Non-invAsive VentIlation for early General wArd respiraTory failurE (NAVIGATE):A multicenter randomized controlled study. Protocol and statistical analysis plan

Few randomized trials have evaluated the use of non-invasive ventilation (NIV) for early acute respiratory failure (ARF) in non-intensive care unit (ICU) wards. The aim of this study is to test the hypothesis that early NIV for mild-moderate ARF in non-ICU wards can prevent development of severe ARF

The impact of chest CT body composition parameters on clinical outcomes in COVID-19 patients

We assessed the impact of chest CT body composition parameters on outcomes and disease severity at hospital presentation of COVID-19 patients, focusing also on the possible mediation of body composition in the relationship between age and death in these patients. Chest CT scans performed at hospital presentation by consecutive COVID-19 patients (02/27/2020-03/13/2020) were retrospectively reviewed to obtain pectoralis muscle density and total, visceral, and intermuscular adipose tissue areas (TAT, VAT, IMAT) at the level of T7-T8 vertebrae. Primary outcomes were: hospitalization, mechanical ventilation (MV) and/or death, death alone. Secondary outcomes were: C-reactive protein (CRP), oxygen saturation (SO2), CT disease extension at hospital presentation. The mediation of body composition in the effect of age on death was explored. Of the 318 patients included in the study (median age 65.7 years, females 37.7%), 205 (64.5%) were hospitalized, 68 (21.4%) needed MV, and 58 (18.2%) died. Increased muscle density was a protective factor while increased TAT, VAT, and IMAT were risk factors for hospitalization and MV/death. All these parameters except TAT had borderline effects on death alone. All parameters were associated with SO2 and extension of lung parenchymal involvement at CT; VAT was associated with CRP. Approximately 3% of the effect of age on death was mediated by decreased muscle density. In conclusion, low muscle quality and ectopic fat accumulation were associated with COVID-19 outcomes, VAT was associated with baseline inflammation. Low muscle quality partly mediated the effect of age on mortality.We assessed the impact of chest CT body composition parameters on outcomes and disease severity at hospital presentation of COVID-19 patients, focusing also on the possible mediation of body composition in the relationship between age and death in these patients. Chest CT scans performed at hospital presentation by consecutive COVID-19 patients (02/ 27/2020-03/13/2020) were retrospectively reviewed to obtain pectoralis muscle density and total, visceral, and intermuscular adipose tissue areas (TAT, VAT, IMAT) at the level of T7-T8 vertebrae. Primary outcomes were: hospitalization, mechanical ventilation (MV) and/or death, death alone. Secondary outcomes were: C-reactive protein (CRP), oxygen saturation (SO2), CT disease extension at hospital presentation. The mediation of body composition in the effect of age on death was explored. Of the 318 patients included in the study (median age 65.7 years, females 37.7%), 205 (64.5%) were hospitalized, 68 (21.4%) needed MV, and 58 (18.2%) died. Increased muscle density was a protective factor while increased TAT, VAT, and IMAT were risk factors for hospitalization and MV/death. All these parameters except TAT had borderline effects on death alone. All parameters were associated with SO2 and extension of lung parenchymal involvement at CT; VAT was associated with CRP. Approximately 3% of the effect of age on death was mediated by decreased muscle density. In conclusion, low muscle quality and ectopic fat accumulation were associated with COVID-19 outcomes, VAT was associated with baseline inflammation. Low muscle quality partly mediated the effect of age on mortality

Differential impact of anthropogenic pressures on Caspian Sea ecoregions

Over the past decades, overall ecological conditions in the Caspian Sea have deteriorated. However, a comprehensive understanding of lake-wide spatial differences in anthropogenic pressures is lacking and the biological consequences of human impacts are poorly understood. This paper therefore aims at assessing the individual and combined effects of critical anthropogenic pressures on the Caspian Sea ecoregions. First, cumulative pressure scores were calculated with a cumulative environmental assessment (CEA) analysis. Then, the individual contribution of anthropogenic pressures was quantified. Finally, ecoregion-specific differences were assessed. The analyses show that both cumulative and individual pressure scores are unevenly distributed across the Caspian Sea. The most important individual pressures are invasive species, chemical pollution and poaching. This uneven distribution of pressure scores across Caspian Sea ecoregions creates new challenges for future conservation strategies, as different ecoregions usually require different conservation measures

Protein adsorption on ion exchange resins and monoclonal antibody charge variant modulation

A novel multicomponent adsorption equilibrium model for proteins on ion-exchange resins is developed on a statistical thermodynamic basis including surface coverage effects and protein-resin and protein-protein interactions. The resulting model exhibits a general competitive Langmuirian behavior and was applied to the study and optimization of the separation of monoclonal antibody charge variants on two strong cation exchangers. The model accounts explicitly for the effect of both pH and salt concentration, and its parameters can be determined in diluted conditions, that is, through physically sound assumptions, all model parameters can be obtained using solely experiments in diluted conditions, and be used to make predictions in overloaded conditions.The parameterization of the model and optimization of the separation is based on a two-step approach. First, gradient experiments in diluted conditions are undertaken in order to determine the model parameters. Based on these experiments and on information about the proteins of interest and the stationary phase used, all the model parameters can be estimated. Second, using the parameterized model, an initial Pareto optimization is undertaken where overloaded operating conditions are investigated. Experiments from this Pareto set are then used to refine the estimation of the model parameters. A second Pareto optimization can then be undertaken, this time with the refined parameters. This can be repeated until a satisfactory set of model parameters is found.This iterative approach is shown to be extremely efficient and to provide large amounts of knowledge based on only a few experiments. It is shown that due to the strong physical foundation of the model and the very low number of adjustable parameters, the number of iterations is expected to be at most two or three. Furthermore, the model based tool is improved as more experimental knowledge is provided, allowing for better estimations of the chromatographic processes considered at each iteration. This makes it a very suitable tool for the design and the development of preparative and industrial purification processes, including the determination of both the optimal operating conditions, as well as the allowable process operating space

Online Learning of Oil Leaks Anomalies in Wind Turbines with Block Based Binary Reservoir

The focus of this work is to design a deeply quantized anomaly detector of oil leaks that may happen at the junction between the wind turbine high-speed shaft and the external bracket of the power generator. We propose a block-based binary shallow echo state network (BBS-ESN) architecture belonging to the reservoir computing (RC) category and, as we believe, it also extends the extreme learning machines (ELM) domain. Furthermore, BBS-ESN performs binary block-based online training using fixed and minimal computational complexity to achieve low power consumption and deployability on an off-the-shelf micro-controller (MCU). This has been achieved through binarization of the images and 1-bit quantization of the network weights and activations. 3D rendering has been used to generate a novel publicly available dataset of photo-realistic images similar to those potentially acquired by image sensors on the field while monitoring the junction, without and with oil leaks. Extensive experimentation has been conducted using a STM32H743ZI2 MCU running at 480 MHz and the results achieved show an accurate identification of anomalies, with a reduced computational cost per image and memory occupancy. Based on the obtained results, we conclude that BBS-ESN is feasible on off-the-shelf 32 bit MCUs. Moreover, the solution is also scalable in the number of image cameras to be deployed and to achieve accurate and fast oil leak detections from different viewpoints

Polyhydroxylated GdDTPA-derivatives as high relaxivity magnetic resonance imaging contrast agents

The search for new MRI agents endowed with high relaxivity at the magnetic field strength of clinical scanners (1.5–3 T) is still receiving great attention from researchers involved in the development of new probes. Such Gd(III) complexes should combine a fast inner-sphere water exchange rate (kex) with an enhanced contribution from water molecules in the second and outer coordination spheres. In the present work, dendrimeric-like structures were synthesized by coupling diethylenetriaminepentaacetic acid (DTPA) and its mono-methylphosphonic derivative (P-DTPA) with two differently branched, highly hydrophilic, gluconyl moieties. A 1H and 17O NMR relaxometric study on the corresponding Gd(III) complexes reveals that the Gd-P-DTPA-polyol complex displays very high relaxivities (around 20 mM1 s1 at 298 K) over the 0.5–3 T range of field strengths as a result of a fast kex and the presence of a strong second sphere contribution