we analyze the properties of the equilibrium. In a symmetric case, if a single Autonomous System (AS) is found to be deaggregating a given prefix, then all others will have the incentive to do the same, even if they end up with lower benefits. We find that pure equilibria do not always exist and we derive the conditions based on two model parameters. These findings suggest that BGP instability can be a common problem in a competitive scenario.European Community's Seventh Framework ProgramPublicad

Trace Mineral Intake and Deficiencies in Older Adults Living in the Community and Institutions: A Systematic Review

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. The global population is ageing with many older adults suffering from age-related malnutrition, including micronutrient deficiencies. Adequate nutrient intake is vital to enable older adults to continue living independently and delay their institutionalisation, as well as to prevent deterioration of health status in those living in institutions. This systematic review investigated the insufficiency of trace minerals in older adults living independently and in institutions. We examined 28 studies following a cross-sectional or cohort design, including 7203 older adults (≥60) living independently in 13 Western countries and 2036 living in institutions in seven Western countries. The estimated average requirement (EAR) cut-off point method was used to calculate percentage insufficiency for eight trace minerals using extracted mean and standard deviation values. Zinc deficiency was observed in 31% of community-based women and 49% of men. This was higher for those in institutional care (50% and 66%, respectively). Selenium intakes were similarly compromised with deficiency in 49% women and 37% men in the community and 44% women and 27% men in institutions. We additionally found significant proportions of both populations showing insufficiency for iron, iodine and copper. This paper identifies consistent nutritional insufficiency for selenium, zinc, iodine and copper in older adults

Latest LAPS developments Assimilating remote sensing data and its impact on LAPS predictability

Presentación realizada en la 3rd European Nowcasting Conference, celebrada en la sede central de AEMET en Madrid del 24 al 26 de abril de 2019

Behavioral modeling of low-frequency noise in switched-capacitor circuits using Python

In precision circuits validating the performance in the presence of low-frequency noise is particularly challenging especially at transistor level, as long simulations are required to observe the low frequency performance. However, running such system-level simulations is rarely practical at transistor level as these simulations can take days to weeks to complete. This work presents a high-level model in Python for generating low-frequency noise which can be used for validating the low-frequency performance of a design in a timely manner. Simulation times can be reduced from days to minutes, enabling designers to achieve a high-level simulation coverage. With Python and NumPy this can be achieved using open-source software tools at no cost

Performance Evaluation of a New Dual-Polarization Microphysical Algorithm Based on Long-Term X-Band Radar and Disdrometer Observations

Abstract Accurate estimation of precipitation at high spatial and temporal resolution of weather radars is an open problem in hydrometeorological applications. The use of dual polarization gives the advantage of multiparameter measurements using orthogonal polarization states. These measurements carry significant information, useful for estimating rain-path signal attenuation, drop size distribution (DSD), and rainfall rate. This study evaluates a new self-consistent with optimal parameterization attenuation correction and rain microphysics estimation algorithm (named SCOP-ME). Long-term X-band dual-polarization measurements and disdrometer DSD parameter data, acquired in Athens, Greece, have been used to quantitatively and qualitatively compare SCOP-ME retrievals of median volume diameter D0 and intercept parameter NW with two existing rain microphysical estimation algorithms and the SCOP-ME retrievals of rain rate with three available radar rainfall estimation algorithms. Error statistics for rain rate estimation, in terms of relative mean and root-mean-square error and efficiency, show that the SCOP-ME has low relative error if compared to the other three methods, which systematically underestimate rainfall. The SCOP-ME rain microphysics algorithm also shows a lower relative error statistic when compared to the other two microphysical algorithms. However, measurement noise or other signal degradation effects can significantly affect the estimation of the DSD intercept parameter from the three different algorithms used in this study. Rainfall rate estimates with SCOP-ME mostly depend on the median volume diameter, which is estimated much more efficiently than the intercept parameter. Comparisons based on the long-term dataset are relatively insensitive to path-integrated attenuation variability and rainfall rates, providing relatively accurate retrievals of the DSD parameters when compared to the other two algorithms

Analysis of root growth from a phenotyping data set using a density-based model

Major research efforts are targeting the improved performance of root systems for more efficient use of water and nutrients by crops. However, characterizing root system architecture (RSA) is challenging, because roots are difficult objects to observe and analyse. A model-based analysis of RSA traits from phenotyping image data is presented. The model can successfully back-calculate growth parameters without the need to measure individual roots. The mathematical model uses partial differential equations to describe root system development. Methods based on kernel estimators were used to quantify root density distributions from experimental image data, and different optimization approaches to parameterize the model were tested. The model was tested on root images of a set of 89 Brassica rapa L. individuals of the same genotype grown for 14 d after sowing on blue filter paper. Optimized root growth parameters enabled the final (modelled) length of the main root axes to be matched within 1% of their mean values observed in experiments. Parameterized values for elongation rates were within ±4% of the values measured directly on images. Future work should investigate the time dependency of growth parameters using time-lapse image data. The approach is a potentially powerful quantitative technique for identifying crop genotypes with more efficient root systems, using (even incomplete) data from high-throughput phenotyping systems

Coupling X-band dual-polarized mini-radars and hydro-meteorological forecast models: the HYDRORAD project

Abstract. Hydro-meteorological hazards like convective outbreaks leading to torrential rain and floods are among the most critical environmental issues world-wide. In that context weather radar observations have proven to be very useful in providing information on the spatial distribution of rainfall that can support early warning of floods. However, quantitative precipitation estimation by radar is subjected to many limitations and uncertainties. The use of dual-polarization at high frequency (i.e. X-band) has proven particularly useful for mitigating some of the limitation of operational systems, by exploiting the benefit of easiness to transport and deploy and the high spatial and temporal resolution achievable at small antenna sizes. New developments on X-band dual-polarization technology in recent years have received the interest of scientific and operational communities in these systems. New enterprises are focusing on the advancement of cost-efficient mini-radar network technology, based on high-frequency (mainly X-band) and low-power weather radar systems for weather monitoring and hydro-meteorological forecasting. Within the above context, the main objective of the HYDRORAD project was the development of an innovative \\mbox{integrated} decision support tool for weather monitoring and hydro-meteorological applications. The integrated system tool is based on a polarimetric X-band mini-radar network which is the core of the decision support tool, a novel radar products generator and a hydro-meteorological forecast modelling system that ingests mini-radar rainfall products to forecast precipitation and floods. The radar products generator includes algorithms for attenuation correction, hydrometeor classification, a vertical profile reflectivity correction, a new polarimetric rainfall estimators developed for mini-radar observations, and short-term nowcasting of convective cells. The hydro-meteorological modelling system includes the Mesoscale Model 5 (MM5) and the Army Corps of Engineers Hydrologic Engineering Center hydrologic and hydraulic modelling chain. The characteristics of this tool make it ideal to support flood monitoring and forecasting within urban environment and small-scale basins. Preliminary results, carried out during a field campaign in Moldova, showed that the mini-radar based hydro-meteorological forecasting system can constitute a suitable solution for local flood warning and civil flood protection applications