Association of kidney disease measures with risk of renal function worsening in patients with type 1 diabetes

Background: Albuminuria has been classically considered a marker of kidney damage progression in diabetic patients and it is routinely assessed to monitor kidney function. However, the role of a mild GFR reduction on the development of stage 653 CKD has been less explored in type 1 diabetes mellitus (T1DM) patients. Aim of the present study was to evaluate the prognostic role of kidney disease measures, namely albuminuria and reduced GFR, on the development of stage 653 CKD in a large cohort of patients affected by T1DM. Methods: A total of 4284 patients affected by T1DM followed-up at 76 diabetes centers participating to the Italian Association of Clinical Diabetologists (Associazione Medici Diabetologi, AMD) initiative constitutes the study population. Urinary albumin excretion (ACR) and estimated GFR (eGFR) were retrieved and analyzed. The incidence of stage 653 CKD (eGFR < 60 mL/min/1.73 m2) or eGFR reduction > 30% from baseline was evaluated. Results: The mean estimated GFR was 98 \ub1 17 mL/min/1.73m2 and the proportion of patients with albuminuria was 15.3% (n = 654) at baseline. About 8% (n = 337) of patients developed one of the two renal endpoints during the 4-year follow-up period. Age, albuminuria (micro or macro) and baseline eGFR < 90 ml/min/m2 were independent risk factors for stage 653 CKD and renal function worsening. When compared to patients with eGFR > 90 ml/min/1.73m2 and normoalbuminuria, those with albuminuria at baseline had a 1.69 greater risk of reaching stage 3 CKD, while patients with mild eGFR reduction (i.e. eGFR between 90 and 60 mL/min/1.73 m2) show a 3.81 greater risk that rose to 8.24 for those patients with albuminuria and mild eGFR reduction at baseline. Conclusions: Albuminuria and eGFR reduction represent independent risk factors for incident stage 653 CKD in T1DM patients. The simultaneous occurrence of reduced eGFR and albuminuria have a synergistic effect on renal function worsening

Energy Efficient System for Environment Observation

Environment observations provide a unique source of consistent information about the natural environment and they provide resource managers the information to assess the current state of the environment, weight the requirements of different uses by multiple stakeholders, and manage the natural resources and ecosystemsinasustainablemanner.Mostoftheobservationsarebasedonsatellites, but remote-sensing technologies alone cannot guarantee observations at the spatiotemporal resolution and with the accuracy requested for monitoring and modeling applications targeting, like weather and climate extremes and the complex feedback processes between the natural environment and human activities. Dense networks of standard and in-situ weather related sensors are present in EU and US, but it may happen that their data are not always available in real-time or updated with the required scale for various weather and climate applications. Then, highresolution, (near) real-time on field monitoring systems are needed to satisfy the demand to sample environmental data, both in dense populated regions and in less developedandgettingmorepopulatedregions,whereessentialin-situobservational capabilities can be lacking or deteriorating. The paper would demonstrate the possibility to have energy efficient computing and communication systems that can be employed for environment observation and that can enrich traditional in-situ and remote sensing environmental data, to enable a significant step forward in the environment monitoring of a wide range of weather and climate data. The paper will present an approach going in this direction (computing/communication everywhere withlow-powerconstrains),testedinaharshenvironment,byexploitinglow-power boardstoperformdatapre-processingandreconfigurableantennastosenddataina moreenergeticallyconvenientwayappliedtoarealcaseasitmaybethemonitoring of ionospheric scintillation in Antarctica

Energy Efficient System for Environment Observation

Environment observations provide a unique source of consistent information about the natural environment and they provide resource managers the information to assess the current state of the environment, weight the requirements of different uses by multiple stakeholders, and manage the natural resources and ecosystemsinasustainablemanner.Mostoftheobservationsarebasedonsatellites, but remote-sensing technologies alone cannot guarantee observations at the spatiotemporal resolution and with the accuracy requested for monitoring and modeling applications targeting, like weather and climate extremes and the complex feedback processes between the natural environment and human activities. Dense networks of standard and in-situ weather related sensors are present in EU and US, but it may happen that their data are not always available in real-time or updated with the required scale for various weather and climate applications. Then, highresolution, (near) real-time on field monitoring systems are needed to satisfy the demand to sample environmental data, both in dense populated regions and in less developedandgettingmorepopulatedregions,whereessentialin-situobservational capabilities can be lacking or deteriorating. The paper would demonstrate the possibility to have energy efficient computing and communication systems that can be employed for environment observation and that can enrich traditional in-situ and remote sensing environmental data, to enable a significant step forward in the environment monitoring of a wide range of weather and climate data. The paper will present an approach going in this direction (computing/communication everywhere withlow-powerconstrains),testedinaharshenvironment,byexploitinglow-power boardstoperformdatapre-processingandreconfigurableantennastosenddataina moreenergeticallyconvenientwayappliedtoarealcaseasitmaybethemonitoring of ionospheric scintillation in Antarctica